bluuebunny/crossref_metadata_2025_split huggingface dataset:
Addressing six standard model problems with Technically Natural Higgs models
Authors: Rosenlyst Martin 
Published: October 2023

Abstract
We aim to study the potential of the recently proposed model framework, called Technically Natural Higgs (TNH), in addressing six fundamental problems in particle physics and cosmology. These questions encompass the electroweak (EW) naturalness problem, neutrino mass generation, nature of the inflaton, the matter-antimatter asymmetry problem, origin of dark matter (DM) and the strong CP problem. We investigate various solutions within the TNH framework for three inflation scenarios — Higgs, Starobinsky and scale-independent inflation. In the minimal TNH model, the Higgs is a mixture of an elementary and a composite state, with a compositeness scale far exceeding the EW scale. Traditionally, this has required an unnatural small vacuum misalignment, but in the TNH framework a novel mechanism enables a technically natural large compositeness scale, even up to the Planck scale. In this model framework, we demonstrate that a scale-invariant version of the minimal TNH model, featuring a special energy scale of around $$ \mathcal{O} $$
O
(1012) GeV, loop-induced by the inflaton, simultaneously yields a technically natural 125-GeV Higgs boson, scotogenic neutrinos, a scale-invariant inflaton and a QCD axion DM candidate. These components dynamically generate the Planck scale and collectively have the potential to address all six open questions.
Wrinkles in the Froggatt-Nielsen mechanism and flavorful new physics
Authors: Asadi Pouya , Bhattacharya Arindam , Fraser Katherine , Homiller Samuel , Parikh Aditya 
Published: October 2023

Abstract
When the Froggatt-Nielsen mechanism is used to explain the Standard Model flavor hierarchy, new physics couplings are also determined by the horizontal symmetry. However, additional symmetries or dynamics in the UV can sometimes lead to a departure from this naïve scaling for the new physics couplings. We show that an effective way to keep track of these changes is by using the new spurions of the U(3)5 global flavor symmetry, where we parameterize extra suppression or enhancement factors, referred to as wrinkles, using the same power counting parameter as in the original Froggatt-Nielsen model. As a concrete realization, we consider two flavor spurions of the S1 leptoquark, and demonstrate that wrinkles can be used to make an enhanced value of $$ \textrm{BR}\left({B}^{+}\to {K}^{+}\nu \overline{\nu}\right) $$
BR

B
+

→

K
+

ν

ν
¯

consistent with other flavor observables. We also present example UV models that realize wrinkles, and comment on choosing consistent charges in ordinary Froggatt-Nielsen models without the typical monotonicity condition.
A Universal Space for the Bourbaki-Complete Spaces and Further Examples
Authors: Meroño Ana S. 
Published: October 2023

AbstractIn this paper it is provided an explicit embedding for complete metric spaces having a star-finite base of its uniformity into the universal space $$\kappa ^{\omega _0} \times \mathbb {R}^{\omega _0}$$

κ

ω
0

×

R

ω
0

, where $$\kappa \ge \omega _0$$

κ
≥

ω
0

is the cellularity of the space and $$\kappa ^{\omega _0}$$

κ

ω
0

is the Baire space of weight $$\kappa $$
κ
. From this result, similar embeddings for general Bourbaki-complete uniform spaces as well as for metric spaces are derived. In particular, these embeddings partially preserve the uniform structure of the original space. Several examples of Bourbaki-complete metric spaces having no star-finite base for its metric uniformity are constructed.
Well ordering principles for iterated $$\Pi ^1_1$$-comprehension
Authors: Freund Anton , Rathjen Michael 
Published: October 2023

AbstractWe introduce ordinal collapsing principles that are inspired by proof theory but have a set theoretic flavor. These principles are shown to be equivalent to iterated $$\Pi ^1_1$$

Π
1
1

-comprehension and the existence of admissible sets, over weak base theories. Our work extends a previous result on the non-iterated case, which had been conjectured in Montalbán’s “Open questions in reverse mathematics" (Bull Symb Log 17(3):431–454, 2011). This previous result has already been applied to the reverse mathematics of combinatorial and set theoretic principles. The present paper is a significant contribution to a general approach that connects these fields.
Comparative analysis of diagnostic ultrasound and histopathology for detecting cervical lymph node metastases in head and neck cancer
Authors: Sproll Karl Christoph , Hermes Iryna , Felder Gerd , Stoecklein Nikolas H. , Seidl Maximilian , Kaiser Peter , Kaisers Wolfgang 
Published: October 2023

Abstract
Purpose
We evaluated the current performance of diagnostic ultrasound (US) for detecting cervical lymph node (LN) metastases based on objective measures and subjective findings in comparison to the gold standard, histopathological evaluation.

