bluuebunny/crossref_metadata_2025_split huggingface dataset:
Examining memory reconsolidation as a mechanism of nitrous oxide’s antidepressant action
Authors: Williams Ella , Taujanskaite Ursule , Kamboj Sunjeev K. , Murphy Susannah E. , Harmer Catherine J. 
Published: January 2025

Abstract
There is an ongoing need to identify novel pharmacological agents for the effective treatment of depression. One emerging candidate, which has demonstrated rapid-acting antidepressant effects in treatment-resistant groups, is nitrous oxide (N2O)—a gas commonly used for sedation and pain management in clinical settings and with a range of pharmacological effects, including antagonism of NMDA glutamate receptors. A growing body of evidence suggests that subanaesthetic doses of N2O (50%) can interfere with the reconsolidation of maladaptive memories in healthy participants and across a range of disorders. Negative biases in memory play a key role in the onset, maintenance, and recurrence of depressive episodes, and the disruption of affective memory reconsolidation is one plausible mechanism through which N2O exerts its therapeutic effects. Understanding N2O’s mechanisms of action may facilitate future treatment development in depression. In this narrative review, we introduce the evidence supporting an antidepressant profile of N2O and evaluate its clinical use compared to other treatments. With a focus on the specific memory processes that are thought to be disrupted in depression, we consider the effects of N2O on memory reconsolidation and propose a memory-based mechanism of N2O antidepressant action.
Structural basis for metal ion transport by the human SLC11 proteins DMT1 and NRAMP1
Authors: Liziczai Márton , Fuchs Ariane , Manatschal Cristina , Dutzler Raimund 
Published: January 2025

Abstract
Iron and manganese are essential nutrients whose transport across membranes is catalyzed by members of the SLC11 family. In humans, this protein family contains two paralogs, the ubiquitously expressed DMT1, which is involved in the uptake and distribution of Fe2+ and Mn2+, and NRAMP1, which participates in the resistance against infections and nutrient recycling. Despite previous studies contributing to our mechanistic understanding of the family, the structures of human SLC11 proteins and their relationship to functional properties have remained elusive. Here we describe the cryo-electron microscopy structures of DMT1 and NRAMP1 and relate them to their functional properties. We show that both proteins catalyze selective metal ion transport coupled to the symport of H+, but additionally also mediate uncoupled H+ flux. Their structures, while sharing general properties with known prokaryotic homologs, display distinct features that lead to stronger transition metal ion selectivity.
A multi-frequency altimetry snow depth product over Arctic sea ice
Authors: Carret Alice , Fleury Sara , Di Bella Alessandro , Landy Jack , Lawrence Isobel , Kurtz Nathan , Laforge Antoine , Bouffard Jérome , Parrinello Tommaso 
Published: January 2025

Abstract
Sea ice thickness is an essential variable to understand and forecast the dynamic ice cover and can be estimated by satellite altimetry. Nevertheless, it is affected by uncertainties especially from snow depth, a key parameter to derive it from ice freeboard. We developed a snow depth product based on the differences between CryoSat-2 SAR Ku and IceSat-2 laser altimeters which have different snow penetration capabilities. We compared this product to other existing snow depth products. This comparison indicates correlations all above 0.37 and reaching 0.91 relative to airborne snow radar. We estimate the snow depth uncertainties of our product to be 0.06 m on average. Combining two frequencies to simultaneously measure ice and total freeboard reduces the uncertainties in ice thickness by around a factor of two compared with a single-frequency solution combined with a snow depth climatology. The lack of in situ measurements is a limiting factor to assess the advantages of coincident CryoSat-2 and ICESat-2 acquisitions. Validation data are of major importance for upcoming missions.
Spin transport properties in a topological insulator sandwiched between two-dimensional magnetic layers
Authors: Pournaghavi Nezhat , Sadhukhan Banasree , Delin Anna 
Published: January 2025

