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Fracture mechanical properties of shale and macro-meso-micro multi-scale fracture surface characteristics
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Data will be made available on request.The presence of bedding planes imparts pronounced anisotropy to the mechanical behavior of shale, fundamentally influencing its response to external stress. This anisotropic behavior is critical in determining the fracturing characteristics and overall mechanical performance of shale in engineering applications, particularly in resource extraction and stability evaluations. In this study, fracture tests were conducted on shale specimens with varying bedding angles (0°, 30°, 60°, and 90°) using the notched semi-circular bend (NSCB) method. The influence of the bedding angle on fracture toughness and failure pattern was systematically investigated. Additionally, multi-scale fracture surface morphology characteristics were analyzed through 3D optical scanning, ultra-depth field microscopy, and scanning electron microscope (SEM), enabling a comprehensive evaluation of the structural effects of bedding angles. The results indicate that fracture toughness decreases with increasing bedding angle, crack propagation becomes more stable, and the dispersion of fracture toughness diminishes. The failure pattern observed can be categorized as follows: tensile failure across the bedding plane (0°), shear failure along the bedding plane with mixed failure across the bedding plane (30°), shear failure along the bedding plane or tensile failure across the bedding plane (60°), and tensile failure along the bedding plane with mixed failure across the bedding plane (90°). These distinct failure patterns underscore the critical influence of bedding angle on fracture mechanisms. Moreover, the multi-scale failure characteristics exhibit significant correlation and consistency. The fractal dimension and joint roughness coefficient (JRC) initially increase and decrease with increasing bedding angle. Based on parameters such as asperity height, slope angle, and aspect direction, quantitative morphology characterization confirms that 30° specimens exhibit the highest surface complexity. A strong correlation is observed between the fractal dimension and the standard deviation of morphology descriptors, indicating robust geometric consistency across scales. These findings provide compelling evidence for the intrinsic link between macroscopic mechanical response and microscopic fracture surface morphology, offering critical insights into the multi-scale evolution of shale failure mechanisms and furnishing a theoretical foundation for designing and optimizing fracturing strategies in anisotropic shale formations.The authors would like to acknowledge the financial support from the National Natural Science Foundation for Young Scientists of China (Grant No. 52104084), the Science and Technology Tackling Project of Henan Province, China (Grant No. 252102321155, 252102321101), the China Postdoctoral Science Foundation, China (Grant No. 2024M760807), and the UK Research and Innovation, UK (Grant No. EP/Y02754X/1)
Secure and Private Over-the-air Federated Learning: Biased and Unbiased Aggregation Design
Get PDFOver-the-air federated learning (OTA-FL) presents a promising paradigm that improves the efficiency of local update aggregation by leveraging the superposition property of wireless multiple access channels (MACs). However, it faces significant security and privacy concerns that demand careful consideration. To address these threats associated with OTA-FL, we develop a secure and private over-the-air federated learning (SP-OTA-FL) framework, which can realize the secure and private aggregation for both OTA-FL with unbiased aggregation (UB-OTA-FL) and OTA-FL with biased aggregation (B-OTA-FL). In this framework, a subset of devices participate in training, while another subset functions as jammers, emitting jamming signals to enhance the security and privacy of the OTA-FL process. In particular, we measure the privacy leakage of users’ data using differential privacy (DP) and introduce an innovative application of mean squared error security (MSE-security) to evaluate the security of the OTA-FL system. We conduct convergence analyses for both convex and non-convex loss functions. Building on these analytical results, we separately formulate optimization problems for UB-OTA-FL and B-OTA-FL to enhance the learning performance of SP-OTA-FL by strategically optimizing the scheduling of training participants and jammers. The effectiveness of the proposed schemes is verified through simulations.10.13039/100000001-National Science Foundation (Grant Number: ECCS-2335876)
Contemporary Performance and Political Economy: Oikonomia as a New Ethico-Political Paradigm
