bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design and fabrication of integrator using adiabatic quantum-flux-parametron circuit
Authors: Shen Hongxiang , Han Zeyu , Li Zongyuan , He Yuxing , Yoshikawa Nobuyuki 
Published: January 2025

Abstract
We believe that the adiabatic quantum flux parametron (AQFP) circuit, as a novel low-power superconducting circuit technology, has potential application in various fields, including utilizing its high precision to determine the phase of input signals. To improve the precision of AQFP circuits, it is crucial to reduce the gray zone of the system. In this paper, we investigate a digital integration method to reduce the gray zone and enhance the precision of the AQFP circuits. Theoretical analysis demonstrates that the gray zone narrows, and the precision of the system improves as more data points are integrated. Additionally, we establish the quantitative relationship between the reduction in gray zone and the number of integrated data points. To validate these findings, we fabricate AQFP integrator circuits and perform experimental verification. Furthermore, we estimate the relationship between the scale of the integration circuit and the chip area, emphasizing possibilities for various future application scenarios.
Creating Disparate Regimes in the Polity
Authors: Shanahan Brendan A 
Published: January 2025

Abstract
Nineteenth-century American federalism and constitutional jurisprudence afforded states wide latitude to determine the exclusive political rights of US citizenship vis-à-vis noncitizen immigrants. Many states enfranchised white noncitizen immigrant men who possessed their “first papers” as an inducement for settler colonialism. Others defined voting as a citizen-only right. Some even counted noncitizens out of the population for the purposes of state legislative apportionment. Though noncitizen voting rights and anti-alien apportionment schemes became subjects of federal debate during Reconstruction, they remained primarily a matter of state constitutional law and political development. Several (but far from all) alien suffrage laws were repealed at or in the aftermath of state and statehood constitutional conventions during the late 1800s. This chapter illustrates how nineteenth-century state constitutional politics made and reshaped disparate regimes of citizenship rights in the polity.
Embedding American Citizenship and Citizenship Rights
Authors: Shanahan Brendan A 
Published: January 2025

Abstract
This chapter explores the lives and nebulous legal status of marital expatriates (US-born women who lost their nationality upon marriage to noncitizen men). It estimates that at least 100,000 women, and likely tens of thousands more, petitioned to naturalize as immigrants in their own country or took an oath of allegiance under federal repatriation law between 1922 and 1975. While the vast majority of marital expatriates’ applications succeeded, federal naturalization authorities generally interpreted citizenship law restrictively when their petitions appeared in court during the 1920s and 1930s. Immigration and Naturalization Service leaders reversed course in 1940, declaring all permanently resident marital expatriates “citizens without citizenship rights” by decree. The chapter argues that the ultimate failure of the Immigration and Naturalization Service to have this position universally recognized demonstrates how embedded the idea of American citizenship rights as citizen-only rights had become in both law and popular perception by the mid-twentieth century.
Cognitive Functioning in Females with Endometriosis-Associated Chronic Pelvic Pain: A Literature Review
Authors: Berryman Ashlee , Machado Liana 
Published: January 2025

Abstract

Objective
Cognitive complaints are commonplace among women living with endometriosis-associated chronic pelvic pain (CPP); yet, surprisingly few studies have assessed their cognitive functioning. As an initial step to address the resulting knowledge gap, this review aimed to synthesize the current literature reporting on cognition in females with endometriosis-associated CPP, and due to the poverty of endometriosis studies, to draw on data from female cohorts with other chronic pain conditions to gain potentially relevant insights.

Methods
Three database searches were conducted (Scopus, PubMed, and PsycINFO). Eighteen studies met the inclusion criteria (n = 8 regarding endometriosis, n = 10 regarding other chronic pain conditions).

