bluuebunny/crossref_metadata_2025_split huggingface dataset:
Remote possibilities in branching time structures
Authors: Wenmackers Sylvia 
Published: July 2024

AbstractTo analyse contingent propositions, this paper investigates how branching time structures can be combined with probability theory. In particular, it considers assigning infinitesimal probabilities—available in non-Archimedean probability theory—to individual histories. This allows us to introduce the concept of ‘remote possibility’ as a new modal notion between ‘impossibility’ and ‘appreciable possibility’. The proposal is illustrated by applying it to a future contingent and a historical counterfactual concerning an infinite sequence of coin tosses. The latter is a toy model that is used to illustrate the applicability of the proposal to more realistic physical models.
Emergency Resection for Colonic Cancer Has an Independent and Unfavorable Effect on Long-Term Oncologic Outcome
Authors: Sandini Marta , Piccioni Stefania , Badalucco Simona , Andreucci Eleonora , Gambelli Margherita , Fontani Andrea , Piagnerelli Riccardo , Verre Luigi , Marrelli Daniele , Roviello Franco 
Published: July 2024

Abstract
Background
Long-term outcomes in patients undergoing emergency versus elective resection for colorectal cancer (CRC) remain controversial. This study aims to assess short- and long-term outcomes of emergency versus elective CRC surgery.

Methods
In this single-center retrospective cohort study, patients undergoing emergency or elective colonic resections for CRC from January 2013 to December 2017 were included. Primary outcome was long-term survival. As secondary outcomes, we sought to analyze potential differences on postoperative morbidity and concerning the oncological standard of surgical resection. The Kaplan-Meier curves and Cox proportional hazard model were used to compare survival between the groups.

Results
Overall, 225 CRC patients were included. Of these 192 (85.3%) had an elective and 33 (14.7%) an emergency operation. Emergency indications were due to obstruction, perforation, or bleeding. Patients in the emergency group had higher ASA score (p = 0.023), higher Charlsson comorbidity index (CCI, p = 0.012), and were older than those in the elective group, with median age 70 (IQR 63–79) years and 78 (IQR 68–83) years, for elective and emergency, respectively (p = 0.020). No other preoperative differences were observed. Patients in the emergency group experienced significantly more major complications (12.1% vs. 3.6%, p = 0.037), more anastomotic leakage (12.1% vs. 1.6%, p = 0.001), need for reoperation (12.1% vs. 3.1%, p = 0.021), and postoperative mortality (2 patients vs. 0, p < 0.001). No differences in terms of final pathological stage, nor in accuracy of lymphadenectomy were observed. Overall survival was significantly worse in case of emergency operation, with estimated median 41 months vs. not reached in elective cases (p < 0.001). At the multivariate analysis, emergency operation was confirmed as independent unfavorable determinant of survival (with hazard rate HR = 1.97, p = 0.028), together with age (HR = 1.05, p < 0.001), postoperative major morbidity (HR = 3.18, p = 0.012), advanced stage (HR = 5.85, p < 0.001), and need for transfusion (HR = 2.10, p = 0.049).

Conclusion
Postoperative morbidity and mortality were increased in emergency versus elective CRC resections. Despite no significant differences in terms of accuracy of resection and pathological stages, overall survival was significantly worse in patients who underwent emergency procedure, and independent of other determinants of survival.
Integrative mRNA and miRNA Expression Profiles from Developing Zebrafish Head Highlight Brain-Preference Genes and Regulatory Networks
Authors: Zhang Shuqiang , Yang Jian , Xu Jie , Li Jing , Xu Lian , Jin Nana , Li Xiaoyu 
Published: July 2024

