30793 research outputs found
Sort by
Search for Higgs boson pair production in the bb¯W+W− decay mode in proton-proton collisions at √s = 13 TeV
Get PDFA preprint version of the article is available at arXiv:2403.09430v2 [hep-ex], https://arxiv.org/abs/2403.09430. Comments: Replaced with the published version. Added the journal reference and the DOI. All the figures and tables can be found at https://cms-results.web.cern.ch/cms-results/public-results/publications/HIG-21-005 (CMS Public Pages). Report number: CMS-HIG-21-005, CERN-EP-2024-043. Journal reference: JHEP 07 (2024) 293. Submission history: From: The CMS Collaboration: [v1] Thu, 14 Mar 2024 14:22:29 UTC (941 KB);
[v2] Sun, 18 Aug 2024 20:30:37 UTC (985 KB).A search for Higgs boson pair (HH) production with one Higgs boson decaying to two bottom quarks and the other to two W bosons are presented. The search is done using proton-proton collisions data at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb−1 recorded by the CMS detector at the LHC from 2016 to 2018. The final states considered include at least one leptonically decaying W boson. No evidence for the presence of a signal is observed and corresponding upper limits on the HH production cross section are derived. The limit on the inclusive cross section of the nonresonant HH production, assuming that the distributions of kinematic observables are as expected in the standard model (SM), is observed (expected) to be 14 (18) times the value predicted by the SM, at 95% confidence level. The limits on the cross section are also presented as functions of various Higgs boson coupling modifiers, and anomalous Higgs boson coupling scenarios. In addition, limits are set on the resonant HH production via spin-0 and spin-2 resonances within the mass range 250–900 GeV.SCOAP3
Determining the carbon footprint reduction of reusing lightweight exterior infill walls: A case study of a school building in the United Kingdom
Get PDFData availability:
Data will be made available on request.The global construction sector consumes 40 billion tonnes of raw materials and is responsible for considerable CO2 emissions. With growing awareness of its environmental impact, the construction sector is looking to transition from a linear economy “take-make-waste” scenario towards more circular economy principles. Lightweight exterior infill walls are built between floors of primary structural frames to provide building façades. The design of these components is usually based on the current linear economic model. While lightweight exterior infill walls are becoming increasingly common in building construction in the UK, no studies have investigated the potential environmental benefits of designing them with circularity in mind. This means there's a lack of research on both the carbon footprint of these walls and the potential environmental benefits of reusing them. Thus, this article assesses the significance of the carbon emissions from lightweight exterior infill walls and examines whether there is any carbon reduction when lightweight exterior infill walls are demounted from the building frames and reused. This paper first examines the construction process of lightweight exterior infill walls and explores the opportunity to demount and reuse them. Then, the environmental impacts of the lightweight exterior infill walls are analysed using a lifecycle assessment framework. Sensitivity and uncertainty analyses are also conducted. The results demonstrate that (i) the embodied carbon of the lightweight exterior infill walls over their lifecycle represents approximately 22% of the embodied carbon of the entire building, and (ii) the disassembly and reuse of infill walls can reduce a building's embodied carbon over its typical lifetime by about 6% compared to the linear scenario where the walls were not reused.This research is funded by EPSRC through the Interdisciplinary Circular Economy Centre for Mineral-Based Construction Materials from the UK Research and Innovation (EPSRC Reference: EP/V011820/1)
Evaluation of a grid-connected solar PV system in a passive energy designed house in the Western Himalayas
No full textThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe unpredictability of the fossil fuel energy market and the noticeable growing understanding of its impact on the environment, research in reducing energy consumption in buildings, has gained significant traction. The UNEP (United Nation Environment Program) in its 2020 Buildings Global Status Report, suggests the level of CO2 emissions from the building sector is 38% of the total CO2 energy related emission worldwide. This is important in the subtropical regions where the CO2 emission percentage is likely to be higher due to the pattern and nature of energy consumption. The energy portion consumed in the residential sector on comfort cooling is the highest, and the main contributor of other than CO2 GHG (Greenhouse Gases), due to the use of refrigerants, while electricity needed to drive the power-hungry compressor motors is mostly generated from burning fossil fuels. In Southwest Asia, including the Gulf Region, which is the area chosen in this research, up to 70% of the electricity consumption during the long summer months, and approximately 50% annual average, is attributed to air conditioning. This energy consumption will continue to rise due to the unabating population growth, persistent demand for houses, and the growing impoverished neighbourhoods in many metropolises. Energy saving guidelines have become mandatory, particularly, for commercial, institutional, governmental and industrial sectors. However, this is to a lesser extent in the private residential sector. This is further compounded by the inability to enforce these guidelines. In addition, the heavily subsidized electricity tariff in comparison with other sectors. In some of the GCC (Gulf Cooperation Council) countries, the residential tariffs can be up to 13 times lower than other sectors and 20 to 25 times lower than the cost of electricity production. In Kuwait, which holds 7% of the global oil reserves, experiences electricity blackout during the long summer months due to the difficulty of keeping up with the growing demand for electricity.
