Au-Pd alloy nanoparticle catalyzed selective oxidation of benzyl alcohol and tandem synthesis of imines at ambient conditions

Alloy nanoparticles (NPs) of gold and palladium on ZrO2 support (Au–Pd@ZrO2) were found to be highly active in oxidation of benzyl alcohols and can be used for the tandem synthesis of imines from benzyl alcohols and amines via a one-pot, two-step process at mild reaction conditions. The first step of the process is oxidation of benzyl alcohol to benzaldehyde, excellent yields were achieved after 7 h reaction at 40 °C without addition of any base. In the second step, aniline was introduced into the reaction system to produced N-benzylideneaniline. The benzaldehyde obtained in the first step was completely consumed within 1 h. A range of benzyl alcohols and amines were investigated for the general applicability of the Au–Pd alloy catalysts. It is found that the performance of the catalysts depends on the Au–Pd metal contents and composition. The optimal catalyst is 3.0 wt% Au–Pd@ZrO2 with a Au:Pd molar ratio 1:1. The alloy NP catalyst exhibited superior catalytic properties to pure AuNP or PdNP because the surface of alloy NPs has higher charge heterogeneity than that of pure metal NPs according to simulation of density function theory (DFT)

Proteogenomics of selective susceptibility to endotoxin using circulating acute phase biomarkers and bioassay development in sheep: a review

Scientists have injected endotoxin into animals to investigate and understand various pathologies and novel therapies for several decades. Recent observations have shown that there is selective susceptibility to Escherichia coli lipopolysaccharide (LPS) endotoxin in sheep, despite having similar breed characteristics. The reason behind this difference is unknown, and has prompted studies aiming to explain the variation by proteogenomic characterisation of circulating acute phase biomarkers. It is hypothesised that genetic trait, biochemical, immunological and inflammation marker patterns contribute in defining and predicting mammalian response to LPS. This review discusses the effects of endotoxin and host responses, genetic basis of innate defences, activation of the acute phase response (APR) following experimental LPS challenge, and the current approaches employed in detecting novel biomarkers including acute phase proteins (APP) and micro-ribonucleic acids (miRNAs) in serum or plasma. miRNAs are novel targets for elucidating molecular mechanisms of disease because of their differential expression during pathological, and in healthy states. Changes in miRNA profiles during a disease challenge may be reflected in plasma. Studies show that gel-based two-dimensional electrophoresis (2-DE) coupled with either matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) or liquid chromatography-mass spectrometry (LC-MS/MS) are currently the most used methods for proteome characterisation. Further evidence suggests that proteomic investigations are preferentially shifting from 2-DE to non-gel based LC-MS/MS coupled with data extraction by sequential window acquisition of all theoretical fragment-ion spectra (SWATH) approaches that are able to identify a wider range of proteins. Enzyme-linked immunosorbent assay (ELISA), quantitative real-time polymerase chain reaction (qRT-PCR), and most recently proteomic methods have been used to quantify low abundance proteins such as cytokines. qRT-PCR and next generation sequencing (NGS) are used for the characterisation of miRNA. Proteogenomic approaches for detecting APP and novel miRNA profiling are essential in understanding the selective resistance to endotoxin in sheep. The results of these methods could help in understanding similar pathology in humans. It might also be helpful in the development of physiological and diagnostic screening assays for determining experimental inclusion and endpoints, and in clinical trials in future

Inertial sensor real-time feedback enhances the learning of cervical spine manipulation: A prospective study

Background Cervical Spinal Manipulation (CSM) is considered a high-level skill of the central nervous system because it requires bimanual coordinated rhythmical movements therefore necessitating training to achieve proficiency. The objective of the present study was to investigate the effect of real-time feedback on the performance of CSM. Methods Six postgraduate physiotherapy students attending a training workshop on Cervical Spine Manipulation Technique (CSMT) using inertial sensor derived real-time feedback participated in this study. The key variables were pre-manipulative position, angular displacement of the thrust and angular velocity of the thrust. Differences between variables before and after training were investigated using t-tests. Results There were no significant differences after training for the pre-manipulative position (rotation p = 0.549; side bending p = 0.312) or for thrust displacement (rotation p = 0.247; side bending p = 0.314). Thrust angular velocity demonstrated a significant difference following training for rotation (pre-training mean (sd) 48.9°/s (35.1); post-training mean (sd) 96.9°/s (53.9); p = 0.027) but not for side bending (p = 0.521). Conclusion Real-time feedback using an inertial sensor may be valuable in the development of specific manipulative skill. Future studies investigating manipulation could consider a randomized controlled trial using inertial sensor real time feedback compared to traditional training.