Abstract
Zebrafish is an emerging animal model for studying molecular mechanism underlying neurodevelopmental disorder due to its advantage characters. miRNAs are small non-coding RNAs that play a key role in brain development. Understanding of dynamic transcriptional and post-transcriptional molecules and their regulation during the head development is important for the study of neurodevelopmental disorder. In this study, we performed the high-throughput sequencing of mRNAs and miRNAs in developing zebrafish head from pharyngula to early larval stages and carried out bioinformatic analysis including differential expression and functional enrichment as well as joint analysis of miRNAs and mRNAs, and also compared with other related public sequencing datasets to aid our interpretation. A large number of differential expression genes with a large fold change were detected during the head development. Further clustering and functional enrichment analyses indicated that genes in late stage were most related with synaptic signaling. Overlap test analysis showed a significant enrichment of brain-preference and synapse-associated gene set in the head transcriptome compared with the whole embryo transcriptome. We also constructed miRNA-mRNA network for those brain-preference genes and focused on those densely connected network components. CRISPR-Cas9-mediated snap25b mutants led to embryonic development defects and decreases locomotor activity. Altogether, the present study provides developmental profiles of head-enriched mRNAs and miRNAs at three critical windows for nervous system development, which may contribute to the study of neurodevelopmental disorder.
Correction to: Ionospheric scintillation characteristics over Indian region from latitudinally-aligned geodetic GPS observations
Authors: Panda Sampad Kumar , Moses Mefe , Ansari Kutubuddin , Walo Janusz 
Published: July 2024

AbstractThe article “Ionospheric scintillation characteristics over Indian region from latitudinally-aligned geodetic GPS observations” was originally published Online First without open access. After publication in volume 16, issue 3, page 2675–2691, the author decided to opt for Open Choice and to make the article an open access publication.
A fixed-time stable forward–backward dynamical system for solving generalized monotone inclusions
Authors: Tran Nam V. , Hai Le T. T. , An Truong V. , Vuong Phan T. 
Published: July 2024

AbstractWe propose a forward–backward splitting dynamical system for solving inclusion problems of the form $$0\in A(x)+B(x)$$

0
∈
A
(
x
)
+
B
(
x
)

in Hilbert spaces, where A is a maximal operator and B is a single-valued operator. Involved operators are assumed to satisfy a generalized monotonicity condition, which is weaker than the standard monotone assumptions. Under mild conditions on parameters, we establish the fixed-time stability of the proposed dynamical system. In addition, we consider an explicit forward Euler discretization of the dynamical system leading to a new forward backward algorithm for which we present the convergence analysis. Applications to other optimization problems such as constrained optimization problems, mixed variational inequalities, and variational inequalities are presented and some numerical examples are given to illustrate the theoretical results.
Correlation of Quality of Life (QoL) and Self-perception in Patient with Thyroid Eye Disease (TED)
Authors: Bonavolontà Paola , Bernardo Roberta , Improta Giovanni , Iuliano Adriana , Tranfa Fausto , Califano Luigi , Strianese Diego 
Published: July 2024

Abstract
Introduction
Tyroid eye disease (TED) is an autoimmune disorder representing the commonest extrathyroidal manifestation of Graves’ disease (GD), with a prevalence of 10 per 10,000 persons in the European population. Although most frequently associated with hyperthyroidism secondary to GD, about 10% of patients with TED are euthyroid or hypothyroid. Patients with Graves orbitopathy (GO) have a significantly lower life quality, both regarding vision problems and worsened appearance, compared to a healthy person. It has been associated with increased rates of anxiety, depression, social isolation and decreased self-confidence.

Materials and Methods
The results of standard treatments in this disease are often unsatisfactory, but outcomes often do not correlate well with patient reports of how visible they feel their TED is, and the impact on their lives. The present study was designed to correlate QoL and self-perception of well-being with the different clinical and surgical approaches recommended by EUGOGO. The aim is to determine whether there were differences between treatment options in determining patient perception of well-being and satisfaction with treatment received, and whether they would recommend the treatment they had experienced to people with the same condition.

Results
Scheduled patients undergone medical or surgical treatments based on presence or not of inflammation signs. Evaluation of clinically relevant improvements in each clinical variable was carried out 6 months and one year after treatment. Later, patients were asked a set of general questions about improvement (or worsening) of symptoms, health condition before and after the treatment, degree of limitations of daily activities caused by the pathology, overall satisfaction. After one-year, visual acuity unchanged in all the cases, and exophthalmos’ absolute values improved. Daily activities limitations and heath conditions improved in most patients. In this study we demonstrate that although the majority of patients were satisfied with the treatment they received, patients presenting most severe disease at presentation and received most invasive procedures (such orbital decompression) were less satisfied due to an unrealistic expectation about the impact of surgery on their appearance, including expecting to return to a pre-morbid appearance.

