bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dark sector effective field theory
Authors: Liang Jin-Han , Liao Yi , Ma Xiao-Dong , Wang Hao-Lin 
Published: January 2024

Abstract
We introduce the effective field theory of two different light dark particles interacting with the standard model (SM) light states in a single vertex, termed dark sector effective field theory (DSEFT). We focus on the new light particles with spin up to 1 and being real in essence, namely, new real scalars ϕ and S, Majorana fermions χ and ψ, and real vectors Xμ and Vμ. In the framework of low energy effective field theory with QED and QCD symmetry, the DSEFT can be classified into six categories, including the scalar-scalar-SM (ϕS-SM), fermion-fermion-SM (χψ-SM), vector-vector-SM (XV-SM), scalar-fermion-SM (ϕχ-SM), scalar-vector-SM (ϕX-SM), and fermion-vector-SM (χX-SM) cases. For each case, we construct the effective operator basis up to canonical dimension 7, which will cover most interesting phenomenology at low energy. As a phenomenological example, we investigate the longstanding neutron lifetime anomaly through the neutron dark decay modes n → χϕ or χX from the effective interactions in the fermion-scalar-SM or fermion-vector-SM case. When treating the light fermion as a dark matter candidate, we also explore the constraints from DM-neutron annihilation signal at Super-Kamiokande. We find the neutron dark decay in each scenario can accommodate the anomaly, at the same time, without contradicting with the Super-Kamiokande limit.
Pseudospectra of holographic quasinormal modes
Authors: Areán Daniel , Fariña David García , Landsteiner Karl 
Published: January 2024

Abstract
Quasinormal modes and frequencies are the eigenvectors and eigenvalues of a non-Hermitian differential operator. They hold crucial significance in the physics of black holes. The analysis of quasinormal modes of black holes in asymptotically Anti-de Sitter geometries plays also a key role in the study of strongly coupled quantum many-body systems via gauge/gravity duality. In contrast to normal Sturm-Liouville operators, the spectrum of non-Hermitian (and non-normal) operators generally is unstable under small perturbations. This research focuses on the stability analysis of the spectrum of quasinormal frequencies pertaining to asymptotically planar AdS black holes, employing pseudospectrum analysis. Specifically, we concentrate on the pseudospectra of scalar and transverse gauge fields, shedding light on their relevance within the framework of gauge/gravity duality.
The Singularities of Selberg- and Dotsenko–Fateev-Like Integrals
Authors: Sussman Ethan 
Published: January 2024

AbstractWe discuss the meromorphic continuation of certain hypergeometric integrals modeled on the Selberg integral, including the 3-point and 4-point functions of BPZ’s minimal models of 2D CFT as described by Felder & Silvotti and Dotsenko & Fateev (the “Coulomb gas formalism”). This is accomplished via a geometric analysis of the singularities of the integrands. In the case that the integrand is symmetric (as in the Selberg integral itself) or, more generally, what we call “DF-symmetric,” we show that a number of apparent singularities are removable, as required for the construction of the minimal models via these methods.
Computer-aided designed 3D-printed polymeric scaffolds for personalized reconstruction of maxillary and mandibular defects: a proof-of-concept study
Authors: Mattavelli Davide , Verzeletti Vincenzo , Deganello Alberto , Fiorentino Antonio , Gualtieri Tommaso , Ferrari Marco , Taboni Stefano , Anfuso William , Ravanelli Marco , Rampinelli Vittorio , Grammatica Alberto , Buffoli Barbara , Maroldi Roberto , Elisabetta Ceretti , Rezzani Rita , Nicolai Piero , Piazza Cesare 
Published: January 2024

Abstract
Purpose
To investigate the potential reconstruction of complex maxillofacial defects using computer-aided design 3D-printed polymeric scaffolds by defining the production process, simulating the surgical procedure, and explore the feasibility and reproducibility of the whole algorithm.

Methods
This a preclinical study to investigate feasibility, reproducibility and efficacy of the reconstruction algorithm proposed. It encompassed 3 phases: (1) scaffold production (CAD and 3D-printing in polylactic acid); (2) surgical simulation on cadaver heads (navigation-guided osteotomies and scaffold fixation); (3) assessment of reconstruction (bone and occlusal morphological conformance, symmetry, and mechanical stress tests).