Abstract
Non-trivial band topology along with magnetism leads to different novel quantum phases. When time-reversal symmetry is broken in three-dimensional topological insulators (TIs) through, e.g., the proximity effect, different phases such as the quantum Hall phase or the quantum anomalous Hall(QAH) phase emerge, displaying interesting transport properties for spintronic applications. The QAH phase displays sidewall chiral edge states, which leads to the QAH effect. We have considered a heterostructure consisting of a TI, namely Bi
$$_2$$
Se
$$_3$$
, sandwiched between two two-dimensional ferromagnetic monolayers of CrI
$$_3$$
, to study how its topological and transport properties change due to the proximity effect. Combining DFT and tight-binding calculations, along with non-equilibrium Green’s function formalism, we show that a well-defined exchange gap appears in the band structure in which spin-polarised edge states flow. In a finite slab, the nature of the surface states depends on both the cross-section and thickness of the system. Therefore, we also study the width and finite-size effects on the transmission and topological properties of this magnetised TI nanoribbon.
Climate change influences on the potential geographic distribution of the invasive Asian longhorned tick, Haemaphysalis longicornis
Authors: Okely Mohammed , Chen Ze , Adly Eslam , Kamal Mahmoud 
Published: January 2025

Abstract
The Asian long-horned tick, Haemaphysalis longicornis Neumann, 1901, is the competent vector for severe fever with thrombocytopenia syndrome virus (SFTSV). Haemaphysalis longicornis originated mainly in eastern Asia and invaded many areas like Australia, New Zealand, and the Pacific islands, and was recently introduced to eastern parts of the USA. This species is characterized by high adaptability to a wide range of temperatures and can reproduce parthenogenically under stressful conditions. Migratory birds are important hosts of H. longicornis and are thought to be responsible for its unexpected invasion and introduction into new areas worldwide. This study predicted the historical (near current) global environmental suitability and the possible shifts in environmental suitability for H. longicornis under the ongoing climate change between 2021 and 2100. The results demonstrated that Europe is at potential of high environmental suitability for H. longicornis invasion although this species has not been recorded in any regions of Europe yet. Our model also anticipated the environmental suitability for H. longicornis in eastern parts of the USA, although the recently recorded occurrences there were not used in the model calibration. Climate change is thought to affect and increase the range of suitable environments for H. longicornis. The different maps introduced in this study may help improve understanding of the global environmental suitability for this invasive disease vector and predict the areas at high environmental suitability for possible invasion to prioritize the control programs and enhance quarantine procedures in these areas.
Elf autoencoder for unsupervised exploration of flat-band materials using electronic band structure fingerprints
Authors: Pentz Henry Kelbrick , Warford Thomas , Timokhin Ivan , Zhou Hongpeng , Yang Qian , Bhattacharya Anupam , Mishchenko Artem 
Published: January 2025

Abstract
Two-dimensional materials with flat electronic bands are promising for realising exotic quantum phenomena such as unconventional superconductivity and nontrivial topology. However, exploring their vast chemical space is a significant challenge. Here we introduce elf, an unsupervised convolutional autoencoder that encodes electronic band structure images into fingerprint vectors, enabling the autonomous clustering of materials by electronic properties beyond traditional chemical paradigms. Unsupervised visualisation of the fingerprint space then uncovers hidden chemical trends and identifies promising candidates based on similarities to well-studied exemplars. This approach complements high-throughput ab initio methods by rapidly screening candidates and guiding further investigations into the mechanisms underlying flat-band physics. The elf autoencoder is a powerful tool for autonomous discovery of unexplored flat-band materials, enabling unbiased identification of compounds with desirable electronic properties across the 2D chemical space.
Stellar hot spots due to star–planet magnetic interactions
Authors: Paul Arghyadeep , Strugarek Antoine , Réville Victor 
Published: January 2025