No full textContemporary Performance and Political Economy examines haunting concepts, relations, and artworks that demand our attention. Under capitalism, political and ethical considerations are subordinated to economic ones, and this subordination creates ghost worlds. Performance works, however, can offer insights into alternative politico-economic models. In this major contribution to the fields of contemporary performance and political economy, Katerina Paramana proposes that the investigation of performance works as economies can make the insights performance works offer visible. She positions the examination in relation to contemporary critiques of capitalism, neo-feudalism, and their by-products, and proposes and develops the notion of ‘oikonomia’ as a means to theorise artworks which, through their house (oikos) rules (nomoi), propose ethico-political challenges to the economies in which they are embedded. For this, Paramana looks at politically positioned performance works created and presented in Cuba, Europe, Mexico, UK, and US. Her interest is in the politics, ethics, and effects of these works’ ‘house rules’, and the insights they offer to the reconceptualization of political economy. Ultimately, this book aims to transform our understanding of economy’s purpose. It contributes to the development of a new ethico-political paradigm upon which a reconceptualization of political economy can be based. This inspiring study seeks to keep the fire for change alive by demonstrating that political economies, much like performances, are experiments which can be changed. This work will be of great interest to students and scholars in Performance Studies, Theatre, Visual Cultures, Politics, Cultural Studies, Dance and Visual Arts, and Critical Theorists.BRIEF Award (‘BRUNEL RESEARCH INITIATIVE AND ENTERPRISE FUND’) 2019-2
Static Recrystallization Simulation of Interstitial Free‐Steel by Coupling Multi‐Phase‐Field and Crystal Plasticity Model Considering Dislocation Density Distribution
Get PDFData Availability Statement:
The data that support the findings of this study are available from the corresponding author upon reasonable request.Knowledge of alloy recrystallization is key to optimizing microstructures and achieving superior material properties. Computational models predicting microstructural evolution during recrystallization significantly enhance control of microstructure formation during manufacturing. Accurate prediction of microstructural parameters, including recrystallization fraction and grain size, is highly desirable. However, developing robust recrystallization models under various processing conditions remains an active research area. Herein, using interstitial free-steel for simulations and experiments, plastic deformation of polycrystalline material is simulated using a physics-based crystal plasticity model. A real microstructure serves as the initial configuration. The resulting inhomogeneous dislocation density distribution and deformed grain topology are used in a multi-phase-field simulation of recrystallization. In primary recrystallization, nucleation strongly influences kinetics and the final microstructure. In the model, the dislocation density distribution predicts both the number and positions of nuclei. Comparing simulations—one considering the dislocation density distribution in both nucleation and evolution and the other assuming constant dislocation density and random seed positioning—demonstrates the importance of heterogeneous dislocation distribution. Results confirm that static recrystallization simulations, accurately reflecting plastic deformation and utilizing the dislocation density distribution as the driving force for grain growth and nucleation, can be successfully performed using the proposed model.Shiraz University. Grant Number: 99-GR-ENG
Harmonizing hospitality across cultures: Unveiling the role of servant leadership, and strategy in diverse cultural contexts
Get PDFIn the fast-paced and competitive world of the hospitality industry, strategies have an inseparable role in unlocking the full potential of the hotels in this industry. The current study examined how strategy differentiation (SD) and strategy social responsibility (SSR) influence corporate identity (CI), organizational commitment (OC), and organizational citizenship behavior (OCB) of independent hotel employees across various national cultures. Additionally, it investigated the role of servant leadership (SL) in shaping these strategies. Data were gathered through questionnaires from 840 hotel employees in the USA and Portugal, representing two distinct GLOBE cultural clusters. The results indicated that the two cultural groups were significantly different. The main hypothesis proposed a positive link between SL and OCB, which was found to be significant only in the Portugal cluster. The USA cluster did not show this relationship. Four other hypotheses acted as mediators for the main hypothesis. The second and third hypotheses focused on the mediating effects of SD and CI between SL and OCB, showing significance in Portugal but not in the USA. The fourth hypothesis regarding SSR as a mediator was insignificant for both groups, while the fifth hypothesis about SSR and OC as mediators was supported only in the USA. This research sheds more light on servant leadership and strategy in the hotel industry within two distinct GLOBE clusters. It illustrates how cultural differences within these clusters influence relationships between servant leadership, different strategies and their impact on different organisational variables.The authors received no financial support for the research, authorship, and/or publication of this article