Results
Six cadaver heads were dissected. Six types of defects (3 mandibular and 3 maxillary) with different degree of complexity were tested. In all case the reconstruction algorithm could be successfully completed. Bone morphological conformance was optimal while the occlusal one was slightly higher. Mechanical stress tests were good (mean value, 318.6 and 286.4 N for maxillary and mandibular defects, respectively).

Conclusions
Our reconstructive algorithm was feasible and reproducible in a preclinical setting. Functional and aesthetic outcomes were satisfactory independently of the complexity of the defect.
You do you: susceptibility of temporal binding to self-relevance
Authors: Muth Felicitas V. , Ebert Sophia , Kunde Wilfried 
Published: January 2024

AbstractThe self-prioritization effect suggests that self-relevant information has a processing advantage over information that is not directly associated with the self. In consequence, reaction times are faster and accuracy rates higher when reacting to self-associated stimuli rather than to other-related stimuli (Sui et al., Journal of Experimental Psychology: Human Perception and Performance 38:1105–1117, 2012). This spurs the assumption that self-associated action–effects should also be perceived earlier than other-related outcomes. One way to measure this is temporal binding. Previous research indeed showed that the perceived temporal interval between actions and self-associated outcomes was reduced compared to friend- and other-associated outcomes. However, the employed method (interval estimations) and several experimental design choices make it impossible to discern whether the perceived shortening of the interval between a keypress and a self-relevant outcome is due to a perceptual shift of the action or of the action–effect or both. Thus, we conducted four experiments to assess whether temporal binding can indeed be modulated by self-relevance and if so where this perceptual bias is located. The results did not support stronger temporal binding for self- vs other-related action–effects. We discuss these results against the backdrop of the attentional basis of self-prioritization and propose directions for future research.
Predicting the impact of rare variants on RNA splicing in CAGI6
Authors: Lord Jenny , Oquendo Carolina Jaramillo , Wai Htoo A. , Douglas Andrew G. L. , Bunyan David J. , Wang Yaqiong , Hu Zhiqiang , Zeng Zishuo , Danis Daniel , Katsonis Panagiotis , Williams Amanda , Lichtarge Olivier , Chang Yuchen , Bagnall Richard D. , Mount Stephen M. , Matthiasardottir Brynja , Lin Chiaofeng , Hansen Thomas van Overeem , Leman Raphael , Martins Alexandra , Houdayer Claude , Krieger Sophie , Bakolitsa Constantina , Peng Yisu , Kamandula Akash , Radivojac Predrag , Baralle Diana 
Published: January 2024

AbstractVariants which disrupt splicing are a frequent cause of rare disease that have been under-ascertained clinically. Accurate and efficient methods to predict a variant’s impact on splicing are needed to interpret the growing number of variants of unknown significance (VUS) identified by exome and genome sequencing. Here, we present the results of the CAGI6 Splicing VUS challenge, which invited predictions of the splicing impact of 56 variants ascertained clinically and functionally validated to determine splicing impact. The performance of 12 prediction methods, along with SpliceAI and CADD, was compared on the 56 functionally validated variants. The maximum accuracy achieved was 82% from two different approaches, one weighting SpliceAI scores by minor allele frequency, and one applying the recently published Splicing Prediction Pipeline (SPiP). SPiP performed optimally in terms of sensitivity, while an ensemble method combining multiple prediction tools and information from databases exceeded all others for specificity. Several challenge methods equalled or exceeded the performance of SpliceAI, with ultimate choice of prediction method likely to depend on experimental or clinical aims. One quarter of the variants were incorrectly predicted by at least 50% of the methods, highlighting the need for further improvements to splicing prediction methods for successful clinical application.
Mating system induced lags in rates of range expansion for different simulated mating systems and dispersal strategies: a modelling study
Authors: Morgan W. H. , Palmer S. C. F. , Lambin X. 
Published: January 2024