Results
Six of the seven studies employing objective cognitive measures in females with other chronic pain reported significant cognitive deficits. Associated changes in neural circuitry thought to underpin these deficits align with neural patterns reported in females with endometriosis-associated CPP. While two studies reported a high prevalence (≥60%) of self-reported cognitive impairment in endometriosis-associated CPP, objective performance deficits have not been reported. Nonetheless, self-reported accounts of cognitive impairment suggest females with endometriosis-associated CPP may experience difficulties with inhibition, attention, and memory. Most studies did not control for potential moderating factors and comorbidities that prevail among endometriosis populations.

Conclusion
The field is in desperate need of research assessing cognitive performance in females with endometriosis-associated CPP, to objectively determine any cognitive difficulties. Attention should be paid to likely moderators, pain-related mechanisms, and whether findings extend to endometriosis without CPP.
Towards molecular structure discovery from cryo-ET density volumes via modelling auxiliary semantic prototypes
Authors: Nair Ashwin , Li Xingjian , Solanki Bhupendra , Mukhopadhyay Souradeep , Jha Ankit , Rafid Uddin Mostofa , Singha Mainak , Banerjee Biplab , Xu Min 
Published: January 2025

Abstract
Cryo-electron tomography (cryo-ET) is confronted with the intricate task of unveiling novel structures. General class discovery (GCD) seeks to identify new classes by learning a model that can pseudo-label unannotated (novel) instances solely using supervision from labeled (base) classes. While 2D GCD for image data has made strides, its 3D counterpart remains unexplored. Traditional methods encounter challenges due to model bias and limited feature transferability when clustering unlabeled 2D images into known and potentially novel categories based on labeled data. To address this limitation and extend GCD to 3D structures, we propose an innovative approach that harnesses a pretrained 2D transformer, enriched by an effective weight inflation strategy tailored for 3D adaptation, followed by a decoupled prototypical network. Incorporating the power of pretrained weight-inflated Transformers, we further integrate CLIP, a vision-language model to incorporate textual information. Our method synergizes a graph convolutional network with CLIP’s frozen text encoder, preserving class neighborhood structure. In order to effectively represent unlabeled samples, we devise semantic distance distributions, by formulating a bipartite matching problem for category prototypes using a decoupled prototypical network. Empirical results unequivocally highlight our method’s potential in unveiling hitherto unknown structures in cryo-ET. By bridging the gap between 2D GCD and the distinctive challenges of 3D cryo-ET data, our approach paves novel avenues for exploration and discovery in this domain.
Prediction of tissue and clinical thrombectomy outcome in acute ischaemic stroke using deep learning
Authors: von Braun Marie-Sophie , Starke Kristin , Peter Lucas , Kürsten Daniel , Welle Florian , Schneider Hans Ralf , Wawrzyniak Max , Kaiser Daniel P O , Prasse Gordian , Richter Cindy , Kellner Elias , Reisert Marco , Klingbeil Julian , Stockert Anika , Hoffmann Karl-Titus , Scheuermann Gerik , Gillmann Christina , Saur Dorothee 
Published: January 2025

Abstract
The advent of endovascular thrombectomy has significantly improved outcomes for stroke patients with intracranial large vessel occlusion, yet individual benefits can vary widely. As demand for thrombectomy rises and geographic disparities in stroke care access persist, there is a growing need for predictive models that quantify individual benefits. However, current imaging methods for estimating outcomes may not fully capture the dynamic nature of cerebral ischemia and lack a patient-specific assessment of thrombectomy benefits.
Our study introduces a deep learning approach to predict individual responses to thrombectomy in acute ischemic stroke patients. The proposed models provide predictions for both tissue and clinical outcomes under two scenarios: one assuming successful reperfusion and another assuming unsuccessful reperfusion. The resulting simulations of penumbral salvage and difference in NIHSS at discharge quantify the potential individual benefits of the intervention. Our models were developed on an extensive dataset from routine stroke care, which included 405 ischemic stroke patients who underwent thrombectomy. We used acute data for training (n = 304), including multimodal CT imaging and clinical characteristics, along with post hoc markers like thrombectomy success, final infarct localization, and NIHSS at discharge.
We benchmarked our tissue outcome predictions under the observed reperfusion scenario against a thresholding-based clinical method and a generalised linear model. Our deep-learning model showed significant superiority, with a mean Dice score of 0.48 on internal (n = 50) and 0.52 on external (n = 51) test data, versus 0.26/0.36 and 0.34/0.35 for the baselines, respectively. The NIHSS sum score prediction achieved median absolute errors of 1.5 NIHSS points on the internal test dataset and 3.0 NIHSS points on the external test dataset, outperforming other machine learning models.
By predicting the patient-specific response to thrombectomy for both tissue and clinical outcomes, our approach offers an innovative biomarker that captures the dynamics of cerebral ischemia. We believe this method holds significant potential to enhance personalised therapeutic strategies and to facilitate efficient resource allocation in acute stroke care.
Solid–liquid extraction of lithium chloride with a simple and flexible heteroditopic receptor
Authors: Mimuro Tsubasa , Yoshino Seiichi , Hirasawa Manabu , Kondo Shin-ichi 
Published: January 2025

