bluuebunny/crossref_metadata_2025_split huggingface dataset:
Variable transformations in combination with wavelets and ANOVA for high-dimensional approximation
Authors: Potts Daniel , Weidensager Laura 
Published: May 2024

AbstractWe use hyperbolic wavelet regression for the fast reconstruction of high-dimensional functions having only low-dimensional variable interactions. Compactly supported periodic Chui-Wang wavelets are used for the tensorized hyperbolic wavelet basis on the torus. With a variable transformation, we are able to transform the approximation rates and fast algorithms from the torus to other domains. We perform and analyze scattered data approximation for smooth but arbitrary density functions by using a least squares method. The corresponding system matrix is sparse due to the compact support of the wavelets, which leads to a significant acceleration of the matrix vector multiplication. For non-periodic functions, we propose a new extension method. A proper choice of the extension parameter together with the piecewise polynomial Chui-Wang wavelets extends the functions appropriately. In every case, we are able to bound the approximation error with high probability. Additionally, if the function has a low effective dimension (i.e., only interactions of a few variables), we qualitatively determine the variable interactions and omit ANOVA terms with low variance in a second step in order to decrease the approximation error. This allows us to suggest an adapted model for the approximation. Numerical results show the efficiency of the proposed method.
Methodology and real-world applications of dynamic uncertain causality graph for clinical diagnosis with explainability and invariance
Authors: Zhang Zhan , Zhang Qin , Jiao Yang , Lu Lin , Ma Lin , Liu Aihua , Liu Xiao , Zhao Juan , Xue Yajun , Wei Bing , Zhang Mingxia , Gao Ru , Zhao Hong , Lu Jie , Li Fan , Zhang Yang , Wang Yiming , Zhang Lei , Tian Fengwei , Hu Jie , Gou Xin 
Published: May 2024

AbstractAI-aided clinical diagnosis is desired in medical care. Existing deep learning models lack explainability and mainly focus on image analysis. The recently developed Dynamic Uncertain Causality Graph (DUCG) approach is causality-driven, explainable, and invariant across different application scenarios, without problems of data collection, labeling, fitting, privacy, bias, generalization, high cost and high energy consumption. Through close collaboration between clinical experts and DUCG technicians, 46 DUCG models covering 54 chief complaints were constructed. Over 1,000 diseases can be diagnosed without triage. Before being applied in real-world, the 46 DUCG models were retrospectively verified by third-party hospitals. The verified diagnostic precisions were no less than 95%, in which the diagnostic precision for every disease including uncommon ones was no less than 80%. After verifications, the 46 DUCG models were applied in the real-world in China. Over one million real diagnosis cases have been performed, with only 17 incorrect diagnoses identified. Due to DUCG’s transparency, the mistakes causing the incorrect diagnoses were found and corrected. The diagnostic abilities of the clinicians who applied DUCG frequently were improved significantly. Following the introduction to the earlier presented DUCG methodology, the recommendation algorithm for potential medical checks is presented and the key idea of DUCG is extracted.
Analytical methods in celestial mechanics: satellites’ stability and galactic billiards
Authors: De Blasi Irene 
Published: May 2024

AbstractIn this paper, two models of interest for Celestial Mechanics are presented and analysed, using both analytic and numerical techniques, from the point of view of the possible presence of regular and/or chaotic motion, as well as the stability of the considered orbits. The first model, presented in a Hamiltonian formalism, can be used to describe the motion of a satellite around Earth, taking into account both the non-spherical shape of our planet and the third-body gravitational influence of Sun and Moon. Using semi-analytical techniques coming from Normal Form and Nekhoroshev theories it is possible to provide stability estimates for the orbital elements of its geocentric motion. The second dynamical system presented can be used as a simplified model to describe the motion of a particle in an elliptic galaxy having a central massive core; it is constructed as a refraction billiard where an inner dynamics, induced by a Keplerian potential, is coupled with an external one, where a harmonic oscillator-type potential is considered. The investigation of the dynamics is carried on by using results of ODEs’ theory and is focused on studying the trajectories’ properties in terms of periodicity, stability and, possibly, chaoticity.
Integrating optical and electrical sensing with machine learning for advanced particle characterization
Authors: Kokabi Mahtab , Tayyab Muhammad , Rather Gulam M. , Pournadali Khamseh Arastou , Cheng Daniel , DeMauro Edward P. , Javanmard Mehdi 
Published: May 2024

