bluuebunny/crossref_metadata_2025_split huggingface dataset:
Antipredator behaviour in semi-feral horses: innate response and the influence of external factors
Authors: Bercy Antoine , Ceacero Francisco , Komárková Martina 
Published: February 2025

Abstract
Rewilding can play a vital role in safeguarding biodiversity, with the grazing pressure exerted by large ungulates and controlled by their predators being a significant factor, particularly in European contexts. Domestic horses are becoming integral to such ungulates’ biomass, but they may differ from truly wild species due to their domesticated origin. This raises concerns about whether feral horses retain adequate antipredator behaviours, especially in the presence of expanding, large predators like wolves. The field of antipredator behaviour research is hampered by inconsistent results and a lack of standardisation, and the behaviour of free-ranging horses remains underexplored. To address this gap, we conducted a playback experiment on semi-feral Exmoor ponies (n = 97) in the Czech Republic, exposing them to wolf howls, deer rut calls, and static noise as a control. We assessed alert behaviour and herd grouping while accounting for variables such as herd size, sex, time of day, weather conditions, environment type, presence of other ungulates, and habituation effects. Over 70% of the ponies exhibited alert behaviour in response to both wolf and deer calls. Although the magnitude of responses did not differ significantly between wolf and deer calls, both elicited distinct reactions compared to the control. Most of the studied external factors significantly affected the observed alert responses, highlighting that they must be carefully considered in such studies since these may explain the conflicting results observed in previous studies. The significant behavioural differences in reaction to the sounds indicate that the horses can differentiate them and likely still possess some innate memory, as reported in other ungulates. This is a positive sign towards reintroduction. Future research should carefully consider the validity of the testing environment, habituation effects, and other external factors to ensure robust results.
Recent developments in waterborne pathogen detection technologies
Authors: Feleni Usisipho , Morare Rebotiloe , Masunga Ginny S. , Magwaza Nontokozo , Saasa Valentine , Madito Moshawe J. , Managa Muthumuni 
Published: February 2025

Abstract
Waterborne pathogens find their way into water bodies through contamination of fecal discharge, stormwater run-offs, agriculture and industrial activities, and poor water infrastructure. These organisms are responsible for causing diarrheal, gastroenteritis, cholera, and typhoid diseases which raise an alarming sense on public human health due to the high mortality rate, especially in children. Several studies have indicated that these waterborne diseases can be managed by monitoring pathogens in water using traditional culture-based and molecular techniques. However, these methods have shown several setbacks such as the longer duration for detection and the inability to detect pathogens at low concentrations. Effective management of these diseases requires rapid, sensitive, highly selective, fast, and efficient economic methods to monitor pathogens in water. Since the creation of biosensors, these tools have been applied and shown the ability to detect pathogens at low concentrations. The highlights of biosensor systems are that they are fast, portable, easy to use, highly sensitive, and specific. The capabilities of biosensors have given these tools exposure to be widely applied in detecting pharmaceutical pollutants, pesticides, toxins, residues of detergents, and cosmetics from household activities in soil and water. With such difficulties faced for detecting waterborne pathogens, this review evaluates the effectiveness of technologies for waterborne pathogens detection and their drawbacks. It further highlights biosensors as the current reliable method available for detecting pathogens in water and its future capabilities in sustaining safe potable water.
Does financial development influence environmental quality? Evidence from emerging and developing countries
Authors: Elatroush Ibrahim 
Published: February 2025

Abstract
This study aims to explore the link between financial development (FD) and economic growth on environmental quality in 60 developing and emerging countries over the period 1980–2021. Before assessing the employed model, the CDS, slope heterogeneity, and CIPS tests are performed for the study variables. Afterwards, the Pooled Mean Group and panel quantile regression techniques are carried out. The countries were clustered to assess the impact of FD and the study variables on environmental quality, as measured by CO2 emissions. Additionally, the Dumitrescu-Hurlin panel causality test was performed. The findings revealed a positive relationship between variables and CO2 in some clusters, which contributed to greater environmental degradation. In contrast, in other clusters, there was a significant negative relationship existed between study variables and CO2 emissions, which helped to mitigate of environmental damage. The discrepancy in results between groups can be related to differences in income levels, development patterns, production technologies, FD scores, and other socioeconomic characteristics between countries. The study underlines the crucial role of policymakers, authorities, and financial institutions in achieving the 2030 sustainable development goals (SDGs) 7, 11, 12, and 13 to improve the environmental quality in developing and emerging countries. It recommends that policies and strategies be undertaken to promote environmentally friendly products, eliminate polluting activities, embrace eco-friendly manufacturing technologies, and increase the use of bioenergy and renewable energy while reducing nonrenewable energy use. Policymakers, authorities, civic society, and financial institutions must all take responsibility for ensuring the proposals' successful implementation.
The ABC Model of Positive Feelings: A Preliminary Test
Authors: Tiba Alexandru , Drugaș Marius , Sîrbu Ioana , Simona Trip , Bora Carmen , Miclăuș Daiana , Voss Laura , Sanislav Ioana , Ciurescu Daniel 
Published: February 2025

