bluuebunny/crossref_metadata_2025_split huggingface dataset:
A molecular toolbox to study progesterone receptor signaling
Authors: Aarts Marleen T. , Wagner Muriel , van der Wal Tanne , van Boxtel Antonius L. , van Amerongen Renée 
Published: November 2023

AbstractProgesterone receptor (PR) signaling is required for mammary gland development and homeostasis. A major bottleneck in studying PR signaling is the lack of sensitive assays to measure and visualize PR pathway activity both quantitatively and spatially. Here, we develop new tools to study PR signaling in human breast epithelial cells. First, we generate optimized Progesterone Responsive Element (PRE)-luciferase constructs and demonstrate that these new reporters are a powerful tool to quantify PR signaling activity across a wide range of progesterone concentrations in two luminal breast cancer cell lines, MCF7 and T47D. We also describe a fluorescent lentiviral PRE-GFP reporter as a novel tool to visualize PR signaling at the single-cell level. Our reporter constructs are sensitive to physiological levels of progesterone. Second, we show that low background signaling, and high levels of PR expression are a prerequisite for robustly measuring PR signaling. Increasing PR expression by transient transfection, stable overexpression in MCF7 or clonal selection in T47D, drastically improves both the dynamic range of luciferase reporter assays, and the induction of endogenous PR target genes as measured by qRT-PCR. We find that the PR signaling response differs per cell line, target gene and hormone concentration used. Taken together, our tools allow a more rationally designed approach for measuring PR signaling in breast epithelial cells.
A Step Towards Absolute Versions of Metamathematical Results
Authors: Grabmayr Balthasar 
Published: November 2023

AbstractThere is a well-known gap between metamathematical theorems and their philosophical interpretations. Take Tarski’s Theorem. According to its prevalent interpretation, the collection of all arithmetical truths is not arithmetically definable. However, the underlying metamathematical theorem merely establishes the arithmetical undefinability of a set of specific Gödel codes of certain artefactual entities, such as infix strings, which are true in the standard model. That is, as opposed to its philosophical reading, the metamathematical theorem is formulated (and proved) relative to a specific choice of the Gödel numbering and the notation system. A similar observation applies to Gödel’s and Church’s theorems, which are commonly taken to impose severe limitations on what can be proved and computed using the resources of certain formalisms. The philosophical force of these limitative results heavily relies on the belief that these theorems do not depend on contingencies regarding the underlying formalisation choices. The main aim of this paper is to provide metamathematical facts which support this belief. While employing a fixed notation system, I showed in previous work (Review of Symbolic Logic, 2021, 14(1):51–84) how to abstract away from the choice of the Gödel numbering. In the present paper, I extend this work by establishing versions of Tarski’s, Gödel’s and Church’s theorems which are invariant regarding both the notation system and the numbering. This paper thus provides a further step towards absolute versions of metamathematical results which do not rely on contingent formalisation choices.
Natural language inference model for customer advocacy detection in online customer engagement
Authors: Abu-Salih Bilal , Alweshah Mohammed , Alazab Moutaz , Al-Okaily Manaf , Alahmari Muteeb , Al-Habashneh Mohammad , Al-Sharaeh Saleh 
Published: November 2023

AbstractOnline customer advocacy has developed as a distinctive strategic way to improve organisational performance by fostering favourable reciprocal affinitive customer behaviours between the business and its customers. Intelligent systems that can identify online social advocates based on their social interaction and long-standing conversations with the brads are still lacking. This study adds to the burgeoning body of literature in this research area by developing a novel model to identify brand advocates using natural language inference (NLI) and artificial intelligence (AI) approaches. In particular, a hybridised deep learning model (BERT-BiLSTM-TextCNN) is proposed and adept at extracting the amount of entailment, contradiction, and neutrality obtained from the advocates' replies to the brands. This offers a new dimension to identify advocates based on the semantic similarities between the brands’ tweets and customers’ replies. The experimental results demonstrate the applicability of integrating the advantages of fine-tuned BERT, TextCNN, and BiLSTM using various evaluation metrics. Further, the proposed model is incorporated in a downstream task to verify and validate its effectiveness in capturing the correlation between brands and their advocates. Our findings contribute to the burgeoning body of literature in this research area and have important implications for identifying and engaging with brand advocates in online customer engagement.
Targeted immunotherapy for glioblastoma involving whole tumor-derived autologous cells in the upfront setting after craniotomy
Authors: Andrews Carrie E. , Zilberberg Jenny , Perez-Olle Raul , Exley Mark A. , Andrews David W. 
Published: November 2023