Context. Star-planet magnetic interactions (SPMIs) have been proposed as a mechanism for generating stellar hot spots with energy outputs on the order of 1019–21 watts. This interaction is primarily believed to be mediated by Alfvén waves, which are produced by the planetary obstacle and propagate towards the star. The stellar atmosphere, as a highly structured region, dictates where and how much of this incoming energy can actually be deposited as heat.
Aims. The stellar transition region separating the chromosphere from the corona of cool stars gives rise to a significant variation of the Alfvén speed over a short distance. Therefore, a reflection of the Alfvén waves at the transition region is naturally expected. We aim to characterize the efficiency of energy transfer due to SPMIs by quantifying a frequency-dependent reflection of the wave energy at the stellar transition region and its transmission to the stellar chromosphere.
Methods. We employed magnetohydrodynamic (MHD) simulations to model the frequency-dependent propagation of Alfvén waves through a realistic background stellar wind profile. The transmission efficiency as a function of the wave frequency was quantified. Further analyses were conducted to characterize the overall energy transfer efficiency of SPMIs in several candidate systems where chromospheric hot spots have been tentatively detected.
Results. Low-frequency waves experience greater reflection compared to high-frequency waves, resulting in reduced energy transfer efficiency for lower frequencies. Conversely, the parametric decay instability of Alfvén waves substantially diminishes the energy transfer efficiency at higher frequencies. As a result, there is a specific frequency range where energy transfer is most efficient. A significant fraction of the Alfvén wave energy is reflected at the stellar transition region and, in most realistic scenarios, the transmission efficiency to the chromosphere is found to be at a level of approximately 10%.
Invasive wild pig carcass availability does not affect coyote abundance in South Carolina, USA
Authors: Gaya Heather E. , D’Angelo Gino J. , Vukovich Mark , Youngmann Jordan L. , Lance Stacey L. , Kilgo John C. 
Published: January 2025

Context Control of invasive wild pigs (Sus scrofa) is a growing management concern throughout their invaded range. In the United States, control programs often leave wild pig carcasses on the landscape where they are freely available for consumption by scavengers such as coyotes (Canis latrans). Coyotes consume wild pigs, but no studies have investigated the importance of pig carcasses for maintaining coyote abundance. Aims We tested the hypothesis that coyote populations may be bolstered by wild pig carcasses created by control programs. Methods From July 2014 to July 2017, we surveyed road transects for scat to monitor coyote abundance in response to changing levels of pig carcass availability. From June 2015 to July 2017, wild pigs were removed from the eastern half of the study area and placed at one of four carcass dump sites on the western side. We analysed the scat data using an open population spatially-explicit capture–mark recapture model to estimate seasonal abundance and movement of coyotes in response to the carcass treatment. Results Coyote density across the entire study area declined from 95 coyotes/100 km2 in July 2014 to 65 coyotes/100 km2 by July 2016, but declines were unrelated to the carcass availability treatment. Additional analysis on non-genotyped scat data showed no apparent effect of carcass availability on coyote density. Coyote activity centers moved fewer than 100 m towards the nearest carcass dump site in response to the carcass treatment. Conclusions Wild pig carcass availability is not likely to be a primary driver of coyote abundance or territory selection at the study location. Implications We conclude that the availability of wild pig carcasses has little effect on coyote abundance and thus wild pig carcass removal will not be an effective coyote management strategy.
Establishing researcher identity as an emerging scholar
Authors: Nouri Melika 
Published: January 2025

Abstract
Becoming a researcher not only involves the acts of contributing to the body of knowledge in a field but also
constructing the image or identity of a researcher. Doctoral students who aim for positions within academia upon graduation see
doctoral education as a phase in which they develop their research and publication skills. An existing body of literature in the
field of writing has explored doctoral students’ experiences in research and publication focusing on the role of the external
factors, such as mentoring, resource accessibility, issue of authority, and so on. Other studies have explored how various
experiences facilitate or inhibit the development of research skills. However, less attention has been paid to the role of
internal motivators or intrinsic factors in doctoral writing and how these factors relate to research work and research
productivity. Using a narrative approach, this study explores the experiences of four doctoral students in developing a researcher
identity, focusing on the challenges that they face, and the role of the doctoral program in shaping their researcher identity.
This study offers insights into doctoral students’ training and advising by illustrating how research productivity can be enhanced
at the doctoral level.
The good, the bad, and the ugly
Authors: Lipińska Maria , Jemielniak Dariusz 
Published: January 2025

