Modelling and Simulation of Heterogeneous and Anisotropic Formations using Advanced Fractal Reservoir Models

Energy and carbon-efficient exploitation, management, and remediation of subsurface aquifers, gas and oil resources, CO2-disposal sites, and energy storage reservoirs all require high quality modelling and simulation. The heterogeneity and anisotropy of such subsurface formations has always been a challenge to modellers, with the best current technology not being able to deal with variations at scales of less than about 30-50 m. Most formations exhibit heterogeneities and anisotropy which result in variations of the petrophysical properties controlling fluid flow down to millimetre scale and below. These variations are apparent in well-logs and core material, but cannot be characterised in the inter-well volume which makes up the great majority of the formation. This paper describes a new fractal approach to the modelling and simulation of heterogeneous and anisotropic aquifers and reservoirs. This approach includes data at all scales such that it can represent the heterogeneity of the reservoir correctly at each scale. Advanced Fractal Reservoir Models (AFRMs) in 3D can be produced using our code. These AFRMs can be used to model fluid flow in formations generically to understand the effects of an imposed degree of heterogeneity and anisotropy, or can be conditioned to match the characteristics of real aquifers and reservoirs. This paper will show how 3D AFRMs can be created such that they represent critical petrophysical parameters, as well as how fractal 3D porosity and permeability maps, synthetic poro-perm cross-plots, water saturation maps and relative permeability curves can all be calculated. It will also show how quantitative controlled variation of heterogeneity and anisotropy of generic models affects fluid flow. We also show how AFRMs can be conditioned to represent real reservoirs, and how they provide a much better simulated fluid flow than the current best technology. Results of generic modelling and simulation with AFRMs show how total hydrocarbon production, hydrocarbon production rate, water cut and the time to water breakthrough all depend strongly on heterogeneity, and also depend upon anisotropy. Modelling with different degrees and directions of anisotropy shows how critical hydrocarbon production data depends on the direction of the anisotropy, and how that changes over the lifetime of the reservoir. Advanced fractal reservoir models are of greatest utility if they can be conditioned to represent individual reservoirs. We have developed a method for matching AFRMs to aquifer and reservoir data across a wide range of scales that exceeds the range of scales currently used in such modelling. We show a hydrocarbon production case study which compares the hydrocarbon production characteristics of such an approach to a conventional krigging approach. The comparison shows that modelling of hydrocarbon production is appreciably improved when AFRMs are used, especially if heterogeneity and anisotropy are high. In this study AFRMs in moderate to high heterogeneity reservoirs always provided results within 5% of the reference case, while the conventional approach resulted in massive systematic underestimations of production rate by over 70%

Developing soft skills through project-based learning in technical and vocational institutions

Soft skills have become critical in the preparation of employable graduates. The education system must, therefore, aim to ensure quality training for the production of employable graduates. Soft skills are personal abilities that one retains and can adequately be nurtured through active participation of students in the teaching and learning process. It is validated by researchers that the prevalent employability skills deficiencies have been one of the main causes of unemployment globally. Consequently, soft skills have all the potentials for equipping graduates with adequate employability skills. Thus, this study investigated the effect of project-based learning on the development of soft skills among technical students at technical and vocational colleges, Kaduna State, Nigeria Smart PLS software was used to test the developed model. As the sample size for this study was relatively small, the researchers were not certain to have normally distributed data. Subsequently, Smart PLS is appropriate for non-normally distributed data and therefore, it was used to simultaneously evaluate the measurement model, structural models and to confirm the convergent and discriminant validity of the measure. The study revealed that collaborative skills construct have a significant positive relationship with soft skills of technical students at technical and vocational colleges, while communication skills, initiative skills, and problem-solving skills have a positive insignificant relationship with soft skills of technical students at technical and vocational colleges. The findings of this study suggest that the curriculum of technical programs in Nigerian technical colleges need to be reviewed and geared more towards activity-based teaching and learning to enable technical students effectively develop soft skills for employment

VarLOCK - sequencing independent, rapid detection of SARS-CoV-2 variants of concern for point-of-care testing, qPCR pipelines and national wastewater surveillance

The COVID-19 pandemic continues to pose a threat to the general population. The ongoing vaccination programs provide protection to individuals and facilitate the opening of society and a return to normality. However, emergent and existing SARS-CoV-2 variants capable of evading the immune system endanger the efficacy of the vaccination strategy. To preserve the efficacy of SARS-CoV-2 vaccination globally, aggressive and effective surveillance for known and emerging SARS-CoV-2 Variants of Concern (VOC) is required. Rapid and specific molecular diagnostics can provide speed and coverage advantages compared to genomic sequencing alone, benefitting the public health response and facilitating VOC containment. In this work, we expand the recently developed SARS-CoV-2 CRISPR-Cas detection technology (SHERLOCK) to allow rapid and sensitive discrimination of VOCs, that can be used at point of care and/or implemented in the pipelines of small or large testing facilities, and even determine proportion of VOCs in pooled population-level wastewater samples. This technology aims to complement the ongoing sequencing efforts to allow facile and, crucially, rapid identification of individuals infected with VOCs to help break infection chains. Here, we show the optimisation of our VarLOCK assays (Variant-specific SHERLOCK) for multiple specific mutations in the S gene of SARS-CoV-2 and validation with samples from the Cardiff University Testing Service. We also show the applicability of VarLOCK to national wastewater surveillance of SARS-CoV-2 variants. In addition, we show the rapid adaptability of the technique for new and emerging VOCs such as Omicron

Photocatalytic Degradation of Organic Pollutants in Water Using Graphene Oxide Composite

Developing sustainable and less-expensive technique is always challenging task in water treatment process. This chapter explores the recent development of photocatalysis technique in organic pollutant removal from the water. Particularly, advantages of graphene oxide in promoting the catalytic performance of semiconductor, metal nanoparticle and polymer based photocatalyst materials. Owing to high internal surface area and rapid electron conducting property of graphene oxide fostering as backbone scaffold for effective hetero-photocatalyst loading, and rapid photo-charge separation enables effective degradation of pollutant. This chapter summaries the recent development of graphene oxide composite (metal oxide, metal nanoparticle, metal chalcogenides, and polymers) in semiconductor photocatalysis process towards environmental remediation application

Inborn errors of type I IFN immunity in patients with life-threatening COVID-19.

