Optimizing spin polarization in quantum dot vertical-gain structures through pump wavelength selection

Spintronic applications require an efficient injection of spin-polarized carriers. We study the maximally achievable spin polarization in InAs quantum dots in a vertical-cavity gain structure to be used in telecoms-wavelength vertical-external-cavity surface-emitting lasers via measurement of the Stokes parameter of the photoluminescence emission around 1290 nm. Using five pump wavelengths between 850 and 1070 nm, the observed spin polarization depends strongly on the pump wavelength with the highest polarization of nearly 5% found for excitation at 980 nm. This corresponds to an effective spin lifetime of 40 ps and is attributed to the dominant excitation of heavy holes only

Comparison of directional and diffused lighting for pixel-level segmentation of concrete cracks

Visual inspections of concrete infrastructure in low-light environments require external lighting to ensure adequate visibility. Directional lighting sources, where an image scene is illuminated with an angled lighting source from one direction, can enhance the visibility of surface defects in an image. This paper compares directional and diffused scene illumination images for pixel-level concrete crack segmentation. A novel directional lighting image segmentation algorithm is proposed, which applies crack segmentation image processing techniques to each directionally lit image before combining all images into a single output, highlighting the extremities of the defect. This method was benchmarked against two diffused lighting crack detection techniques across a dataset with crack widths typically ranging from 0.07 mm to 0.4 mm. When tested on cracked and uncracked data, the directional lighting method significantly outperformed other benchmarked diffused lighting methods, attaining a 10% higher true-positive rate (TPR), 12% higher intersection over union (IoU), and 10% higher F1 score with minimal impact on precision. Further testing on only cracked data revealed that directional lighting was superior across all crack widths in the dataset. This research shows that directional lighting can enhance pixel-level crack segmentation in infrastructure requiring external illumination, such as low-light indoor spaces (e.g., tunnels and containment structures) or night-time outdoor inspections (e.g., pavement and bridges)

Dysregulation of lipid metabolism in the liver of Tspo knockout mice

The translocator protein, TSPO, has been implicated in a wide range of cellular processes exerted from its position in the outer mitochondrial membrane from where it influences lipid metabolism and mitochondrial oxidative activity. Understanding how this protein regulates a profusion of processes requires further elucidation and to that end we have examined lipid metabolism and used an RNAseq strategy to compare transcript abundance in wildtype and Tspo knockout (KO) mouse liver. The levels of cholesterol, triglyceride and phospholipid were significantly elevated in the KO mouse liver. The expression of cholesterol homeostasis genes was markedly downregulated. Determination of the differential expression revealed that many genes were either up- or downregulated in the KO animals. However, a striking observation within the results was a decrease of transcripts for protein degradation proteins in KO animals while protease inhibitors were enriched. When the entire abundance data-set was analysed with CEMiTool, and revealed a module of proteins that were under-represented in the KO animals. These could subsequently be formed into a network comprising three interlinked clusters at the centre of which were proteins of cytoplasmic ribosomes with gene ontology terms suggesting impairment to translation. The largest cluster was dominated by proteins of lipid metabolism but also contained disparate systems of iron metabolism and behaviour. The third cluster was dominated by proteins of the electron transport chain and oxidative phosphorylation. These findings suggest that TSPO contributes to lipid metabolism, detoxification of active oxygen species and oxidative phosphorylation, and regulates mitochondrial retrograde signalling

Covariance density neural networks

Graph neural networks have re-defined how we model and predict on network data but there lacks a consensus on choosing the correct underlying graph structure on which to model signals. CoVariance Neural Networks (VNN) address this issue by using the sample covariance matrix as a Graph Shift Operator (GSO). Here, we improve on the performance of VNNs by constructing a Density Matrix where we consider the sample Covariance matrix as a quasi-Hamiltonian of the system in the space of random variables. Crucially, using this density matrix as the GSO allows components of the data to be extracted at different scales, allowing enhanced discriminability and performance. We show that this approach allows explicit control of the stability-discriminability trade-off of the network, provides enhanced robustness to noise compared to VNNs, and outperforms them in useful real-life applications where the underlying covariance matrix is informative. In particular, we show that our model can achieve strong performance in subject-independent Brain Computer Interface EEG motor imagery classification, outperforming EEGnet while being faster. This shows how covariance density neural networks provide a basis for the notoriously difficult task of transferability of BCIs when evaluated on unseen individuals

Comparing the chatter characteristic in milling of Ti6Al4V alloy with and without laser assistance

Laser-assisted machining (LAM) is a promising technique to enhance the machinability of difficult-to-cut materials. However, many challenges remain for its practical engineering application, despite extensive research on the material removal mechanism in LAM. One key challenge is to elucidate how the laser affects the machining dynamics (e.g. cutting forces and chatter characteristics) and machined qualities in realistic machining scenarios. Therefore, this study aims to investigate the relationship between chatter characteristics and laser assistance in milling processes. Two sets of milling experiments with different depths of cut were conducted on wedge-shaped Ti6Al4V alloys with and without laser assistance. The milling forces were measured and analyzed using Short-time Fourier transforms and Wavelet transforms to detect chatter in frequency and time-frequency domains. Moreover, four indicators (i.e., standard deviation, Kurtosis, fuzzy entropy, envelope entropy) were extracted to monitor the milling conditions. The results showed that dry milling experienced a transition from stable machining to slight chatter at an axial depth of cut (ADOC) of 1.75 µm and then to severe chatter at ADOC=4.63 µm under the same cutting parameters, while LAM only exhibited slight chatter at ADOC=4.00 µm, demonstrating the specific effect of laser assistance on suppressing chatter. This was further confirmed by the observed surface morphology and roughness

Scotland’s Assets for Epidemic Preparedness : Workshop at the University of Strathclyde