Abstract
The article focuses on anti-Ukrainian narratives spread on Twitter. We performed a Thick Big Data analysis of
words and hashtags connected with anti-Ukrainian narratives. We collected 16,700 tweets from 25 January 2023 to 22 February 2023,
focusing on the most popular and commented ones. Furthermore, we conducted multi-modal narrative and rhetorical analyses to
distinguish the typology of narrations. This article sheds light on how vital narration in disinformation campaigns and media
warfare on social media is. Most tweets contained narration highlighting the alleged appropriation of Polish culture by displaying
Ukrainian nationality. Such narration strongly influences a sense of insecurity and alienation in one’s own country. We discovered
that Ukrainian-related posts have negative sentiment and frequently spread disinformation.
A psycholinguistic analysis of clinical list-learning tests
Authors: Lansue Brette , Buchanan Lori 
Published: January 2025

Abstract
Neuropsychological assessments depend on language-based measures of cognitive functioning and the proper diagnosis
of certain disorders relies on patterns of impairment shown on these measures (Lezak et al., 2004). The current project was
motivated by the relative lack of literature integrating psycholinguistic experimental findings and clinical neuropsychological
research on tests of verbal memory, specifically list learning. It has been well documented that word-level characteristics impact
language processing and memory (see Yap & Balota, 2015 for a review). Therefore,
it is critical that neuropsychologists begin to understand how current measures can be confounded by the underlying lexical and
semantic characteristics of the stimuli and how, if used properly, those characteristics could aid in diagnostic specificity. The
current study examined the structure of popular list learning tests and analyzed the influence of several psycholinguistic
variables on the performance of healthy undergraduate participants. Results demonstrated that (1) age of acquisition, emotional
valence, semantic neighborhood density, and imageability predicted recall accuracy of items from neuropsychological tests and (2)
only one of the ten clinical test lists examined adequately controlled for these influential variables. Thus, clinicians could be
missing clinically relevant data by ignoring psycholinguistic contributions to patient performance.
Sisterhood construction through commenting by Chinese women
Authors: Wang Bin 
Published: January 2025

Abstract
This paper takes the form of a case study which examines to what extent a comment can be analyzed as a type of
speech action. This study analyzed 507 replies to a post on a popular Chinese social media application, Xiaohongshu, which
concerns feminist issues. A speech act analysis of these replies offers new insights on comments as a type of speech act by
showing their constructive functions across intra-utterance, inter-utterance, and extra-textual contexts. Comments can facilitate
the securing of hearer’s uptake of an illocutionary act, may modify the actual hearer’s uptake of another illocutionary act, and
may ultimately contribute to the construction of sisterhood within a redefined context. The performance of comments in this study
is grounded in a particular circumstance and is highly context-dependent. Nevertheless, this finding leaves open the possibility
that comments may display other effects in different contexts.
A robust auto-contouring and data augmentation pipeline for adaptive MRI-guided radiotherapy of pancreatic cancer with a limited dataset
Authors: Shojaei Mehdi , Eiben Björn , McClelland Jamie R , Nill Simeon , Dunlop Alex , Hunt Arabella , Ng-Cheng-Hin Brian , Oelfke Uwe 
Published: January 2025