Abstract
Purpose
To date, immunotherapeutic approaches in glioblastoma (GBM) have had limited clinical efficacy as compared to other solid tumors. Here we explore autologous cell treatments that have the potential to circumvent treatment resistance to immunotherapy for GBM.

Methods
We performed literature review and assessed clinical outcomes in phase 1 safety trials as well as phase 2 and 3 autologously-derived vaccines for the treatment of newly-diagnosed GBM. In one recent review of over 3,000 neuro-oncology phase 2 and phase 3 clinical trials, most trials were nonblinded (92%), single group (65%), nonrandomized (51%) and almost half were GBM trials. Only 10% involved a biologic and only 2.2% involved a double-blind randomized trial design.

Results
With this comparative literature review we conclude that our autologous cell product is uniquely antigen-inclusive and antigen-agnostic with a promising safety profile as well as unexpected clinical efficacy in our published phase 1b trial. We have since designed a rigorous double-blinded add-on placebo-controlled trial involving our implantable biologic drug device. We conclude that IGV-001 provides a novel immunotherapy platform for historically intransigent ndGBM in this ongoing phase 2b trial (NCT04485949).
Probabilistic mapping of life loss due to dam-break flooding
Authors: Maranzoni Andrea , D’Oria Marco , Rizzo Carmine 
Published: November 2023

AbstractAssessment of flood damage caused by dam failures is typically performed deterministically on the basis of a single preselected scenario, neglecting uncertainties in dam-break parameters, exposure information, and vulnerability model. This paper proposes a probabilistic flood damage model for the estimation of life loss due to dam-break flooding with the aim of overcoming this limitation and performing a more comprehensive and informative evaluation of flood risk. The significant novelty lies in the fact that the model combines uncertainties associated with all three components of risk: hazard, exposure, and vulnerability. Uncertainty in flood hazard is introduced by considering a set of dam-break scenarios, each characterized by different breach widths and reservoir levels. Each scenario is linked to a probability, which is assumed conditional on the dam-break event. Uncertainty in exposure is accounted for using dasymetric maps of the population at risk for two socio-economic states (representing business and non-business hours of a typical week), along with associated likelihood. Vulnerability to flooding is described through a well-established empirical hazard-loss function relating the fatality rate of the population at risk to the flood hazard, the flood severity understanding, and the warning time; a confidence band provides quantitative information about the associated uncertainty. The probabilistic damage model was applied to the case study of the hypothetical collapse of Mignano concrete gravity dam (northern Italy). The main outcome is represented by probabilistic flood damage maps, which show the spatial distribution of selected percentiles of a loss-of-life risk index coupled with the corresponding uncertainty bounds.
Comparative study of rainfall measurement by optical disdrometer, tipping-bucket rain gauge, and weighing precipitation gauge
Authors: Ro Yonghun , Chang Ki-Ho , Hwang Hyunjun , Kim Minhoo , Cha Joo-Wan , Lee Chulkyu 
Published: November 2023

