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A Tomb Fit for a Prophet: An Investigation into the Historical Plausibility of the Gospel Burial Accounts
No full textWhy was the body of a man crucified by the Romans buried in a rock-hewn tomb? Whereas Jewish scruples about leaving the dead unburied would have been satisfied by burying Jesus in a shallow grave, a survey of Jewish burial practices indicates that instead he was buried in the kind of tomb normally reserved for the elite. Two of the Gospel accounts suggest that Joseph of Arimathea was a follower of Jesus, but this is historically unlikely. Piecing together the evidence from the Gospel narratives, it is proposed that, as a wealthy member of the Jewish ruling council, Joseph could well have been engaged in a programme of building tombs to honour prophets from the past. When faced with the death of a prophet in his own day, he may well have felt constrained to avert any divine retribution by giving Jesus an honourable burial. Memory theory is employed to suggest that distorted recollections of Joseph bribing Pilate to release Jesus’ body can be detected in the accounts of Jesus’ burial found in Matthew and John. This article aims to demonstrate that Jesus receiving an honourable burial in a rock-hewn tomb is historically plausible
Automating dense GPR simulations for C-scan imaging of subsurface infrastructure
No full textCivil infrastructure requires continuous assessments to address aging, deterioration, and climate change impacts. Subsurface assets present particular challenges due to their invisibilities and the highly uncertain ground conditions. Ground Penetrating Radar (GPR) is widely employed for infrastructure inspection while its interpretation often demands significant expert knowledge. This paper presents an integrated framework for efficiently simulating dense GPR B-scans to support C-scan imaging and data-driven applications. Using pipeline leakage detection as a demonstration, the framework couples digital modelling, hydromechanical (HM) simulation, and finite-difference time-domain (FDTD) electromagnetic (EM) simulation. Automated data sharing between digital models and multi-physics solvers eliminates manual model setup. Simulated B-scans and C-scans capturing water-induced changes are validated against field experiments, with reality gap sources analysed. The framework enables scalable generation of physically informed synthetic GPR datasets for complex scenarios requiring geospatially registered inputs, supporting efficient C-scan imaging and data-driven interpretation
The PAU Survey: measuring intrinsic galaxy alignments in deep wide fields as a function of colour, luminosity, stellar mass, and redshift
Get PDFWe present the measurements and constraints of intrinsic alignments (IAs) in the Physics of the Accelerating Universe Survey (PAUS) deep wide fields, which include the W1 and W3 fields from the Canada–France–Hawaii Telescope Legacy Survey (CFHTLS) and the G09 field from the Kilo-Degree Survey (KiDS). Our analyses cover 51deg, in the photometric redshift (photo-z) range and a magnitude limit . The precise photo-zs and the luminosity coverage of PAUS enable robust IA measurements, which are key for setting informative priors for upcoming stage-IV surveys. For red galaxies, we detect an increase in IA amplitude with both luminosity and stellar mass, extending previous results towards fainter and less massive regimes. As a function of redshift, we observe strong IA signals at intermediate () and high () redshift bins. However, we find no significant trend of IA evolution with redshift after accounting for the varying luminosities across redshift bins, consistent with the literature. For blue galaxies, no significant IA signal is detected, with when splitting only by galaxy colour, yielding some of the tightest constraints to date for the blue population and constraining a regime of very faint and low-mass galaxies
Mapping the interconnections among non-suicidal self-injury, depressive symptoms, and reward sensitivity: A network analysis
No full textBackgroundDeficits of reward sensitivity has been proposed as a key mechanism underlying both non-suicidal self-injury (NSSI) and depressive symptoms. However, the complex interplays between NSSI, depressive symptoms, and different components of reward sensitivity remain inadequately understood.MethodsNetwork analysis was utilized to examine the inter-relationship patterns between NSSI, depressive symptoms (both total and item scores), reward sensitivity, and associated risk factors (e.g. emotion regulation strategies and childhood trauma) in a sample of Chinese college students (n = 5190). Network Comparison Tests were conducted to explore differences across three groups, including individuals with high depressive symptoms with a history of NSSI, individuals with high depressive symptoms without NSSI, and individuals with low depressive symptoms without NSSI.ResultsIn the networks for the entire sample, NSSI was indirectly linked to specific components of reward sensitivity, suggesting that theses associations may be explained by their shared connections with depressive symptoms, emotion regulation difficulties, and childhood trauma. ‘Reward responsiveness’ and ‘emotional abuse’ were the most central nodes. Network Comparison Tests revealed significant differences in network structure across groups. Specifically, ‘behavioral inhibition system’ was the most important node in the high-depressive subgroup with NSSI, while ‘reward responsiveness’ was the most central node in the high-depressive subgroup without NSSI.ConclusionOur findings highlight the important role of reward sensitivity in NSSI and depressive symptoms, and provide specific targets for future research and potential intervention development among depressive individuals with and without a history of NSSI
Computing balanced solutions for large international kidney exchange schemes when cycle length is unbounded