AbstractMismatches between current and potential species distributions are commonplace due to lags in the response of populations to changing environmental conditions. The prevailing mating system may contribute to such lags where it leads to mating failure at the range edge, but how active dispersers might mitigate these lags using social information to inform dispersal strategies warrants greater exploration. We used an individual-based model to explore how different mating systems for species that actively search for habitat can impose a filter on the ability to colonise empty, fragmented landscapes, and explored how using social information during dispersal can mitigate the lags caused by more constrained mating systems. The mate-finding requirements implemented in two-sex models consistently led to slower range expansion compared to those that were not mate limited (i.e., female only models), even when mating was polygynous. A mate-search settlement strategy reduced the proportion of unmated females at the range edge but had little impact on rate of spread. In contrast, a negative density-dependent settlement strategy resulted in much faster spread, which could be explained by a greater number of long-distance dispersal events. Our findings suggest that even low rates of mating failure at the range edge can lead to considerable lags in range expansion, though dispersal strategies that favour colonising more distant, sparsely occupied habitat patches may effectively mitigate these lags.
Modeling the compressive strength of binary and ternary blended high-performance concrete mixtures using ensemble machine learning models
Authors: Murthy Madhu Narasimha , Amruth S. Kumar , Marulasiddappa Sreedhara B. , Naganna Sujay Raghavendra 
Published: January 2024

AbstractIn the present study, the compressive strength of binary and ternary blended high-performance concrete mixtures was modeled using different machine learning tools, such as artificial neural network (ANN), gradient tree boosting (GTB), and multivariate adaptive regression splines (MARS). The compressive strength of binary and ternary blended concrete at 28 days of curing period was modeled using seven quantitative input parameters such as cement, blast furnace slag, fly ash, superplasticizer, water, coarse aggregate, and fine aggregate based on three different training and testing (Tr–Te) scenarios. The performance of the models developed was analyzed based on several statistical evaluation metrics, of error and efficiency. During the testing phase, the compressive strength estimates obtained via modeling using ANN, GTB, and MARS had Kling–Gupta efficiency (KGE) values of 0.8389, 0.8602, and 0.8423, respectively, for the first Tr–Te scenario; similarly, the KGE values were 0.8025/0.8830, 0.8541/0.8901, and 0.8434/0.8582, respectively, for the second/third Tr–Te scenarios. The estimation accuracy of the GTB model was relatively superior to that of the ANN and MARS models, taking into consideration both the error and efficiency indices. All three models perform relatively well for the first I/O combination compared to the other two combinations.
Knowledge and care regarding long-term cardiovascular risk after hypertensive disorders of pregnancy and gestational diabetes
Authors: Pfaller Birgit , Busvine Constance , Rosenauer Alena , Schenzel Andreas , Fournier Camille , Aringer Ida , Lösch Alexander , Wiesholzer Martin , Schubert Susanne , Wichert-Schmitt Barbara 
Published: January 2024

Summary
Background
Adverse pregnancy outcomes (APO), such as preeclampsia (PE) and gestational diabetes (GDM) are substantial risk factors for cardiovascular disease (CVD) later in life. Identifying these high-risk female individuals during pregnancy offers the possibility of preventing long-term CVD and chronic kidney disease via a structured therapeutic and surveillance plan. We aimed to evaluate the current practice of postpartum care in women after APO and the impact on the women’s awareness about their future risk for CVD.

Methods
Women diagnosed with PE and GDM at the University Hospital of St. Poelten/Lilienfeld between 2015–2020 were identified and participated in a structured telephone interview about postpartum medical care and knowledge about the impact of APOs on long-term cardiovascular health.

Results
Of 161 out of the 750 women contacted, 29% (n = 46) were diagnosed with PE and 71% (n = 115) with GDM. One third of all women and up to 44% of women diagnosed with PE, were unaware that APOs are related to CVD. Women diagnosed with PE were less likely to receive postpartum care information than those with GDM (30.4% vs. 49.6%, p = 0.027), and only one third of all women after APOs were counselled by a physician or healthcare professional. Of the women 50% received recommendations regarding lifestyle changes after delivery; significantly more women with GDM than women with PE (54% vs. 37%, p = 0.05). Only 14% had at least one long-term follow-up.

