Simonboysen7456

Phishing is one of the most common threats that users face while browsing the web. In the current threat landscape, a targeted phishing attack (i.e., spear phishing) often constitutes the first action of a threat actor during an intrusion campaign. To tackle this threat, many data-driven approaches have been proposed, which mostly rely on the use of supervised machine learning under a single-layer approach. However, such approaches are resource-demanding and, thus, their deployment in production environments is infeasible. Moreover, most previous works utilise a feature set that can be easily tampered with by adversaries. In this paper, we investigate the use of a multi-layered detection framework in which a potential phishing domain is classified multiple times by models using different feature sets. In our work, an additional classification takes place only when the initial one scores below a predefined confidence level, which is set by the system owner. Panobinostat We demonstrate our approach by implementing a two-layered detection system, which uses supervised machine learning to identify phishing attacks. We evaluate our system with a dataset consisting of active phishing attacks and find that its performance is comparable to the state of the art.The deep ocean is the largest habitat for life on Earth, though the microorganisms that occupy this unique environmental niche remain largely unexplored. Due to the significant logistical and operational challenges associated with accessing the deep ocean, bioprospecting programmes that seek to generate novel products from marine organisms have, to date, focused predominantly on samples recovered from shallow seas. For this reason, the deep ocean remains a largely untapped resource of novel microbiological life and associated natural products. Here we report the establishment of the Bristol Sponge Microbiome Collection (BISECT), a unique repository of deep-sea microorganisms and associated metabolites isolated from the microbiota of marine sponges, recovered from previously unsurveyed regions of the mid Atlantic Ocean, at depths of 0.3-3 km. An integrated biodiscovery pipeline comprising molecular, genetic, bioinformatic and analytical tools is also described, which is being applied to interrogate this collection. The potential of this approach is illustrated using data reporting our initial efforts to identify antimicrobial natural product lead compounds. Prospects for the use of BISECT to address allied pharmaceutical needs, along with mechanisms of access to the collection are also discussed.Rosmarinic acid (RosA), an important polyphenol, is known for its antioxidant and anti-inflammatory activities. However, its application in theranostics has been rarely reported. Therefore, a new single-molecule anti-inflammatory theranostic compound containing RosA would be of great interest. A gadolinium (Gd) complex of 1,4,7,10-tetraazacyclododecane-1,4,7-trisacetic acid (DO3A) and RosA (Gd(DO3A-RosA)(H2O)) was synthesized and examined for use as a single-molecule theranostic agent. Its kinetic stability is comparable to that of clinically used macrocyclic magnetic resonance imaging contrast agents. In addition, its relaxivity is higher than that of structurally analogous Gd-BT-DO3A. This agent was evaluated for inflammatory targeting magnetic resonance contrast and showed strong and prolonged enhancement of imaging in inflamed tissues of mice. The theranostic agent also possesses antioxidant and anti-inflammatory activities, as evidenced by reactive oxygen species scavenging, superoxide dismutase activity, and inflammatory factors. The novel RosA-conjugated Gd complex is a promising theranostic agent for the imaging of inflamed tissues, as well as for the treatment of inflammation and oxidative stress.Microalgae isolated from the Qatari desert was identified as thermotolerant, with a rich metabolite profile that is appropriate for use as food and health supplements. In this research, a species of Chlorella, QUCCCM3, from the Qatar University Culture Collection of Cyanobacteria and Microalgae, was investigated for its growth characteristics and metabolite compositions for use as potential feedstock for food production. The strain was cultivated at 30, 35, and 40 °C, covering the annual average low and high temperatures in Qatar. The highest growth rates were recorded for cultures at 30 °C with 0.64 ± 0.04 day-1, followed by a growth rate of 0.54 ± 0.06 day-1 at 40 °C, indicating its thermotolerance ability. The biomass exhibited a high protein content (43 ± 2.3%), with existence of lysine (4.13%) as an essential amino acid, and docosahexaenoic acid, linoleic acid, and alpha-linolenic acid as important omega fatty acids present. On the other hand, Chlorella sp. QUCCCM3 also exhibited a high capacity for scavenging free radicals with an antiproliferative effect against chronic myeloid leukemia K562 cancer cells. The results indicate that Chlorella sp. QUCCCM3 is a promising candidate that can be produced year-round, in the Qatar environment, for commercial applications such as feed and nutraceutical supplements.Calcium carbonate cements have been synthesized by mixing amorphous calcium carbonate and vaterite powders with water to form a cement paste and study how mechanical strength is created during the setting reaction. In-situ X-ray diffraction (XRD) was used to monitor the transformation of amorphous calcium carbonate (ACC) and vaterite phases into calcite and a rotational rheometer was used to monitor the strength evolution. There are two characteristic timescales of the strengthening of the cement paste. The short timescale of the order 1 h is controlled by smoothening of the vaterite grains, allowing closer and therefore adhesive contacts between the grains. The long timescale of the order 10-50 h is controlled by the phase transformation of vaterite into calcite. This transformation is, unlike in previous studies using stirred reactors, found to be mainly controlled by diffusion in the liquid phase. The evolution of shear strength with solid volume fraction is best explained by a fractal model of the paste structure.