An anticipative reactive control strategy to deal with unforeseen obstacles during a multi-sensor-based navigation task

We address the problem of the rangefinder-based avoidance of unforeseen static obstacles during a visual navigation task. We extend previous strategies which are efficient in most cases but remain still hampered by some drawbacks (e.g., risks of collisions or of local minima in some particular cases, etc.). The key idea is to complete the control strategy by adding a controller providing the robot some anticipative skills to guarantee non collision and by defining more general transition conditions to deal with local minima. Simulation results show the proposed strategy efficiency.

Remote Sensing and Data Collection from Solar Powered Wireless Sensor Network using an Unmanned Aerial Vehicle System

Sensor networks for environmental monitoring present enormous benefits to the community and society as a whole. Currently there is a need for low cost, compact, solar powered sensors suitable for deployment in rural areas. The purpose of this research is to develop both a ground based wireless sensor network and data collection using unmanned aerial vehicles. The ground based sensor system is capable of measuring environmental data such as temperature or air quality using cost effective low power sensors. The sensor will be configured such that its data is stored on an ATMega16 microcontroller which will have the capability of communicating with a UAV flying overhead using UAV communication protocols. The data is then either sent to the ground in real time or stored on the UAV using a microcontroller until it lands or is close enough to enable the transmission of data to the ground station.

LiDAR Augmented Optimal Path Planning for Unmanned Aerial Vehicle during Remote Sensing at Low Altitude and Network Sensor Data Acquisition

This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.

Rapid, selective, and reversible Nitroxide Radical Coupling (NRC) reactions at amibient temperature

High activation of polystyrene with bromine end groups (PSTY-Br) to their incipient radicals occurred in the presence of Cu(I)Br, Me6TREN, and DMSO solvent. These radicals were then trapped by nitroxide species leading to coupling reactions between PSTY-Br and nitroxides that were ultrafast and selective in the presence of a diverse range of functional groups. The nitroxide radical coupling (NRC) reactions have the attributes of a “click” reaction with near quantitative yields of product formed, but through the reversibility of this reaction, it has the added advantage of permitting the exchange of chemical functionality on macromolecules. Conditions were chosen to facilitate the disproportionation of Cu(I)Br to the highly activating nascent Cu(0) and deactivating Cu(II)Br2 in the presence of DMSO solvent and Me6TREN ligand. NRC at room temperature gave near quantitative yields of macromolecular coupling of low molecular weight polystyrene with bromine chain-ends (PSTY-Br) and nitroxides in under 7 min even in the presence of functional groups (e.g., −≡, −OH, −COOH, −NH2, =O). Utilization of the reversibility of the NRC reaction at elevated temperatures allowed the exchange of chain-end groups with a variety of functional nitroxide derivatives. The robustness and orthogonality of this NRC reaction were further demonstrated using the Cu-catalyzed azide/alkyne “click” (CuAAC) reactions, in which yields greater than 95% were observed for coupling between PSTY-N3 and a PSTY chain first trapped with an alkyne functional TEMPO (PSTY-TEMPO-≡).

Alloying gold with copper makes for a highly selective visible-light photocatalyst for the reduction of nitroaromatics to anilines

Finely control of product selectivity is an essential issue in organic chemical production. In the synthesis of functionalized anilines via reduction of the corresponding nitroarenes, the challenge is to selectively reduce only the nitro group in the presence of other reducible functional groups in nitroarene molecules at a high reaction rate. Normally, the nitroarene is reduced stepwise through a series of intermediates that remain as byproducts, increasing the aniline synthesis cost. Here we report that alloying small amounts of copper into gold nanoparticles can alter the reaction pathway of the catalytic reduction under visible-light irradiation at ambient temperature, allowing nitroaromatics to be transformed directly to anilines in a highly selective manner. The reasons for the high efficiency of the photocatalytic reduction under these comparatively benign conditions as well as the light-excited reaction mechanisms are discussed. This photocatalytic process avoids byproducts, exhibits a high reaction rate and excellent substituent tolerance, and can be used for the synthesis of many useful functionalized anilines under environmentally benign conditions. Switching of the reaction pathway simply by tailoring the bimetallic alloy NPs of the photocatalysts is effective for engineering of product chemoselectivity.

Design and synthesis of novel 3-hydroxy-cyclobut-3-ene-1,2-dione derivatives as thyroid hormone receptor β (TR-β) selective ligands

Design and synthesis of a novel 3-hydroxy-cyclobut-3-ene-1,2-dione derivatives are reported and their in vitro thyroid hormone receptor selectivity has been evaluated in the thyroid luciferase receptor assay. The 3-[3,5-dichloro-4-(4-hydroxy-3-isopropylphenoxy)-phenylamino]-4-hydroxy-cyclobut-3-ene-1,2-dione 21 has shown selectivity towards thyroid hormone receptor β.

