bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cognitive reserve against Alzheimer’s pathology is linked to brain activity during memory formation
Authors: Vockert Niklas , Machts Judith , Kleineidam Luca , Nemali Aditya , Incesoy Enise I. , Bernal Jose , Schütze Hartmut , Yakupov Renat , Peters Oliver , Gref Daria , Schneider Luisa Sophie , Preis Lukas , Priller Josef , Spruth Eike Jakob , Altenstein Slawek , Schneider Anja , Fliessbach Klaus , Wiltfang Jens , Rostamzadeh Ayda , Glanz Wenzel , Teipel Stefan , Kilimann Ingo , Goerss Doreen , Laske Christoph , Munk Matthias H. , Spottke Annika , Roy Nina , Heneka Michael T. , Brosseron Frederic , Wagner Michael , Wolfsgruber Steffen , Dobisch Laura , Dechent Peter , Hetzer Stefan , Scheffler Klaus , Zeidman Peter , Stern Yaakov , Schott Björn H. , Jessen Frank , Düzel Emrah , Maass Anne , Ziegler Gabriel ,   the DELCODE study group
Published: November 2024

AbstractThe cognitive reserve (CR) hypothesis posits that individuals can differ in how their brain function is disrupted by pathology associated with aging and neurodegeneration. Here, we test this hypothesis in the continuum from cognitively normal to at-risk stages for Alzheimer’s Disease (AD) to AD dementia using longitudinal data from 490 participants of the DELCODE multicentric observational study. Brain function is measured using task fMRI of visual memory encoding. Using a multivariate moderation analysis, we identify a CR-related activity pattern underlying successful memory encoding that moderates the detrimental effect of AD pathological load on cognitive performance. CR is mainly represented by a more pronounced expression of the task-active network encompassing deactivation of the default mode network (DMN) and activation of inferior temporal regions including the fusiform gyrus. We devise personalized fMRI-based CR scores that moderate the impact of AD pathology on cognitive performance and are positively associated with years of education. Furthermore, higher CR scores attenuate the effect of AD pathology on cognitive decline over time. Our findings primarily provide evidence for the maintenance of core cognitive circuits including the DMN as the neural basis of CR. Individual brain activity levels of these areas during memory encoding have prognostic value for future cognitive decline.
Hepatocellular senescence induces multi-organ senescence and dysfunction via TGFβ
Authors: Kiourtis Christos , Terradas-Terradas Maria , Gee Lucy M. , May Stephanie , Georgakopoulou Anastasia , Collins Amy L. , O’Sullivan Eoin D. , Baird David P. , Hassan Mohsin , Shaw Robin , Tan Ee Hong , Müller Miryam , Engelmann Cornelius , Andreola Fausto , Hsieh Ya-Ching , Reed Lee H. , Borthwick Lee A. , Nixon Colin , Clark William , Hanson Peter S. , Sumpton David , Mackay Gillian , Suzuki Toshiyasu , Najumudeen Arafath K. , Inman Gareth J. , Campbell Andrew , Barry Simon T. , Quaglia Alberto , Morris Christopher M. , LeBeau Fiona E. N. , Sansom Owen J. , Kirschner Kristina , Jalan Rajiv , Oakley Fiona , Bird Thomas G. 
Published: November 2024

AbstractCellular senescence is not only associated with ageing but also impacts physiological and pathological processes, such as embryonic development and wound healing. Factors secreted by senescent cells affect their microenvironment and can induce spreading of senescence locally. Acute severe liver disease is associated with hepatocyte senescence and frequently progresses to multi-organ failure. Why the latter occurs is poorly understood. Here we demonstrate senescence development in extrahepatic organs and associated organ dysfunction in response to liver senescence using liver injury models and genetic models of hepatocyte-specific senescence. In patients with severe acute liver failure, we show that the extent of hepatocellular senescence predicts disease outcome, the need for liver transplantation and the occurrence of extrahepatic organ failure. We identify the TGFβ pathway as a critical mediator of systemic spread of senescence and demonstrate that TGFβ inhibition in vivo blocks senescence transmission to other organs, preventing liver senescence induced renal dysfunction. Our results highlight the systemic consequences of organ-specific senescence, which, independent of ageing, contributes to multi-organ dysfunction.
Past foraminiferal acclimatization capacity is limited during future warming
Authors: Ying Rui , Monteiro Fanny M. , Wilson Jamie D. , Ödalen Malin , Schmidt Daniela N. 
Published: November 2024

