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The investigation and prosecution of financial crime: a comparative perspective on institutional roles and responsibilities
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GDP Revisions are Not Cool: The Impact of Statistical Agencies’ Trade-Off
No full textJEL Classification: C01, C82, E01.A working paper version of the article is available at ECB (https://www.ecb.europa.eu/pub/pdf/scpwps/ecb.wp2857~073085df17.en.pdf) and at SSRN (Asimakopoulos, Stylianos and Lalik, Magdalena and Paredes, Joan and García, José Salvado, GDP Revisions are Not Cool: The Impact of Statistical Agencies’ Trade-Off (October, 2023). ECB Working Paper No. 2023/2857, Available at SSRN: https://ssrn.com/abstract=4618392 or http://dx.doi.org/10.2139/ssrn.4618392). It has not been certified by peer review.Official estimates of economic growth are regularly revised and therefore forecasts for GDP growth are done on the basis of ever-changing data. The economic literature has intensively studied the properties of those revisions and their implications for forecasting models. However, it is much less known about the reasons for Statistical Agencies (SAs) to revise their estimates. In order to be timely and reliable, SAs have an explicit interest in not revising their initial GDP estimates too much, while they are much more open to revise GDP components over time. More than a curiosity, we exploit this resulting cross-correlation of GDP components revisions to build a model to better forecast GDP...
Ultrahigh strength magnesium via solidification of nanocolloid
No full text...We report a simple, scalable route to produce ultrahigh-strength magnesium (Mg) viasolidification of a colloidal solution containing nanoscale niobium carbide (NbC) particles suspended in liquid magnesium (Mg(l)). A single-atom-level investigation reveals that NbC exhibits excellent spontaneous wetting with molten Mg, driven by the formation of an ordered layer of Mg atoms strongly bonded to the carbon atoms on the NbC {001} surface. This creates a novel type of Mg-coated NbC (Mg@NbC) particles in liquid Mg and is referred to as Mg(l)-Mg@NbC nanocolloid. This unique and spontaneous wetting behaviour enables uniform nanoparticle dispersion in the molten Mg without external fields, and in the solidified Mg matrix without the need for thermomechanical processing. The resulting NbC dispersoids act as coherent, hard reinforcement phases, significantly strengthening the Mg matrix. As a result, the Mg-NbC material exhibits ultrahigh tensile strength and stiffness, surpassing those of all previously reported Mg alloy systems.Acknowledgements
X.Y. and H.B.N. acknowledge funding from the Engineering and Physical Sciences Research Council (EPSRC), grant number EP/W005042/1. The SuperSTEM Laboratory is the UK National Research Facility for Advanced Electron Microscopy, supported by EPSRC under grant number EP/W021080/1. M.K. acknowledges the fundings of the A-Step program grant number JPMJTR23R9 and of the KSAC program grant number 2024_21 from Japan Science and Technology Agency (JST). S.N. and M.K. also thank to the funding of Bilateral Joint Research, grant number JPJSBP120235704 from the Japan Society for the Promotion of Science (JSPS). X.Y. and H.B.N. thank CBMM (Companhia Brasileira de Metalurgia e Mineração) for supporting a range of NbC powder feedstock. We thank Dr Qing Cai for assistance in microscopy characterisation
V2X-Assisted Distributed Computing and Control Framework for Connected and Automated CAVs under Ramp Merging Scenario
Full text linkThis paper presents a mobile computing-based framework for distributed computing and cooperative control of connected and automated vehicles (CAVs) in ramp merging scenarios under intelligent transportation systems (ITS). A centralized trajectory planning problem is first formulated to optimize merging efficiency and safety. To eliminate reliance on a central controller, a distributed solution is developed using ADMM algorithm based on V2X communication, enabling CAVs to collaboratively compute trajectories in parallel by leveraging their onboard computing power. Building on this, a multi-vehicle model predictive control (MPC) problem is proposed to enhance system stability under strict constraints. To solve it efficiently, a Distributed Cooperative Iterative MPC (DCIMPC) method is introduced, which decomposes and reformulates the problem for real-time distributed execution across CAVs. Together, these methods form a mobile edge computing-driven control framework. Simulations and experiments demonstrate significant improvements in computational efficiency and system performance, highlighting the potential of mobile computing in cooperative CAV control.This work was supported in part by Jiangxi Province Science and
Technology Development Programme under Grant No. 20242BCC32016, in
part by the National Natural Science Foundation of China under Grant No.
61701197, 62531015 and U25A20399, in part by the Basic Research Program of Jiangsu under Grant BK20252084, in part by the National Key Research and Development Program of China under Grant No. 2021YFA1000500(4), in part by the Shanghai Kewei under Grant 24DP1500500, in part by the Research Grants Council under the Areas of Excellence Scheme under Grant AoE/E-601/22-R and in part by the 111 Project under Grant No. B23008
Perfusion microbioreactor for CAR-Treg manufacturing
Full text linkHighlights:
• Perfusion microbioreactor achieves Treg expansion comparable to gold standard G-Rex device.
• Spatial confinement increases lentiviral transduction efficiency of primary, human cells.
• Compact, low-volume platform reduces the physical footprint of cell manufacturing.
• Device supports future automation and advances progress toward point-of-care production.Data and code availability:
All data reported in this paper will be shared by Ciro Chiappini upon request; this paper does not report original code. All datasets generated and analysed in this study, including raw flow cytometry files and source data, are available from the lead contact upon reasonable request.Supplemental Information is available online.This is a PDF of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability. This version will undergo additional copyediting, typesetting and review before it is published in its final form. As such, this version is no longer the Accepted Manuscript, but it is not yet the definitive Version of Record; we are providing this early version to give early visibility of the article. Please note that Elsevier’s sharing policy for the Published Journal Article applies to this version, see: https://www.elsevier.com/about/policies-andstandards/sharing#4-published-journal-article. Please also note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.Summary:
Manufacturing cell and gene therapies (CGTs) at scale presents challenges in cost, product consistency, and adaptability to personalised treatments. Traditional large-volume bioreactors are designed to support cell growth through controlled nutrient delivery and gas exchange, but are poorly suited to the decentralised, small-batch production required for personalised therapies like Chimeric Antigen Receptor (CAR) T-cells.