Abstract
The global demand for lithium has surged in recent years due to its wide applications in industry and medicine. We have achieved selective solid–liquid extraction of LiCl using a heteroditopic receptor with an ether linker as a cation recognition site and 2 urea functionalities as cooperative anion recognition sites. The receptor exhibits high selectivity for LiCl from 1H nuclear magnetic resonance (NMR) spectra by complexation in CD3CN and CDCl3. The solid–liquid extraction, followed by stripping to neutral aqueous phase using with the receptor, revealed recovery of LiCl about 90% by ion chromatography and inductively coupled plasma mass spectrometry (ICP-MS) analyses, with a slight competition with MgCl2. LiCl was also recovered from the artificially prepared salt mixture and natural one from the Salar de Uyuni by the solid–liquid extraction with less competitive recovery of MgCl2.
Investigation of patterns and associations of neuroinflammation in cognitive impairment
Authors: Gan Ruoqiu , Xie Hongsheng , Zhao Ziru , Wu Xiaoai , Wang Ruihan , Wu Baolin , Chen Qin , Jia Zhiyun 
Published: January 2025

Abstract
Neuroinflammation has been identified as an important pathological component of cognitive impairment, and translocator protein imaging has become a valuable tool for assessing its patterns. We aimed to obtain the exact distribution of neuroinflammation in cognitive impairment and its underlying mechanisms with amyloid-beta. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, two investigators searched literature databases for studies that measured translocator protein binding levels. This measurement was performed between healthy controls and subjects with mild cognitive impairment or Alzheimer’s disease via voxel-based positron emission tomography image analysis at the whole-brain level. This meta-analysis was performed with the anisotropic effect-size based algorithm. Neuroinflammation in patients with mild cognitive impairment was mainly concentrated in the left middle temporal gyrus and left amygdala. In Alzheimer’s disease patients, the brain regions involved were the left inferior temporal gyrus, left calcarine fissure/surrounding cortex, left parahippocampal gyrus, right lingual gyrus, and right middle temporal gyrus. In addition, neuroinflammation in patients with cognitive impairment was highly correlated with amyloid-beta deposition in the cortex. This study deepens our understanding of the patterns of neuroinflammation in patients with cognitive impairment and its interaction with amyloid-beta, providing potential insights for therapeutic approaches targeting neuroinflammation in Alzheimer’s disease.
SAAChain: release and storage platform of digital works based on non-fungible tokens
Authors: Liu Jianan , Wang Yongjuan , Lu Siqi , Yu Gang , Wang Xiangyu , Feng Peixuan 
Published: January 2025

