Deep-pretrained-FWI: combining supervised learning with physics-informed neural network

An accurate velocity model is essential to make a good seismic image. Conventional methods to perform Velocity Model Building (VMB) tasks rely on inverse methods, which, despite being widely used, are ill-posed problems that require intense and specialized human supervision. Convolutional Neural Networks (CNN) have been extensively investigated as an alternative to solve the VMB task. Two main approaches were investigated in the literature: supervised training and Physics-Informed Neural Networks (PINN). Supervised training presents some generalization issues since structures, and velocity ranges must be similar in training and test set. Some works integrated Full-waveform Inversion (FWI) with CNN, defining the problem of VMB in the PINN framework. In this case, the CNN stabilizes the inversion, acting like a regularizer and avoiding local minima-related problems and, in some cases, sparing an initial velocity model. Our approach combines supervised and physics-informed neural networks by using transfer learning to start the inversion. The pre-trained CNN is obtained using a supervised approach based on training with a reduced and simple data set to capture the main velocity trend at the initial FWI iterations. We show that transfer learning reduces the uncertainties of the process, accelerates model convergence, and improves the final scores of the iterative process.Comment: Paper present at machine Learning and the Physical Sciences workshop, NeurIPS 202

Post-weaning Exposure to High-Fat Diet Induces Kidney Lipid Accumulation and Function Impairment in Adult Rats

Aim: We investigated the kidney morphofunctional consequences of high-fat diet intake since post-weaning in adult rats.Main Methods: Male Wistar rats were divided into two groups: ND (normal diet; n = 10) and HD (high-fat diet; n = 10). The high-fat diet was introduced post-weaned and animals were followed for 8 weeks.Key Findings: HD group did not change body weight gain even though food consumption has decreased with no changes in caloric consumption. The HD group showed glucose intolerance and insulin resistance. The glomerular filtration rate (GFR) was decreased in vivo (ND: 2.8 ± 1.01; HD: 1.1 ± 0.14 ml/min) and in the isolated perfusion method (34% of decrease). Renal histological analysis showed a retraction in glomeruli and an increase in kidney lipid deposition (ND: 1.5 ± 0.17 HD: 5.9 ± 0.06%). Furthermore, the high-fat diet consumption increased the pro-inflammatory cytokines IL-6 (ND: 1,276 ± 203; HD: 1,982 ± 47 pg/mL/mg) and IL-1b (ND: 97 ± 12 HD: 133 ± 5 pg/mL/mg) without changing anti-inflammatory cytokine IL-10.Significance: Our study provides evidence that high-fat diet consumption leads to renal lipid accumulation, increases inflammatory cytokines, induces glomeruli retraction, and renal dysfunction. These damages observed in the kidney could be associated with an increased risk to advanced CKD in adulthood suggesting that reduction of high-fat ingestion during an early period of life can prevent metabolic disturbances and renal lipotoxicity

High Prevalence of Malaria in Zambezia, Mozambique: The Protective Effect of IRS versus Increased Risks Due to Pig-Keeping and House Construction

BACKGROUND: African countries are scaling up malaria interventions, especially insecticide treated nets (ITN) and indoor residual spraying (IRS), for which ambitious coverage targets have been set. In spite of these efforts infection prevalence remains high in many parts of the continent. This study investigated risk factors for malaria infection in children using three malaria indicator surveys from Zambezia province, Mozambique. The impact of IRS and ITNs, the effects of keeping farm animals and of the construction material of roofs of houses and other potential risk factors associated with malaria infection in children were assessed. METHODS: Cross-sectional community-based surveys were conducted in October of 2006, 2007 and 2008. A total of 8338 children (ages 1-15 years) from 2748 households were included in the study. All children were screened for malaria by rapid diagnostic tests. Caregiver interviews were used to assess household demographic and wealth characteristics and ITN and IRS coverage. Associations between malaria infection, vector control interventions and potential risk factors were assessed. RESULTS: Overall, the prevalence of malaria infection was 47.8% (95%CI: 38.7%-57.1%) in children 1-15 years of age, less than a quarter of children (23.1%, 95%CI: 19.1%-27.6%) were sleeping under ITN and almost two thirds were living in IRS treated houses (coverage 65.4%, 95%CI: 51.5%-77.0%). Protective factors that were independently associated with malaria infection were: sleeping in an IRS house without sleeping under ITN (Odds Ratio (OR)= 0.6; 95%CI: 0.4-0.9); additional protection due to sleeping under ITN in an IRS treated house (OR = 0.5; 95%CI: 0.3-0.7) versus sleeping in an unsprayed house without a ITN; and parental education (primary/secondary: OR = 0.6; 95%CI: 0.5-0.7) versus parents with no education. Increased risk of infection was associated with: current fever (OR = 1.2; 95%CI: 1.0-1.5) versus no fever; pig keeping (OR = 3.2; 95%CI: 2.1-4.9) versus not keeping pigs; living in houses with a grass roof (OR = 1.7; 95%CI: 1.3-2.4) versus other roofing materials and bigger household size (8-15 people: OR = 1.6; 95%CI: 1.3-2.1) versus small households (1-4 persons). CONCLUSION: Malaria infection among children under 15 years of age in Zambezia remained high but conventional malaria vector control methods, in particular IRS, provided effective means of protection. Household ownership of farm animals, particularly pigs, and living in houses with a grass roof were independently associated with increased risk of infection, even after allowing for household wealth. To reduce the burden of malaria, national control programs need to ensure high coverage of effective IRS and promote the use of ITNs, particularly in households with elevated risks of infection, such as those keeping farm animals, and those with grass roofs