To address this, we have developed the KCL-Microbioreactor (K-MBR), a closed microbioreactor platform based on microfluidic principles. Engineered in polydimethylsiloxane (PDMS), the K-MBR combines spatial confinement, semi-continuous perfusion, and integrated viral transduction in a compact footprint enabling efficient gene delivery and robust expansion of therapeutic cells.
We demonstrate the platform’s utility by generating functional CAR-Tregs targeting HLA-A2, achieving a 92% increase in yield compared to conventional methods. The K-MBR offers a streamlined, solution for CGT manufacturing, with potential to reduce productions cost and enhance scalability across a broad range of cell therapies.C.C. acknowledges funding from the European Union under the ERC Starting Grant ENBION 759577 and the medical research council under the Confidence in Concept award (MC_PC_18052); Medical Research Council (MRC); MFX (MicrofluidX) Ltd. acknowledges funding from the MRC DTP iCASE Studentship Scheme
Adapting through adversity: The transformation of art therapists’ professional identity
Full text linkHighlights:
• Dual-dialectical lens reveals how crises disrupt and transform professional identity.
• COVID-19, digitalisation and war reshaped arts therapists’ professional identity.
• Practitioners adapted roles, boundaries, and practices to sustain identity.
• Reflection and learning rebuilt confidence and strengthened professional roles.
• Crises spurred creativity and peer support, reaffirming professional meaning.Data availability:
The authors do not have permission to share data.Professional identity, constantly reshaped by social and technological change, comes under increased pressure during crises. The COVID-19 pandemic and the war in Ukraine profoundly disrupted healthcare systems, and art therapy was no exception. This study examines how these overlapping crises have reshaped art therapists’ professional identity, focusing on dialectical processes of contradiction, adaptation, and the restructuring of therapeutic roles and self-concept. Semi-structured interviews were conducted with 31 Latvian art therapists working across diverse settings. Reflexive thematic analysis, guided by a dual-dialectical framework drawing on Hegel and Badiou, identified five key tensions: disconnection versus belonging; vulnerability versus responsibility; tradition versus innovation; collaboration versus distinctiveness; and doubt versus confidence. Through reflection and adaptive strategies, art therapists integrated these contradictions, strengthening and sustaining their professional identities. Hegel’s dialectics accounted for gradual synthesis, while Badiou’s concept of rupture captured abrupt redefinitions, together showing how professionals maintain and reshape identity during disruption
Large Language Model-Based Task Offloading and Resource Allocation for Digital Twin Edge Computing Networks
Full text linkIn this paper, we propose a general digital twin edge computing network comprising multiple vehicles and a server. Each vehicle generates multiple computing tasks within a time slot, leading to queuing challenges when offloading tasks to the server. The study investigates task offloading strategies, queue stability, and resource allocation. Lyapunov optimization is employed to transform long-term constraints into tractable short-term decisions. To solve the resulting problem, an in-context learning approach based on large language model (LLM) is adopted, replacing the conventional multi-agent reinforcement learning (MARL) framework. Experimental results demonstrate that the LLM-based method achieves comparable or even superior performance to MARL.This work was supported in part by Jiangxi Province Science and Technol- ogy Development Programme
under Grant No. 20242BCC32016, in part by the National Natural Science Foundation of China under
Grant No. 61701197, in part by the National Key Research and Development Program of China under
Grant No. 2021YFA1000500(4), in part by the Research Grants Council under the Areas of Excellence
Scheme under Grant AoE/E601/22R and in part by the 111 Project under Grant No. B23008
Revisiting the Nazi-Fascist Military Alliance: Italo-German Rivalry and Cooperation during the Mediterranean War, 1940-1943
No full text..
A response to Granberg et al. (2024)
Full text linkIn this response to Granberg et al. (2024), I explain my reasons for using the Flesch Reading Ease, Flesch-Kincaid, Gunning Fog, SMOG and Dale-Chall readability scores in Hengel (2022). I also identify several errors in textstat, the program Granberg et al. (2024) use to calculate their scores. After correcting these errors, textstat’s gender readability gaps and p-values for the Flesch Reading Ease, Flesch-Kincaid, Gunning Fog and SMOG scores are very similar to those reported in Hengel (2022). textstat also generates Dale-Chall gender readability gaps that are 62–79 percent of the Dale-Chall estimate from Hengel (2022) and remaining variation is entirely due to differences in the familiar word lists used by each program (e.g., textstat omits words such as “men’s” and “women’s” that are disproportionately found in female-authored papers). Meanwhile, Granberg et al. (2024)’s alternative scores either generate similarly-sized readability gaps or have been shown to be less powerful predictors of reading comprehension in adult reading material. I conclude by noting that Hengel (2022) neither relies on nor claims to rely on an assumption that readability scores predict scientific quality.Forms part of the public project: Brodeur, Abel. 2026. “Reproduction of "publishing While Female: Are Women Held to Higher Standards? Evidence from Peer Review".” OSF. January 27. doi:10.17605/OSF.IO/ZB73Y. The full reproduction report is available under "Files". The author [Erin Hengel] responded in December 2024. The replicators' response and author's second response are also available under "Files" at https://doi.org/10.17605/OSF.IO/ZB73Y
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