AbstractIn this study, the rainfall measurement characteristics of an optical particle size velocity (Parsivel) disdrometer, tipping-bucket rain gauge (TBG), and Pluvio weighing precipitation gauge (WPG) were analyzed and compared. Correlation analysis was performed between the 10-min and 1-h rainfall data observed with the Parsivel, TBG, and Pluvio from 2010 to 2019 at the Cloud Physics Observation Site which is located in northeast area of South Korea (N37.6869, E128.7586). At higher rainfall intensities, the Parsivel observed more rainfall; however, the TBG lost more rainfall during observation. The correlation between the Pluvio and Parsivel data was higher than that between the TBG and Parsivel data. Additionally, the Pluvio showed reduced loss in the rainfall observation than that by the TBG. The correlation between the Pluvio and TBG data was the highest, and the coefficient of determination increased by a maximum of 42.08% for 1-h rainfall compared to that for 10-min rainfall. Therefore, the Pluvio can generate relatively accurate rainfall data for water resource utilization.
Delivering mindset interventions to teachers as an efficient way to leverage the impact of mindset interventions
Authors: Combette Léa Tân , Rotgé Jean-Yves , Darnon Céline , Schmidt Liane 
Published: November 2023

AbstractResearch in social psychology and education proposes that adopting a growth mindset of intelligence is an important mediator for the well-being and performance of students at school. As a consequence, wise interventions have been developed to target student mindsets and change their beliefs about how much their intelligence can grow with training and experience. However, the efficacy of mindset interventions is highly debated, as effect sizes vary widely across studies. Here, we hypothesized that the study environment and, in particular, the teacher’s mindset about intelligence is an important moderator of mindset intervention efficacy. We tested this hypothesis by randomly assigning six middle schools from underprivileged neighborhoods in the Paris area in France to a no intervention condition, a condition with mindset interventions delivered only to the students, and a condition with mindset interventions for teachers and students. The results show that the combined teacher and student mindset intervention condition was the most efficient for increasing the student’s growth mindset. This finding suggests that a short and easy-to-implement mindset intervention for teachers can help students develop a growth mindset.
Fostering knowledge integration through individual competencies: the impacts of perspective taking, reflexivity, analogical reasoning and tolerance of ambiguity and uncertainty
Authors: Vogel Olga , Hunecke Marcel 
Published: November 2023

AbstractThe present study examines the influence of individual competencies on knowledge integration in inter- and transdisciplinary work. Perspective taking, reflexivity, analogical reasoning, and tolerance of ambiguity and uncertainty were investigated as core competencies for fostering knowledge integration. Additional hypotheses assumed that the positive effects are valid in the scientific and economic contexts and that individual competencies predict knowledge integration at different levels of expertise. To test the hypotheses, 421 participants, comprised of students (N = 165) and individuals working in science (N = 152) and economics (N = 104), answered questionnaires on knowledge integration and competencies of knowledge integration in an online survey. Further questions collected demographic data and inquired about experience and expertise in inter- and transdisciplinary work. The main result was that all postulated competencies positively related to knowledge integration. Analogical reasoning and perspective taking showed the strongest relationships with knowledge integration. Further results show that all competencies are positively related to knowledge integration in the student and expert sample, yet the interrelationships differ between the scientific and economic sample. This investigation into the competencies of knowledge integration contributes to the education of inter- and transdisciplinarians in academia and business practice.
Clinical Outcome Prediction of Early Brain Injury in Aneurysmal Subarachnoid Hemorrhage: the SHELTER-Score
Authors: Hofmann Björn B. , Donaldson Daniel M. , Neyazi Milad , Abusabha Yousef , Beseoglu Kerim , Hänggi Daniel , Cornelius Jan F. , Fischer Igor , Muhammad Sajjad 
Published: November 2023

Abstract
Background
Despite intensive research on preventing and treating vasospasm and delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage (aSAH), mortality and morbidity rates remain high. Early brain injury (EBI) has emerged as possibly the major significant factor in aSAH pathophysiology, emphasizing the need to investigate EBI-associated clinical events for improved patient management and decision-making. This study aimed to identify early clinical and radiological events within 72 h after aSAH to develop a conclusive predictive EBI score for clinical practice.

Methods
This retrospective analysis included 561 consecutive patients with aSAH admitted to our neurovascular center between 01/2014 and 09/2022. Fourteen potential predictors occurring within the initial 72 h after hemorrhage were analyzed. The modified Rankin Scale (mRS) score at 6 months, discretized to three levels (0–2, favorable; 3–5, poor; 6, dead), was used as the outcome variable. Univariate ordinal regression ranked predictors by significance, and forward selection with McFadden’s pseudo-R2 determined the optimal set of predictors for multivariate proportional odds logistic regression. Collinear parameters were excluded, and fivefold cross-validation was used to avoid overfitting.