In this research a number of measures to reduce electricity consumption has been reviewed.
• The house performance throughout the various stages of construction and occupancy has been examined using the wealth of data available, which extends over a period of 12 years - during construction (2012 to 2015), before the installation of a grid connected 12.18 KWp Solar PV (2016to 2020), and after the installation of the Solar PV system (2021 to 2023).
TRNSYS used to simulate the Solar PV installed system, with a cross reference using PVGIS. 12 simulation cases at different tilt and azimuth angles and tracking on one, and two axes were conducted. This including the actual case of exported monthly electricity units. TRNSYS and PVGIS results exhibited acceptable margin of error in the annual total for each case when comparing with actual, from -2% to +7%. Accounting for the number of electricity blackout hours was quite challenging, otherwise the difference between actual and simulated would have been even less. The analysis proved that up to 50% more KWH can be generated by the same system when tracking on 2 axes, and approximately 40% when tracking on the Azimuth only. Tracking on two axes is commercially prohibitive, but on one axis only is feasible
Observation of quantum entanglement in top quark pair production in proton-proton collisions at √ = 13 TeV
Get PDFData availability statement:
Release and preservation of data used by the CMS Collaboration as the basis for publications is guided by the CMS data preservation, re-use, and open access policy.A version of the article is available at arXiv:2406.03976v2 [hep-ex] (the peer reviewed version, https://arxiv.org/abs/2406.03976). Comments: Replaced with the published version. Added the journal reference and the DOI. Journal reference: Rep. Prog. Phys. 87 (2024) 117801. All the figures and tables can be found at https://cms-results.web.cern.ch/cms-results/public-results/publications/TOP-23-001 (CMS Public Pages). Report numbers: CMS-TOP-23-001, CERN-EP-2024-137. Submission history: [v2] Tue, 29 Oct 2024 12:35:26 UTC (840 KB).Entanglement is an intrinsic property of quantum mechanics and is predicted to be exhibited in the particles produced at the Large Hadron Collider. A measurement of the extent of entanglement in top quark-antiquark ( t t ¯ ) events produced in proton-proton collisions at a center-of-mass energy of 13 TeV is performed with the data recorded by the CMS experiment at the CERN LHC in 2016, and corresponding to an integrated luminosity of 36.3 fb^−1. The events are selected based on the presence of two leptons with opposite charges and high transverse momentum. An entanglement-sensitive observable D is derived from the top quark spin-dependent parts of the t t ¯ production density matrix and measured in the region of the t t ¯ production threshold. Values of D < − 1 / 3 are evidence of entanglement and D is observed (expected) to be − 0.480 − 0.029 + 0.026 ( − 0.467 − 0.029 + 0.026 ) at the parton level. With an observed significance of 5.1 standard deviations with respect to the non-entangled hypothesis, this provides observation of quantum mechanical entanglement within t t ¯ pairs in this phase space. This measurement provides a new probe of quantum mechanics at the highest energies ever produced.SCOAP³
Piecewise convolutional neural network relation extraction with self-attention mechanism
Get PDFData availability:
Data will be made available on request.The task of relation extraction in natural language processing is to identify the relation between two specified entities in a sentence. However, the existing model methods do not fully utilize the word feature information and pay little attention to the influence degree of the relative relation extraction results of each word. In order to address the aforementioned issues, we propose a relation extraction method based on self-attention mechanism (SPCNN-VAE) to solve the above problems. First, we use a multi-head self-attention mechanism to process word vectors and generate sentence feature vector representations, which can be used to extract semantic dependencies between words in sentences. Then, we introduce the word position to combine the sentence feature representation with the position feature representation of words to form the input representation of piecewise convolutional neural network (PCNN). Furthermore, to identify the word feature information that is most useful for relation extraction, an attention-based pooling operation is employed to capture key convolutional features and classify the feature vectors. Finally, regularization is performed by a variational autoencoder (VAE) to enhance the encoding ability of model word information features. The performance analysis is performed on SemEval 2010 task 8, and the experimental results show that the proposed relation extraction model is effective and outperforms some competitive baselines.This work was supported in part by the National Natural Science Foundation of China under Grant 62372300, Grant 62302306, Grant 62201350, and Grant 62477032, in part by the National Key Research and Development Program of China under Grant No. 2022YFB4501704