Conclusion
This study identified a significant deficit of structured postpartum care and a lack of awareness among women after APO and their healthcare providers about the increased risk of long-term CVD.
Evaluating a shared care pathway intervention for people receiving chemotherapy to reduce post-treatment unplanned hospital presentations: a randomised controlled trial
Authors: Fethney Judith , Kim Bora , Boustany Chantale , McKenzie Heather , Hayes Lillian , Cox Keith , Simpson Judy M. , Horvath Lisa G. , Vardy Janette L. , McLeod Jodi , Willcock Simon , Cook Natalie , Acret Louise , White Kate 
Published: January 2024

Abstract
Purpose
The aim of this randomised controlled trial (RCT) was to explore whether a community nursing intervention for outpatients receiving systemic therapy reduced unplanned hospital presentations and improved physical and psychosocial health outcomes over the first three cycles of treatment compared to a control group receiving standard care.

Methods
The number of and reasons for unplanned presentations were obtained for 170 intervention and 176 control group adult patients with solid tumours starting outpatient chemotherapy. Poisson regression was used to compare the number of presentations between the intervention and control groups. Patients self-completed the Hospital Anxiety and Depression Scale, the Cancer Behavior Inventory and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire core 30 (EORTC QLQ-C30) at the start of the first four cycles. Linear regression techniques were used to compare quality of life outcomes.

Results
The reduction in unplanned presentations in the intervention group relative to the control group was 12% (95% CI, − 25%, 37%; P = 0.48). At the start of cycle 4, there was no difference in anxiety (difference = 0.47 (95% CI, − 0.28, 1.22; P = 0.22)), depression (difference = 0.57 (95% CI, − 0.18, 1.31; P = 0.13)) or EORTC QLQ-C30 summary score (difference = 0.16 (95% CI, − 2.67, 3.00; P = 0.91)). Scores for self-efficacy as measured by the Cancer Behavior Inventory were higher in the intervention group (difference = 4.3 (95% CI, 0.7, 7.9; P = 0.02)).

Conclusion
This RCT did not demonstrate a benefit in reducing unplanned presentations to hospital. The trial identified improved cancer-based self-efficacy in patients receiving the intervention.

Trial registration
Registered at Australian and New Zealand Clinical Trials Registry: ACTRN12614001113640, registered 21/10/2014.
A spatiotemporal oscillator model for ENSO
Authors: Li Yaokun 
Published: January 2024

AbstractA spatiotemporal oscillator model for El Niño/Southern Oscillation (ENSO) is constructed based on the thermodynamics and thermocline dynamics. The model is enclosed by introducing a proportional relationship between the gradient in sea surface temperature (SST) and the oceanic zonal current and can be transformed into a standard wave equation that can be decomposed into a series of eigenmodes by cosine series expansion. Each eigenmode shows a spatial mode that oscillates with its natural frequency. The first spatial mode, that highlights SST anomaly (SSTA) contrast between the eastern and western Pacific—a fundamental characteristic of the eastern Pacific (EP) El Niño events, oscillates with a natural period of around 4.6 years, consistent with the quasi-quadrennial (QQ) mode. The second spatial mode, that emphasizes SSTA contrast between the central and the eastern, western Pacific—a basic spatial structure of the central Pacific (CP) El Niño events, oscillates with a natural period of 2.3 years that is half of the first natural period. It is also consistent with the quasi-biennial (QB) modes. The combinations of the eigenmodes with different weights can feature complex spatiotemporal variations in SSTAs. In open ocean that is far away from the coastlines, the model can predict waves propagating both eastward and westward. Besides, the net surface heating further complicates the temporal variations by exerting forced frequencies. The model unifies the temporal and spatial variations and may provide a comprehensive viewpoint for understanding the complex spatiotemporal variations of ENSO.
Safety and efficacy of bone marrow mononuclear cell therapy for ischemic stroke recovery: a systematic review and meta-analysis of randomized controlled trials
Authors: Tang Yanbing , Wang Zilan , Teng Haiying , Ni Hanyu , Chen Huiru , Lu Jiaye , Chen Zhouqing , Wang Zhong 
Published: January 2024

Abstract
Background
Cell-based therapy represents a potential treatment for ischemic stroke (IS). Here, we performed a systematic review and meta-analysis to summarize the evidence provided by randomized controlled trials (RCTs) for the transplantation of bone marrow mononuclear cells (BMMNCs) in patients with IS in any phase after stroke.

Methods
We searched several databases for relevant articles up to the 10th of March 2023, including MEDLINE, EMBASE, the Cochrane Library, and ClinicalTrials.gov. Subgroup analyses were implemented to evaluate the dose and route of BMMNC administration. Statistical data were analyzed by Review Manager version 5.3 software.