Get PDFIn kidney exchange programmes, patients with incompatible donors obtain kidneys via cycles of transplants. Countries may merge their national patient-donor pools to form international programmes. To ensure fairness, a credit-based system is used: a cooperative game-theoretic solution concept prescribes a “fair” initial allocation, which is adjusted with accumulated credits to form a target allocation. The objective is to maximize the number of transplants while staying close to the target allocation. When only 2-cycles are permitted, a solution that lexicographically minimizes deviations from the target can be found in polynomial time. However, even the problem of maximizing the number of transplants is NP-hard for larger upper bounds on cycle length. This latter problem is tractable when cycle lengths are not bounded. We formalize this setting via a new class of cooperative games called partitioned permutation games, and prove that computing an optimal solution that is lexicographically closest to the target allocation is NP-hard. We give a randomized XP-time algorithm for solve this problem exactly. We present an experimental study, simulating programmes with up to 10 countries. Allowing unbounded cycle lengths increases the number of transplants by up to 46% compared to 2-cycles. Using credits and selecting lexicographically closest solutions yields low total relative deviation (below 2% for all fairness notions). Among the seven fairness notions tested, a modified Banzhaf value performs best in balancing fairness and efficiency, achieving average deviations below 0.65%. Lexicographic minimization from the target allocation leads to significantly (36 - 56%) smaller average deviations than minimizing maximum difference only
Theorising an Integrative Framework for Education-Based Interventions as Part of a Whole University Approach to Wellbeing
Get PDFGlobal interest in student mental health has led to a proliferation of research and practice aimed at operationalising a whole university approach to wellbeing. In education, this has entailed innovation and evaluation of different assessment types and conditions; curricular content and skills interventions; and pedagogical practices. To date however, these studies typically utilise quasi-experimental designs to evaluate isolated, additive, individual-level interventions. The absence of rigorous theoretical framing to conceptualise and operationalise holistic wellbeing-promotive practices and cultures has compromised the translation of this research activity into positive outcomes for students and staff. In response, this paper aims to develop an integrative and enactive framework drawing on the embodied learner and pragmatist philosophy to address the following research question: what value does an integrative framework for conceptualising student wellbeing in education have for policy and practice within a whole university approach? Piloted with narrative data from a case study vignette using a focus group method with five students, the findings demonstrate how this integrative framework can help situate wellbeing-promoting interventions in the wider frame of educational cultures, contexts, and systems, whilst remaining aligned to educational goals and responsive to the diverse experience of multiple learners. The implications for a whole university approach are discussed
An Intercontinental and Transhistorical “Matter of Mutual Concern”: A Response to George Shepperson, “The American Negro and Africa” (1964)
No full textFading Parameter Estimation for Backscattering Signals Using Method of Moments
Get PDFBackscattering communication has gained significant interest due to its low power consumption and wide applicability in the Internet of Things (IoT) and wireless sensing systems. Accurate parameter estimation of backscat-tering signals is essential for improving system performance and optimizing communication efficiency. This article focuses on the channel model parameter estimation using the method of moments for backscattering signals in three different fading channels: Nakagami-m, Rayleigh, and Rician. A total of five different cases are considered using these distributions. Moment-based estimators are derived for key channel model parameters in each case, and their accuracy is verified through MATLAB simulation by comparing them with the case without backscattering and the case without noise. The results indicate that the moment-based estimators provide accurate parameter estimation in various fading conditions
How to find opinion leader on the online social network?
Get PDFOnline social networks (OSNs) provide a platform for individuals to share information, exchange ideas, and build social connections beyond in-person interactions. For a specific topic or community, opinion leaders are individuals who have a significant influence on others’ opinions. Detecting opinion leaders and modeling influence dynamics is crucial as they play a vital role in shaping public opinion and driving conversations. Existing research have extensively explored various graph-based and psychology-based methods for detecting opinion leaders, but there is a lack of cross-disciplinary consensus between definitions and methods. For example, node centrality in graph theory does not necessarily align with the opinion leader concepts in social psychology. This review paper aims to address this multi-disciplinary research area by introducing and connecting the diverse methodologies for identifying influential nodes. The key novelty is to review connections and cross-compare different multi-disciplinary approaches that have origins in: social theory, graph theory, compressed sensing theory, and control theory. Our first contribution is to develop cross-disciplinary discussion on how they tell a different tale of networked influence. Our second contribution is to propose trans-disciplinary research method on embedding socio-physical influence models into graph signal analysis. We showcase inter- and trans-disciplinary methods through a Twitter case study to compare their performance and elucidate the research progression with relation to psychology theory. We hope the comparative analysis can inspire further research in this cross-disciplinary area
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