A (sub)field guide to quality control in hippocampal subfield segmentation on high‐resolution <scp>T<sub>2</sub></scp>‐weighted <scp>MRI</scp>
No full textData Availability Statement:
The data that supports the findings of this study are available in the supplementary material of this article.Supporting Information is available online at: https://onlinelibrary.wiley.com/doi/10.1002/hbm.70004#support-information-section .Inquiries into properties of brain structure and function have progressed due to developments in magnetic resonance imaging (MRI). To sustain progress in investigating and quantifying neuroanatomical details in vivo, the reliability and validity of brain measurements are paramount. Quality control (QC) is a set of procedures for mitigating errors and ensuring the validity and reliability of brain measurements. Despite its importance, there is little guidance on best QC practices and reporting procedures. The study of hippocampal subfields in vivo is a critical case for QC because of their small size, inter-dependent boundary definitions, and common artifacts in the MRI data used for subfield measurements. We addressed this gap by surveying the broader scientific community studying hippocampal subfields on their views and approaches to QC. We received responses from 37 investigators spanning 10 countries, covering different career stages, and studying both healthy and pathological development and aging. In this sample, 81% of researchers considered QC to be very important or important, and 19% viewed it as fairly important. Despite this, only 46% of researchers reported on their QC processes in prior publications. In many instances, lack of reporting appeared due to ambiguous guidance on relevant details and guidance for reporting, rather than absence of QC. Here, we provide recommendations for correcting errors to maximize reliability and minimize bias. We also summarize threats to segmentation accuracy, review common QC methods, and make recommendations for best practices and reporting in publications. Implementing the recommended QC practices will collectively improve inferences to the larger population, as well as have implications for clinical practice and public health.This study was supported by funding by the NIH/NIA R01AG070592 (L. Wang, L.E.M. Wisse, R. Olsen, V.A. Carr, A.M. Daugherty, P.A. Yushkevich, R. La Joie) and NIH/NICHD F32HD108960 (K.L. Canada). Authors were additionally supported by funding from NIH/NIA R01AG011230 (A.M. Daugherty, N. Raz); NIH/NIA P30AG072931 (A.M. Daugherty); NIH/NIA R01AG069474 (P.A. Yushkevich); NIH/NIA RF1AG056014 (P.A. Yushkevich); NIH/NIA F32AG074621 (J.N. Adams); NIH/NIA F32AG071263 (T.T. Tran); the Alzheimer's Association AARFD-21-852597 (T.T. Tran); the Alzheimer's Society, UK AS-JF-19a-004-517 (M. Bocchetta); the Australian Research Council DP2010102378 (M.A. Dalton); Motor Neuron Disease Research Australia (MNDRA) PDF2112 (T. Shaw); MultiPark—a strategic research area at Lund University (L.E.M. Wisse) and the Swedish Research Council 2022-00900 (L.E.M. Wisse)
Intervention study of climate correlation model predictions for occupant control of indoor environment
Get PDFOccupants in natural ventilated buildings usually control ventilation through window opening. As part of the PRELUDE H2020 project a framework of how to predict an indoor environment by correlating internal environmental variables and external climatic variables was developed; this was presented at the AIVC conference in 2022. The climate correlation model consists of equations correlating external and internal parameters, derived from predictions of a thermal model (EnergyPlus) of the target building. Using these equations, thermal comfort (operative temperature) and IAQ (CO2 concentration) are calculated using short term (24hrs) forecasted external weather data (air temperature and wind speed) that informs for window opening actions by the occupants. The model was applied in three naturally ventilated buildings in Greece (hostel), Switzerland (apartment) and Poland (office). A climate correlation model was developed for each building and equations derived specifically for the building. Occupant actions for opening windows were then determined for two consequent days in each of the buildings. The actions were communicated to the building occupants using conventional method (email); this was done through the building manager for the hostel and directly to occupants for the office and apartment. Data of internal temperature and CO2 concentration were measured, analysed and compared to the predictions of the climate correlation model. The tests were carried out successfully and the comparison of