AbstractParticle classification plays a crucial role in various scientific and technological applications, such as differentiating between bacteria and viruses in healthcare applications or identifying and classifying cancer cells. This technique requires accurate and efficient analysis of particle properties. In this study, we investigated the integration of electrical and optical features through a multimodal approach for particle classification. Machine learning classifier algorithms were applied to evaluate the impact of combining these measurements. Our results demonstrate the superiority of the multimodal approach over analyzing electrical or optical features independently. We achieved an average test accuracy of 94.9% by integrating both modalities, compared to 66.4% for electrical features alone and 90.7% for optical features alone. This highlights the complementary nature of electrical and optical information and its potential for enhancing classification performance. By leveraging electrical sensing and optical imaging techniques, our multimodal approach provides deeper insights into particle properties and offers a more comprehensive understanding of complex biological systems.
Graphical abstract
Measuring serum oestrogen levels in breast cancer survivors using vaginal oestrogens: a systematic review
Authors: Pearson Antonia , Chen Jill , Dhillon Haryana M. , Kiely Belinda E. 
Published: May 2024

Abstract
Purpose
Vaginal oestrogens can be used to treat genitourinary symptoms in women with early breast cancer. Studies evaluating vaginal oestrogens have commonly measured serum oestrogen levels as a surrogate marker of safety, but methods vary. We sought to summarise the data on serum oestrogen measurement in women with breast cancer using vaginal oestrogens to better understand the methods, levels and reliability.

Methods
We searched Medline, Embase, CENTRAL, SCOPUS and CINAHL from inception to October 2023 for clinical studies where serum oestrogen was measured in women with a history of early breast cancer using vaginal oestrogens. Studies with a reported testing methodology were included.

Results
Nine studies met the inclusion criteria for this systematic review. Methods used to measure oestradiol and oestriol in selected studies included mass spectrometry and immunoassays; several studies used more than one with variable concordance. Mass spectrometry detected oestradiol levels down to a lower limit between 1.0 pg/mL and 3.0 pg/mL. Immunoassays such as ELISA (enzyme-linked immunosorbent assay), ECLIA (enhanced chemiluminiscence immunoassay) and RIA (radioimmunoassay) had lower detection limits ranging between 0.8 pg/mL and 10 pg/mL. Studies were heterogeneous in testing techniques used, timing of testing, and the population including with subsequent varying results in the effect on oestrogens reported.

Conclusions
Adopting consistent and standardised methods of measuring oestrogens in clinical trials involving women with early breast cancer on vaginal oestrogens is critical. Serum oestrogens are used as a surrogate marker of safety in this population, and good-quality data are necessary to enable clinicians and patients to feel confident in prescribing and taking vaginal oestrogens. Mass spectrometry, although more expensive, gives more reliable results when dealing with very low levels of oestrogens often found in women on aromatase inhibitors, compared to immunoassays.
Prognostic relevance of global work index and global constructive work in patients with non-ischemic dilated cardiomyopathy
Authors: Chen Peng , Aurich Matthias , Greiner Sebastian , Maliandi Gabriele , Müller-Hennessen Matthias , Giannitsis Evangelos , Meder Benjamin , Frey Norbert , Pleger Sven , Mereles Derliz 
Published: May 2024

