Heriot-Watt University
  • Scotland, United Kingdom
Recent publications
Membrane materials might be used for face protection because they can decontaminate the inhaled air from particle pollution and viruses like the SARS-Cov0-2 which damages our respiration system. In this study, plyethersulfone membranes (PES) were synthesized with green solvent at room temperature and its filtration effectiveness was investigated against nano-bacteria (size 0.05 to 0.2 µm) by measuring their Bacterial Filtration Efficiency (BFE) and micro aerosol size (0.3 µm), and Particulate Filtration Efficiency (PFE). The average SARS-CoV-2 diameters are between 50 nm to 160 nm. A series of experiments were performed to accomplish between 0.03 to 0.21 µm PES sponge like diameters so that can be used for SARS-CoV-2 filtration. Results showed that nanofiltration/ultrafiltration could filter 99.9% of bacteria and aerosol from contaminated air the size of the Covid-19 molecule.
We report on a room temperature Kerr-lens mode-locked chromium-doped zinc selenide (Cr:ZnSe) laser emitting four optical-cycles pulses in the mid-infrared spectral region in which the laser polycrystal has been treated by hot isostatic pressing (HIP). The laser emits 34 fs pulses at 2.4 μm, with a repetition rate of 171 MHz and average output power capabilities of up to 150 mW. This is the first mode-locking investigation conducted using the HIP treated material and to our knowledge, is the shortest pulse width demonstrated, to date, from polycrystalline Cr:ZnSe. The experimental comparison with respect to an untreated polycrystal indicates that HIP treatment is advantageous for mode-locking action of this active material.
Rainfall simulators have been used extensively for a variety of research applications. The uniformity and spatial distribution of simulated rainfall is an important metric to consider when conducting rainfall simulator experiments. Over the past 80 years, several methods of assessing rainfall distribution and uniformity over the plot surface below a rainfall simulator have been developed. However, the Christiansen Uniformity Coefficient (CU; Christiansen, 1942) is most frequently used. Here, we provide a critique of this established methodology and metric for quantifying rainfall distribution characteristics. Uniformity coefficients express the distribution of rainfall across the plot surface as a single percentage value. Therefore, if all collection beakers receive equal volumes of water during an experimental run, the rainfall simulator or irrigation system would be applying water with 100% uniformity. There are shortcomings with using a single percentage value to represent rainfall simulator rainfall distribution, especially over a larger plot surface, and CU is highly dependent on the sampling methodology employed. This paper assesses rainfall uniformity by conducting a series of controlled uniformity experiments and resampling different grid layouts of collection containers. Results demonstrate that the coarseness of the sampling methodology affects rainfall uniformity coefficient values. CU values of 45 – 51% were recorded under a dense (17 × 17) sampling grid layout, compared to CU values of 81% using a coarser (8 × 8) sampling methodology, despite being subjected to comparable rainfall events. This paper explores the sensitivity of CU to the resolution and spatial layout of the sampling methodology used and assesses whether the CU captures repeatability and localised variability of uniformity between experimental runs. A complementary statistical approach expressing variations in relation to their standard deviation from the mean is presented. Understanding how experimental setup (i.e. number, density, spatial configuration of collection containers) affects CU is critical when interpreting results from different rainfall simulator studies and an understanding of the factors which influence CU is critical to benchmark the results of uniformity testing across different rainfall simulator setups.
Permeability governs the fluid flow of hydrate-bearing sediment and affects the efficiency of natural gas production from hydrate reservoirs. The permeability in hydrate-bearings sediments is estimated empirically and appears to vary widely for sediments. This study focused on the sandy hydrate-bearing sediments and intended to elucidate the evolution of effective permeability by the mean of pore network modeling. A hydrate kinetics theory-based pore network model (KT-PNM) has been developed, in which the simulation of hydrate formation in porous media is implemented by employing two sub-processes, i.e., hydrate nucleation and hydrate growth. This KT-PNM has been applied to simulate hydrate formation in different pore networks. The permeability reduction exponent (N) for sandy hydrate-bearing sediments is determined to fall in the range of 3–4 based on the simulations of seven sandy samples. An empirical equation used for predicting the effective permeability in sandy hydrate-bearing sediments has been further proposed. The developed model and simulations are hoped to provide valuable insights of pore-space effects on hydrate into permeability prediction for studying the fluid seepage in hydrate-bearing sediments and facilitate the numerical simulation of gas production from the hydrate reservoirs.