Abstract

Objective. This study aims to develop and evaluate a fast and robust deep learning-based auto-segmentation approach for organs at risk in MRI-guided radiotherapy of pancreatic cancer to overcome the problems of time-intensive manual contouring in online adaptive workflows. The research focuses on implementing novel data augmentation techniques to address the challenges posed by limited datasets. Approach. This study was conducted in two phases. In phase I, we selected and customized the best-performing segmentation model among ResU-Net, SegResNet, and nnU-Net, using 43 balanced 3DVane images from 10 patients with 5-fold cross-validation. Phase II focused on optimizing the chosen model through two advanced data augmentation approaches to improve performance and generalizability by increasing the effective input dataset: (1) a novel structure-guided deformation-based augmentation approach (sgDefAug) and (2) a generative adversarial network-based method using a cycleGAN (GANAug). These were compared with comprehensive conventional augmentations (ConvAug). The approaches were evaluated using geometric (Dice score, average surface distance (ASD)) and dosimetric (D2% and D50% from dose-volume histograms) criteria. Main results. The nnU-Net framework demonstrated superior performance (mean Dice: 0.78 ± 0.10, mean ASD: 3.92 ± 1.94 mm) compared to other models. The sgDefAug and GANAug approaches significantly improved model performance over ConvAug, with sgDefAug demonstrating slightly superior results (mean Dice: 0.84 ± 0.09, mean ASD: 3.14 ± 1.79 mm). The proposed methodology produced auto-contours in under 30 s, with 75% of organs showing less than 1% difference in D2% and D50% dose criteria compared to ground truth. Significance. The integration of the nnU-Net framework with our proposed novel augmentation technique effectively addresses the challenges of limited datasets and stringent time constraints in online adaptive radiotherapy for pancreatic cancer. Our approach offers a promising solution for streamlining online adaptive workflows and represents a substantial step forward in the practical application of auto-segmentation techniques in clinical radiotherapy settings.
Crystal-level timing calibration using cascaded photons of 60Co point source for long axial animal PET system
Authors: Wei Qing , Li Daowu , Huang Xianchao , Wei Long , Zhang Zhiming , Xiaorou Han , Wang Yingjie 
Published: January 2025

Abstract
Objective. Timing calibration is essential for positron emission tomography (PET) system as it enhances timing resolution to improve image quality. Traditionally, positron sources are employed for timing calibration. However, the photons emitted by these sources travel in opposite directions, necessitating that positrons annihilate at multiple locations to collect coincidence data across a greater number of lines of response (LORs). To overcome this limitation, this study proposes a timing calibration method utilising a 60Co point source. Approach. The 60Co source emits cascaded photons without angular correlation, allowing the collection of coincidence events throughout the field of view (FOV) with a single 60Co point source positioned at the centre of the FOV to determine the timing offsets of the pixels. Leveraging the properties of 60Co, we propose a calibration method and implement it on a long axial animal PET system. Initially, we calibrated the timing offsets of the pixels within two blocks to establish reference detectors, and subsequently employed a 60Co point source to determine the timing offsets of all the pixels in the system relative to these reference detectors. In addition, we evaluated the system's timing resolution before and after the calibration to validate the efficacy of the proposed method. Main results. We measured the timing offsets of the pixels across the entire system, ranging from -5.0 to 2.0 ns. After implementing the timing offset lookup table, the system timing resolution was improved from 6.30 ns before calibration to 1.04 ns. Significance. In this study, the 60Co source is employed for timing calibration, offering the advantages of operational simplicity, broad applicability, and potential application in time-of-flight (TOF) PET.
Interatomic Coulombic decay in lithium-doped large helium nanodroplets induced by photoelectron impact excitation
Authors: Ben Ltaief L , Sishodia K , Asmussen J D , Abid A R , Krishnan S R , Pedersen H B , Sisourat N , Mudrich M 
Published: January 2025

Abstract
Irradiation of condensed matter with ionizing radiation generally causes direct photoionization as well as secondary processes that often dominate the ionization dynamics. Here, large helium (He) nanodroplets with radius

≳
40

nm doped with lithium (Li) atoms are irradiated with extreme ultraviolet (XUV) photons of energy

h
ν
⩾
44.4

eV and indirect ionization of the Li dopants is observed in addition to direct photoionization of the He droplets. Specifically, Li ions are efficiently produced by an interatomic Coulombic decay (ICD) process involving metastable He

∗

atoms and He

2
∗

excimers which are populated by elastic and inelastic scattering of photoelectrons in the nanodroplets as well as by electron-ion recombination. This type of indirect ICD, observed in large He nanodroplets in nearly the entire XUV range, turns out to be more efficient than Li dopant ionization by ICD following direct resonant photoexcitation at

h
ν
=
21.6

eV and by charge-transfer ionization. Indirect ICD processes induced by scattering of photoelectrons likely play an important role in other condensed phase systems exposed to ionizing radiation as well, including biological matter.