Results
The analysis resulted in the Subarachnoid Hemorrhage Associated Early Brain Injury Outcome Prediction score (SHELTER-score), comprising seven clinical and radiological events: age (0–4 points), World Federation of Neurosurgical Societies (0–2.5 points), cardiopulmonary resuscitation (CPR) (2 points), mydriasis (1–2 points), midline shift (0.5–1 points), early deterioration (1 point), and early ischemic lesion (2 points). McFadden’s pseudo-R2 = 0.339, area under the curve for death or disability 0.899 and 0.877 for death. A SHELTER-score below 5 indicated a favorable outcome (mRS 0–2), 5–6.5 predicted a poor outcome (mRS 3–5), and ≥ 7 correlated with death (mRS 6) at 6 months.

Conclusions
The novel SHELTER-score, incorporating seven clinical and radiological features of EBI, demonstrated strong predictive performance in determining clinical outcomes. This scoring system serves as a valuable tool for neurointensivists to identify patients with poor outcomes and guide treatment decisions, reflecting the great impact of EBI on the overall outcome of patients with aSAH.
The mediating role of response-focused emotion regulation strategies in intimate partner violence across the stages of change
Authors: Puente-Martínez Alicia , Ubillos-Landa Silvia , Rovira Darío Páez 
Published: November 2023

AbstractIntimate partner violence against women is a pervasive and significant problem around the world that causes victims to suffer grave mental and physical health issues. The Stages of Change or SOC model has been used in recent study to examine the stage of change in female victims as a potential predictor of their readiness to end their relationship. This study's objective was to analyse emotion-focused coping strategies used by female victims to deal with emotions arising from trauma, violence or abuse, according to the SOC model. The sample comprised 200 victims of gender violence who had received formal assistance in Spain. The standardised test was administered in face–to-face interviews. According to the women's SOC, the findings showed differences in the use of emotion-focused coping strategies and indicated that emotion regulation efforts were greater in the early SOC- especially in precontemplation and action—of the continuum towards action. Emotion-focused coping strategies were activated to regulate either positive or negative emotions, again in accordance with participants’ stage of change, with negative affectivity predominating in the early stages (precontemplation and contemplation), and positive affectivity having a greater presence in the later ones (action and maintenance). A series of mediation analyses demonstrated that although negative emotions immobilise female victims in the precontemplation stage, they also facilitate effective coping in the action stage, thereby helping to reduce the emotional impact of violence.
Knowledge Management and Data Analysis Techniques for Data-Driven Financial Companies
Authors: Pisoni Galena , Molnár Bálint , Tarcsi Ádám 
Published: November 2023

AbstractIn today’s fast-paced financial industry, knowledge management and data-driven decision making have become essential for the success of financial technology (FinTech) companies. Big data (BD) is a prevalent phenomenon that can be found across many industries, including finance. Despite its complexity and difficulty to comprehend, big data is a critical component of financial services enterprises and technology architectures. We examine BD from various aspects, considering data science (DS) techniques and methodologies that can be applied during the operation of an enterprise. Our aim is to provide an overview of knowledge management (KM) practices and data analysis (DA) strategies and techniques in the daily operations of financial companies. We address the role of knowledge management, data analytics in a financial institution. The paper demonstrates financial institutions’ enablement for new services resulting from technological advancements.
Employment effects of the minimum wage: evidence from the Spanish 2019 reform
Authors: Gorjón Lucía , Martinez de Lafuente David , Romero Gonzalo 
Published: November 2023