AbstractClimate change affects marine organisms, causing migrations, biomass reduction and extinctions1,2. However, the abilities of marine species to adapt to these changes remain poorly constrained on both geological and anthropogenic timescales. Here we combine the fossil record and a global trait-based plankton model to study optimal temperatures of marine calcifying zooplankton (foraminifera, Rhizaria) through time. The results show that spinose foraminifera with algal symbionts acclimatized to deglacial warming at the end of the Last Glacial Maximum (LGM, 19–21 thousand years ago, ka), whereas foraminifera without symbionts (non-spinose or spinose) kept the same thermal preference and migrated polewards. However, when forcing the trait-based plankton model with rapid transient warming over the coming century (1.5 °C, 2 °C, 3 °C and 4 °C relative to pre-industrial baseline), the model suggests that the acclimatization capacities of all ecogroups are limited and insufficient to track warming rates. Therefore, foraminifera are projected to migrate polewards and reduce their global carbon biomass by 5.7–15.1% (depending on the warming) by 2100 relative to 1900–1950. Our study highlights the different challenges posed by anthropogenic and geological warming for marine plankton and their ecosystem functions.
Observation of Hilbert space fragmentation and fractonic excitations in 2D
Authors: Adler Daniel , Wei David , Will Melissa , Srakaew Kritsana , Agrawal Suchita , Weckesser Pascal , Moessner Roderich , Pollmann Frank , Bloch Immanuel , Zeiher Johannes 
Published: November 2024

AbstractThe relaxation behaviour of isolated quantum systems taken out of equilibrium is among the most intriguing questions in many-body physics1. Quantum systems out of equilibrium typically relax to thermal equilibrium states by scrambling local information and building up entanglement entropy. However, kinetic constraints in the Hamiltonian can lead to a breakdown of this fundamental paradigm owing to a fragmentation of the underlying Hilbert space into dynamically decoupled subsectors in which thermalization can be strongly suppressed2–5. Here we experimentally observe Hilbert space fragmentation in a two-dimensional tilted Bose–Hubbard model. Using quantum gas microscopy, we engineer a wide variety of initial states and find a rich set of manifestations of Hilbert space fragmentation involving bulk states, interfaces and defects, that is, two-, one- and zero-dimensional objects. Specifically, uniform initial states with equal particle number and energy differ strikingly in their relaxation dynamics. Inserting controlled defects on top of a global, non-thermalizing chequerboard state, we observe highly anisotropic, subdimensional dynamics, an immediate signature of their fractonic nature6–9. An interface between localized and thermalizing states in turn shows dynamics depending on its orientation. Our results mark the observation of Hilbert space fragmentation beyond one dimension, as well as the concomitant direct observation of fractons, and pave the way for in-depth studies of microscopic transport phenomena in constrained systems.
Edge dislocations, alloy composition, and grain boundaries effects on the mechanical properties in NiCo binary alloy
Authors: Nobin Md. Nadim Mahamud , Ali Md. Lokman , Alam Md. Khairul 
Published: November 2024

AbstractIn this research, we investigated the mechanical properties of NiCo binary alloy both with and without grain boundaries, across various alloy compositions. We investigated the effects of edge dislocation, alloy compositions, and grain boundaries on the mechanical properties of FCC $$NiCo$$

NiCo

using molecular dynamics (MD) simulations. By analyzing the influence of the grain boundaries with different alloy compositions on several mechanical properties, we were able to gain a deeper understanding of how these characteristics were modified. The elastic moduli increased with increasing grain boundaries for a specific chemical composition, indicating that $$NiCo$$

NiCo

becomes more rigid. The anisotropy factor analysis showed that $$NiCo$$

NiCo

have a natural tendency toward anisotropy, which is further influenced by the presence of grain boundaries. Grain boundaries have a significant effect on strength and ductility across a wide range of alloy compositions. These results indicate that a deeper comprehension of these implications can aid in designing improved binary alloy with superior mechanical characteristics.
Neural networks for abstraction and reasoning
Authors: Bober-Irizar Mikel , Banerjee Soumya 
Published: November 2024