Elliptical summary randomisation for sensor-based human activity recognition

Many conventional statistical machine learning al- gorithms generalise poorly if distribution bias ex- ists in the datasets. For example, distribution bias arises in the context of domain generalisation, where knowledge acquired from multiple source domains need to be used in a previously unseen target domains. We propose Elliptical Summary Randomisation (ESRand), an efficient domain generalisation approach that comprises of a randomised kernel and elliptical data summarisation. ESRand learns a domain interdependent projection to a la- tent subspace that minimises the existing biases to the data while maintaining the functional relationship between domains. In the latent subspace, ellipsoidal summaries replace the samples to enhance the generalisation by further removing bias and noise in the data. Moreover, the summarisation enables large-scale data processing by significantly reducing the size of the data. Through comprehensive analysis, we show that our subspace-based approach outperforms state-of-the-art results on several activity recognition benchmark datasets, while keeping the computational complexity significantly low.

Surface-mediated selective photocatalytic aerobic oxidation reactions on TiO2 nanofibres

N-doped TiO2 nanofibres were observed to possess lower aerobic oxidation activity than undoped TiO2 nanofibres in the selective photocatalytic aerobic oxidation of enzylamine and 4-methoxybenzyl alcohol. This was attributed to the reduction free energy of O2 adsorption in the vicinity of nitrogen dopant sites, as indicated by density functional theory (DFT) calculations when three-coordinated oxygen atoms are substituted by nitrogen atoms. It was found that the activity recovered following a controlled calcination of the N-doped NFs in air. The dependence of the conversion of benzylamine and 4-methoxybenzyl alcohol on the intensity of light irradiation confirmed that these reactions were driven by light. Action spectra showed that the two oxidation reactions are responsive to light from the UV region through to the visible light irradiation range. The extended light absorption wavelength range in these systems compared to pure TiO2 materials was found to result from the formation of surface complex species following adsorption of reactants onto the catalysts' surface, evidenced by the in situ IR experiment. Both catalytic and in situ IR results reveal that benzaldehyde is the intermediate in the aerobic oxidation of benzylamine to N-benzylidenebenzylamine process.

Heterojunctions between amorphous and crystalline niobium oxide with enhanced photoactivity for selective aerobic oxidation of benzylamine to imine under visible light

The formation of heterojunctions between two crystals with different band gap structures, acting as a tunnel for the unidirectional transfer of photo-generated charges, is an efficient strategy to enhance photocatalytic performance in semiconductor photocatalysts. The heterojunctions may also promote the photoactivity in the visible-light-response of any surface complex catalysts by influencing the transfer of photo-generated electrons. Herein, Nb2O5 microfibers, with a high surface area of interfaces between an amorphous phase and crystalline phase, were designed and synthesised by the calcination of hydrogen-form niobate while controlling the crystallization The photoactivity of these microfibers towards selective aerobic oxidation reactions was investigated. As predicted, the Nb2O5 microfibres containing heterojunctions exhibited the highest photoactivity. This could be due to the band gap difference between the amorphous phase and the crystalline phase, which shortened the charge mobile distance and improved the efficiency.

Developing an Unmanned Aerial Vehicle (UAV) multi-sensor payload carrier for air quality monitoring

Emissions of gases and particles from sea-faring ships have been shown to impact on the atmospheric chemistry and climate. To efficiently monitor and report these emissions found from a ship’s plume, the concept of using a multi-rotor or UAV to hover inside or near the exhaust of the ship to actively record the data in real time is being developed. However, for the required sensors obtain the data; their sensors must face into the airflow of the ships plume. This report presents an approach to have sensors able to read in the chemicals and particles emitted from the ship without affecting the flight dynamics of the multi-rotor UAV by building a sealed chamber in which a pump can take in the surrounding air (outside the downwash effect of the multi-rotor) where the sensors are placed and can analyse the gases safely. Results show that the system is small, lightweight and air-sealed and ready for flight test.

Green Falcon IV: An Unmanned Aerial System and an integrated Wireless Sensor Network for remote sensing tasks

This report summarises the development of an Unmanned Aerial System and an integrated Wireless Sensor Network (WSN), suitable for the real world application in remote sensing tasks. Several aspects are discussed and analysed to provide improvements in flight duration, performance and mobility of the UAV, while ensuring the accuracy and range of data from the wireless sensor system.