AbstractWe examine the employment effects of the 2019 minimum wage increase in Spain on individual probabilities of losing employment status (extensive margin) and lowering work intensity (intensive margin). To do so, we use variation of workers’ exposure to the reform by comparing monthly employment transitions into unemployment and reductions in number of working hours between employees earning less than the minimum wage (treatment group) and those earning more and that should therefore be unaffected by the reform (control group). We find that the new minimum wage significantly increased the probability of experiencing unemployment (1.7 percentage points) and a reduction in work intensity (0.9 percentage points) for treated workers after one year. Our results suggest substantial heterogeneity by age, prior work intensity, economic sector and geographical region of employees affected by the reform.
The effects of anthropogenic toxins on honey bee learning: Research trends and significance
Authors: DesJardins Nicole S. , Harrison Jon F. , Smith Brian H. 
Published: November 2023

AbstractManaged honey bees are experiencing high rates of colony loss, in part due to widespread exposure to agrochemicals and other environmental toxins. The ability to learn about relevant environmental stimuli is an important skill necessary for foraging and navigation, although it is sometimes impaired in bees that have been exposed to toxins or other stressors. Here, we review the effects of anthropogenic toxins (which we divide into five major classes: insecticides, acaricides, biopesticides, other agrochemicals, and other toxins) on learning performance in European honey bees. We discuss the general trends of these studies, including that neurotoxic insecticides are overwhelmingly the most well-studied, and that most studies focus on acute exposure of individual, adult bees to a single toxin. Protocols for field-relevant exposure vary widely among labs, and we make suggestions to aid in the standardization of future studies. We review the relevance of learning studies for toxicological risk assessment, concluding that they are valuable tools for assessing sublethal behavioral effects of toxins. Their inclusion in risk assessment studies would be an improvement over current procedures, which focus largely on lethality.
On the Western reception of Prince Zhu Zaiyu’s music theory from the eighteenth to the twentieth century
Authors: Peng Bei 
Published: November 2023

AbstractThis article provides a case study of the historical process of the reception of an eminent aspect of pre-modern Chinese music theory in Western scholarship: The music-theoretical works of Zhu Zaiyu 朱载堉 (1536–1611), often considered as the greatest theorist in the history of Chinese music, are discussed in relation to their initial Western reception by Joseph-Marie Amiot, a Jesuit missionary who lived in China during the eighteenth century. It is shown how Amiot’s most important corresponding work, which still remains one of the basic texts for the study of Zhu Zaiyu in the West, initiated the reception of Zhu’s theoretical views in Europe, how it influenced and partly also misinformed the views mostly in German musicology from the late eighteenth century to the 1920s, and how the later and more progressive Anglophone Zhu Zaiyu studies from the 1960s to the 1980s emancipated themselves from this. Critical reflections on the Western history of the reception of Zhu’s thought and especially his understanding of the equal temperament system are included along the way and in the final section.
Self-organization of photoionized plasmas via kinetic instabilities
Authors: Zhang Chaojie , Huang Chen-Kang , Joshi Chan 
Published: November 2023

AbstractSelf-organization in an unmagnetized collisionless plasma (in this paper) refers to formation of transient coherent structures such as collective oscillations (electrostatic waves) or magnetic fields resulting from so-called kinetic effects in the plasma. This topical review provides a comprehensive analysis of the self-organization of strong-field photoionized, non-equilibrium plasmas through kinetic instabilities. The authors propose and demonstrate a novel experimental platform that enables the formation of dense plasmas with known highly anisotropic and non-thermal electron velocity distribution functions on a timescale on the order of an inverse electron plasma frequency. We then show that such plasmas are highly susceptible to a hierarchy of kinetic instabilities, including two-stream, current filamentation and Weibel, that convert a fraction of the electron kinetic energy into electric and/or magnetic energy stored in self-organized structures. The electrostatic waves so produced are measured using a collective light (Thomson) scattering technique with femtosecond resolution as the kinetic instabilities aided by collisions eventually thermalize the plasma electrons. In addition, we describe a novel experimental technique that has made it possible to map the temporal evolution of the wavenumber spectrum of the thermal Weibel instability with picosecond resolution, which leads to the formation of quasi-static coherent magnetic fields with different topologies in photoionized plasmas. Finally, the paper summarizes the important results and discusses future directions on this topic.