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Real-time determination of molecular weight : use of MaDDOSY (Mass Determination Diffusion Ordered Spectroscopy) to monitor the progress of polymerization reactions
No full textKnowledge of molecular weight is an integral factor in polymer synthesis, and while many synthetic strategies have been developed to help control this, determination of the final molecular weight is often only measured at the end of the reaction. Herein, we provide a technique for the online determination of polymer molecular weight using a universal, solvent-independent diffusion ordered spectroscopy (DOSY) calibration and evidence its use in a variety of polymerization reactions
An analysis of financial hardship faced by patients with First Episode Psychosis, and their families, in an Indian setting
No full textBackground
The economic burden of psychotic disorders is not well documented in LMICs like India, due to several bottlenecks present in Indian healthcare system like lack of adequate resources, low budget for mental health services and inequity in accessibility of treatment. Hence, a large proportion of health expenditure is paid out of pocket by the households.
Objective
To evaluate the direct and indirect costs incurred by patients with First Episode Psychosis and their families in a North Indian setting.
Method
Direct and Indirect costs were estimated for 87 patients diagnosed at AIIMS, New Delhi with first-episode psychosis (nonaffective) in the first- and sixth month following diagnosis, and the six months before diagnosis, using a bespoke questionnaire. Indirect costs were valued using the Human Capital Approach.
Results
Mean total costs in month one were INR 7991 ($107.5). Indirect costs were 78.3% of this total. Productivity losses was a major component of the indirect cost. Transportation was a key component of direct costs. Costs fell substantially at six months (INR 2732, Indirect Costs 61%). Respondents incurred substantial costs pre-diagnosis, related to formal and informal care seeking and loss of income.
Conclusion
Families suffered substantial productivity loss. Care models and financial protection that address this could substantially reduce the financial burden of mental illness. Measures to address disruption to work and education during FEP are likely to have significant long-term benefits. Families also suffered prolonged income loss pre-diagnosis, highlighting the benefits of early and effective diagnosis
Foresight plus : serverless spatio-temporal traffic forecasting
No full textBuilding a real-time spatio-temporal forecasting system is a challenging problem with many practical applications such as traffic and road network management. Most forecasting research focuses on achieving (often marginal) improvements in evaluation metrics such as MAE/MAPE on static benchmark datasets, with less attention paid to building practical pipelines which achieve timely and accurate forecasts when the network is under heavy load. Transport authorities also need to leverage dynamic data sources such as roadworks and vehicle-level flow data, while also supporting ad-hoc inference workloads at low cost. Our cloud-based forecasting solution Foresight, developed in collaboration with Transport for the West Midlands (TfWM), is able to ingest, aggregate and process streamed traffic data, enhanced with dynamic vehicle-level flow and urban event information, to produce regularly scheduled forecasts with high accuracy. In this work, we extend Foresight with several novel enhancements, into a new system which we term Foresight Plus. New features include an efficient method for extending the forecasting scale, enabling predictions further into the future. We also augment the inference architecture with a new, fully serverless design which offers a more cost-effective solution and which seamlessly handles sporadic inference workloads over multiple forecasting scales. We observe that Graph Neural Network (GNN) forecasting models are robust to extensions of the forecasting scale, achieving consistent performance up to 48 hours ahead. This is in contrast to the 1 hour forecasting periods popularly considered in this context. Further, our serverless inference solution is shown to be more cost-effective than provisioned alternatives in corresponding use-cases. We identify the optimal memory configuration of serverless resources to achieve an attractive cost-to-performance ratio
Towards neural architecture search through hierarchical generative modeling
No full textNeural Architecture Search (NAS) aims to automate deep neural network design across various applications, while a good search space design is core to NAS performance. A too-narrow search space may fail to cover diverse task requirements, whereas a too-broad one can escalate computational expenses and reduce efficiency. In this work, we aim to address this challenge by leaning on the recent advances in generative modelling -- we propose a novel method that can navigate through an extremely large, general-purpose initial search space efficiently by training a two-level generative model hierarchy. The first level uses Conditional Continuous Normalizing Flow (CCNF) for micro-cell design, while the second employs a transformer-based sequence generator to craft macro architectures aligned with task needs and architectural constraints. To ensure computational feasibility, we pre-train the generative models in a task-agnostic manner using a metric space of graph and zero-cost (ZC) similarities between architectures. We show our approach can achieve state-of-the-art performance among other low-cost NAS methods across different tasks on CIFAR-10/100, ImageNet and NAS-Bench-360
Practical guide for noise characterisation of back pressure sensor : towards digital twin for an industrial high horse power diesel engine test cell
No full textExtensive testing is crucial to ensure exhaust emission compliance for high-horsepower (H-hp) commercial engines. Back pressure sensors, integral to the exhaust system, are prone to producing noisy measurements due to the turbulent nature of the exhaust gas flow and other testing inaccuracies, mandating the use of a noise reduction filter. The time-consuming process of filter tuning, required to remove excessive process/measurement noise, often involves trial-and-error. This practice, entailing numerous experiments with live engines, results in high financial costs and emissions due to challenges in extracting the ground truth signal from noisy measurements. Developing a digital twin (DT) of this system is proposed to expedite filter tuning, hence reducing cost and emissions output. Creating such a DT necessitates a method of back pressure sensor noise classification to accurately simulate the signal. This letter introduces a step-by-step procedure for characterising the H-hp engine back pressure sensor through statistical measures, leading to the development of the DT. This letter demonstrates the potential of this approach in an industrial case study, showcasing its viability for application in engine test-bed facilities and across industries. The economic calculation estimates a potential £184,400 reduction in diesel fuel costs and 321,600 kg of CO2 emissions by tuning the filter through the DT compared to current industrial practice. Keywords: flowering time; hypocotyl elongation; light quality; light intensity; light ratio; light order; plant growth; smart greenhouse farming
CHEOPS observations of KELT-20 b/MASCARA-2 b : an aligned orbit and signs of variability from a reflective day side
No full textContext. Occultations are windows of opportunity to indirectly peek into the dayside atmosphere of exoplanets. High-precision transit events provide information on the spin-orbit alignment of exoplanets around fast-rotating hosts.