predictions (based on weather forecasts) and measurements in the building is quite good for IAQ (CO2) as the ventilation intervals are captured well. Thermal comfort was also captured well with some under prediction at night, because of differences in air flow rates due to different window opening areas and some divergence when windows were simulated open during cold days with heating off. This study demonstrates that for low technology buildings where actuators and sensors are not present, a single thermal study and associated correlation equations for the building can effectively inform the occupants on the best way to control their internal environment based on prevailing external conditions.This study would have not been possible without them. This study was funded by the European Union’s Horizon 2020 research and innovation programme under Grant Agreement N° 958345 for the PRELUDE project (https://prelude-project.eu)
SDNet: Noise-Robust Bandwidth Extension under Flexible Sampling Rates
Get PDFBandwidth extension (BWE), also known as audio super-resolution (SR), aims to predict a high resolution (HR) speech signal from its low resolution (LR) corresponding part. Most neural BWE models work at a specific sampling rate but, producing the final result in a noise-free environment by recovering the spectrogram of high-frequency part of the signal and concatenating it with the original low-frequency part. Although these methods achieve high accuracy, they become less effective when facing the real-world scenario, where unavoidable noise is present and sampling rates are flexible. To address this problem, we propose Super Denoise Net (SDNet), a neural network for a joint task of BWE and noise reduction from a flexible low sampling rate signal. To that end, we design gated convolution and lattice convolution blocks to enhance the repair capability and capture information in the time-frequency axis, respectively. The experiments show our method outperforms all current state-of-the-art (SOTA) noise-robust BWE model in Valentini-Botinhao test set. Our model also outperforms other baselines on DNS 2020 no-reverb test set with higher objective and subjective scores
The development and internal pilot trial of a digital physical activity and emotional well-being intervention (Kidney BEAM) for people with chronic kidney disease
Get PDFAvailability of data and materials: The data underlying this article will be shared on reasonable request to the corresponding author.Trial registration NCT04872933. Date of first registration 05/05/2021.Supplementary Information is available online at: https://link.springer.com/article/10.1038/s41598-023-50507-4#Sec48 .Copyright © The Author(s) 2024. This trial assessed the feasibility and acceptability of Kidney BEAM, a physical activity and emotional well-being self-management digital health intervention (DHI) for people with chronic kidney disease (CKD), which offers live and on-demand physical activity sessions, educational blogs and videos, and peer support. In this mixed-methods, multicentre randomised waitlist-controlled internal pilot, adults with established CKD were recruited from five NHS hospitals and randomised 1:1 to Kidney BEAM or waitlist control. Feasibility outcomes were based upon a priori progression criteria. Acceptability was primarily explored via individual semi-structured interviews (n = 15). Of 763 individuals screened, n = 519 (68%, 95% CI 65 to 71%) were eligible. Of those eligible, n = 303 (58%, 95% CI 54–63%) did not respond to an invitation to participate by the end of the pilot period. Of the 216 responders, 50 (23%, 95% CI 18–29%) consented. Of the 42 randomised, n = 22 (10 (45%) male; 49 ± 16 years; 14 (64%) White British) were allocated to Kidney BEAM and n = 20 (12 (55%) male; 56 ± 11 years; 15 (68%) White British) to the waitlist control group. Overall, n = 15 (30%, 95% CI 18–45%) withdrew during the pilot phase. Participants completed a median of 14 (IQR 5–21) sessions. At baseline, 90–100% of outcome data (patient reported outcome measures and a remotely conducted physical function test) were completed and 62–83% completed at 12 weeks follow-up. Interview data revealed that remote trial procedures were acceptable. Participants’ reported that Kidney BEAM increased their opportunity and motivation to be physically active, however, lack of time remained an ongoing barrier to engagement with the DHI. An randomised controlled trial of Kidney BEAM is feasible and acceptable, with adaptations to increase recruitment, retention and engagement.Kidney Research UK; Kidney Care UK, National Kidney Federation; UK Kidney Association; NIHR [NIHR302926]; HMLY is funded by the NIHR [NIHR302926]. Part of this research was carried out at the National Institute for Health and Care Research (NIHR) Leicester Biomedical Research Centre (BRC)
Data sources:
Access Repository Dashboard
Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