Patients and methods
From 2007 to 2016, we prospectively included patients with head and neck cancer who were scheduled for surgical therapy including neck dissection. LNs were examined by multimodal US by a level III head and neck sonologist and individually assigned to a map containing six AAO-HNS neck LN levels preoperatively. During the operation, LNs were dissected and then assessed by routine histopathology, with 86% of them examined individually and the remaining LNs (14%) per AAO-HNS neck LN level. The optimal cutoff points (OCPs) of four defined LN diameters and 2D and 3D roundness indices per AAO-HNS neck LN level were determined.

Results
In total, 235 patients were included, and 4539 LNs were analyzed by US, 7237 by histopathology and 2684 by both methods. Of these, 259 (9.65%) were classified as suspicious for metastasis by US, whereas 299 (11.14%) were found to be positive by histopathology. Subjective US sensitivity and specificity were 0.79 and 0.99, respectively. The OCPs of the individual LN diameters and the 2D and 3D roundness index were determined individually for all AAO-HNS neck LN levels. Across all levels, the OCP for the 2D index was 1.79 and the 3D index was 14.97. The predictive performance of all distances, indices, and subjective findings improved with increasing metastasis size. Anticipation of pN stage was best achieved with subjective US findings and the smallest diameter (Cohen’s κ = 0.713 and 0.438, respectively).

Conclusion
Our LN mapping and meticulous 1:1 node-by-node comparison reveals the usefulness of US for detecting metastatic involvement of neck LNs in head and neck carcinomas as compared to histopathology. The predictive ability for small tumor deposits less than 8 mm in size remains weak and urgently needs improvement.
Evolution of major flowering pathway integrators in Orchidaceae
Authors: Madrigal Yesenia , Alzate Juan F. , Pabón-Mora Natalia 
Published: October 2023

AbstractThe Orchidaceae is a mega-diverse plant family with ca. 29,000 species with a large variety of life forms that can colonize transitory habitats. Despite this diversity, little is known about their flowering integrators in response to specific environmental factors. During the reproductive transition in flowering plants a vegetative apical meristem (SAM) transforms into an inflorescence meristem (IM) that forms bracts and flowers. In model grasses, like rice, a flowering genetic regulatory network (FGRN) controlling reproductive transitions has been identified, but little is known in the Orchidaceae. In order to analyze the players of the FRGN in orchids, we performed comprehensive phylogenetic analyses of CONSTANS-like/CONSTANS-like 4 (COL/COL4), FLOWERING LOCUS D (FD), FLOWERING LOCUS C/FRUITFULL (FLC/FUL) and SUPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1) gene lineages. In addition to PEBP and AGL24/SVP genes previously analyzed, here we identify an increase of orchid homologs belonging to COL4, and FUL gene lineages in comparison with other monocots, including grasses, due to orchid-specific gene lineage duplications. Contrariwise, local duplications in Orchidaceae are less frequent in the COL, FD and SOC1 gene lineages, which points to a retention of key functions under strong purifying selection in essential signaling factors. We also identified changes in the protein sequences after such duplications, variation in the evolutionary rates of resulting paralogous clades and targeted expression of isolated homologs in different orchids. Interestingly, vernalization-response genes like VERNALIZATION1 (VRN1) and FLOWERING LOCUS C (FLC) are completely lacking in orchids, or alternatively are reduced in number, as is the case of VERNALIZATION2/GHD7 (VRN2). Our findings point to non-canonical factors sensing temperature changes in orchids during reproductive transition. Expression data of key factors gathered from Elleanthus auratiacus, a terrestrial orchid in high Andean mountains allow us to characterize which copies are actually active during flowering. Altogether, our data lays down a comprehensive framework to assess gene function of a restricted number of homologs identified more likely playing key roles during the flowering transition, and the changes of the FGRN in neotropical orchids in comparison with temperate grasses.
DeepSIM: a novel deep learning method for graph similarity computation
Authors: Liu Bo , Wang Zhihan , Zhang Jidong , Wu Jiahui , Qu Guangzhi 
Published: October 2023