Conclusion
This study highlights the importance of healthcare professionals eliciting and managing patients’ expectations, in order to optimize surgical outcomes.
Glucuronide metabolites of trans-ε-viniferin decrease triglycerides accumulation in an in vitro model of hepatic steatosis
Authors: Beaumont Pauline , Amintas Samuel , Krisa Stéphanie , Courtois Arnaud , Richard Tristan , Eseberri Itziar , Portillo Maria P. 
Published: July 2024

AbstractTrans-ε-viniferin, a resveratrol dimer found mainly in grapevine wood, has shown protective capacities against hepatic steatosis in vivo. Nevertheless, this compound is very poorly bioavailable. Thus, the aim of the present study is to determine the potential anti-steatotic properties of 1 and 10 µM of trans-ε-viniferin and its four glucuronide metabolites in AML-12 cells treated with palmitic acid as an in vitro model of hepatic steatosis. The effect of the molecules in cell viability and triglyceride accumulation, and the underlying mechanisms of action by Real-Time PCR and Western Blot were analysed, as well as the quantification of trans-ε-viniferin and the identified bioactive metabolite inside cells and their incubation media. Interestingly, we were able to determine the triglyceride-lowering property of one of the glucuronides (trans-ε-viniferin-2-glucuronide), which acts on de novo lipogenesis, fatty acid uptake and triglyceride assembly. The glucuronides of trans-ε-viniferin would therefore be partly responsible for the in vivo observed anti-steatotic properties of the parent compound.
Description and Validation of a Novel AI Tool, LabelComp, for the Identification of Adverse Event Changes in FDA Labeling
Authors: Neyarapally George A. , Wu Leihong , Xu Joshua , Zhou Esther H. , Dang Oanh , Lee Joann , Mehta Dharmang , Vaughn Rochelle D. , Pinnow Ellen , Fang Hong 
Published: July 2024

Abstract
Introduction
The accurate identification and timely updating of adverse reactions in drug labeling are crucial for patient safety and effective drug use. Postmarketing surveillance plays a pivotal role in identifying previously undetected adverse events (AEs) that emerge when a drug is used in broader and more diverse patient populations. However, traditional methods of updating drug labeling with new AE information have been manual, time consuming, and error prone. This paper introduces the LabelComp tool, an innovative artificial intelligence (AI) tool designed to enhance the efficiency and accuracy of postmarketing drug safety surveillance. Utilizing a combination of text analytics and a trained Bidirectional Encoder Representations from Transformers (BERT) model, the LabelComp tool automatically identifies changes in AE terms from updated drug labeling documents.

Objective
Our objective was to create and validate an AI tool with high accuracy that could enable researchers and FDA reviewers to efficiently identify safety-related drug labeling changes.

Results
Our validation study of 87 drug labeling PDF pairs demonstrates the tool's high accuracy, with F1 scores of overall performance ranging from 0.795 to 0.936 across different evaluation tiers and a recall of at least 0.997 with only one missed AE out of 483 total AEs detected, indicating the tool's efficacy in identifying new AEs.

Conclusion
The LabelComp tool can support drug safety surveillance and inform regulatory decision-making. The publication of this tool also aims to encourage further community-driven enhancements, aligning with broader interests in applying AI to advance regulatory science and public health.
A FDA-based multi-robot cooperation algorithm for multi-target searching in unknown environments
Authors: Ye Wenwen , Cai Jia , Li Shengping 
Published: July 2024

