Sector skills insights : construction

The UK Commission for Employment and Skills is a social partnership, led by Commissioners from large and small employers, trade unions and the voluntary sector. Our mission is to raise skill levels to help drive enterprise, create more and better jobs and promote economic growth. Our strategic objectives are to: • Provide outstanding labour market intelligence which helps businesses and people make the best choices for them; • Work with businesses to develop the best market solutions which leverage greater investment in skills; • Maximise the impact of employment and skills policies and employer behaviour to support jobs and growth and secure an internationally competitive skills base. These strategic objectives are supported by a research programme that provides a robust evidence base for our insights and actions and which draws on good practice and the most innovative thinking. The research programme is underpinned by a number of core principles including the importance of: ensuring ‘relevance ’ to our most pressing strategic priorities; ‘salience ’ and effectively translating and sharing the key insights we find; internationa

ViewRefer: Grasp the Multi-view Knowledge for 3D Visual Grounding with GPT and Prototype Guidance

Understanding 3D scenes from multi-view inputs has been proven to alleviate the view discrepancy issue in 3D visual grounding. However, existing methods normally neglect the view cues embedded in the text modality and fail to weigh the relative importance of different views. In this paper, we propose ViewRefer, a multi-view framework for 3D visual grounding exploring how to grasp the view knowledge from both text and 3D modalities. For the text branch, ViewRefer leverages the diverse linguistic knowledge of large-scale language models, e.g., GPT, to expand a single grounding text to multiple geometry-consistent descriptions. Meanwhile, in the 3D modality, a transformer fusion module with inter-view attention is introduced to boost the interaction of objects across views. On top of that, we further present a set of learnable multi-view prototypes, which memorize scene-agnostic knowledge for different views, and enhance the framework from two perspectives: a view-guided attention module for more robust text features, and a view-guided scoring strategy during the final prediction. With our designed paradigm, ViewRefer achieves superior performance on three benchmarks and surpasses the second-best by +2.8%, +1.5%, and +1.35% on Sr3D, Nr3D, and ScanRefer.Comment: Accepted by ICCV 202

TerrainNet: Visual Modeling of Complex Terrain for High-speed, Off-road Navigation

Effective use of camera-based vision systems is essential for robust performance in autonomous off-road driving, particularly in the high-speed regime. Despite success in structured, on-road settings, current end-to-end approaches for scene prediction have yet to be successfully adapted for complex outdoor terrain. To this end, we present TerrainNet, a vision-based terrain perception system for semantic and geometric terrain prediction for aggressive, off-road navigation. The approach relies on several key insights and practical considerations for achieving reliable terrain modeling. The network includes a multi-headed output representation to capture fine- and coarse-grained terrain features necessary for estimating traversability. Accurate depth estimation is achieved using self-supervised depth completion with multi-view RGB and stereo inputs. Requirements for real-time performance and fast inference speeds are met using efficient, learned image feature projections. Furthermore, the model is trained on a large-scale, real-world off-road dataset collected across a variety of diverse outdoor environments. We show how TerrainNet can also be used for costmap prediction and provide a detailed framework for integration into a planning module. We demonstrate the performance of TerrainNet through extensive comparison to current state-of-the-art baselines for camera-only scene prediction. Finally, we showcase the effectiveness of integrating TerrainNet within a complete autonomous-driving stack by conducting a real-world vehicle test in a challenging off-road scenario

THUNDER: A reference-free deconvolution method to infer cell type proportions from bulk Hi-C data

Hi-C data provide population averaged estimates of three-dimensional chromatin contacts across cell types and states in bulk samples. Effective analysis of Hi-C data entails controlling for the potential confounding factor of differential cell type proportions across heterogeneous bulk samples. We propose a novel unsupervised deconvolution method for inferring cell type composition from bulk Hi-C data, the Two-step Hi-c UNsupervised DEconvolution appRoach (THUNDER). We conducted extensive simulations to test THUNDER based on combining two published single-cell Hi-C (scHi-C) datasets. THUNDER more accurately estimates the underlying cell type proportions compared to reference-free methods (e.g., TOAST, and NMF) and is more robust than reference-dependent methods (e.g. MuSiC). We further demonstrate the practical utility of THUNDER to estimate cell type proportions and identify cell-type-specific interactions in Hi-C data from adult human cortex tissue samples. THUNDER will be a useful tool in adjusting for varying cell type composition in population samples, facilitating valid and more powerful downstream analysis such as differential chromatin organization studies. Additionally, THUNDER estimated contact profiles provide a useful exploratory framework to investigate cell-type-specificity of the chromatin interactome while experimental data is still rare

Chiral structures and defects of lyotropic chromonic liquid crystals induced by saddle-splay elasticity

An experimental and theoretical study of lyotropic chromonic liquid crystals (LCLCs) confined in cylinders with degenerate planar boundary conditions elucidates LCLC director configurations. When the Frank saddle-splay modulus is more than twice the twist modulus, the ground state adopts an inhomogeneous escaped-twisted configuration. Analysis of the configuration yields a large saddle-splay modulus, which violates Ericksen inequalities but not thermodynamic stability. Lastly, we observe point defects between opposite-handed domains, and we explain a preference for point defects over domain wallsclose3

Differential Apoptosis Radiosensitivity of Neural Progenitors in Adult Mouse Hippocampus

Mammalian tissue-specific stem cells and progenitors demonstrate differential DNA damage response. Neural progenitors in dentate gyrus of the hippocampus are known to undergo apoptosis after irradiation. Using a mouse model of hippocampal neuronal development, we characterized the apoptosis sensitivity of the different neural progenitor subpopulations in adult mouse dentate gyrus after irradiation. Two different bromodeoxyuridine incorporation paradigms were used for cell fate mapping. We identified two apoptosis sensitive neural progenitor subpopulations after irradiation. The first represented non-proliferative and non-newborn neuroblasts and immature neurons that expressed doublecortin, calretinin or both. The second consisted of proliferative intermediate neural progenitors. The putative radial glia-like neural stem cells or type-1 cells, regardless of proliferation status, were apoptosis resistant after irradiation. There was no evidence of radiation-induced apoptosis in the absence of the Trp53 (p53) gene but absence of Cdkn1a (p21) did not alter the apoptotic response. Upregulation of nuclear p53 was observed in neuroblasts after irradiation. We conclude that adult hippocampal neural progenitors may demonstrate differential p53-dependent apoptosis sensitivity after irradiation

Differential Apoptosis Radiosensitivity of Neural Progenitors in Adult Mouse Hippocampus

Mammalian tissue-specific stem cells and progenitors demonstrate differential DNA damage response. Neural progenitors in dentate gyrus of the hippocampus are known to undergo apoptosis after irradiation. Using a mouse model of hippocampal neuronal development, we characterized the apoptosis sensitivity of the different neural progenitor subpopulations in adult mouse dentate gyrus after irradiation. Two different bromodeoxyuridine incorporation paradigms were used for cell fate mapping. We identified two apoptosis sensitive neural progenitor subpopulations after irradiation. The first represented non-proliferative and non-newborn neuroblasts and immature neurons that expressed doublecortin, calretinin or both. The second consisted of proliferative intermediate neural progenitors. The putative radial glia-like neural stem cells or type-1 cells, regardless of proliferation status, were apoptosis resistant after irradiation. There was no evidence of radiation-induced apoptosis in the absence of the Trp53 (p53) gene but absence of Cdkn1a (p21) did not alter the apoptotic response. Upregulation of nuclear p53 was observed in neuroblasts after irradiation. We conclude that adult hippocampal neural progenitors may demonstrate differential p53-dependent apoptosis sensitivity after irradiation