AbstractGraphs are widely used to model real-life information, where graph similarity computation is one of the most significant applications, such as inferring the properties of a compound based on similarity to a known group. Definition methods (e.g., graph edit distance and maximum common subgraph) have extremely high computational cost, and the existing efficient deep learning methods suffer from the problem of inadequate feature extraction which would have a bad effect on similarity computation. In this paper, a double-branch model called DeepSIM was raised to deeply mine graph-level and node-level features to address the above problems. On the graph-level branch, a novel embedding relational reasoning network was presented to obtain interaction between pairwise inputs. Meanwhile, a new local-to-global attention mechanism is designed to improve the capability of CNN-based node-level feature extraction module on another path. In DeepSIM, double-branch outputs will be concatenated as the final feature. The experimental results demonstrate that our methods perform well on several datasets compared to the state-of-the-art deep learning models in related fields.Graphical abstract
Microstate Analysis Reflects Maturation of the Preterm Brain
Authors: Hermans Tim , Khazaei Mohammad , Raeisi Khadijeh , Croce Pierpaolo , Tamburro Gabriella , Dereymaeker Anneleen , De Vos Maarten , Zappasodi Filippo , Comani Silvia 
Published: October 2023

AbstractPreterm neonates are at risk of long-term neurodevelopmental impairments due to disruption of natural brain development. Electroencephalography (EEG) analysis can provide insights into brain development of preterm neonates. This study aims to explore the use of microstate (MS) analysis to evaluate global brain dynamics changes during maturation in preterm neonates with normal neurodevelopmental outcome.The dataset included 135 EEGs obtained from 48 neonates at varying postmenstrual ages (26.4 to 47.7 weeks), divided into four age groups. For each recording we extracted a 5-minute epoch during quiet sleep (QS) and during non-quiet sleep (NQS), resulting in eight groups (4 age group x 2 sleep states). We compared MS maps and corresponding (map-specific) MS metrics across groups using group-level maps. Additionally, we investigated individual map metrics.Four group-level MS maps accounted for approximately 70% of the global variance and showed non-random syntax. MS topographies and transitions changed significantly when neonates reached 37 weeks. For both sleep states and all MS maps, MS duration decreased and occurrence increased with age. The same relationships were found using individual maps, showing strong correlations (Pearson coefficients up to 0.74) between individual map metrics and post-menstrual age. Moreover, the Hurst exponent of the individual MS sequence decreased with age.The observed changes in MS metrics with age might reflect the development of the preterm brain, which is characterized by formation of neural networks. Therefore, MS analysis is a promising tool for monitoring preterm neonatal brain maturation, while our study can serve as a valuable reference for investigating EEGs of neonates with abnormal neurodevelopmental outcomes.
Trustworthy and intelligent fault diagnosis with effective denoising and evidential stacked GRU neural network
Authors: Zhou Hanting , Chen Wenhe , Liu Jing , Cheng Longsheng , Xia Min 
Published: October 2023