Results
Six RCTs were included in this article, including 177 patients who were treated by the transplantation of BMMNCs and 166 patients who received medical treatment. The three-month National Institutes of Health Stroke Scale (NIHSS) score indicated a favorable outcome for the BMMNC transplantation group (standardized mean difference (SMD), − 0.34; 95% confidence interval (CI), − 0.57 to − 0.11; P = 0.004). There were no significant differences between the two groups at six months post-transplantation with regards to NIHSS score (SMD 0.00; 95% CI − 0.26 to 0.27; P = 0.97), modified Rankin Scale (risk ratio (RR) 1.10; 95% CI 0.75 to 1.63; P = 0.62), Barthel Index change (SMD 0.68; 95% CI − 0.59 to 1.95; P = 0.29), and infarct volume change (SMD − 0.08; 95% CI − 0.42 to 0.26; P = 0.64). In addition, there was no significant difference between the two groups in terms of safety outcome (RR 1.24; 95% CI 0.80 to 1.91; P = 0.33).

Conclusion
Our meta-analysis demonstrated that the transplantation of BMMNCs was safe; however, the efficacy of this procedure requires further validation in larger RTCs.
A modular cyber security training programme for the maritime domain
Authors: Oruc Aybars , Chowdhury Nabin , Gkioulos Vasileios 
Published: January 2024

AbstractThe global maritime industry is continuing the rapid digitization of systems and dependency on advancing technology, in a trend akin to other industrial domains. One of the main issues that this integration has brought is an increased vulnerability to a growing number of cyber threats. While several security measures are being implemented to prevent or respond to cyber attacks, the human element is still one of the main weaknesses. Many of today’s cyber attacks take advantage of human personnel’s lack of awareness, which makes cyber security awareness and training activities of critical importance. Unfortunately, current research is still limited in its offerings for cyber security training specific to maritime personnel. Moreover, such training programmes for the professionals should be developed role-based in accordance with the suggestions of many credited maritime organizations. For this reason, we developed a modular cyber security training programme for the maritime domain called Maritime Cyber Security (MarCy) by implementing Critical Events Model (CEM). Then, we evaluated the MarCy programme by utilizing the Delphi technique with the participation of 19 experts from academia and industry. In this study, we offer cyber security training for seafarers and office employees in shipping companies. We proposed eleven elective modules to improve the knowledge, skills, and attitude of learners against cyber risks. The MarCy programme can be implemented by universities, shipping companies, training institutes, and governmental organizations for maritime cyber security training purposes.
Multimorbidity patterns and disability and healthcare use in Europe: do the associations change with the regional socioeconomic status?
Authors: Zacarías-Pons Lluís , Turró-Garriga Oriol , Saez Marc , Garre-Olmo Josep 
Published: January 2024

AbstractMultimorbidity, the concurrence of several chronic conditions, is a rising concern that increases the years lived with disability and poses a burden on healthcare systems. Little is known on how it interacts with socioeconomic deprivation, previously associated with poor health-related outcomes. We aimed to characterize the association between multimorbidity and these outcomes and how this relationship may change with socioeconomic development of regions. 55,915 individuals interviewed in 2017 were drawn from the Survey of Health, Ageing and Retirement in Europe, a population-based study. A Latent Class Analysis was conducted to fit multimorbidity patterns based on 16 self-reported conditions. Physical limitation, quality-of-life and healthcare utilization outcomes were regressed on those patterns adjusting for additional covariates. Those analyses were then extended to assess whether such associations varied with the region socioeconomic status. We identified six different patterns, labelled according to their more predominant chronic conditions. After the “healthy” class, the “metabolic” and the “osteoarticular” classes had the best outcomes involving limitations and the lowest healthcare utilization. The “neuro-affective-ulcer” and the “several conditions” classes yielded the highest probabilities of physical limitation, whereas the “cardiovascular” group had the highest probability of hospitalization. The association of multimorbidity over physical limitations appeared to be stronger when living in a deprived region, especially for metabolic and osteoarticular conditions, whereas no major effect differences were found for healthcare use. Multimorbidity groups do differentiate in terms of limitation and healthcare utilization. Such differences are exacerbated with socioeconomic inequities between regions even within Europe.