AbstractFor half a century, artificial intelligence research has attempted to reproduce the human qualities of abstraction and reasoning - creating computer systems that can learn new concepts from a minimal set of examples, in settings where humans find this easy. While specific neural networks are able to solve an impressive range of problems, broad generalisation to situations outside their training data has proved elusive. In this work, we look at several novel approaches for solving the Abstraction & Reasoning Corpus (ARC). This is a dataset of abstract visual reasoning tasks introduced to test algorithms on broad generalization. Despite three international competitions with $100,000 in prizes, the best algorithms still fail to solve a majority of ARC tasks. The best solvers today rely on complex hand-crafted rules, without using machine learning at all. We revisit whether recent advances in neural networks allow progress on this task, or whether an entirely different class of models are required. First, we adapt the DreamCoder neurosymbolic reasoning solver to ARC. DreamCoder automatically writes programs in a bespoke domain-specific language to perform reasoning, using a neural network to mimic human intuition. We present the Perceptual Abstraction and Reasoning Language (PeARL) language, which allows DreamCoder to solve ARC tasks, and propose a new recognition model that allows us to significantly improve on the previous best implementation. We also propose a new encoding and augmentation scheme that allows large language models (LLMs) to solve ARC tasks, and find that the largest models can solve some ARC tasks. LLMs are able to solve a different group of problems to state-of-the-art solvers, and provide an interesting way to complement other approaches. We perform an ensemble analysis, combining systems to achieve better results than any system alone and analysing individual strengths. However, it is sobering to see that approaches based on neural networks still lag behind existing hand-crafted solvers, and we suggest avenues for future improvements. Our findings with the ensemble model may indicate that a diversity of methods might be necessary to solve problems in ARC. Humans likely employ diverse strategies to solve ARC. Studies involving human participants to identify the strategies they employ to solve ARC could provide valuable insights for future AI approaches. Finally, we publish the Python library to make future research on ARC easier.
Evolution of a laser wake cavity in a MCF plasma
Authors: Bierwage Andreas , Esirkepov Timur Zh. , Koga James K. , Pirozhkov Alexander S. , Aiba Nobuyuki , Huang Kai , Kando Masaki , Kiriyama Hiromitsu , Matsuyama Akinobu , Shinohara Kouji , Yagi Masatoshi , Yun Gunsu S. 
Published: November 2024

AbstractA laser pulse focused to relativistic intensity inside a magnetically confined fusion (MCF) plasma plows away all electrons in its path. The ensuing Coulomb explosion of the ions leaves behind a cavity of microscopic size, with gradients in the electric potential and plasma density orders of magnitude stronger than anything the plasma could generate spontaneously. When posing questions concerning the practical utility of such an exotic perturbation, the life time and structural evolution of the cavity are of interest. Our simulations in a simplified 1D + 2D setting and otherwise realistic parameters suggest that a sub-mm wide seed cavity (meant to resemble the laser wake channel) collapses or disintegrates within 10 ns. The dynamics are sensitive to the relative scales of the cavity, Debye shielding and gyration. We find evidence for the possibility that the collapsing seed cavity spawns solitary micro-cavities. It remains to be seen whether such structures form and survive long enough in a 3D setting to alter the local plasma conditions (e.g., as micro-cavity clusters) in ways that may be utilized for practical purposes such as plasma initiation, diagnostics or control.
Highly conducting Laser-Induced Graphene-Ag nanoparticle composite as an effective supercapacitor electrode with anti-fungal properties
Authors: Prakash Abhishek , Holla Sowmya R. , Selvaraj Subbalaxmi , Nayak Ramakrishna , De Shounak , Saquib Mohammad , Selvakumar M. 
Published: November 2024

AbstractThis study presents a simple and an environmentally friendly approach to make Laser-Induced Graphene (LIG) based supercapacitor electrodes anchored with abundant Silver Nanoparticles (AgNPs). LIG, was synthesized using a CO2 laser writing technique on polyimide substrate. The LIG-Ag composite was prepared using two techniques, drop-coating, and screen-printing. Ag nanoparticles prepared using the plant extract of Swietenia Macrophylla was utilized to drop-coat AgNP on LIG substrate. Screen-printing was done by using a commercial Ag-ink and a suitable mesh. The supercapacitor made from screen-printed electrodes and supercapacitor made form drop-coated electrodes showed a high specific capacitance of 118 mF/cm2, 38 mF/cm2, and a high energy density of 2.42 mWh/cm2, 0.05 mWh/cm2 respectively. The screen-printed composite of LIG and AgNP was further studied for its anti-fungal properties and proved to be effective against Candida sp.
On the directionality of membrane coupled Helmholtz resonators under open air conditions
Authors: Domingo-Roca R. , Feeney A. , Windmill J. F. C. , Jackson-Camargo J. C. 
Published: November 2024