Aging-induced enhancement of corrosion resistance in Al-4Ni-1Mn alloys through Al<inf>3</inf>(Sc, Zr) precipitates
No full textAl-Ni-Mn alloys are attractive for high-temperature, corrosive environment due to the formation of stable intermetallic compounds that can reduce corrosion susceptibility. This study showed that the additions of Mn, Sc, and Zr in Al-4 % Ni alloys significantly enhanced hardness and thermal stability through the simultaneous effect of transformation of the Al + Al3Ni to Al + Al9(Ni, Mn)2 eutectic and precipitation of Al3(Sc, Zr). The thermal stability of an Al-4 % Ni-1 % Mn alloy was very good when exposed to 350 °C for 60 h. Additionally, the hardness substantially increased in an Al-4 % Ni-1 % Mn alloy with the addition of Sc and Zr, showing an approximate increase of 30 %. The highest hardness achieved was approximately 50 % higher with the optimal Sc and Zr content as compared to the Al-4Ni-1Mn alloy. Addition of 1 % Mn to an Al-4 % Ni alloy decreased the current density (Icorr) and increased the corrosion potential (Ecorr), indicating better corrosion resistance. The effects of Sc and Zr additions on corrosion were also investigated, revealing that the increased Sc and Zr content led to more aggressive corrosion in the as-cast condition due to the eutectic coarsening and a high solid solution concentration of Sc and Zr that led to microstructural instability and electrochemical effects. However, after aging at 350 °C, the corrosion resistance significantly improved due to the Al3(Sc, Zr) precipitates that interrupted the corrosion path.The researchers would like to express their gratitude to the Department of Industrial Engineering at King Mongkut's Institute of Technology Ladkrabang and the Department of Production Engineering at King Mongkut's University of Technology Thonburi for providing equipment, tools, and laboratory facilities. This work was financially supported by King Mongkut’s Institute of Technology Ladkrabang (the Grant no. 2567-02-01-007)
Incorporating acute HIV infection screening, same‐day diagnosis and antiretroviral treatment into routine services for key populations at sexual health clinics in Indonesia: a baseline analysis of the INTERACT prospective study
Get PDFData Availability Statement:
Data are available upon reasonable request. Requests for data sharing can be made by submission of a study concept to the INTERACT Study Group for evaluation of the scientific value, relevance, design, feasibility and overlap with existing projects.Introduction:
Indonesia has an escalated HIV epidemic concentrated among key populations. To strengthen the care cascade, we implemented a care pathway for the screening of individuals for acute HIV infection (AHI), to achieve prompt diagnosis and antiretroviral treatment (ART) initiation, at three non-governmental sexual health clinics in Jakarta and Bali. We assessed the AHI testing uptake, yield and prevalence, and the care cascade.
Methods:
This is a cross-sectional baseline analysis of individuals (≥16 years) who presented for HIV testing and were consecutively enrolled (May 2023−November 2024). We used an AHI risk-score self-assessment and test algorithm comprising a fourth-generation antibody/p24 antigen rapid diagnostic test (4gRDT; Abbott Determine HIV Early Detect) and, if negative/discordant, followed by HIV-PCR (Cepheid Xpert) (either individual or pooled-sample testing). AHI was pragmatically defined as having negative/discordant RDT results with positive HIV-PCR (ISRCTN41396071).
Results:
Three thousand seven hundred and ninety-seven (44.0%) of 8665 individuals were screened for study eligibility, and 3689 (97.2%) were enrolled. Median age was 28 years, and 78.2% were male. Men who have sex with men (MSM) accounted for 53.3%, clients of sex workers 19.2%, persons having a sex partner living with HIV 8.9% and sex workers 4.1%. We diagnosed 229 (6.3%; 229/3662) persons with RDT-positive (chronic) HIV, and we additionally identified 13 persons with AHI—that is a diagnostic yield of 5.6% (95% CI 3.1−9.5; 13/229) overall, and 6.1% (95% CI 3.2−10.3; 12/198) among MSM. AHI prevalence was 0.38% (95% CI 0.20−0.65; 13/3429) overall, and 0.72% (95% CI 0.37−1.2; 12/1677) among MSM. The number of persons needed to test to identify one person with AHI was 264 (3429/13) overall and 140 (1677/12) among MSM. The 4gRDT's performance to detect AHI was poor (2/13). Most participants received their HIV-PCR results on the same day (84.8%, 2907/3429) or within 24 hours (92.8%, 3182/3429). Of the 242 newly HIV-diagnosed individuals, 236 (97.5%) started ART, of whom 158 (67.0%) on the same day and 215 (91.1%) within 1 week.