MOSAEC (Mobilising Scotland's Assets in equitable ways for Epidemic Control) seeks to develop interdisciplinary research ideas and teams that will ensure we are better prepared for future epidemics. The focus of this workshop was on Scotland’s assets and how these can be used to improve epidemic preparedness and reduce inequalities. A series of presentations provided context for the diverse assets employed in epidemic response with discussions around previous use of assets, opportunities to employ other assets and the steps needed to operationalise key assets

UK APAP R-matrix electron-impact excitation cross-sections for modelling laboratory and astrophysical plasma

Systematic R-matrix calculations of electron-impact excitation for ions of astrophysical interest have been performed since 2007 for many iso-electronic sequences as part of the UK Atomic Process for Astrophysical Plasma (APAP) network. Rate coefficients for Maxwellian electron distributions have been provided and used extensively in the literature and many databases for astrophysics. Here, we provide averaged collision strengths to be used to model plasma where electrons are non-Maxwellian, which often occurs in laboratory and astrophysical plasma. We also provide many new Maxwellian-averaged collision strengths, which include important corrections to the published values. Recently, we made available the H- and He-like collision strengths. Here, we provide data for ions of the Li-, Be-, B-, C-, N-, O-, Ne-, Na-, and Mg-like sequences

Absolute rate coefficients for dielectronic recombination of sodium-like iron ions : experiment and theory

Absolute dielectronic recombination (DR) rate coefficients for sodium-like Fe15+ forming magnesium-like Fe14+ have been measured using the electron–ion merged-beams technique at the heavy ion storage ring Main Cooler Storage Ring, Lanzhou. The measured DR rate coefficients in the energy range from 0 to 90 eV cover all of the DR resonances due to 3s → 3p and 3s → 3d (Δn = 0) transitions and part of the DR resonances from 3s → 4ℓ (Δn = 1) core excitation. The experimental results are compared with theoretical calculations by using three independent state-of-the-art perturbative techniques: a multiconfiguration Breit–Pauli method using the AUTOSTRUCTURE code, a relativistic configuration interaction method using the Flexible Atomic Code and a multiconfiguration Dirac–Fock method using the Jena Atomic Calculator codes. Our theoretical results show excellent agreement with the experimental data in the energy range of 0–40 eV. However, in the energy range of 40–90 eV, a discrepancy is observed between the experiment and theory. Furthermore, temperature-dependent plasma recombination rate coefficients are derived from the measured DR rate coefficients over the temperature range of 103–108 K and are compared with previously available results in the literature. Within the temperature ranges relevant to photoionized plasmas and collisionally ionized plasmas, our results show good agreement with the experimental result from S. Schippers et al. (2010), as well as with the theoretical data of M. F. Gu (2004) and Z. Altun et al.; however, the earlier theoretical data from M. Arnaud & J. Raymond and P. Mazzotta et al., which are based on LS-coupling calculations, significantly underestimate the plasma rate coefficients in the low-temperature range. The present results provide a benchmark data set for astrophysical modeling

Enhanced interfacial thermal transport in diamond nanothread reinforced polymer nanocomposites : insights from atomistic simulations and density functional theory

Diamond nanothreads (DNTs), a novel class of nanomaterials that outperform traditional carbon-based nanomaterials, are exceptional reinforcers for advanced polymer composites and hold great promise in various applications of composites. In this atomistic simulation study, the novelty lies in the comprehensive exploration of DNT–polymer interfacial thermal conductance and the identification of methyl functionalization as a superior strategy, with clear implications for designing advanced thermal management composites. It is found that DNTs, derived from surface modifications (i.e. hydrogenation and functionalization) of carbon nanotubes (CNTs) with a chirality of (3, 0), demonstrate significantly enhanced interfacial thermal conductance in nanocomposite systems compared to unmodified CNTs. In particular, the incorporation of DNT_C-CH3 achieves the highest interfacial thermal conductance of 0.115 GW m−2 K−1, signifying a 140% improvement over CNTs. Through analyzing the phonon density of states (PDOS) of different reinforcements and a paraffin wax matrix, it is revealed that the low-frequency (0–70 THz) phonons dominate the interfacial thermal conductance due to their more significant contribution compared to the high-frequency (70–120 THz) phonons. Among all interfacial material combinations, DNT_C-CH3/paraffin wax exhibits the best matching in terms of the PDOS overlap, the PDOS peak intensity and the PDOS peak position in the low-frequency regime, which facilitates the most effective phonon transport across the interface and thereby leads to significant enhancement in interfacial thermal conductance. Furthermore, density functional theory (DFT) calculations uncover the optimal molecular electrostatic potential distribution and the highest binding energy of DNT_C-CH3/paraffin wax molecular structures, indicating excellent interfacial compatibility and strong adhesion between the reinforcement and the matrix material, which plays an important role in enhancing the interfacial thermal conductance. The findings of this study not only deepen the understanding of the physical mechanisms governing interfacial thermal conductance but also highlight the great potential of DNT reinforced composites in advanced thermal management applications

Semantic gaussian splatting-enhanced facility management within the framework of IFC-graph

The indoor environment of as-built structures undergo modifications over time, deviating from their original design and complicating facility management. Existing methods struggle to produce high-fidelity 3D models to represent that change. Gaussian splatting, a recent reconstruction technique, enables real-time rendering with high visual quality, offering a promising solution. This paper proposes a method that generates semantic Gaussian splats from panoramic images and integrates them into an IFC-graph for facility management. The approach enhances facility recognition and retrieval while enabling high-fidelity rendering of indoor environments. A case study demonstrates two key applications: semantic-guided facility retrieval and high-fidelity rendering, improving the semantic richness and visual quality of as-built BIM models