AbstractControlling the absorption and diffusion of sound in the audible range constitutes an exciting field of research. Acoustic absorbers and diffusers perform extraordinarily well at high frequencies with sizes comparable to the wavelength of the working frequency. Conversely, efficient low-frequency attenuators demand large volumes leading to unpractical sizes, and there is now interest in determining whether the size of the resonator can be reduced while not compromising – or perhaps even decreasing – the working frequency. One viable approach is through the use of metamaterials to enable the control of device dynamics such that heavy sub-wavelength attenuation can be efficiently realised. To achieve this goal, the theoretical (including a mathematical model and the use of finite element analysis) and experimental characterisation of 3D-printed membrane-coupled Helmholtz resonator (HR) acoustic metamaterials (AMMs) is explored. The results reveal good agreement between theory and experiments, and show that membrane-coupled HR AMMs feature heavy sub-wavelength acoustic attenuation (λ/55) while also showcasing directional responses under open air conditions. These features are explained by the interplay between resonator size, membrane characteristics, and the presence of two acoustic ports. It is anticipated that, together with recent advances on smart AMMs, these systems will foster new progress in the development of dynamic AMMs for wideband attenuation.
DEUFormer: High‐precision semantic segmentation for urban remote sensing images
Authors: Jia Xinqi , Song Xiaoyong , Rao Lei , Fan Guangyu , Cheng Songlin , Chen Niansheng 
Published: November 2024

AbstractUrban remote sensing image semantic segmentation has a wide range of applications, such as urban planning, resource exploration, intelligent transportation, and other scenarios. Although UNetFormer performs well by introducing the self‐attention mechanism of Transformer, it still faces challenges arising from relatively low segmentation accuracy and significant edge segmentation errors. To this end, this paper proposes DEUFormer by employing a special weighted sum method to fuse the features of the encoder and the decoder, thus capturing both local details and global context information. Moreover, an Enhanced Feature Refinement Head is designed to finely re‐weight features on the channel dimension and narrow the semantic gap between shallow and deep features, thereby enhancing multi‐scale feature extraction. Additionally, an Edge‐Guided Context Module is introduced to enhance edge areas through effective edge detection, which can improve edge information extraction. Experimental results show that DEUFormer achieves an average Mean Intersection over Union (mIoU) of 53.8% on the LoveDA dataset and 69.1% on the UAVid dataset. Notably, the mIoU of buildings in the LoveDA dataset is 5.0% higher than that of UNetFormer. The proposed model outperforms methods such as UNetFormer on multiple datasets, which demonstrates its effectiveness.
Pseudorandom high‐frequency injection synchronous reluctance motor sensorless control with parameter variation consideration
Authors: Wang Jianyuan , Jing Hanghui , Zhang Yanping , Yin Zhonggang , Guo Yupeng 
Published: November 2024

AbstractThe sensorless control of synchronous reluctance motor (SynRM) in the zero and low‐speed domain using the traditional high‐frequency injection method has the problems of audible noise caused by the high‐frequency injection and high‐frequency loss caused by the change of working conditions, which limits the practical application of SynRM in the industrial field. To solve the problem of high‐frequency noise and loss, a pseudo‐random high‐frequency injection method considering parameter variation is proposed in this paper. Firstly, the signal injection form was adjusted to expand the power spectral density of the high‐frequency current, and the current energy spike was suppressed to reduce high‐frequency noise. Secondly, the current demodulation was combined with the flux map model to complete the injection voltage amplitude adjustment, so that the response current was kept constant under multiple operating conditions to reduce the high‐frequency loss. At the same time, the flux map model is applied to the observer to reduce the rotor position estimation error caused by the cross‐coupling effect. Under the condition of satisfying the dynamic and steady performance requirements of sensorless control, the high‐frequency loss and sharp noise caused by the high‐frequency injection method are effectively suppressed. Finally, experiments were carried out on a 1.5 kW SynRM drive platform to verify the feasibility and effectiveness of the sensorless control scheme in this paper.
Diuretika bei Patienten mit Bluthochdruck
Authors: Babic Milen 
Published: November 2024

