A DFTB-Based Molecular Dynamics Investigation of an Explicitly Solvated Anatase Nanoparticle

We performed a self-consistent charge density functional tight-binding molecular dynamics (SCC DFTB-MD) simulation of an explicitly solvated anatase nanoparticle. From the 2 ps trajectory, we were able to calculate both dynamic and static properties, such as the energies of interaction and the formation of water layers at the surface, and compare them to the observed behaviour reported elsewhere. The high degree of agreement between our simulation and other sources, and the additional information gained from employing this methodology, highlights the oft-overlooked viability of DFTB-based methods for electronic structure calculations of large systems.

Online Machine Learning of Available Capacity for Vehicle-to-Grid Services during the Coronavirus Pandemic

Vehicle-to-grid services make use of the aggregated capacity available from a fleet of vehicles to participate in energy markets, help integrate renewable energy in the grid and balance energy use. In this paper, the critical components of such a service are described in the context of a commercial service that is currently under development. Key among these components is the prediction of available capacity at a future time. In this paper, we extend a previous work that used a deep learning recurrent neural network for this task to include online machine learning, which enables the network to continually refine its predictions based on observed behaviour. The coronavirus pandemic that was declared in 2020 resulted in closures of the university and substantial changes to the behaviour of the university fleet. In this work, the impact of this change in vehicles usage was used to test the predictions of a network initially trained using vehicle trip data from 2019 with and without online machine learning. It is shown that prediction error is significantly reduced using online machine learning, and it is concluded that a similar capability will be of critical importance for a commercial service such as the one described in this paper.

Selfie and Narcissism in Young Adults

Selfie, a commonly observed behaviour, is symbol of virtual identity. Similarly, narcissism as described by grandiose view of oneself, seeking approval and admiration on social media is also frequent. The purpose of this study is exploring selfie taking behaviour and narcissism among young adults. A total 132 subjects were considered for study through an online questionnaire which included demographic variables, selfie taking behaviour and NPI-16 (Narcissistic Personality Inventory -16). The results showed majority of the subjects N = 76 (57.5%) had high narcissism (NPI ≥ 7). Age group 15 to 25 years (p= 0.0200), males, subjects who stayed in city, post graduates or graduate qualification, and married subjects had high narcissism. Using smart phone use more than 5 years (p=0.00942), taking 5 to 10 selfies per day with (p=0.00331), posting selfie for personal memory (p=0.03268), selfie on WhatsApp messenger (p=0.03268) and taking selfie with person alone and selfie taken on specific occasions (p=0.01122), had high narcissism. The conclusion of this study is selfie and narcissism are closely linked among young adults and a matter of psychological wellbeing during personality development.

The impact of COVID-19 related regulations and restrictions on mobility and potential for sustained climate mitigation across the Netherlands, Sweden and the UK: A data-based commentary.

Human behaviour change is necessary to meet targets set by the Paris Agreement to mitigate climate change. Restrictions and regulations put in place globally to mitigate the spread of COVID-19 during 2020 have had a substantial impact on everyday life, including many carbon-intensive behaviours such as transportation. Changes to transportation behaviour may reduce carbon emissions. Behaviour change theory can offer perspective on the drivers and influences of behaviour and shape recommendations for how policy-makers can capitalise on any observed behaviour changes that may mitigate climate change. For this commentary, we aimed to describe changes in data relating to transportation behavioursrelating to working from home during the COVID-19 pandemic across the Netherlands, Sweden and the UK. We display these identified changes in a concept map, suggesting links between the changes in behaviour and levels of carbon emissions. We consider these changes in relation to a comprehensive and easy to understand model of behaviour, the COM-B, to understand the capabilities, opportunities and behaviours related to the observed behaviour changes and potential policy to mitigate climate change. There is now an opportunity for policy-makers to increase the likelihood of maintaining pro-environmental behaviour changes by providing opportunities, improving capabilities and maintaining motivation for these behaviours.

Popularity, novelty and relevance in point of interest recommendation: an experimental analysis

Recommender Systems (RSs) are often assessed in off-line settings by measuring the system precision in predicting the observed user’s ratings or choices. But, when a precise RS is on-line, the generated recommendations can be perceived as marginally useful because lacking novelty. The underlying problem is that it is hard to build an RS that can correctly generalise, from the analysis of user’s observed behaviour, and can identify the essential characteristics of novel and yet relevant recommendations. In this paper we address the above mentioned issue by considering four RSs that try to excel on different target criteria: precision, relevance and novelty. Two state of the art RSs called and follow a classical Nearest Neighbour approach, while the other two, and are based on Inverse Reinforcement Learning. and optimise precision, tries to identify the characteristics of POIs that make them relevant, and , a novel RS here introduced, is similar to but it also tries to recommend popular POIs. In an off-line experiment we discover that the recommendations produced by and optimise precision essentially by recommending quite popular POIs. can be tuned to achieve a desired level of precision at the cost of losing part of the best capability of to generate novel and yet relevant recommendations. In the on-line study we discover that the recommendations of and are liked more than those produced by . The rationale of that was found in the large percentage of novel recommendations produced by , which are difficult to appreciate. However, excels in recommending items that are both novel and liked by the users.