Aims. We aim to precisely measure the planetary radius and geometric albedo of the ultra-hot Jupiter (UHJ) KELT-20 b along with the spin-orbit alignment of the system.
Methods. We obtained optical high-precision transits and occultations of KELT-20 b using CHEOPS observations in conjunction with simultaneous TESS observations. We interpreted the occultation measurements together with archival infrared observations to measure the planetary geometric albedo and dayside temperatures. We further used the host star’s gravity-darkened nature to measure the system’s obliquity.
Results. We present a time-averaged precise occultation depth of 82 ± 6 ppm measured with seven CHEOPS visits and 131−7+8 from the analysis of all available TESS photometry. Using these measurements, we precisely constrain the geometric albedo of KELT-20 b to 0.26 ± 0.04 and the brightness temperature of the dayside hemisphere to 2566−80+77 K. Assuming Lambertian scattering law, we constrain the Bond albedo to 0.36−0.05+0.04 along with a minimal heat transfer to the night side (ϵ = 0.14−0.10+0.13). Furthermore, using five transit observations we provide stricter constraints of 3 9 ± 1 1 deg on the sky-projected obliquity of the system.
Conclusions. The aligned orbit of KELT-20 b is in contrast to previous CHEOPS studies that have found strongly inclined orbits for planets orbiting other A-type stars. The comparably high planetary geometric albedo of KELT-20 b corroborates a known trend of strongly irradiated planets being more reflective. Finally, we tentatively detect signs of temporal variability in the occultation depths, which might indicate variable cloud cover advecting onto the planetary day side
Electron and photon energy calibration with the ATLAS detector using LHC Run 2 data
No full textThis paper presents the electron and photon energy calibration obtained with the ATLAS detector using 140 fb-1 of LHC proton-proton collision data recorded at √(s) = 13 TeV between 2015 and 2018. Methods for the measurement of electron and photon energies are outlined, along with the current knowledge of the passive material in front of the ATLAS electromagnetic calorimeter. The energy calibration steps are discussed in detail, with emphasis on the improvements introduced in this paper. The absolute energy scale is set using a large sample of Z-boson decays into electron-positron pairs, and its residual dependence on the electron energy is used for the first time to further constrain systematic uncertainties. The achieved calibration uncertainties are typically 0.05% for electrons from resonant Z-boson decays, 0.4% at ET ∼ 10 GeV, and 0.3% at ET ∼ 1 TeV; for photons at ET ∼ 60 GeV, they are 0.2% on average. This is more than twice as precise as the previous calibration. The new energy calibration is validated using J/ψ → ee and radiative Z-boson decays
The graph tempo framework for exploring the evolution of a graph through pattern aggregation
No full textMaterial expertise : the case of the craft entrepreneur Lucie Rie
No full textResearch Summary: By following the historical case of the world‐renowned potter Luce Rie, we study the relationships between the accrual of material expertise, entrepreneurial actions, and successful craft venture outcomes. Drawing from Sennett's material consciousness framework and Fisher's resource‐based propositions of effective entrepreneurial actions, we enhance understanding of the material drivers of such actions, how material expertise can contribute to self‐imposed constraints, and how these constraints may contribute to positive craft venture outcomes. Our findings thereby contribute to a nuanced understanding of the intimacy between human and material agency in entrepreneurship and reveal a craft approach to managing the tension of novelty and control at the heart of strategic entrepreneurship. Furthermore, our analysis contributes to broader reflection on the definitions of venture success, value generation, and growth. Managerial Summary: Craft‐based ventures are increasingly recognized as vital to thriving and sustainable economies. However, our understanding of the drivers of entrepreneurial actions that contribute to successful craft venture outcomes remains limited. In this article, drawing from our analysis of the historical case of the world‐renowned potter Lucie Rie using theoretical insights from the craft literature, we focus on the role of material expertise. We thereby identify how a craft entrepreneur's intimate understanding of their materials may help them identify and act upon opportunities, overcome problems, engage a community, and innovate to support the viability of their venture as well as achieve outcomes that motivate the venture in the first place, namely to continually refine their craft and shape audiences' understanding of the value of skilled making