AbstractMyocardial work (MW) derived from pressure-strain loops is a novel non-invasive tool to assess left ventricular (LV) function, incorporating global longitudinal strain (GLS) by speckle tracking echocardiography and non-invasively assessed blood pressure. Studies on the role of MW in dilated cardiomyopathy (DCM) are still limited. Therefore, the aim of this study was to evaluate the potential value of MW for predicting adverse outcomes in patients with DCM. 116 consecutive patients with DCM who underwent heart catheterization were retrospectively recruited from June 2009 to July 2014. 34 patients (30%) met the composite endpoints for major adverse cardiac events (MACE) of cardiac transplantation, need for implantable cardioverter-defibrillator (ICD) therapy, heart failure hospitalization and all-cause mortality. Patients with DCM were followed up for a mean of 5.1 years (IQR: 2.2–9.1 years). Global work index (GWI) and global constructive work (GCW) were not only independent predictors but also provided incremental predictive values (Integrated discrimination improvement [IDI] > 0) of MACE in multivariate Cox models. Furthermore, Patients with GWI < 788 mm Hg% (HR 5.46, 95%CI 1.66–17.92, p = 0.005) and GCW < 1,238 mm Hg% (HR 4.46, 95%CI 1.53–12.98, p = 0.006) had higher risks of MACE. GWI and GCW assessed by strain imaging echocardiography may have an additional value beyond LV-EF and GLS for predicting adverse outcomes in DCM.
Bounds on data limits for all-to-all comparison from combinatorial designs
Authors: Hall Joanne , Horsley Daniel , Stinson Douglas R. 
Published: May 2024

AbstractIn situations where every item in a data set must be compared with every other item in the set, it may be desirable to store the data across a number of machines in such a way that any two data items are stored together on at least one machine. One way to evaluate the efficiency of such a distribution is by the largest fraction of the data it requires to be allocated to any one machine. The all-to-all comparison (ATAC) data limit formmachines is a measure of the minimum of this value across all possible such distributions. In this paper we further the study of ATAC data limits. We begin by investigating the data limits achievable using various classes of combinatorial designs. In particular, we examine the cases of transversal designs and projective Hjelmslev planes. We then observe relationships between data limits and the previously studied combinatorial parameters of fractional matching numbers and covering numbers. Finally, we prove a lower bound on the ATAC data limit that improves on one of Hall, Kelly and Tian, and examine the special cases where equality in this bound is possible.
Improving Recycling: How Far Should We Go?
Authors: Belleflamme Paul , Ha Huan 
Published: May 2024

AbstractWe analyze, in a game-theoretic model, the strategic interaction between competing firms that source their inputs from either primary or recycled material. Because the manufacturers’ primary production today serves as input for the recyclers’ production tomorrow, manufacturers can limit the recyclers’ scale of operation by reducing their output. Improving the recycling process generates then two opposite effects: it reduces primary production tomorrow by exposing manufacturers to stronger competition from recyclers, but it also lowers the manufacturers’ incentives to reduce their primary production today. If primary production exerts a negative externality on the environment, then making the recycling process too efficient might be counterproductive. This intuition equally applies to remanufacturing.
Colony environment and absence of brood enhance tolerance to a neonicotinoid in winter honey bee workers, Apis mellifera
Authors: Bovier Manon , Camenzind Domenic W. , Brown Andrew F. , Jeker Lukas , Retschnig Gina , Neumann Peter , Straub Lars 
Published: May 2024

AbstractIn eusocial insects, worker longevity is essential to ensure colony survival in brood-free periods. Trade-offs between longevity and other traits may render long-living workers in brood-free periods more susceptible to pesticides compared to short-lived ones. Further, colony environment (e.g., adequate nutrition) may enable workers to better cope with pesticides, yet data comparing long vs. short-living workers and the role of the colony environment for pesticide tolerance are scarce. Here, we show that long-living honey bee workers, Apis mellifera, are less susceptible to the neonicotinoid thiamethoxam than short-lived workers, and that susceptibility was further reduced when workers were acclimatized under colony compared to laboratory conditions. Following an OECD protocol, freshly-emerged workers were exposed to thiamethoxam in summer and winter and either acclimatized within their colony or in the laboratory. Mortality and sucrose consumption were measured daily and revealed that winter workers were significantly less susceptible than summer workers, despite being exposed to higher thiamethoxam dosages due to increased food consumption. Disparencies in fat body activity, which is key for detoxification, may explain why winter bees were less susceptible. Furthermore, colony acclimatization significantly reduced susceptibility towards thiamethoxam in winter workers likely due to enhanced protein nutrition. Brood absence and colony environment seem to govern workers’ ability to cope with pesticides, which should be considered in risk assessments. Since honey bee colony losses occur mostly over winter, long-term studies assessing the effects of pesticide exposure on winter bees are required to better understand the underlying mechanisms.
A Motivational Perspective on (Anticipated) Mental Effort Investment: The Biopsychosocial Model of Challenge and Threat
Authors: van Gog Tamara , Janssen Eva , Lucas Florence , Taheij Maaike 
Published: May 2024