Effective knowledge recontextualization is key to successful knowledge transfer in cross-cultural context. This paper explores how returnee entrepreneurs in Vietnam learn to recontextualize their overseas knowledge while establishing new ventures back in their home country. Our dynamic learning process model suggests that (1) in the pre-founding phase, an interactive vicarious learning and intuitive learning mechanism enables returnees to make sense of overseas knowledge; (2) during the founding phase, blended learning mechanism – the balancing act between market response versus market imposing - helps returnees manage the paradoxical cross cultural tension, importantly (3) in the growth phase, the cycling between unlearning and relearning helps them discard, select and recreate new knowledge in the pursuit of sustainable entrepreneurial growth. The study advances the literature on knowledge recontextualization by clarifying key underpinning learning mechanisms essential for ensuring “effectiveness” outcomes. It also contributes to the work on returnee entrepreneurship and entrepreneurial learning by demonstrating how international entrepreneurs learn overtime to thrive in a conflicting cultural context.
Petroleum resource development generates a legacy of energy wells that must be decommissioned effectively as we transition towards NetZero. Unfortunately, some decommissioned wells (DWs) can suffer integrity failure resulting in release of fugitive natural gas into the surrounding soils and atmosphere. After decommissioning there are typically no ongoing assessments to confirm well integrity, meaning integrity status remains uncertain into the future. Furthermore, factors affecting fugitive natural gas migration in surficial soils around DWs are poorly recognized, inferring integrity assessment and monitoring strategies are lacking. To better understand the integrity status of DWs, identify soil properties controlling fugitive gas migration and help develop more effective monitoring and detection methodologies, we undertook field investigations at six DWs in England involving surficial CH4 measurements, sub-surface soil-gas and sediment sampling and dynamic flux-chamber measurements. We found no evidence of integrity failure at any site. However, the composition and structure of soils in which examined DWs are embedded suggest fugitive gas migration to surface may be severely limited; potentially mitigating methane emissions while making integrity assessment at the surface challenging. Overall, the integrity status of DWs in England is poorly constrained and we show surficial soil properties must be characterised and considered to effectively constrain the fate of fugitive gas and in order to design effective field assessment and monitoring methods.
Words that sound similar tend to have similar meanings, at a distributed, sub-symbolic level (Monaghan, Shillcock, Christiansen, & Kirby, 2014). We extend this paradigm for measuring systematicity to letters and their canonical pronunciations. We confirm that orthographies that were consciously constructed to be systematic (Korean and two shorthand writing systems) yield significant correlations between visual distances between characters and the corresponding phonological distances between canonical pronunciations. We then extend the approach to Arabic, Hebrew, and English and show that letters that look similar tend to sound similar in their canonical pronunciations. We indicate some of the implications for education, and for understanding typical and atypical reading. By using different visual distance metrics we distinguish between symbol-based (Korean, shorthand) and effort-based (Arabic, Hebrew, English) grapho-phonemic systematicity. We reinterpret existing demonstrations of phono-semantic systematicity in terms of cognitive effort.
The United Nations Climate Change Conference COP26 held in 2021 concluded a global effort to hasten the energy transition toward a net-zero emission industry. As such, green initiatives, which transition the conventional oil and gas (O&G) sector towards a circular economy (CE) are necessary. In this work, the integration of waste oil re-refining technology is proposed as a potential strategy to enhance the circularity of the O&G industry. A two-step sequential model, which incorporates multiple systematic analytical tools (e.g., multi-objective decision analysis, information entropy, geospatial information, clustering, and routing analysis) is developed to determine: (i) optimal waste oil re-refinery technologies, and (ii) optimal supply chain design, which addresses the location for setting up the process facilities and the delivery routes, with the consideration of both economic and environmental performances. The effectiveness of the proposed strategy is demonstrated through a case study in Malaysia (that covers both East and West Malaysia). The analysis showed that the proposed strategy is capable of improving economic and environmental performances by about 9.59% and 46.55%, respectively. This work is essentially a useful reference for decision-makers and policymakers in making nationwide transition planning in the O&G sector.
The brine-dependent recovery process mainly known as low salinity/ smart water injection (LSWI/SWI) is of great interest to the oil industry for enhanced oil recovery (EOR), especially for carbonate reservoirs due to their complex rock properties. In-depth understanding of fluid/ carbonate rock interactions helps to better understand carbonate reservoirs’ behavior with respect to low salinity water injection. Mineral dissolution/ precipitation and multi-ion exchange (MIE) are generally known to be key factors in brine/ carbonate interactions, controlling the rock wettability and consequently the performance of low salinity water injection. However, the effect of the aforementioned mechanisms is not fully understood. In this paper we investigate the carbonate/ brine interactions, using geochemical modelling, and study the competition between all active mechanisms which results in an optimum point in water salinity. This optimum point is the best salinity of injected water, leading to the most effective alteration in the wettability towards the water-wet conditions. The simulation outputs are then validated against experimental results previously reported. Finally, a sensitivity analysis of the potential determining ions (PDIs) e.g., calcium, magnesium, and sulfate is performed to systematically understand the effect of each ion on optimum water salinity. Generally, for rocks containing anhydrite, both MIE and dissolution curves have a monotonous trend. However, for free-anhydrite rocks, MIE considered as the dominant mechanism controlling the performance of low salinity water injection. MIE mechanism mainly depends on CaSO4- surface concentration and as sulfate concentration increases a higher fold of dilution would result in a better performance of LSWI. However, calcium and magnesium have not shown significant influence on the dissolution and MIE mechanisms.