AbstractWith the advances in Internet-of-Things and data mining technologies, deep learning-based approaches have been widely used for intelligent fault diagnosis of manufacturing assets. However, uncertainty caused by the non-stationary process data such as vibration signal and noise interference in practical working environments will greatly affect the performance and reliability of predictions. The present paper develops a trustworthy and intelligent fault diagnosis framework based on a two-stage joint denoising method and evidential neural networks. The proposed denoising method integrating the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and the independent component analysis (ICA) method can effectively reduce data uncertainty caused by noise interference. The stacked gated recurrent unit (SGRU) model has been incorporated into the evidential neural networks as a deep classifier. The proposed evidential SGRU (ESGRU) method can quantify the prediction uncertainty, which estimates the prediction trustworthiness. Predictive entropy and reliability diagrams are used as calibration methods to validate the effectiveness of uncertainty estimation. The proposed framework is validated by two case studies of rolling bearing fault diagnosis in variable noise conditions. Experimental results demonstrate that the proposed method can achieve a high denoising effect and provide reliable uncertainty prediction results which are significant for practical applications.
Anxiety and Depression in Early Gestation and the Association with Subsequent Gestational Diabetes Mellitus in a Disadvantaged Population
Authors: Pathirana Maleesa M. , Andraweera Prabha H. , Leemaqz Shalem , Aldridge Emily , Arstall Margaret A. , Dekker Gustaaf A. , Roberts Claire T. 
Published: October 2023

Abstract
Objectives
Evaluate the association between poor mental health and risk of developing gestational diabetes mellitus (GDM) in a cohort of women from a socioeconomically disadvantaged community.

Methods
A total of 1363 nulliparous women with singleton pregnancies recruited to the Screening Tests to Predict Poor Outcomes of Pregnancy study in Adelaide, Australia. Women were assessed for mental health in the first trimester, including likelihood of depression, high functioning anxiety, perceived stress and risk of developing a mental health disorder. GDM was diagnosed based on the International Association of Diabetes in Pregnancy Study Group (IADPSG) criteria. Socioeconomic status was measured using the New Zealand Socioeconomic Index (NZSEI).

Results
Complete mental health data was available for 1281 participants. There was no statistically significant difference in SEI, depression, risk of mental health issues, high functioning anxiety and perceived stress between women who developed GDM and those who did not. There was no difference in history of depression nor risk of developing a high mental health disorder in first trimester after adjusting for SEI, BMI in first trimester, smoking status in first trimester and maternal age between women with a GDM pregnancy and those who did not.

Conclusions for Practice
There was no difference in markers of poor mental health in early pregnancy between women who subsequently did or did not develop GDM. Cohort participants were socioeconomically disadvantaged, potentially contributing to the lack of apparent differences in depression observed between groups. Socioeconomically disadvantaged women should be targeted in pre-conception planning to reduce risk of GDM.
Proanthocyanidin biosynthesis and postharvest seed coat darkening in pinto bean
Authors: Islam Nishat S. , Dhaubhadel Sangeeta 
Published: October 2023

AbstractProanthocyanidins (PAs) are polyphenolic compounds present widely in the plant kingdom. These specialized metabolites are derived from the phenylpropanoid pathway and are known for producing brown pigments in different plant organs. PAs accumulate in the seed coat tissues of flowering plants and play a determinant role in seed germination and viability, protect seeds from biotic and abiotic stresses, and thus ensure the long-term storage potential of seeds. In addition, PAs are a rich source of antioxidants for the health of both human and livestock. Many of the commercially relevant dry beans (Phaseolus vulgaris) contain high levels of PAs, which when oxidized cause the beans to overdarken, a phenomenon known as postharvest darkening. These darker beans give the impression of oldness, and consumers tend to avoid buying them which, in turn, affects their market value. Pinto beans, one of the leading market classes of dry beans, are affected the most by the postharvest darkening. Therefore, exploring the regulation of PA biosynthesis and accumulation in bean seed coat tissues will help to develop strategy to manage the postharvest darkening effect in pintos. In this review, we discuss the PA biosynthesis and its regulation, connecting it to seed coat color genetics for a better understanding of the mechanism of seed coat darkening.
Consistency factor for the MCD estimator at the Student-t distribution
Authors: Barabesi Lucio , Cerioli Andrea , García-Escudero Luis Angel , Mayo-Iscar Agustín 
Published: October 2023