AbstractResearch in cognitive load theory is increasingly recognizing the importance of motivational influences on students’ (willingness to invest) mental effort, in particular in the context of self-regulated learning. Consequently, next to addressing effects of instructional conditions and contexts on groups of learners, there is a need to start investigating individual differences in motivational variables. We propose here that the biopsychosocial model of challenge and threat may offer a useful model to study the motivational antecedents of (anticipated) mental effort. We also report four experiments as initial tests of these ideas, exploring how feedback valence affects students’ challenge/threat experiences, self-efficacy, and mental effort investment. The results showed that negative feedback leads participants to expect that they will have to invest significantly more effort in future problems than positive feedback (Experiments 1, 2, and 3) or no feedback (Experiment 3). Had we not considered the motivational variables in investigating the effect of feedback conditions on effort investment, we would not have known that this effect was fully mediated and thus explained by participants’ feelings of self-efficacy (Experiments 1/2) and threat (Experiment 1). We would also have concluded that feedback does not affect the willingness to invest effort in future problems (all four experiments), whereas actually, there were significant indirect effects of feedback on willingness to invest effort via challenge (in Experiments 1/2) and threat (in all experiments). Thus, our findings demonstrate the added value of considering challenge and threat motivational states to explain individual differences in effort investment.
What drives customer loyalty in a pandemic? Semantic analysis of grocery retailers
Authors: Kuikka Anna , Hallikainen Heli , Tuominen Sasu , Laukkanen Tommi 
Published: May 2024

AbstractThe COVID-19 pandemic accelerated online grocery shopping and disrupted customer loyalty. This study analyzes 45,603 Trustpilot reviews of grocery retailers across three eras: pre-pandemic, pandemic, and the “new normal”. We employ Linguistic Inquiry and Word Count to categorize loyalty drivers into three dimensions—cognitive, affective, and social experiences–and we test their relationship with customer loyalty. Whereas cognitive and affective drivers were dominant before the pandemic, social drivers gained prominence during and after the pandemic, reflecting a desire for social interactions amid social distancing. We demonstrate that the influence of the drivers on customer loyalty remains consistent, except for the post-pandemic period, where the cognitive driver lost influence. Consequently, we conclude that consumer behavior in online grocery retailing has changed profoundly. We further suggest that online reviews provide attractive opportunities for retailers to analyze, build, and sustain customer loyalty.
Eco-sabotage as Defensive Activism
Authors: Manson Dylan 
Published: May 2024

AbstractI argue for the conditions that eco-sabotage (sabotage involving the protection of animals or the environment) must meet to be a morally permissible form of activism in a liberal democracy. I illustrate my case with Jessica Reznicek and Ruby Montoya’s oil pipeline destruction, the Sea Shepherd Conservation Society’s whale hunt sabotage, and the Valve Turners’ pipeline shut-off, climate necessity-defense. My primary contention is that just as it is permissible to destroy an attacker’s weapon in self- or other-defense, it is permissible to engage in some forms of eco-sabotage. Taking inspiration from just war theory, I use the conditions of just cause, reasonable chance of success, proportionality, necessity, and discrimination to both conceptualize eco-sabotage as defense and illustrate the justificatory burden the eco-saboteur must meet. Often eco-sabotage is doubly pro-tanto wrong because it is illegal and involves property destruction. Overcoming these hurdles is particularly difficult because in seemingly bypassing democratic means of dispute resolution, the eco-saboteur seemingly coerces the other members of society by forcing idiosyncratic views upon them. Non-anthropocentric eco-sabotage grounded in defense of animal rights has mixed results regarding the democratic objection just described. I argue that anthropocentric eco-sabotage, grounded in defense of human rights, has the best chance of overcoming this objection, provided a persuasive case can be made for its reasonable chance of success. Passing a reasonable chance of success also causes problems for non-anthropocentric eco-sabotage grounded in species defense, while non-anthropocentric eco-sabotage grounded in defense against animal suffering has a lighter justificatory burden.
Information-flow interfaces
Authors: Bartocci Ezio , Ferrère Thomas , Henzinger Thomas A. , Nickovic Dejan , Oliveira da Costa Ana 
Published: May 2024