Abstract
The rapid growth in the speed and convenience of information dissemination has made copyright infringement increasingly common. Blockchain technology solves pain points such as difficulties in traditional copyright registration, easy infringement, and difficulties in confirming and safeguarding rights. It also realises the decentralised management of copyright, network-wide tracking and monitoring, trusted certificate deposits, among others. However, the efficient original authentication of works and the function of blockchain to create copyright trading channels in the field of copyright are often ignored. This paper designed a self-adaptive learning similarity detection fusion strategy to protect the copyright of original digital works, namely SAAChain, and built a platform for releasing and storing original works based on non-fungible tokens. SAAChain first measures the similarity of a work based on adaptive learning to realise the originality authentication of works. Secondly, the works are stored on the InterPlanetary File System as NFTs, along with copyright information. Finally, a smart contract based on Ethereum and ERC-721 is designed to realise the free circulation of digital rights while simultaneously constructing an efficient and convenient digital rights protection system. Experiments show that the accuracy of the fusion strategy for adaptive work similarity detection can reach above 97%, which meets the requirements of work originality verification. Because of the storage mode of the platform, the system has good performance in terms of response speed and storage efficiency. The entire process provides a full-process and transparent transaction platform for all parties and guarantees the copyright ownership of works as well as the non-tampering and traceability of copyright information.
Cognitive Domains in the National Social Life, Health, and Aging Project
Authors: Zhong Selena , Wroblewski Kristen E 
Published: January 2025

Abstract

Objectives
Cognition consists of specific domains that are differentially linked to health outcomes. We provide guidance on how to derive cognitive domains in the National Social Life, Health, and Aging Project (NSHAP) study. We suggest the use of a bifactor analysis to derive cognitive domains. To support our view that a bifactor analysis is necessary, we created cognitive domains from a bifactor analysis and created cognitive domains through summing the cognitive items; we then regressed the cognitive domains created through both methods with functional health (activites of daily living [ADLs] and instrumental activities of daily living [IADLs]) and compared the regression results.

Methods
NSHAP is a nationally representative longitudinal study of U.S. older adults that started in 2005. Data from Round 3 (2015–2016) were used. The MoCA-SA contains 18 cognitive items to represent 6 cognitive domains: modified trail-making test-B, clock drawing test (3 items), rhinoceros naming, digit span (2 items), serial 7 subtractions, sentence repetition, phonemic fluency, abstraction, delayed recall (5 items), and orientation (2 items). We created cognitive domains through a bifactor analysis and through summing up the cognitive items. We used linear regression to examine how global cognition and each cognitive domain derived from both methods were associated with ADLs and IADLs. Analyses were restricted to respondents aged 50+ without dementia.

Results
The global cognition score derived from both methods was statistically significantly associated with ADLs and with IADLs. All but the memory domain constructed from summing the cognitive items were associated with IADLs; only the visuospatial domain was associated with ADLs. None of the domains derived from a bifactor analysis were associated with ADLs or IADLs.

Discussion
Researchers should derive cognitive domains using a bifactor analysis to reduce spurious associations.
Public disclosures of mental health problems on social media and audiences’ self-reported anti-stigma effects
Authors: Zhang Zhongjie , Reavley Nicola , Armstrong Gregory , Morgan Amy 
Published: January 2025

Abstract
Public disclosures of mental health problems on social media represent a potentially powerful informal avenue for increasing mental health literacy and reducing public stigma in relation to people with mental health problems. We investigated whether the audience reported any reduction in their own stigma toward people with mental health problems after exposure to disclosures. We also examined whether self-reported stigma reduction was associated with the characteristics of audience members, the disclosers and the disclosure messages. We used Prolific to obtain a convenience sample (N = 803) of adults who had been exposed to a disclosure. We administered an online survey to participants and conducted a series of logistic regressions to identify any associations between disclosure-related characteristics and audience self-reported stigma reduction. Our findings showed that certain aspects of the messaging process appeared to be associated with stigma reduction. These included explicit diagnoses from disclosers, particular message themes such as psychosocial causes of mental ill health, and positive and echoing comments from other users. In addition, audience members who reported greater levels of empathy toward, perceived similarity to and identification with disclosers tended to report reduced stigma. These findings contribute to the evidence base underpinning how, when and which public disclosures of mental health problems on social media have the potential for stigma reduction. They can further help inform future health promotion practices on social media aiming to mitigate mental health-related stigma at the population level. Future research may focus more on the dynamics and match between disclosers and audiences and their effects on stigma.
Dance Compounds in OED3 in the Light of Diachronic Big Data Analysis
Authors: Podhajecka Mirosława 
Published: January 2025