ZUSAMMENFASSUNGDiuretika, allen voran die Thiazide und seine Abkömmlinge Chlorthalidon und Indapamid, sind neben Kalzium-Kanal-Blockern, ACE-Hemmern (ACE: Angiotensin Converting Enzyme) und Angiotensin-Rezeptor-Blockern (ARB) Mittel der ersten Wahl zur Behandlung von Bluthochdruck. Insbesondere die thiazidartigen Diuretika senken das Risiko für kardiovaskuläre Ereignisse vergleichbar effektiv wie die übrigen empfohlenen Erstlinientherapien und bieten dabei ein gutes Sicherheitsprofil. Besonders gut auf Diuretika ansprechende Patienten sind solche mit einem Hypertonus, der adipositasassoziiert, salzsensitiv, isoliert systolisch oder therapieresistent ist. Hyponatriämie und Hypokaliämie stellen relevante Risiken dar und bedürfen einer besonderen Sorgfalt in der Betreuung der Patienten; dabei hilft eine Kombination mit kaliumsparenden Diuretika, Hypokaliämien zu vermeiden. Metabolische Nebenwirkungen, wie eine Blut-Zucker-Verschlechterung, sind hingegen bei einer kaliumreichen, herzgesunden ­Ernährungsform nicht relevant.
Incidence of New, Nonphysiologic Maternal Findings on Fetal Magnetic Resonance Imaging
Authors: Shao Shirley J. , Grimes Andrew , Rashad Marley , Poder Liina , Shum Dorothy , Sobhani Nasim C. 
Published: November 2024

Objective Fetal magnetic resonance imaging (MRI) is increasingly used for evaluation of fetal anomalies, and rates of incidental maternal findings are not well characterized. Our objective was to evaluate the rate of incidental maternal findings at the time of antenatal MRI performed for fetal indications.
Study Design This was a retrospective cohort study that included all fetal MRIs performed between 2018 and 2023 at a single tertiary care institution with a multidisciplinary fetal diagnosis and treatment center. The electronic medical record was reviewed to identify all documented maternal findings and any new, nonphysiologic maternal findings. The latter was defined as previously unknown abnormalities of maternal structures unrelated to normal physiology.
Results Our study included 834 imaging events, performed at an average gestational age of 23 weeks. The most common indication for imaging was fetal anomaly (81.1%). The most common imaging type was fetal brain MRI (81.4%). Overall, 16.2% reported a maternal finding and 7% reported a new, nonphysiologic finding. The most common new, nonphysiologic findings were renal cysts (n = 11), liver cysts (n = 6), and gallstones or gallbladder sludge (n = 5). Compared with imaging events that included a fetal brain MRI, imaging events that included a fetal body MRI had a significantly higher rate of any maternal findings (53.0 vs. 10.4%, p < 0.001) and new, nonphysiologic maternal findings (26.9 vs. 3.7%, p < 0.001).
Conclusion Our results suggest that the risk of identifying new, nonphysiologic maternal findings on fetal MRI is low. The rate of any maternal and new, nonphysiologic maternal findings may differ by fetal MRI type due to differences in imaging depth and extent of radiology subspecialist review. These data should be incorporated into pretest counseling for patients planning to have fetal MRI.
Key Points
Investigations on the near-wall bubble dynamic behaviors in a diverging channel
Authors: Zhao Liang , Huang Jiang , Chen Caozhi , Gao Jianan 
Published: November 2024

This study investigates the movement characteristics and causes of the dramatic deceleration of individual bubbles as they enter a diverging channel near the wall, an important phenomenon for understanding fluid dynamics in the Venturi-type bubble generator. The use of a modified volume of fluid model with a user defined source method based on van der Geld’s drag theory improves the accuracy of bubble velocity predictions. Visualization experiments were conducted to observe air bubble motion in water, focusing on deceleration near the wall, while numerical simulations were employed to complement these observations. The results reveal the identification of forces governing bubble deceleration, such as pressure gradient, drag, added mass, and lateral force (lift and wall lubrication). Pressure gradient and added mass forces of magnitudes of 106 N/m3 were found to dominate the deceleration process, with drag and lift forces contributing to bubble acceleration and lateral motion in low-speed liquid flow, respectively. In addition, simulations revealed the formation of a faster-moving liquid region downstream of the bubble during rapid deceleration, highlighting the critical role of added mass on the bubble dramatic deceleration process.