Data-driven feature identification and sparse representation of turbulent flows

Identifying coherent structures in fluid flows is of great importance for reduced order modelling and flow control. However, extracting such structures from experimental or numerical data obtained from a turbulent flow can be challenging. A number of modal decomposition algorithms have been proposed in recent years which decompose time-resolved snapshots of data into spatial modes, each associated with a single frequency and growth-rate. Most prominently among them is dynamic mode decomposition (DMD). However, DMD-like algorithms create an arbitrary number of modes. It is common practice to then choose a smaller subset of these modes, for the purpose of model reduction and analysis, based on some measure of significance. In this work, we present a method of post-processing DMD modes for extracting a small number of dynamically relevant modes. We achieve this through an iterative approach based on the graph-theoretic notion of maximal cliques to identify clusters of modes and representing each cluster with a single representative mode

USE OF CHROMAGAR ORIENTATION FOR PRESEMPTIVE IDENTIFICATION OF ENTEROCOCCI AND CHARACTERIZATION OF ANTIMICROBIAL RESISTANCE OF THE ISOLATES

This study was conducted to evaluate the use of CHROMagar Orientation for presumptive identification of enterococci from poultry, and to characterize the antimicrobial resistance of the isolates. Strains identification with conventional methods allowed confirmation of Enterococcus genus membership of all of the isolates on CHROMagar orientation (100%). Of the 141 enterococci isolates obtained from chicken, 81 (57.45%) were identified as Enterococcus faecalis and 60 (42.55%) as Enterococcus faecium. The antimicrobial susceptibility test presented high level of resistance to Tetracycline (89%) and Erythromycin (65%), low level of resistance to High Level of Streptomycin, Penicillin and Ciprofloxacin (13%, 10% and 9% respectively). Few of isolates were resistant to Chloramphenicol (2%). All the strains were susceptible to High Level of Gentamycin, Ampicillin, Vancomycin and Nitrofurantoin. The predominant phenotype of resistance pattern identified in both E.faecalis and E.faecium was (Erythromycin -Tetracycline)

A Structured Approach to Insider Threat Monitoring for Offensive Security Teams

In many countries, government agencies resort to third parties to acquire security services of many kinds, including Red Team operations to test the effectiveness of own defenses mechanisms. Absolute trust is a key requirement, lest a potentially devastating finding be exploited by a treacherous Red Team against the same entity which commissioned the operation, or sold to its adversaries. In our endeavour as a joint private-academic initiative to address this peculiar market, we observed that a structured approach to this issue is much less common than we would have expected. In this work, we outline the process we are devising to offer customers a verified environment, but integrating it with an evidence-based proof of their correct behavior during the operation, striving to solve the “Quis custodiet ipsos custodes” struggle in an offensive setting

Poster: Continual Network Learning

We make a case for in-network Continual Learning as a solution for seamless adaptation to evolving network conditions without forgetting past experiences. We propose implementing Active Learning-based selective data filtering in the data plane, allowing for data-efficient continual updates. We explore relevant challenges and propose future research directions

Complete Chloroplast Genome Sequence of Omani Lime (Citrus aurantiifolia) and Comparative Analysis within the Rosids

The genus Citrus contains many economically important fruits that are grown worldwide for their high nutritional and medicinal value. Due to frequent hybridizations among species and cultivars, the exact number of natural species and the taxonomic relationships within this genus are unclear. To compare the differences between the Citrus chloroplast genomes and to develop useful genetic markers, we used a reference-assisted approach to assemble the complete chloroplast genome of Omani lime (C. aurantiifolia). The complete C. aurantiifolia chloroplast genome is 159,893 bp in length; the organization and gene content are similar to most of the rosids lineages characterized to date. Through comparison with the sweet orange (C. sinensis) chloroplast genome, we identified three intergenic regions and 94 simple sequence repeats (SSRs) that are potentially informative markers with resolution for interspecific relationships. These markers can be utilized to better understand the origin of cultivated Citrus. A comparison among 72 species belonging to 10 families of representative rosids lineages also provides new insights into their chloroplast genome evolution

Tannery effluent treatment by nanofiltration, reverse osmosis and chitosan modified membranes

UID/QUI/50006/2019The objective of this work is to develop an appropriate technology for environmentally sound membrane-based purification of a tannery effluent assuring, simultaneously, the recovery of chromium, considered as the most hazardous inorganic water pollutant extensively used in leather tanning. A comparison between the permeate fluxes obtained during treatment of a synthetic tannery effluent through nanofiltration (NF270 and NF90 membranes) and reverse osmosis (BW30 and SW30) membranes was first performed. Then, a dedicated polymeric membrane was prepared by coating chitosan (cs) on a polyethersulfone (PES) microfiltration membrane (cs-PES MFO22) support. The resulting membrane was characterized by Fourier Transforms Infrared Spectroscopy Attenuated Total Reflectance (FTIR-ATR), Emission Scanning Electronic Microscopy (SEM) to confirm the process of surface modification and cross-linking of chitosan with glutaraldehyde. This membrane was found to be highly effective for chromium removal (>99%), which was more than eight times higher in reference to monovalent cations (e.g., Na+ and K+) and more than six times higher in reference to the divalent cations (Mg2+ and Ca2+) studied. The reverse osmosis permeate conforms to local Algerian regulations regarding being discharged directly into the natural environment (in this case, Reghaia Lake) or into urban sewers linked to wastewater biological treatment stations. While the SW30 membrane proved to be the most effective for purification of the tannery effluent, the chitosan modified membrane proved to be appropriate for recovery of chromium from the reverse osmosis concentrate.publishersversionpublishe