Abstract
This paper reports on a research project that seeks to explore, firstly, how dance compounds have been described in the Oxford English dictionary and, secondly, to what extent their treatment is likely to be enhanced with textual big data. It begins by presenting a historical sketch of the dictionary, now consisting partly of the second edition and partly of the revised third edition, followed by an outline of the Google Books archive. The research methodology is then explained and the results are discussed and illustrated with examples. Since frequency has become a key parameter in historical lexicography, the compounds with their frequencies are listed in an appendix with the proviso that the figures may be unreliable. Despite the problematic nature of the quantitative data, the qualitative findings indicate potential improvements not only for the entries awaiting revision, but also for those which have already been updated. Once revised, OED3 will no doubt surpass its predecessor in accuracy and richness of detail, but, in the meantime, it should be examined for consistency between traditional principles and modern working practices.
Polynomial quasi-Trefftz DG for PDEs with smooth coefficients: elliptic problems
Authors: Imbert-Gérard Lise-Marie , Moiola Andrea , Perinati Chiara , Stocker Paul 
Published: January 2025

Abstract
Trefftz schemes are high-order Galerkin methods whose discrete spaces are made of elementwise exact solutions of the underlying partial differential equation (PDE). Trefftz basis functions can be easily computed for many PDEs that are linear, homogeneous and have piecewise-constant coefficients. However, if the equation has variable coefficients, exact solutions are generally unavailable. Quasi-Trefftz methods overcome this limitation relying on elementwise ‘approximate solutions’ of the PDE, in the sense of Taylor polynomials. We define polynomial quasi-Trefftz spaces for general linear PDEs with smooth coefficients and source term, describe their approximation properties and, under a nondegeneracy condition, provide a simple algorithm to compute a basis. We then focus on a quasi-Trefftz DG method for variable-coefficient elliptic diffusion–advection–reaction problems, showing stability and high-order convergence of the scheme. The main advantage over standard DG schemes is the higher accuracy for comparable numbers of degrees of freedom. For nonhomogeneous problems with piecewise-smooth source term we propose to construct a local quasi-Trefftz particular solution and then solve for the difference. Numerical experiments in two and three space dimensions show the excellent properties of the method both in diffusion-dominated and advection-dominated problems.
Virulent Bacteriophages for Controlling Shiga Toxin–Producing Escherichia coli Without Inducing Toxin Production
Authors: Cho Eunshin , Kim Jinshil , Won Taehee , Ryu Sangryeol , Jeon Byeonghwa 
Published: January 2025

Abstract
Shiga toxin–producing Escherichia coli (STEC) infections pose a significant public health challenge, characterized by severe complications including hemolytic uremic syndrome (HUS) due to Shiga toxin (Stx) production. Current therapeutic approaches encounter a critical limitation, as conventional antibiotic treatment is contraindicated due to its propensity to trigger bacterial SOS response and subsequently enhance Stx production, which increases the likelihood of developing HUS in antibiotic-treated patients. The lack of effective, safe therapeutic options has created an urgent need for alternative treatment strategies for STEC infections. This study investigates the therapeutic potential of virulent bacteriophages (phages) against STEC O157:H7. Our findings demonstrate that these phages effectively reduce STEC populations to levels comparable to ciprofloxacin treatment, while crucially avoiding the induction of SOS response and subsequent enhancement of Stx production. This is a significant advantage over conventional antibiotics, which increase Stx levels. Furthermore, these phages exhibited broad-spectrum antimicrobial activity against multiple clinical STEC isolates without triggering toxin expression. The capability of virulent phages to effectively control STEC without enhancing toxin production represents a promising therapeutic strategy that combines antimicrobial efficacy with safety considerations. These characteristics indicate that virulent phages represent a potential solution to address the current therapeutic challenges in STEC infections, particularly in mitigating the risk of HUS development in infected patients.