AbstractTarget search using a swarm of robots is a classic research topic that poses challenges, particularly in conducting multi-target searching in unknown environments. Key challenges include high communication cost among robots, unknown positions of obstacles, and the presence of multiple targets. To address these challenges, we propose a novel Robotic Flow Direction Algorithm (RFDA), building upon the modified Flow Direction Algorithm (FDA) to suit the characteristics of the robot’s motion. RFDA efficiently reduces the communication cost and navigates around unknown obstacles. The algorithm also accounts for scenarios involving isolated robots. The pipeline of the proposed RFDA method is outlined as follows: (1). Learning strategy: a neighborhood information based learning strategy is adopted to enhance the FDA’s position update formula. This allows swarm robots to systematically locate the target (the lowest height) in a stepwise manner. (2). Adaptive inertia weighting: An adaptive inertia weighting mechanism is employed to maintain diversity among robots during the search and avoid premature convergence. (3). Sink-filling process: The algorithm simulates the sink-filling process and moving to the aspect slope to escape from local optima. (4). Isolated robot scenario: The case of an isolated robot (a robot without neighbors) is considered. Global optimal information is only required when the robot is isolated or undergoing the sink-filling process, thereby reducing communication costs. We not only demonstrate the probabilistic completeness of RFDA but also validate its effectiveness by comparing it with six other competing algorithms in a simulated environment. Experiments cover various aspects such as target number, population size, and environment size. Our findings indicate that RFDA outperforms other methods in terms of the number of required iterations and the full success rate. The Friedman and Wilcoxon tests further demonstrate the superiority of RFDA.
Pulmonary function in patients with adolescent idiopathic scoliosis: an explorative study of a wearable smart shirt as a measurement instrument
Authors: Te Hennepe N. , Steegh V. L. J. M. , Pouw M. H. , Roukema J. , De Kleuver M. , Van Hooff M. L. 
Published: July 2024

Abstract

Purpose
Adolescent idiopathic scoliosis (AIS) presents various challenges, including respiratory symptoms that impact pulmonary function. This study aims to explore the feasibility of using a smart shirt for continuous monitoring of lung volumes and heart rate during routine activities in AIS patients.

Methods
A single-center exploratory feasibility study was conducted with AIS patients aged 16–22 years with a thoracic curvature of ≥ 30 degrees and absence of respiratory comorbidities. A smart shirt was utilized to continuously monitor cardiopulmonary parameters during mild exercise, which included a standardized walking route with the ascent of multiple stairs.

Results
Five participants completed the study. Baseline spirometry measurements showed a range of values for forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), and FEV1/FVC ratio. During mild exercise, participants exhibited variability in tidal volume, heart rate, breathing rate, and minute ventilation, with increases observed during stair climbing. Breathlessness levels also varied throughout the activity but did not correlate with the measured lung volumes. Overall, the use of the smart shirt for assessing pulmonary function in AIS patients was deemed feasible and well tolerated by participants during the test activities.

Conclusion
The study confirms the feasibility of using a smart shirt for continuous measurement of cardiopulmonary parameters in AIS patients during daily activities. Incongruities between spirometry results and perceived dyspnea exists, which questions the nature of the perceived dyspnea. Further research is needed to validate these findings and explore the impact of AIS characteristics on measurement accuracy.
Minimum levels of interpretability for artificial moral agents
Authors: Vijayaraghavan Avish , Badea Cosmin 
Published: July 2024

AbstractAs artificial intelligence (AI) models continue to scale up, they are becoming more capable and integrated into various forms of decision-making systems. For models involved in moral decision-making (MDM), also known as artificial moral agents (AMA), interpretability provides a way to trust and understand the agent’s internal reasoning mechanisms for effective use and error correction. In this paper, we bridge the technical approaches to interpretability with construction of AMAs to establish minimal safety requirements for deployed AMAs. We begin by providing an overview of AI interpretability in the context of MDM, thereby framing different levels of interpretability (or transparency) in relation to the different ways of constructing AMAs. Introducing the concept of the Minimum Level of Interpretability (MLI) and drawing on examples from the field, we explore two overarching questions: whether a lack of model transparency prevents trust and whether model transparency helps us sufficiently understand AMAs. Finally, we conclude by recommending specific MLIs for various types of agent constructions, aiming to facilitate their safe deployment in real-world scenarios.
The green city as a driver of sustainable development
Authors: Azizi Loubna , Kouddane Noureddine 
Published: July 2024