Plain Language Summary Natural gas leaking from imperfectly sealed oil and gas wells can lead to explosive conditions in soil gas and methane emissions to the atmosphere. To understand the impacts and improve monitoring practices of fugitive gas migration, there is a need to characterize processes that control gas transport and fate in the unsaturated zone. We simulated subsurface wellbore leakage by injecting natural gas into thick unsaturated deposits in a region of petroleum development in Western Canada. The response was monitored by measuring methane and carbon dioxide concentrations and emissions on the ground surface and in soil gas in the unsaturated zone. Our results show that numerous compounding processes influence methane concentrations in the unsaturated zone and emissions to the atmosphere. While microbially mediated reactions consume methane in the unsaturated zone, variations in soil grain sizes and changes in barometric pressure strongly influence gas transport, which can lead to high episodic emissions in unpredictable locations. To accurately detect, quantify and assess fugitive gas migration at oil and gas well sites, adequate site characterization and continuous, spatially dense monitoring are necessary.
Light detection and ranging (LiDAR) odometry plays a crucial role in autonomous mobile robots and unmanned ground vehicles (UGVs). This paper presents a deep learning–based odometry system using two successive three-dimensional (3D) point clouds to estimate their scene flow and then predict their relative pose. The network consumes continuous 3D point clouds directly and outputs their scene flow and uncertain mask in a coarse-to-fine fashion. A pose estimation layer without trainable parameters is designed to compute the pose with the scene flow. We also introduce a scan-to-map optimization algorithm to enhance the robustness and accuracy of the system. Our experiments on the KITTI odometry data set and our campus data set demonstrate the effectiveness of the proposed deep learning–based point cloud odometry.
In this paper we prove a regularity and rigidity result for displacements in $$GSBD^p$$ G S B D p , for every $$p>1$$ p > 1 and any dimension $$n\ge 2$$ n ≥ 2 . We show that a displacement in $$GSBD^p$$ G S B D p with a small jump set coincides with a $$W^{1,p}$$ W 1 , p function, up to a small set whose perimeter and volume are controlled by the size of the jump. This generalises to higher dimension a result of Conti, Focardi and Iurlano. A consequence of this is that such displacements satisfy, up to a small set, Poincaré-Korn and Korn inequalities. As an application, we deduce an approximation result which implies the existence of the approximate gradient for displacements in $$GSBD^p$$ G S B D p .
Tourism research has yet to consider the growing esport sector. Through a mixed-method research design, we employ the theoretical lens of fandom to examine what online and experiential factors may influence esport players and spectators to attend physical events, which we argue have the potential to grow into a new tourism sub-sector. Study one surveys 549 League of Legends spectators; while study two consists of a twelve-month virtual ethnography on World of Warcraft coupled with 13 player interviews. We find antecedents such as star players, team loyalty, flow experiences, and self-congruity with event image may encourage live event attendance. Furthermore, our findings emphasise the importance of social and interactive experiences in generating friendship and a perceptual sense of belonging at events. Community socialisation is a fundamental tenet of fandom and plays a key role in intentions to attend esport events.
Recently, a series of experimental tests and accompanying numerical studies has been conducted on austenitic and duplex stainless steel moment resisting connections which highlighted both the excellent ductility and significant overstrength exhibited by such connections as well as the severe conservatism of current design rules specified in EN 1993-1-8 when applied to stainless steel joints. This study builds upon a previous experimental research on bolted austenitic and duplex stainless steel T-stubs in tension conducted by the authors and reports in depth the development and validation of an advanced FE model able to predict the overall behaviour, failure modes and fracture mechanisms of bolted T-stubs in tension. Key simulation strategies regarding the explicit modelling of bolt geometry and overcoming numerical instabilities are discussed and recommendations on best modelling practices are made. The model is utilised thereafter to conduct parametric studies on austenitic, duplex and ferritic stainless steel T-stubs of various geometric configurations, thus investigating the effect of plate thickness, material grade, bolt spacing and bolt strength on the joint plastic resistance, ultimate capacity, ductility as well as overall response. Based on the obtained results, the design provisions of EN 1993-1-8 are assessed.