AbstractIt is well known that trimmed estimators of multivariate scatter, such as the Minimum Covariance Determinant (MCD) estimator, are inconsistent unless an appropriate factor is applied to them in order to take the effect of trimming into account. This factor is widely recommended and applied when uncontaminated data are assumed to come from a multivariate normal model. We address the problem of computing a consistency factor for the MCD estimator in a heavy-tail scenario, when uncontaminated data come from a multivariate Student-tdistribution. We derive a remarkably simple computational formula for the appropriate factor and show that it reduces to an even simpler analytic expression in the bivariate case. Exploiting our formula, we then develop a robust Monte Carlo procedure for estimating the usually unknown number of degrees of freedom of the assumed and possibly contaminated multivariate Student-tmodel, which is a necessary ingredient for obtaining the required consistency factor. Finally, we provide substantial simulation evidence about the proposed procedure and apply it to data from image processing and financial markets.
Genome-wide association study reveals candidate genes for traits related to meat quality in Colombian Creole hair sheep
Authors: Revelo Herman Alberto , López-Alvarez Diana , Palacios Yineth Alexandra , Vergara Oscar David , Yánez Moris Bustamante , Ariza Manuel Fernando , Molina Susan Lorena Castro , Sanchez Yurany Ortiz , Alvarez Luz Ángela 
Published: October 2023

AbstractGenome-wide association studies (GWAS) allow identifying genomic regions related to traits of economic importance in animals of zootechnical interest. The objective of this research was to conduct a genome-wide association study on meat quality traits using the Illumina OvineSNPs50 BeadChip array. The animals were sampled in the departments of Córdoba, Cesar, and Valle del Cauca. The genotypes obtained with the Illumina OvineSNP50 BeadChip microarray were analyzed SNP (single-nucleotide polymorphism) data to conduct a GWAS for pH and water-holding capacity (WHC) traits measured after 7 days of maturation, in the Longissimus dorsi (LD) muscle, in 167 Creole hair sheep of 12 months old belonging to Pelibuey (CHSP, n = 60), Ethiopian (CHSE, n = 44), and Sudan (CHSS, n = 63) breeds. The GWAS was done using a mixed linear model (MLMA) and based on the Ovis aries v3.1 genome. The CHSE showed the lowest meat juice release and, consequently, the highest water-holding capacity (WHC = 30.6 ± 0.1), suggesting that this breed has better performance in the meat industry compared with CHSS (WHC = 41.7 ± 0.1) and CHSP (WHC = 36.8 ± 0.1), since there is a relationship between WHC and juiciness. For the character pH, it was not possible to annotate genes related to meat quality, while, for the WHC, they have obtained 11 candidate genes associated (ELOVL2, ARAP2, LOC101102527, SHOC2, AIPL1, CSRNP3, IFRD, KDM8, NANS, DAPK1, IBN2, TPM2). Particularly, ELOVL2, ARAP2, IBN2, and TPM2 genes are involved in muscle contraction and fatty acid composition in sheep. In this study, we generated a baseline for GWAS related to meat quality traits in Colombian Creole hair sheep that can be used for future genomic selection plans.
VisualPDE: Rapid Interactive Simulations of Partial Differential Equations
Authors: Walker Benjamin J. , Townsend Adam K. , Chudasama Alexander K. , Krause Andrew L. 
Published: October 2023

AbstractComputing has revolutionised the study of complex nonlinear systems, both by allowing us to solve previously intractable models and through the ability to visualise solutions in different ways. Using ubiquitous computing infrastructure, we provide a means to go one step further in using computers to understand complex models through instantaneous and interactive exploration. This ubiquitous infrastructure has enormous potential in education, outreach and research. Here, we present VisualPDE, an online, interactive solver for a broad class of 1D and 2D partial differential equation (PDE) systems. Abstract dynamical systems concepts such as symmetry-breaking instabilities, subcritical bifurcations and the role of initial data in multistable nonlinear models become much more intuitive when you can play with these models yourself, and immediately answer questions about how the system responds to changes in parameters, initial conditions, boundary conditions or even spatiotemporal forcing. Importantly, VisualPDE is freely available, open source and highly customisable. We give several examples in teaching, research and knowledge exchange, providing high-level discussions of how it may be employed in different settings. This includes designing web-based course materials structured around interactive simulations, or easily crafting specific simulations that can be shared with students or collaborators via a simple URL. We envisage VisualPDE becoming an invaluable resource for teaching and research in mathematical biology and beyond. We also hope that it inspires other efforts to make mathematics more interactive and accessible.