Genome of the Avirulent Human-Infective Trypanosome—Trypanosoma rangeli

Background: Trypanosoma rangeli is a hemoflagellate protozoan parasite infecting humans and other wild and domestic mammals across Central and South America. It does not cause human disease, but it can be mistaken for the etiologic agent of Chagas disease, Trypanosoma cruzi. We have sequenced the T. rangeli genome to provide new tools for elucidating the distinct and intriguing biology of this species and the key pathways related to interaction with its arthropod and mammalian hosts.  Methodology/Principal Findings: The T. rangeli haploid genome is ,24 Mb in length, and is the smallest and least repetitive trypanosomatid genome sequenced thus far. This parasite genome has shorter subtelomeric sequences compared to those of T. cruzi and T. brucei; displays intraspecific karyotype variability and lacks minichromosomes. Of the predicted 7,613 protein coding sequences, functional annotations could be determined for 2,415, while 5,043 are hypothetical proteins, some with evidence of protein expression. 7,101 genes (93%) are shared with other trypanosomatids that infect humans. An ortholog of the dcl2 gene involved in the T. brucei RNAi pathway was found in T. rangeli, but the RNAi machinery is non-functional since the other genes in this pathway are pseudogenized. T. rangeli is highly susceptible to oxidative stress, a phenotype that may be explained by a smaller number of anti-oxidant defense enzymes and heatshock proteins.  Conclusions/Significance: Phylogenetic comparison of nuclear and mitochondrial genes indicates that T. rangeli and T. cruzi are equidistant from T. brucei. In addition to revealing new aspects of trypanosome co-evolution within the vertebrate and invertebrate hosts, comparative genomic analysis with pathogenic trypanosomatids provides valuable new information that can be further explored with the aim of developing better diagnostic tools and/or therapeutic targets

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

A search for ultra-high-energy photons at the Pierre Auger Observatory exploiting air-shower universality

The Pierre Auger Observatory is the most sensitive detector to primary photons with energies above ∼0.2 EeV. It measures extensive air showers using a hybrid technique that combines a fluorescence detector (FD) with a ground array of particle detectors (SD). The signatures of a photon-induced air shower are a larger atmospheric depth at the shower maximum (X$_{max}$) and a steeper lateral distribution function, along with a lower number of muons with respect to the bulk of hadron-induced background. Using observables measured by the FD and SD, three photon searches in different energy bands are performed. In particular, between threshold energies of 1-10 EeV, a new analysis technique has been developed by combining the FD-based measurement of X$_{max}$ with the SD signal through a parameter related to its muon content, derived from the universality of the air showers. This technique has led to a better photon/hadron separation and, consequently, to a higher search sensitivity, resulting in a tighter upper limit than before. The outcome of this new analysis is presented here, along with previous results in the energy ranges below 1 EeV and above 10 EeV. From the data collected by the Pierre Auger Observatory in about 15 years of operation, the most stringent constraints on the fraction of photons in the cosmic flux are set over almost three decades in energy

Study on multi-ELVES in the Pierre Auger Observatory

Since 2013, the four sites of the Fluorescence Detector (FD) of the Pierre Auger Observatory record ELVES with a dedicated trigger. These UV light emissions are correlated to distant lightning strikes. The length of recorded traces has been increased from 100 μs (2013), to 300 μs (2014-16), to 900 μs (2017-present), to progressively extend the observation of the light emission towards the vertical of the causative lightning and beyond. A large fraction of the observed events shows double ELVES within the time window, and, in some cases, even more complex structures are observed. The nature of the multi-ELVES is not completely understood but may be related to the different types of lightning in which they are originated. For example, it is known that Narrow Bipolar Events can produce double ELVES, and Energetic In-cloud Pulses, occurring between the main negative and upper positive charge layer of clouds, can induce double and even quadruple ELVES in the ionosphere. This report shows the seasonal and daily dependence of the time gap, amplitude ratio, and correlation between the pulse widths of the peaks in a sample of 1000+ multi-ELVES events recorded during the period 2014-20. The events have been compared with data from other satellite and ground-based sensing devices to study the correlation of their properties with lightning observables such as altitude and polarity

Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks

We present a method based on the use of Recurrent Neural Networks to extract the muon component from the time traces registered with water-Cherenkov detector (WCD) stations of the Surface Detector of the Pierre Auger Observatory. The design of the WCDs does not allow to separate the contribution of muons to the time traces obtained from the WCDs from those of photons, electrons and positrons for all events. Separating the muon and electromagnetic components is crucial for the determination of the nature of the primary cosmic rays and properties of the hadronic interactions at ultra-high energies. We trained a neural network to extract the muon and the electromagnetic components from the WCD traces using a large set of simulated air showers, with around 450 000 simulated events. For training and evaluating the performance of the neural network, simulated events with energies between 1018.5, eV and 1020 eV and zenith angles below 60 degrees were used. We also study the performance of this method on experimental data of the Pierre Auger Observatory and show that our predicted muon lateral distributions agree with the parameterizations obtained by the AGASA collaboration