HYDROMECHANICAL BEHAVIOUR OF TWO UNSATURATED SILTS: LABORATORY DATA AND MODEL PREDICTIONS

This paper presents the results from a campaign of unsaturated and saturated isotropic tests performed on two compacted silts of different coarseness, namely a clayey silt and a sandy silt, inside triaxial cells. Some tests involved an increase/decrease of mean net stress at constant suction or an increase/decrease of suction at constant mean net stress. Other tests involved an increase of mean net stress at constant water content with measurement of suction. During all tests, the void ratio and degree of saturation were measured to investigate the mechanical and retention behaviour of the soil. The experimental results were then simulated by the bounding surface hydromechanical model of Bruno and Gallipoli (2019), which was originally formulated to describe the behaviour of clays and clayey silts. Model parameters were calibrated against unsaturated tests including isotropic loading stages at constant water content with measurement of varying suction. Loading at constant water content is relatively fast and allows the simultaneous exploration of large ranges of mean net stress and suction, thus reducing the need of multiple experiments at distinct suction levels. Predicted data match well the observed behaviour of both soils, including the occurrence of progressive yielding and hysteresis, which extends the validation of this hydromechanical model to coarser soils. Specific features of the unsaturated soil behaviour, such as wetting-induced collapse, are also well reproduced.

Development and investigation of the applicability of microstructural models for polymeric low density foams directly obtained from computed tomography data

Nowadays, there are several methods to obtain simulation models for foams which consider important microstructural features. This research study presents a method to obtain low density foam models directly from computed tomography (CT) data. Finite element meshes are created from CT measurement results of a polypropylene extrusion foam with two different densities. Sensitivity studies with regard to the tension behaviour are performed with the microstructural models. The study shows that the tension behaviour highly depends on the examined area of the foam because the microstructure and density vary through the foam. Furthermore, the simulation results are validated with experimental results. The validation shows that the tension behaviour of the investigated foams characterised by the simulation approach is in good agreement with the experimentally observed behaviour and that specific microstructural characteristics (e.g. anisotropic cell shapes) are captured in the model.

Challenges of Engineering the Hottest Subsea Heated Pipeline for the CRISP Project

Objectives/Scope The project was a 2km, electrically heat-traced, subsea pipe-in-pipe (PIP) system for transportation of a bitumen-like material across a shipping channel. Due to the viscosity of the bitumen, it must be transported at a minimum of 160°C; has a normal pipeline operating temperature of 200°C; and a design temperature is 228°C. Methods, Procedures, Process Due to the high operating temperature, pre-stressing and backfilling the PIP was required to lock in stresses at an intermediate pre-stressing temperature. The electrical heat-trace wires (installed to heat up the inner pipe and prevent setting of the bitumen during cooldowns) were used to achieve this pre-stressing during the fabrication process. The heating schedule causes high stress levels and require advanced engineering analyses to model the behaviour of the inner and outer pipe during the fabrication, installation, pre-stressing, and operation. The complex loading history of the inner pipe and the expansion spools was included in the global 3D, finite element (FE) models that were used to validate the pipeline profile, backfilling, pre-stressing temperature, and sequence of operations. Results, Observations, Conclusions The complex buckling behaviour of the inner pipe is presented and shown to be within DNV GL OS-F- 101 code limits. The end expansion during the various stages of pre-stressing is presented and compared to observed behaviour. The loads and stresses in the bulkheads are presented and shown to be acceptable. The analysis demonstrates that the pipeline system can be safely installed and operated up to the maximum design temperature of 228°C. Novel/Additive Information The project used pre-stressing by heating the inner pipe to an intermediate temperature before coupling the inner pipe to the outer pipe. The purpose of the pre-stressing was to manage the high axial stresses making it feasible to achieve the high design temperature of 228°C. Pre-expanding of the expansion spools at either end of the subsea pipelines was also used due to the space limitations. Innovative engineering analysis and construction methods were used to ensure the integrity of the inner pipe during the pre-stressing process and operation.

Family-specific chemical profiles provide potential kin recognition cues in the sexually cannibalistic spider Argiope bruennichi

Kin recognition, the ability to detect relatives, is important for cooperation, altruism and also inbreeding avoidance. A large body of research on kin recognition mechanisms exists for vertebrates and insects, while little is known for other arthropod taxa. In spiders, nepotism has been reported in social and solitary species. However, there are very few examples of kin discrimination in a mating context, one coming from the orb-weaver Argiope bruennichi . Owing to effective mating plugs and high rates of sexual cannibalism, both sexes of A. bruennichi are limited to a maximum of two copulations. Males surviving their first copulation can either re-mate with the current female (monopolizing paternity) or leave and search for another. Mating experiments have shown that males readily mate with sisters but are more likely to leave after one short copulation as compared with unrelated females, allowing them to search for another mate. Here, we ask whether the observed behaviour is based on chemical cues. We detected family-specific cuticular profiles that qualify as kin recognition cues. Moreover, correlations in the relative amounts of some of the detected substances between sexes within families indicate that kin recognition is likely based on subsets of cuticular substances, rather than entire profiles.