Conclusions:
We successfully implemented prompt AHI diagnosis and treatment, and identified a high AHI prevalence among Indonesian MSM. Prioritizing access to AHI testing can create opportunities for enhanced interventions to curb the HIV epidemic among key populations.Wellcome Africa Asia Programme Vietnam;
UK Medical Research Council (MRC) and the Foreign Commonwealth and Development Office (FCDO)
Non-parametric probabilistic machine learning methodologies suited to real-world data
Get PDFThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonRecent years have seen a massive increase in the use of supervised learning for prediction
tasks in various real-world applications. In supervised learning, the relationship between two
variables - an input and an output - is sought. In spite of several existing learning models, the
learning of this sought relation poses several challenges given real-world data due to different
characteristics of this data, such as noise of the observations; non-stationarity in the data;
inhomogeneities present in the correlations between different output pairs that are realised at
inputs located differently in the space of the input variable. Moreover, real-world data can
be high-dimensional, where both the input and the output can be tensor-valued in general.
These challenges induce the following desirables in the prediction that is performed after
such learning is undertaken: fast prediction that is accurate, uncertainty-included and reliable,
as well as low in computational complexity, for easy implementation. Additionally, the
prediction exercise - foreshadowed by the learning - needs to be scalable to high-dimensions.
Although, some of the existing learning models address a subset of the challenges
given non-stationary data, (towards reliable, uncertainty-included predictions), they typically
require learning of a large number of hyperparameters, making these learning techniques
computationally intensive. Also, they do not come with easy-to-implement algorithms,
which makes these models infeasible for applications using medium sized real-world data.
Furthermore, some of the existing models are designed for dedicated applications, using
domain-specific model assumptions, generalisability of which outside the domains can be
questioned.
This thesis addresses challenges of real-world data, and presents applications of a generic,
completely non-parametric learning model that is reliable, accurate, parsimonious, and works
given non-stationary data that can be high-dimensional in general. Equipped with an easy-toimplement
algorithm, such a learning technique overcomes the limitations of existing models.
More precisely, this thesis attempts demonstration of reliable learning of a function (that
represents the relation between a pair of random variables), by modelling this function as a
sample function of a Gaussian Process. Such learning will be followed by fast prediction of
the output that is realised at test inputs, where said prediction offers closed-form mean and
variance of this output. In fact, in this approach, the predictions that follow the learning of the inter-variable
relation, follows from the identification of the posterior predictive distribution of outputs
realised at test inputs.
The illustration of this approach has been performed for applications in various domains
such as finance, energy consumption and astrophysics, were the data is inhomogeneously
correlated and have diverse dimensions. From finance sector, real-world time-series data has
been considered where both the input and output is scalar-variate. In the real-world energy
consumption data, the input is vector-variate and the output is a scalar. The astrophysics
application uses an astronomical simulation data where the input is a vector and the output is
a matrix, yielding the sought function to be high-dimensional.
Inference is undertaken throughout my doctoral work using Markov chain Monte Carlo
(MCMC) sampling techniques. This thesis also highlights the sensitivity of predictions
achieved with Deep Neural Networks (DNN), to the architecture of the DNNs.
The chapter-wise distribution is as follows. The first chapter introduces the topic. The
second chapter discusses various MCMC techniques and illustrations of these inference
techniques to perform parametric learning with a small real-world data. The third chapter
introduces the background of Gaussian Process (GP) based learning, application of GP-based
supervised learning for efficient learning of uncertainty with an under-constraint MCMC for
prediction. A probabilistic, non-parametric, non-stationary, parsimonious learning strategy is
presented in the fourth chapter along with results on applying the model, and on comparison
against existing models. This application is relevant to the case of both input and output is
scalar-variate and the data is inhomogeneously-correlated. The fifth chapter includes the
application of the learning strategy with a multivariate (with vector input and scalar output),
inhomogeneously-correlated real-world data. This chapter also discusses some ideas about
inhomogeneities in the correlation structure of the training data and the DNN exposition in
both univariate and multivariate setups. An application of the learning of a high-dimensional
function is discussed in the sixth chapter. In this application, the input is a vector and the
output is a matrix. Prediction of the output at a test input vector is then presented. Finally the
thesis has been concluded in chapter seven.