Clinical outcome upon infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ranges from silent infection to lethal coronavirus disease 2019 (COVID-19). We have found an enrichment in rare variants predicted to be loss-of-function (LOF) at the 13 human loci known to govern Toll-like receptor 3 (TLR3)- and interferon regulatory factor 7 (IRF7)-dependent type I interferon (IFN) immunity to influenza virus in 659 patients with life-threatening COVID-19 pneumonia relative to 534 subjects with asymptomatic or benign infection. By testing these and other rare variants at these 13 loci, we experimentally defined LOF variants underlying autosomal-recessive or autosomal-dominant deficiencies in 23 patients (3.5%) 17 to 77 years of age. We show that human fibroblasts with mutations affecting this circuit are vulnerable to SARS-CoV-2. Inborn errors of TLR3- and IRF7-dependent type I IFN immunity can underlie life-threatening COVID-19 pneumonia in patients with no prior severe infection

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic

Diversity, distribution and conservation of the terrestrial reptiles of Oman (Sauropsida, Squamata)

All authors: Salvador Carranza , Meritxell Xipell, Pedro Tarroso, Andrew Gardner, Edwin Nicholas Arnold, Michael D. Robinson, Marc Simó-Riudalbas, Raquel Vasconcelos, Philip de Pous, Fèlix Amat, Jiří Šmíd, Roberto Sindaco, Margarita Metallinou †, Johannes Els, Juan Manuel Pleguezuelos, Luis Machado, David Donaire, Gabriel Martínez, Joan Garcia-Porta, Tomáš Mazuch, Thomas Wilms, Jürgen Gebhart, Javier Aznar, Javier Gallego, Bernd-Michael Zwanzig, Daniel Fernández-Guiberteau, Theodore Papenfuss, Saleh Al Saadi, Ali Alghafri, Sultan Khalifa, Hamed Al Farqani, Salim Bait Bilal, Iman Sulaiman Alazri, Aziza Saud Al Adhoobi, Zeyana Salim Al Omairi, Mohammed Al Shariani, Ali Al Kiyumi, Thuraya Al Sariri, Ahmed Said Al Shukaili, Suleiman Nasser Al Akhzami.In the present work, we use an exceptional database including 5,359 records of 101 species of Oman’s terrestrial reptiles together with spatial tools to infer the spatial patterns of species richness and endemicity, to infer the habitat preference of each species and to better define conservation priorities, with especial focus on the effectiveness of the protected areas in preserving this unique arid fauna. Our results indicate that the sampling effort is not only remarkable from a taxonomic point of view, with multiple observations for most species, but also for the spatial coverage achieved. The observations are distributed almost continuously across the two-dimensional climatic space of Oman defined by the mean annual temperature and the total annual precipitation and across the Principal Component Analysis (PCA) of the multivariate climatic space and are well represented within 17 out of the 20 climatic clusters grouping 10% of the explained climatic variance defined by PC1 and PC2. Species richness is highest in the Hajar and Dhofar Mountains, two of the most biodiverse areas of the Arabian Peninsula, and endemic species richness is greatest in the Jebel Akhdar, the highest part of the Hajar Mountains. Oman’s 22 protected areas cover only 3.91% of the country, including within their limits 63.37% of terrestrial reptiles and 50% of all endemics. Our analyses show that large areas of the climatic space of Oman lie outside protected areas and that seven of the 20 climatic clusters are not protected at all. The results of the gap analysis indicate that most of the species are below the conservation target of 17% or even the less restrictive 12% of their total area within a protected area in order to be considered adequately protected. Therefore, an evaluation of the coverage of the current network of protected areas and the identification of priority protected areas for reptiles using reserve design algorithms are urgently needed. Our study also shows that more than half of the species are still pending of a definitive evaluation by the International Union for Conservation of Nature (IUCN).This work was funded by grants CGL2012-36970, CGL2015-70390-P from the Ministerio de Economía y Competitividad, Spain (cofunded by FEDER) to SC, the project Field study for the conservation of reptiles in Oman, Ministry of Environment and Climate Affairs, Oman (Ref: 22412027) to SC and grant 2014-SGR-1532 from the Secretaria d'Universitats i Recerca del Departament d'Economia i Coneixement de la Generalitat de Catalunya to SC. MSR is funded by a FPI grant from the Ministerio de Economía y Competitividad, Spain (BES-2013-064248); RV, PT and LM were funded by Fundação para a Ciência e Tecnologia (FCT) through post-doc grants (SFRH/BPD/79913/2011) to RV, (SFRH/BPD/93473/2013) to PT and PhD grant (SFRH/BD/89820/2012) to LM, financed by Programa Operacional Potencial Humano (POPH) – Quadro de Referência Estrategico Nacional (QREN) from the European Social Fund and Portuguese Ministerio da Educação e Ciência

Reproducibility in the absence of selective reporting : An illustration from large-scale brain asymmetry research

Altres ajuts: Max Planck Society (Germany).The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes

Novel genetic loci associated with hippocampal volume

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg =-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness