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Indirect Tensile Strength Test on Heterogeneous Rock Using Square Plate Sample with a Circular Hole
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The data underpinning this publication can be accessed from the Brunel University London’s data repository, Brunelfigshare here under a CCBY licence: https://doi.org/10.17633/rd.brunel.25386487.An indirect testing method for determining the tensile strength of rock-like heterogeneous materials is proposed. The realistic failure process analysis method, which can consider material inhomogeneity, is applied to model the failure process of the square plate containing a circular hole under uniaxial compression. The influence of plate thickness and applied loads on the maximum tensile stress is investigated, and the tensile strength equation is deduced. Meanwhile, the initial cracking loads are obtained by the corresponding physical tests, and the tensile strengths are determined by substituting the initial cracking loads into the developed tensile strength equation. The values predicted by the newly proposed method are almost identical to those of the direct tensile tests. Furthermore, the proposed method can give the relatively small tensile strength error with the direct tensile test in comparison to the other test methods, which indicates that the proposed method is effective and valid for determining the tensile strength of rock-like heterogeneous materials.National Natural Science Foundation of China, China (grant no. 51978322)
EEG-DBNet: A Dual-Branch Network for Temporal-Spectral Decoding in Motor-Imagery Brain-Computer Interfaces.
Get PDFThe source code is available at https://github.com/xicheng105/EEG-DBNet .A preprint version of the article is available at arXiv:2405.16090v3 [cs.HC], https://arxiv.org/abs/2405.16090 . It has not been certified by peer review.Motor imagery electroencephalogram (EEG)-based brain-computer interfaces (BCIs) offer significant advantages for individuals with restricted limb mobility. However, challenges such as low signal-to-noise ratio and limited spatial resolution impede accurate feature extraction from EEG signals, thereby affecting the classification accuracy of different actions. To address these challenges, this study proposes an end-to-end dual-branch network (EEG-DBNet) that decodes the temporal and spectral sequences of EEG signals in parallel through two distinct network branches. Each branch comprises a local convolutional block and a global convolutional block. The local convolutional block transforms the source signal from the temporal-spatial domain to the temporal-spectral domain. By varying the number of filters and convolution kernel sizes, the local convolutional blocks in different branches adjust the length of their respective dimension sequences. Different types of pooling layers are then employed to emphasize the features of various dimension sequences, setting the stage for subsequent global feature extraction. The global convolution block splits and reconstructs the feature of the signal sequence processed by the local convolution block in the same branch and further extracts features through the dilated causal convolutional neural networks. Finally, the outputs from the two branches are concatenated, and signal classification is completed via a fully connected layer. Our proposed method achieves classification accuracies of 85.84% and 91.60% on the BCI Competition 4-2a and BCI Competition 4-2b datasets, respectively, surpassing existing state-of-the-art models...
Functional Oil Price Expectations Shocks and Inflation
Get PDFData Availability Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.JEL Classification: C32, E31, Q43This paper investigates the inflation effects of oil price expectations shocks constructed as functional shocks, that is, as shifts in the entire oil futures term structure (both standard and risk-adjusted). The latter are then included in a vector autoregressive model with exogenous variables (VARX) to examine the US case. Counterfactual analysis is also carried out to investigate second-round effects on inflation through the inflation expectations channel. These are found to be significant, in contrast to earlier studies based on standard oil price shocks. Additional nonlinear local projections including a shock decomposition exercise show that inflation and inflation expectations are primarily driven by changes in the curvature (level and slope) factor when the latter are anchored (unanchored). These findings provide useful information to policymakers concerning the impact of oil price expectations on inflation and inflation expectations.The authors received no specific funding for this work
Health facilities readiness for standard precautions to infection prevention and control in Nepal: A secondary analysis of Nepal Health Facility Survey 2021
Get PDFData Availability: The data is available publicly in the open-access repository. The data can be downloaded from the official website of “The Demographic and Health Surveys” program (https://dhsprogram.com/data/dataset/Nepal_SPA_2021.cfm?flag=0). The dataset used in this study has been deposited to Open Science Framework (OSF) public repository with URL: https://osf.io/bkyva/.Acknowledgments: We would like to thank “The DHS program” for data access.Supporting information is available online at: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0307589#sec020 .Background:
Improvements in standard precaution related to infection prevention and control (IPC) at the national and local-level health facilities (HFs) are critical to ensuring patient’s safety, preventing healthcare-associated infections (HAIs), mitigating Antimicrobial Resistance (AMR), protecting health workers, and improving trust in HFs. This study aimed to assess HF’s readiness to implement standard precautions for IPC in Nepal.
Methods:
This study conducted a secondary analysis of the nationally-representative Nepal Health Facility Survey (NHFS) 2021 data and used the Service Availability and Readiness Assessment (SARA) Manual from the World Health Organization (WHO) to examine the HF’s readiness to implement standard precautions for IPC. The readiness score for IPC was calculated for eight service delivery domains based on the availability of eight tracer items: guidelines for standard precautions, latex gloves, soap and running water or alcohol-based hand rub, single use of standard disposal or auto-disable syringes, disinfectant, safe final disposal of sharps, safe final disposal of infectious wastes, and appropriate storage of infectious waste. We used simple and multiple linear regression and quantile regression models to examine the association of HF’s readiness with their characteristics. Results were presented as beta (β) coefficients and 95% confidence interval (95% CI).
Results:
The overall readiness scores of all HFs, federal/provincial hospitals, local HFs, and private hospitals were 59.9±15.6, 67.1±14.4, 59.6±15.6, and 62.6±15.5, respectively. Across all eight health service delivery domains, the HFs’ readiness for tuberculosis services was the lowest (57.8±20.0) and highest for delivery and newborn care services (67.1±15.6). The HFs performing quality assurance activities (β = 3.68; 95%CI: 1.84, 5.51), reviewing clients’ opinions (β = 6.66; 95%CI: 2.54, 10.77), and HFs with a monthly meeting (β = 3.28; 95%CI: 1.08, 5.49) had higher readiness scores. The HFs from Bagmati, Gandaki, Lumbini, Karnali and Sudurpaschim had readiness scores higher by 7.80 (95%CI: 5.24, 10.36), 7.73 (95%CI: 4.83, 10.62), 4.76 (95%CI: 2.00, 7.52), 9.40 (95%CI: 6.11, 12.68), and 3.77 (95%CI: 0.81, 6.74) compared to Koshi.
Conclusion:
The readiness of HFs to implement standard precautions was higher in HFs with quality assurance activities, monthly HF meetings, and mechanisms for reviewing clients’ opinions. Emphasizing quality assurance activities, implementing client feedback mechanisms, and promoting effective management practices in HFs with poor readiness can help to enhance IPC efforts.The author(s) received no specific funding for this work. Sundar Budhathoki is supported in part by the NW London NIHR Applied Research Collaboration. Imperial College London is grateful for support from the NW London NIHR Applied Research Collaboration
Gel-OPTOFORT Sensor: Multi-axis Force/Torque Measurement and Geometry Observation Using GelSight and Optoelectronic Sensor Technology
Get PDFA preprint version of this conference paper is available at: arXiv:2407.16082v1 [cs.RO], https://arxiv.org/abs/2407.16082 . It has not been certified by peer review.Although conventional GelSight-based tactile and force/torque sensors excel in detecting objects' geometry and texture information while simultaneously sensing multi-axis forces, their performance is limited by the camera's lower frame rates and the inherent properties of the elastomer. These limitations restrict their ability to measure higher force ranges at high sampling frequencies. Besides, due to the coupling of the Gelsight sensor unit and multi-axis force/torque unit structurally, the force/torque measurement ranges of the Gelsight-based force/torque sensors are not adjustable. To address these weaknesses, this paper proposes the GEL-OPTOFORT sensor that combines a GelSight sensor and an optoelectronic sensor-based force/torque sensor.Brunel University London; Great Britain Sasakawa Foundation
Invisible Barriers: Exposing Inequality and Discrimination in Contemporary Migration Policies <b> <i>Undesirable immigrants : why racism persists in international migration</i> </b> / Andrew S. Rosenberg. - Princeton : Princeton University Press, 2022. - xxii, 359 p. - (Princeton studies in international history and politics). - ISBN 978-0-691-23873-9 ; 978-0-691-23874-6 (pbk) ; 978-0-691-23875-3 (ebk)
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Identifying the interplay between protective measures and settings on the SARS-CoV-2 transmission using a Bayesian network
Get PDFData Availability: The used datasets along with the source code are made available through Zenodo repository at https://doi.org/10.5281/zenodo.10610726.Contact tracing played a crucial role in minimizing the onward dissemination of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in the recent pandemic. Previous studies had also shown the effectiveness of preventive measures such as mask-wearing, physical distancing, and exposure duration in reducing SARS-CoV-2 transmission. However, there is still a lack of understanding regarding the impact of various exposure settings on the spread of SARS-CoV-2 within the community, as well as the most effective preventive measures, considering the preventive measures adherence in different daily scenarios. We aimed to evaluate the effect of individual protective measures and exposure settings on the community transmission of SARS-CoV-2. Additionally, we aimed to investigate the interaction between different exposure settings and preventive measures in relation to such SARS-CoV-2 transmission. Routine SARS-CoV-2 contact tracing information was supplemented with additional data on individual measures and exposure settings collected from index patients and their close contacts. We used a case-control study design, where close contacts with a positive test for SARS-CoV-2 were classified as cases, and those with negative results classified as controls. We used the data collected from the case-control study to construct a Bayesian network (BN). BNs enable predictions for new scenarios when hypothetical information is introduced, making them particularly valuable in epidemiological studies. Our results showed that ventilation and time of exposure were the main factors for SARS-CoV-2 transmission. In long time exposure, ventilation was the most effective factor in reducing SARS-CoV-2, while masks and physical distance had on the other hand a minimal effect in this ventilation spaces. However, face masks and physical distance did reduce the risk in enclosed and unventilated spaces. Distance did not reduce the risk of infection when close contacts wore a mask. Home exposure presented a higher risk of SARS-CoV-2 transmission, and any preventive measures posed a similar risk across all exposure settings analyzed. Bayesian network analysis can assist decision-makers in refining public health campaigns, prioritizing resources for individuals at higher risk, and offering personalized guidance on specific protective measures tailored to different settings or environments.This study was funded by the Royal College of Nurses from the Balearic Islands (Ref.: 2021-0564). This research was also supported by the Florence Nightingale fellowship program, Royal College of Nurses from the Balearic Islands and the Nursing and Physiotherapy Department, University of the Balearic Islands
Disruption of the thyroid hormone system and patterns of altered thyroid hormones after gestational chemical exposures in rodents – a systematic review
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The original contributions presented in the study are included in the article/Supplementary Material (), further inquiries can be directed to the corresponding author.Supplementary material:
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fendo.2023.1323284/full#supplementary-materialWe present a comprehensive overview of changes in thyroxine (T4) and thyroid stimulating hormone (TSH) serum concentrations after pre-gestational, gestational and/or lactation exposures of rodents to various chemicals that affect the thyroid hormone system. We show that T4 and TSH changes consistent with the idealized view of the hypothalamic-pituitary-thyroid (HPT) feedback loop (T4 decrements accompanied by TSH increases) are observed with only a relatively small set of chemicals. Most substances affect concentrations of various thyroid hormones without increasing TSH. Studies of altered T4 concentrations after gestational exposures are limited to a relatively small set of chemicals in which pesticides, pharmaceuticals and industrial chemicals are under-represented. Our risk-of-bias analysis exposed deficits in T4/TSH analytics as a problem area. By relating patterns of T4 – TSH changes to mode-of-action (MOA) information, we found that chemicals capable of disrupting the HPT feedback frequently affected thyroid hormone synthesis, while substances that produced T4 serum decrements without accompanying TSH increases lacked this ability, but often induced liver enzyme systems