Although occupancy information is critical to energy consumption of existing buildings, it still remains to be a major source of uncertainty. For reliable and accurate occupant modeling with minimal uncertainties, capturing precise occupant information on occupants is essential. This paper proposes a computer vision-based approach that utilizes deep learning architectures to estimate of the number of people in large, crowded spaces using multiple cameras. Various vision techniques (head detection, background elimination, head tracking) are implemented in three methods: (i) a method that instantaneously counts people in a scene, (ii) a method that incrementally counts people entering/exiting a room and (iii) a combination of the first two methods. These methods were applied in a classroom with heavy occlusions, and resulted in a high prediction capacity when compared to ground truth measurements. Future work in video-analytical approaches can address problems regarding lowering the computational cost of analysis, capturing occupancy data in complex room geometries and addressing concerns in privacy preservation.
Peripersonal space (PPS), the space closely surrounding the body, is typically characterised by enhanced multisensory integration. Neurophysiological and behavioural studies have consistently shown stronger visuo-tactile integration when a visual stimulus is presented close to the tactually stimulate body part in near space (within PPS) than in far space. However, in the majority of these studies, tactile stimuli were delivered to the upper limbs, torso and face. Therefore, it is not known whether the space surrounding the lower limbs is characterised by similar multisensory properties. To address this question, we asked participants to complete two versions of the classic visuo-tactile crossmodal congruency task in which they had to perform speeded elevation judgements of tactile stimuli presented to the dorsum of the hand and foot while a simultaneous visual distractor was presented at spatially congruent or incongruent locations either in near or far space. In line with existing evidence, when the tactile target was presented to the hand, the size of the crossmodal congruency effect (CCE) decreased in far as compared to near space, suggesting stronger visuo-tactile multisensory integration within PPS. In contrast, when the tactile target was presented to the foot, the CCE decreased for visual distractors in near than far space. These findings show systematic differences between the representation of PPS around upper and lower limbs, suggesting that the multisensory properties of the different body part-centred representations of PPS are likely to depend on the potential actions performed by the different body parts.
Anointing is a behaviour in which animals apply pungent-smelling materials over their bodies. It can be done individually or socially in contact with others. Social anointing can provide coverage of body parts inaccessible to the individual, consistent with hypotheses that propose medicinal benefits. However, in highly social capuchin monkeys, Sapajus and Cebus spp., anointing has been suggested to also benefit group members through ‘social bonding’. To test this, we used social network analysis to measure changes in proximity patterns during and shortly after anointing compared to a baseline condition. We presented two capuchin groups with varying quantities of onion, which reliably induces anointing, to create ‘rare resource’ and ‘abundant resource’ conditions. We examined the immediate and overall effects of anointing behaviour on the monkeys' social networks, using patterns of proximity as a measure of social bonds. For one group, proximity increased significantly after anointing over baseline values for both rare and abundant resource conditions, but for the other group proximity only increased following the rare resource condition, suggesting a role in mediating social relationships. Social interactions were affected differently in the two groups, reflecting the complex nature of capuchin social organization. Although peripheral males anointed in proximity to other group members, the weak centrality only changed in one group following anointing bouts, indicating variable social responses to anointing. We suggest in part that anointing in capuchins is analogous to social grooming: both behaviours have an antiparasitic function and can be done individually or socially requiring contact between two or more individuals. We propose that they have evolved a social function within complex repertoires of social behaviours. Our alternative perspective avoids treating medicinal and social explanations as alternative hypotheses and, along with increasing support for the medical explanations for anointing, allows us to conceptualize social anointing in capuchins as ‘social medication’.
Backscatter communication, an emerging ultra‐low‐power wireless communication paradigm, has been studied as a promising solution for wireless communications in some Internet‐of‐Things (IoT) applications. The required ubiquitous data transmission in the IoT world is demanding information security. Different from mathematical encryption at higher protocol layers, the directional modulation (DM) technology can provide physical‐layer wireless security, which does not require digital and computation resources that are otherwise scarce in low‐power IoT devices. In this paper, a synthesis‐free Van‐Atta backscatter array is constructed and studied. The authors show that a Van‐Atta array can be made to project orthogonal interference upon the backscattered signals in the radio frequency domain. The design details of the Van‐Atta DM array are elaborated, and its efficacy is validated via bit error rate simulations.
Remote manipulation plays a key role for applications in hazardous conditions, yet designing a robust controller enabling safe interaction with unknown environment and under the influence of disturbances is a challenge. In this study, we propose effective control and optimization methods for mobile robotic manipulator systems that can increase effort transmission to a task in desired directions. The vehicle position is optimized by utilizing constrained particle swarm optimization where the objective is to enhance directional manipulability of the robotic arm within the system. A forward dynamic controller is implemented to eliminate undesired excessive motions near singular joint configurations. A reset control algorithm along with an admittance type controller are developed for stable interaction with an unknown object under environmental disturbances. The experimentally validated results show that the proposed method phase out undesired position disturbances and increase the directional manipulability for the required task enabling augmented effort transmission for the task execution.
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Yeaw Chu Lee
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Heriot-Watt University, Scotland, United Kingdom
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