Quantifying the need for supervised machine learning in conducting live forensic analysis of emergent configurations (ECO) in IoT environments

© 2020 The Author(s) Machine learning has been shown as a promising approach to mine larger datasets, such as those that comprise data from a broad range of Internet of Things devices, across complex environment(s) to solve different problems. This paper surveys existing literature on the potential of using supervised classical machine learning techniques, such as K-Nearest Neigbour, Support Vector Machines, Naive Bayes and Random Forest algorithms, in performing live digital forensics for different IoT configurations. There are also a number of challenges associated with the use of machine learning techniques, as discussed in this paper

A critical look at studies applying over-sampling on the TPEHGDB dataset

Preterm birth is the leading cause of death among young children and has a large prevalence globally. Machine learning models, based on features extracted from clinical sources such as electronic patient files, yield promising results. In this study, we review similar studies that constructed predictive models based on a publicly available dataset, called the Term-Preterm EHG Database (TPEHGDB), which contains electrohysterogram signals on top of clinical data. These studies often report near-perfect prediction results, by applying over-sampling as a means of data augmentation. We reconstruct these results to show that they can only be achieved when data augmentation is applied on the entire dataset prior to partitioning into training and testing set. This results in (i) samples that are highly correlated to data points from the test set are introduced and added to the training set, and (ii) artificial samples that are highly correlated to points from the training set being added to the test set. Many previously reported results therefore carry little meaning in terms of the actual effectiveness of the model in making predictions on unseen data in a real-world setting. After focusing on the danger of applying over-sampling strategies before data partitioning, we present a realistic baseline for the TPEHGDB dataset and show how the predictive performance and clinical use can be improved by incorporating features from electrohysterogram sensors and by applying over-sampling on the training set

Biotic and Abiotic Stresses of Major Fruit Crops in Oman: A Review

Oman is located in an arid region of the world that is characterized by adverse climatic conditions, including heat and drought. In recent years, it has also been affected by climate turbulence and the occurrence of severe weather, such as cyclones and heat/cold waves affecting large agricultural areas of the country. Fruit cultivation area represents 31% of the total cultivated area (97,239.58 ha) in the country. However, the production share is only 17% of the total crop production in the country (2.6 million tons). About 90% of the fruit cultivation area is dominated by date palm, banana, lime, and mango. In addition to the abiotic stresses, such as drought, heat, and salinity, major fruit crops have declined in recent years due to various biotic stressors, primarily insect pests, and diseases. For several decades, the date palm has suffered from the Dubas bug and in recent years from Red Palm Weevil. Lime has been infected with Witch’s Broom Disease of Lime (WBDL) caused by ‘Candidatus Phytoplasma aurantifolia’ that has led to the decline of production to 25% from its peak in the nineties. Banana is Oman`s second-largest fruit crop in production and export. It has also been the subject of studies due to losses incurred by farmers during pre-and post-harvest stages, in addition to several pests and diseases that affect bananas in Oman. Mango is another major fruit crop that is primarily cultivated in northern Oman. Severe infection with mango decline has led to the eradication of mango orchards from many regions of Oman, particularly in Batinah Coast, where increased salinity has led to a decline in mango yield. Research conducted in Oman has investigated several aspects of these challenges. This review paper summarizes the outcome from studies conducted in the country and proposes directions towards resolving current and future challenges to the fruit industry

Probabilistic seismic hazard maps for the sultanate of Oman

This study presents the results of the first probabilistic seismic hazard assessment (PSHA) in the framework of logic tree for Oman. The earthquake catalogue was homogenized, declustered, and used to define seismotectonic source model that characterizes the seismicity of Oman. Two seismic source models were used in the current study; the first consists of 26 seismic source zones, while the second is expressing the alternative view that seismicity is uniform along the entire Makran and Zagros zones. The recurrence parameters for all the seismogenic zones were determined using the doubly bounded exponential distribution except the zones of Makran, which were modelled using the characteristic distribution. Maximum earthquakes were determined and the horizontal ground accelerations in terms of geometric mean were calculated using ground-motion prediction relationships developed based upon seismic data obtained from active tectonic environments similar to those surrounding Oman. The alternative seismotectonic source models, maximum magnitude, and ground-motion prediction relationships were weighted and used to account for the epistemic uncertainty. Hazard maps at rock sites were produced for 5 % damped spectral acceleration (SA) values at 0.1, 0.2, 0.3, 1.0 and 2.0 s spectral periods as well as peak ground acceleration (PGA) for return periods of 475 and 2,475 years. The highest hazard is found in Khasab City with maximum SA at 0.2 s spectral period reaching 243 and 397 cm/s[superscript 2] for return periods 475 and 2,475 years, respectively. The sensitivity analysis reveals that the choice of seismic source model and the ground-motion prediction equation influences the results most.Oman Ministerial Cabinet (project number 22409017