responsible for the elimination of TH by glucuronidation. Importantly, a multitude of MOA leads to decrements of serum T4. The current EU approaches for identifying thyroid hormone system-disrupting chemicals, with their reliance on altered TH serum levels as indicators of a hormonal mode of action and thyroid histopathological changes as indicators of adversity, will miss chemicals that produce T4/T3 serum decreases without accompanying TSH increases. This is of concern as it may lead to a disregard for chemicals that produce developmental neurotoxicity by disrupting adequate T4/T3 supply to the brain, but without increasing TSH.EU Horizon 2020 program, ATHENA project, grant number 825161
AI-powered voice assistants: developing a framework for building consumer trust and fostering brand loyalty
Get PDFData availability: The data that support the findings of this study are available from the corresponding author upon request.Supplementary information is available online at: https://link.springer.com/article/10.1007/s10660-024-09850-5#Sec26 .This paper explores the role of artificial intelligence (AI)-powered voice assistants (VAs) in the context of online shopping, with a specific focus on Indian consumers. Through a quantitative research approach, data were collected with an online survey of 150 Indian participants based on constructs and measurement tools, which are meticulously defined, ensuring the reliability and validity of the results. The study (1) explores previous research to understand the use of AI-powered VAs in online shopping and their varied antecedents/dimensions; (2) analyses the influence of consumer trust on intention to use, satisfaction, and emotional attachment among individuals who use AI-powered VAs in online shopping; (3) develops a framework that reflects the antecedents of AI-powered VAs in online shopping and the outcome as brand loyalty, while taking consumer trust as the mediator for users' intention to use AI-powered VAs, customer satisfaction, and emotional attachment in their journey towards brand loyalty; (4) studies how Alexa, an AI-powered VA, influences the consumer journey when shopping online in India and ultimately affects the brand loyalty of Indian consumers...
Hydrophobic and Hydrophilic Functional Groups and their Impact on Physical Adsorption of CO2 in Presence of H2O: A Critical Review
Get PDFData availability: No data was used for the research described in the article.Surface functional groups (SFGs) play a key role in adsorption of any target molecule and CO2 is no exception. In fact, due to its quadrupole nature, different SFGs may attract either the oxygen or the carbon atoms to facilitate improved sorption characteristics in porous materials, hence the proliferation of this approach in the context of carbon capture via solid adsorbents. However, actual processes involve CO2 capture/removal from a mixed gas stream that may have a non-negligible water content. The presence of humidity significantly hampers the sorption properties of classical physisorbents. To overcome this, the surface of the adsorbent can be modified to include hydrophobic/hydrophilic SFGs making the materials more resilient to moisture. However, the mechanisms behind H2O-tolerance depend greatly on the characteristics of SFGs themselves. Herein, a multitude of hydrophobic and hydrophilic SFGs (e.g. carbonyls, halogens, hydroxyls, nitro groups, phenyls, various alkyl chains and etc.) for physical CO2 adsorption are reviewed within the context of their separation performance in a humid environment, highlighting their merits and limitations as well as their impact on cooperative or competitive H2O – CO2 adsorption.This work has been funded by the UK Carbon Capture and Storage Research Centre (EP/W002841/1) through the flexible funded research programme “Investigation of Environmental and Operational Challenges of Adsorbents Synthesised from Industrial Grade Biomass Combustion Residues”. The UKCCSRC is supported by the Engineering and Physical Sciences Research Council (EPSRC), UK, as part of the UKRI Energy Programme. Additionally, the authors are grateful to the UK’s Department for Energy Security and Net Zero’s funding via Sea Carbon Unlocking and Removal (SeaCURE) grant, which has enabled this work
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