AbstractContract-based design is a promising methodology for taming the complexity of developing sophisticated systems. A formal contract distinguishes between assumptions, which are constraints that the designer of a component puts on the environments in which the component can be used safely, and guarantees, which are promises that the designer asks from the team that implements the component. A theory of formal contracts can be formalized as an interface theory, which supports the composition and refinement of both assumptions and guarantees. Although there is a rich landscape of contract-based design methods that address functional and extra-functional properties, we present the first interface theory designed to ensure system-wide security properties. Our framework provides a refinement relation and a composition operation that support both incremental design and independent implementability. We develop our theory for both stateless and stateful interfaces. Additionally, we introduce information-flow contracts where assumptions and guarantees are sets of flow relations. We use these contracts to illustrate how to enrich information-flow interfaces with a semantic view. We illustrate the applicability of our framework with two examples inspired by the automotive domain.
In silico prediction of microRNA families involved in the biosynthesis of lignans and cyanogenic glycosides in flax (Linum usitatissimum L.)
Authors: Harenčár Ľubomír , Ražná Katarína 
Published: May 2024

AbstractFlaxseed (Linum usitatissimum L.) is renowned for having the highest concentration of lignans among all plant species worldwide. However, it also contains a notable amount of cyanogenic glycosides, prompting efforts to reduce their levels. MicroRNAs, recognized as significant epigenetic factors, hold the potential to serve as genetic markers in achieving this breeding goal. In this study, 44,885 mature microRNAs were utilized alongside one genome and four transcriptomes of flax. Twelve gene sequences were obtained for five lignan enzymes and three enzymes related to cyanogenic glycosides. Based on our in silico approach, we identified 15 microRNA families for the lignan metabolic pathway, 10 for the cyanogenic glycoside pathway, and 6 regulating both pathways. Additionally, we contributed to the annotation of the used transcriptomes and verified the functionality of the “Finding genes by keyword” algorithm available on Phytozome 13. The results obtained led to the design of a unique schema for microRNA mediated regulation in the biosynthetic pathways of lignans and cyanogenic glycosides. This research will enhance our understanding of the regulatory mechanisms of microRNA in these biosynthetic pathways, along with other specialized metabolites. The predicted microRNAs can be employed in marker-assisted selection with the breeding objective of optimizing the ratio of nutritional and antinutritional components in flaxseed while maintaining current physiological parameters.
Home- and community-based care in the new generation of Medicaid administrative data
Authors: Wang Sijiu , Qi Mingyu , Konetzka R. Tamara 
Published: May 2024

Abstract
This study aimed to assess the quality of Home and Community-Based Services (HCBS) data elements within the Transformed Medicaid Statistical Information System Analytical File (TAF) and to devise strategies for improving its research usability. Analyzing Medicaid TAF data from 2016 to 2018, we conducted a retrospective data quality analysis, focusing specifically on HCBS-related data elements. Through secondary data analysis, we identified significant challenges, including considerable missingness and inconsistencies that hamper the effective use of TAF for research purposes. Despite these issues, we developed three approaches that enabled us to identify 94% of known 1915(c) waiver claims as HCBS. Our study also revealed considerable cross-state variations in data quality, prompting specific recommendations for utilizing HCBS data within TAF. Ultimately, the study concludes that while challenges exist, applying our recommended strategies can yield data of acceptable quality for most states, particularly in identifying HCBS usage and classifying them into service categories. Given the growing importance of home-based care, there is a pressing need to prioritize improvements in TAF’s HCBS data quality to better inform policy and practice.