The first appendix includes the application of the presented non-parametric learning strategy
towards forecasting, along which a new strategy for designing of priors for performing
forecasting with real-world inhomogeneously-correlated data. The second appendix includes
some of the results of inference preformed with various MCMC techniques included in
chapter two.EPSRC & the Prachi Dwivedi awar
Predictors of waste management behaviours in coastal communities in Indonesia: The role of community attachment and environmental concern
Get PDFAcknowledgements:
This study benefitted greatly from the support of several research assistants: Achmad Rikza, Titing Reza Fahrisa, Abraham Partogi Pardamean Tambunan, Anisa Ratnasari. We also thank the Environmental Agency divisions of Jembrana and Banyuwangi for giving us permission and support in conducting the data collection.Data availability:
Data will be made available on request.Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S0025326X25002164?via%3Dihub#s0155 .The global challenge of marine plastic pollution requires systemic change in our relationship with plastic. The current linear plastic economy must transition to a sustainable circular model, but is hindered by behavioural change difficulties, particularly in coastal regions facing resource limitations and a lack of research attention.
This study investigates waste management (WM) behaviours in Java and Bali, Indonesia, through a household survey (N = 506). By examining the roles of community attachment and environmental concern in WM behaviours, we contribute to the theoretical understanding of these concepts within a novel context. Our findings reveal that community attachment and environmental concern predict WM behaviours, yet lead to divergent outcomes. Furthermore, the provision of infrastructure is associated with changes in some, but not all, WM behaviours. These results underscore the importance of considering a variety of waste management behaviours and adopting a balanced approach that integrates both infrastructural and psychological interventions.This work was supported by the Natural Environment Research Council [grant number NE/V006428/1; “A Systems Analysis Approach to Reduce Plastic Waste in Indonesian Societies (PISCES)”]
Per- and Polyfluorinated Alkyl Substances in Different Water Matrices: Nontargeted Analysis, Suspect Screening, and Targeted Analysis
Get PDFSupporting Information:
The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsestwater.5c00145 .This study investigated the presence of unknown and known PFAS in wastewater treatment plants, drinking water treatment plants, bottled water, tap water, and surface water using both high-resolution and tandem mass spectrometry. The sources of PFAS in these matrices were elucidated via a multivariate statistical analysis. A total of 70 PFAS features were identified using nontargeted analysis at varying confidence levels. For the first time in South Africa, and probably on the African continent, novel PFAS (MeFOSA, EtFOSA, 6:2 FTUCA, 8:2 FTUCA, 6:2 FTCA, 8:2 FTCA, 10:2 FTCA, PFHxI, PFOI, 8:2 FTAC, 6:2 FTMAC, and 8:2 FTMAC) and emerging PFAS (PFMOPrA, PFPrOPrA, PFO2HxA, PFO3OA, and PFO4DA) were detected and reported in various water sources. The sum of ∑21 PFAS concentrations in bottled water, tap water, surface water, DWTP, and WWTP samples ranged from <LOD-126, <LOD-363, <LOD-716, <LOD-1056, and <LOD-2304 ng/L, respectively. The average concentrations of PFOA, PFOS, PFNA, and PFHxS in drinking tap water exceeded their respective US EPA maximum contaminant levels. PFO2HxA, PFO4DA, and PFO3OA were reported for the first time in drinking water, with PFAS displaying potential similarities in sources. This study underscores the importance of PFAS regulation in drinking water in South Africa to safeguard public health.This project was sponsored by the Water Research Commission of South Africa (WRC Project No: C2019/2020-00187) and the Agricultural Research Council-Onderstepoort Veterinary Institute, South Africa for access to UHPLC-TripleToF, through grant number P10000115 awarded to Dr. Ovokeroye A. Abafe
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