AbstractGiven the accelerating pace of urbanization and worsening environmental constraints, it has become imperative to explore innovative and integrated solutions to shape a sustainable urban future. In this context, the emergence of the “Green City” stands out as an innovative approach to addressing environmental challenges while promoting sustainable urban development. This study aims to deepen our understanding of the crucial role played by the Green City as a driver to overcome obstacles related to environmental and urban sustainability. To achieve this objective, our methodology is based on several essential steps. Firstly, we establish a solid conceptual framework by comparing the Green City to sustainable cities. This initial step allows us to precisely define the contours and specific objectives of each concept, laying the groundwork for our comparative analysis. Next, we conduct a comprehensive analysis to explore how the Green City can contribute in a targeted manner to achieving sustainable development goals. By integrating these different approaches, our goal is to substantially advance knowledge and practices in sustainable urban planning, as well as the creation of more resilient and environmentally friendly cities.
Some Applications of Dynamical Belyi Polynomials
Authors: Anderson Jacqueline , Manes Michelle , Tobin Bella 
Published: July 2024

AbstractWe give necessary and sufficient conditions for post-critically finite polynomials to have persistent bad reduction at a given prime. We also answer in the negative a pair of questions posed by Silverman about conservative polynomials. Our proofs rely on conservative dynamical Belyi polynomials as exemplars of PCF (resp. conservative) maps.
Tail variance and confidence of using tail conditional expectation: Analytical representation, capital adequacy, and asymptotics
Authors: Duan Jun , Landsman Zinoviy , Yao Jing 
Published: July 2024

AbstractIn this paper, we explore the applications of Tail Variance (TV) as a measure of tail riskiness and the confidence level of using Tail Conditional Expectation (TCE)-based risk capital. While TCE measures the expected loss of a risk that exceeds a certain threshold, TV measures the variability of risk along its tails. We first derive analytical formulas of TV and TCE for a large variety of probability distributions. These formulas are useful instruments for relevant research works on tail risk measures. We then propose a distribution-free approach utilizing TV to estimate the lower bounds of the confidence level of using TCE-based risk capital. In doing so, we introduce sharpened conditional probability inequalities, which halve the bounds of conventional Markov and Cantelli inequalities. Such an approach is easy to implement. We further investigate the characterization of tail risks by TV through an exploration of TV’s asymptotics. A distribution-free limit formula is derived for the asymptotics of TV. To further investigate the asymptotic properties, we consider two broad distribution families defined on tails, namely, the polynomial-tailed distributions and the exponential-tailed distributions. The two distribution families are found to exhibit an asymptotic equivalence between TV and the reciprocal square of the hazard rate. We also establish asymptotic relationships between TCE and VaR for the two families. Our asymptotic analysis contributes to the existing research by unifying the asymptotic expressions and the convergence rate of TV for Student-t distributions, exponential distributions, and normal distributions, which complements the discussion on the convergence rate of univariate cases in [28]. To show the usefulness of our results, we present two case studies based on real data from the industry. We first show how to use conditional inequalities to assess the confidence of using TCE-based risk capital for different types of insurance businesses. Then, for financial data, we provide alternative evidence for the relationship between the data frequency and the tail categorization by the asymptotics of TV.
Revisiting Elevated δ13C Values of Sediment on Modern Carbonate Platforms
Authors: Trower Elizabeth J. , Hibner Brianna M. , Lincoln Tyler A. , Dodd Jacqueline E. , Hagen Cedric J. , Cantine Marjorie D. , Gomes Maya L. 
Published: July 2024

AbstractThe measured carbon isotopic compositions of carbonate sediments (δ13Ccarb) on modern platforms are commonly 13C‐enriched compared to predicted values for minerals forming in isotopic equilibrium with the dissolved inorganic carbon (DIC) of modern seawater. This offset undermines the assumption that δ13Ccarb values of analogous facies in the rock record are an accurate archive of information about Earth's global carbon cycle. We present a new data set of the diurnal variation in carbonate chemistry and seawater δ13CDIC values on a modern carbonate platform. These data demonstrate that δ13Ccarb values on modern platforms are broadly representative of seawater, but only after accounting for the recent decrease in the δ13C value of atmospheric CO2 and shallow seawater DIC due to anthropogenic carbon release, a phenomenon commonly referred to as the 13C Suess effect. These findings highlight an important, yet overlooked, aspect of some modern carbonate systems, which must inform their use as ancient analogs.