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    A Numerical Model for Predicting Powder Characteristics in LMD Considering Particle Interaction

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    In this work, a numerical model is proposed to analyze the influence of particle-particle interaction in laser directed energy deposition or LMD (laser metal deposition) of CM247 Ni-based superalloy. The model is based on the analysis of contact between particles and the potential agglomeration of powder to predict powder conditions at the nozzle exit. Simulation results were experimentally validated and a good agreement was observed. At the nozzle exit mainly large particles (>100 µm) are found and small ones (<10 µm) tend to flow away from this region. This was also observed in the experimental PSD. Additionally, based on the relative velocity of particles, simulations are able to predict the formation of dents. In comparing virgin powder PSD and the one at the nozzle exit, it was observed that largest particles are collected at the exit. In order to explain this phenomena, particle agglomeration was analysed numerically. It was seen that small particles tend to adhere to the big ones due to their higher adhesive forces, which would explain the change in PSD

    Modelling stellar variability in archival HARPS data:I -- Rotation and activity properties with multi-dimensional Gaussian Processes

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    Although instruments for measuring the radial velocities (RVs) of stars now routinely reach sub-meter per second accuracy, the detection of low-mass planets is still very challenging. The rotational modulation and evolution of spots and/or faculae can induce variations in the RVs at the level of a few m/s in Sun-like stars. To overcome this, a multi-dimensional Gaussian Process framework has been developed to model the stellar activity signal using spectroscopic activity indicators together with the RVs. A recently published computationally efficient implementation of this framework, S+LEAF 2, enables the rapid analysis of large samples of targets with sizeable data sets. In this work, we apply this framework to HARPS observations of 268 well-observed targets with precisely determined stellar parameters. Our long-term goal is to quantify the effectiveness of this framework to model and mitigate activity signals for stars of different spectral types and activity levels. In this first paper in the series, we initially focus on the activity indicators (S-index and Bisector Inverse Slope), and use them to a) measure rotation periods for 49 slow rotators in our sample, b) explore the impact of these results on the spin-down of middle-aged late F, G & K stars, and c) explore indirectly how the spot to facular ratio varies across our sample. Our results should provide valuable clues for planning future RV planet surveys such as the Terra Hunting Experiment or the PLATO ground-based follow-up observations program, and help fine-tune current stellar structure and evolution models

    Unsupervised learning-based approach for detecting 3D edges in depth maps

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    3D edge features, which represent the boundaries between different objects or surfaces in a 3D scene, are crucial for many computer vision tasks, including object recognition, tracking, and segmentation. They also have numerous real-world applications in the field of robotics, such as vision-guided grasping and manipulation of objects. To extract these features in the noisy real-world depth data, reliable 3D edge detectors are indispensable. However, currently available 3D edge detection methods are either highly parameterized or require ground truth labelling, which makes them challenging to use for practical applications. To this extent, we present a new 3D edge detection approach using unsupervised classification. Our method learns features from depth maps at three different scales using an encoder-decoder network, from which edge-specific features are extracted. These edge features are then clustered using learning to classify each point as an edge or not. The proposed method has two key benefits. First, it eliminates the need for manual fine-tuning of data-specific hyper-parameters and automatically selects threshold values for edge classification. Second, the method does not require any labelled training data, unlike many state-of-the-art methods that require supervised training with extensive hand-labelled datasets. The proposed method is evaluated on five benchmark datasets with single and multi-object scenes, and compared with four state-of-the-art edge detection methods from the literature. Results demonstrate that the proposed method achieves competitive performance, despite not using any labelled data or relying on hand-tuning of key parameters.</p

    Histology independent drug development - Is this the future for cancer drugs?

