Detection of explosive markers using zeolite modified gas sensors

Detection of hidden explosive devices is a key priority for security and defence personnel around the globe. Electronic noses, based on metal oxide semiconductors (MOS), are a promising technology for creating inexpensive, portable and sensitive devices for such a purpose. An array of seven MOS gas sensors was fabricated by screen printing, based on WO3 and In2O3 inks. The sensors were tested against six gases, including four explosive markers: nitromethane, DMNB (2,3-dimetheyl-2,3-dinitrobutane), 2-ethylhexanol and ammonia. The gases were successfully detected with good sensitivity and selectivity from the array. Sensitivity was improved by overlaying or admixing the oxides with two zeolites, H-ZSM-5 and TS-1, and each showed improved responses to –NO2 and –OH moieties respectively. Admixtures in particular showed promise, with excellent sensitivity and good stability to humidity. Machine learning techniques were applied to a subset of the data and could accurately classify the gases detected, even when confounding factors were introduced

A Systematic Review of the State of Cyber-Security in Water Systems

Critical infrastructure systems are evolving from isolated bespoke systems to those that use general-purpose computing hosts, IoT sensors, edge computing, wireless networks and artificial intelligence. Although this move improves sensing and control capacity and gives better integration with business requirements, it also increases the scope for attack from malicious entities that intend to conduct industrial espionage and sabotage against these systems. In this paper, we review the state of the cyber-security research that is focused on improving the security of the water supply and wastewater collection and treatment systems that form part of the critical national infrastructure. We cover the publication statistics of the research in this area, the aspects of security being addressed, and future work required to achieve better cyber-security for water systems

Preparation and Characterization of Biobased Poly(Ethylene- 2,5-Furan Dicarboxylate)/Clay Nanocomposites

Poly(ethylene 2,5-furan dicarboxylate)/Clay nanocomposites was prepared via esterification and polycondensation reaction. Biobased monomer was first intercalated into the interlayer regions of clay minerals by ion exchange reaction. Then, the clay was dispersed in the monomer at different loading degrees to conduct the polymerization process. Polymerization through the interlayer of the clay led to the exfoliated poly(ethylene-2,5-furan dicarboxylate)/montmorillonite nanocomposite formation. X-ray diffraction (XRD) analysis revealed that the resultant nanocomposites exhibited exfoliated polymer/clay nanocompositesKeywords: Poly(ethylene-2,5- furan dicarboxylate); renewable polymers; nanocomposites, montmorinollit

Cycling near misses: A review of the current methods, challenges and the potential of an AI-embedded system

Whether for commuting or leisure, cycling is a growing transport mode in many countries. However, cycling is still perceived by many as a dangerous activity. Because the mode share of cycling tends to be low, serious incidents related to cycling are rare. Nevertheless, the fear of getting hit or falling while cycling hinders its expansion as a transport mode and it has been shown that focusing on killed and seriously injured casualties alone only touches the tip of the iceberg. Compared with reported incidents, there are many more incidents in which the person on the bike was destabilised or needed to take action to avoid a crash; so-called near misses. Because of their frequency, data related to near misses can provide much more information about the risk factors associated with cycling. The quality and coverage of this information depends on the method of data collection; from survey data to video data, and processing; from manual to automated. There remains a gap in our understanding of how best to identify and predict near misses and draw statistically significant conclusions, which may lead to better intervention measures and the creation of a safer environment for people on bikes. In this paper, we review the literature on cycling near misses, focusing on the data collection methods adopted, the scope and the risk factors identified. In doing so, we demonstrate that, while many near misses are a result of a combination of different factors that may or may not be transport-related, the current approach of tackling these factors may not be adequate for understanding the interconnections between all risk factors. To address this limitation, we highlight the potential of extracting data using a unified input (images/videos) relying on computer vision methods to automatically extract the wide spectrum of near miss risk factors, in addition to detecting the types of events associated with near misses

Norcoclaurine Synthase-Mediated Stereoselective Synthesis of 1,1'-Disubstituted, Spiro- and Bis-Tetrahydroisoquinoline Alkaloids

The Pictet–Spenglerase norcoclaurine synthase (NCS) catalyzes the formation of (S)-norcoclaurine, an important intermediate in the biosynthetic pathway of benzylisoquinoline alkaloids. NCS has been used as a biocatalyst with meta-hydroxy phenethylamines and aldehydes for the preparation of single-isomer tetrahydroisoquinoline alkaloids (THIAs). Recently, it was also reported that some ketones can be accepted as substrates, including 4-substituted cyclohexanones and phenyl acetones. Here, we report the use of wild-type NCS and selected variants with aliphatic, cyclic, α-substituted cyclic, heterocyclic, and bicyclic ketones to access challenging non-natural THIAs. Remarkably, fused bicyclic ketones as well as diketones could also be accepted by some of the NCS variants, and in silico modeling was used to provide insights into the rationale for this

Pore performance: artificial nanoscale constructs that mimic the biomolecular transport of the nuclear pore complex

The nuclear pore complex is a nanoscale assembly that achieves shuttle-cargo transport of biomolecules: a certain cargo molecule can only pass the barrier if it is attached to a shuttle molecule. In this review we summarize the most important efforts aiming to reproduce this feature in artificial settings. This can be achieved by solid state nanopores that have been functionalized with the most important proteins found in the biological system. Alternatively, the nanopores are chemically modified with synthetic polymers. However, only a few studies have demonstrated a shuttle-cargo transport mechanism and due to cargo leakage, the selectivity is not comparable to that of the biological system. Other recent approaches are based on DNA origami, though biomolecule transport has not yet been studied with these. The highest selectivity has been achieved with macroscopic gels, but they are yet to be scaled down to nano-dimensions. It is concluded that although several interesting studies exist, we are still far from achieving selective and efficient artificial shuttle-cargo transport of biomolecules. Besides being of fundamental interest, such a system could be potentially useful in bioanalytical devices

Tracking Promyelocytic Leukemia Nuclear Bodies for Disease Detection: a Proof of Concept via Filtering

Abstrac

The UCL Integrated Engineering Programme

In 2014, the UCL Faculty of Engineering Sciences introduced the Integrated Engineering Programme – a revision of eight existing degree programmes across a range of engineering disciplines. Centered on a thread of authentic project-based activities, the programme aimed to enhance the students’ understanding of key theoretical concepts and heighten the development of key professional skills. This paper provides an outline of the rationale for the various project-based activities implemented, details their key features and described the impact these activities have had on the students’ development of key skills

Gaussian process inference approximation for indoor pedestrian localisation

Clutter has a complex effect on radio propagation, and limits the effect- iveness of deterministic methods in wireless indoor positioning. In contrast, a Gaussian process ( GP ) can be used to learn the spatially correlated measurement error directly from training samples, and build a representation from which a position can be inferred. A method of exploiting GP inference to obtain measurement predictions from within a pose graph optimisation framework is presented. However, GP inference has a run-time complexity of O ( N 3 ) in the number of train- ing samples N , which precludes it from being called in each optimiser iteration. The novel contributions of this work are a method for building an approximate GP inference map and an O (1) bi-cubic interpolation strategy for sampling this map during optimisation. Using inertial, magnetic, signal strength and time-of- fl ight measurements between four anchors and a single mobile sensor, it is shown empirically that the presented approach leads to decimetre precision indoor pedestrian localisatio