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    The Cancer Drug Development Forum (CDDF)’s ‘Histology independent drug development – is this the future for cancer drugs?’ workshop was set up to explore the current landscape of histology independent drug development, review the current regulatory landscape and propose recommendations for improving the conduct of future trials.The first session considered lessons learnt from previous trials, including innovative solutions for reimbursement. The session explored why overall survival represents the most valuable endpoint, and the importance of duration of response, which can be captured with swimmer and spider plots.The second session on biomarker development and treatment optimisation considered current regulations for companion diagnostics, FDA guidance on histology independent drug development in oncology, and the need to establish cut-offs for the biomarker of tumour mutational burden to identify the patients most likely to benefit from PDL1 treatment.The third session reviewed novel trial designs, including basket, umbrella and platform trials, and statistical approaches of hierarchical modelling where homogeneity between study cohorts enables information to be borrowed between cohorts. The discussion highlighted the need to agree ‘common assessment standards’ to facilitate pooling of data across studies.In the fourth session, the sharing of data sets was recognised as a key step for improving equity of access to precision medicines across Europe. The session considered how the European Health Data Space (EHDS) could streamline access to medical records, emphasizing the importance of introducing greater accountability into the digital space.In conclusion the workshop proposed 11 recommendations to facilitate histology agnostic drug development.</p

    Doing car-based youth justice appointments during young people’s mobility transitions

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    This chapter uses a mobilities lens to develop understandings of discretionary youth justice practitioner lifts in a large English rural area. Geographically dispersed youth justice produces onerous access requirements for a population that has impaired mobility in the context of past learning, present transitions and imagined futures. Although urban opportunity clustering and assumed ‘automobility’ has produced barriers for poor, rural-dwelling young people, recent research has revealed new openings for car-based support and relationship building through discretionary ‘mobile work’. Recommendations will suggest that non-linear mobility trajectories and the relationships between mobility learning/transitions and static/moving practice need to be better understood

    Green securities policy and the environmental performance of firms:Assessing the impact of China's pre-IPO environmental inspection policy

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    China has experimented with a wide range of policies to encourage firms to improve their environmental performance, often with mixed results. This paper investigates the effectiveness of combining two different policies at the same time: (1) a more centralised environmental inspection process and (2) new rules on the public disclosure of policy compliance for firms wanting to undertake an initial public offering (IPO). A theoretical framework predicts that a more centralised inspection and public disclosure should improve both a firm's environmental performance and profitability. The results of instrumental variable estimations for 536 listed Chinese firms for the period 2009 to 2019 confirm the theoretical predictions although the positive effect on profitability only lasts for two years after compliance with the IPO requirements. An investigation into possible mechanisms shows that the joint policy promotes investment in green projects while also increasing demand for the firm's products. The findings highlight greater regulatory complexity may be needed if a country wishes to change the behaviour of firms in a manner that is consistent with overcoming environmental challenges.</p

    Generation of a human iPSC-derived cardiomyocyte/fibroblast engineered heart tissue model [version 1; peer review: 1 approved, 2 approved with reservations]

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    Animal models have proven integral to broadening our understanding of complex cardiac diseases but have been hampered by significant species-dependent differences in cellular physiology. Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have shown great promise in the modelling of cardiac diseases despite limitations in functional and structural maturity. 3D stem cell-derived cardiac models represent a step towards mimicking the intricate microenvironment present in the heart as an in vitro model. Incorporation of non-myocyte cell types, such as cardiac fibroblasts, into engineered heart tissue models (EHTs) can help better recapitulate the cell-to-cell and cell-to-matrix interactions present in the human myocardium. Integration of human-induced pluripotent stem cell-derived cardiac fibroblasts (hiPSC-CFs) and hiPSC-CM into EHT models enables the generation of a genetically homogeneous modelling system capable of exploring the abstruse structural and electrophysiological interplay present in cardiac pathophysiology. Furthermore, the construction of more physiologically relevant 3D cardiac models offers great potential in the replacement of animals in heart disease research. Here we describe efficient and reproducible protocols for the differentiation of hiPSC-CMs and hiPSC-CFs and their subsequent assimilation into EHTs. The resultant EHT consists of longitudinally arranged iPSC-CMs, incorporated alongside hiPSC-CFs. EHTs with both hiPSC-CMs and hiPSC-CFs exhibit slower beating frequencies and enhanced contractile force compared to those composed of hiPSC-CMs alone. The modified protocol may help better characterise the interplay between different cell types in the myocardium and their contribution to structural remodelling and cardiac fibrosis

    Time Travel

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    Tiny pores turning the tide

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