Abstract
According to the ABC model of positive feelings, responding to positive activating events with irrational beliefs will result in dysfunctional positive feelings. Evidencing the role of irrational beliefs in dysfunctional positive feelings may have important clinical implications. However, no study has tested this model. Here, we tested the ABC model of positive feelings based on the REBT model of emotion. 115 participants had to imagine eight anticipatory positive situations. Then they reported how vividly they imagined the situations, and what they would believe and feel if they were in each situation. After that, they completed a hypomania scale, a general measure of positive irrational beliefs, and a general measure of irrational beliefs about adverse events. Results showed that situational positive primary irrational beliefs mediate the effect of vividness of imagining positive situations on dysfunctional positive feelings (b = 2.436, 95% CI: LL = 1.314 to UL = 3.832) while situational preferences mediated the effect of positive events on functional positive feelings (b = 0.642, 95% CI: LL = 0.165 to UL = 1.209). Moreover, the effect of positive primary irrational beliefs on dysfunctional positive feelings was mediated by secondary positive irrational beliefs such as positive intolerance (b = 3.826, 95% CI: LL = 0. 370; to UL = 7.740), and extreme self-valuing (b = 1. 330, 95% CI: LL = 0.287 to UL = 2.471) but not by wonderfulizing (b = 0.061, 95% CI: LL = −3.337 to UL = 3.298). Finding support for the ABC model of positive feelings and showing the role of irrational beliefs in dysfunctional and functional positive feelings may advance existing treatments for promoting mental health and reducing the disturbances of positive emotions.
Predictors of favorable long-term outcomes in first-line surgery for microprolactinomas
Authors: Andereggen Lukas , Christ Emanuel 
Published: February 2025

Abstract

Purpose
Opting for first-line surgery in carefully selected patients with microprolactinomas provides the advantage of avoiding long-term dopamine agonist (DA) medication and potential associated side effects. However, the lack of comprehensive long-term data poses a challenge in identifying those patients who would benefit the most from upfront surgery. To improve guidance in the selection process for microprolactinoma patients in clinical practice, we aimed to establish simple clinical and biochemical parameters predicting non-dependence on DAs.

Methodology
Retrospective analysis of a prospectively maintained database, focusing on patients with microprolactinomas who underwent upfront surgery. We assessed clinical and biochemical risk factors for the patients’ reliance on DAs at their latest follow-up using regression analysis. We next proceeded to conduct Receiver Operating Characteristic (ROC) analysis to determine the optimal threshold cutoff prolactin (PRL) level for practical application in clinical settings that best differentiates between surgical long-term remission status and long-term dependence on DAs.

Results
A microadenoma was observed in 46 patients, of whom 12 (26%) exhibited long-term dependence on DAs at a median follow-up of 78 months. Baseline PRL values were significantly higher in patients with long-term DA dependence compared to those without (p = 0.05). High baseline PRL values (HR 23.9, 95% CI 1.0-593.7, p = 0.05), but not the presence of headache or male gender, were identified as independent predictors of long-term dependence on DAs. PRL thresholds for discriminating long-term DA dependence were estimated to be 290 µg/L (AUROC = 0.73, 95% CI 0.55–0.92, p = 0.03; sensitivity = 90%, specificity = 80%).

Conclusions
In patients with microprolactinomas, first-line surgery presents a favorable prospect for reducing reliance on DAs. However, for those with high PRL levels ≥ 290 µg/L at diagnosis, first-line surgery is not recommended, as the majority of them require adjuvant DA therapy in the long term.
Dietary phytochemical indole-3-carbinol regulates metabolic reprogramming in mouse prostate tissue
Authors: Peter Rebecca Mary , Sarwar Md. Shahid , Wang Lujing , Chou Pochung , Wang Chao , Wang Yujue , Su Xiaoyang , Kong Ah-Ng 
Published: February 2025

Abstract

Purpose
Indole-3-carbinol (I3C) is shown to possess multiple pharmacological activities such as anti-inflammatory, antimicrobial, antioxidant, antiviral, and anti-cancer activities. It is widely accepted as modulator of multiple signaling pathways particularly those related to cell cycle, cell growth and division, angiogenesis, apoptosis and immunity. We explored the metabolic reprogramming based on treatment with I3C in mice prostate tissue.

Methods
In this study we utilized Pten knockout (KO)-induced prostate tumorigenesis mouse model to examine mechanism of action of I3C via metabolic rewiring. Phosphatase and tensin homolog deleted on chromosome 10 (Pten), a tumor suppressor gene is frequently found to be mutated or deleted in prostate cancer. Untargeted metabolomics was performed using liquid-chromatography mass-spectrometry (LC–MS) based platform to investigate Pten-dependent and Pten-independent metabolic targets of I3C.

Results
The most impacted pathways by I3C included pyrimidine metabolism, arginine and proline metabolism, porphyrin metabolism, citrate cycle and lipoic acid metabolism.

Conclusion
These pathways taken together help in understanding the overall health beneficial effects of I3C.
Examining Mathematics Teachers Noticing the Rationality: Scenario-Based Training with AI Chatbot
Authors: Galiç Selen , Urhan Selin , Dost Şenol , Lavicza Zsolt 
Published: February 2025

Abstract
It is essential that students are encouraged to become rational thinkers for building thinking classrooms. Teachers must adopt rational questioning techniques to facilitate the development of rational behaviours in their students. However, the implementation of rational questioning requires the ability to respond to students based on their performance, thereby requiring teacher noticing in the context of rationality. In this study, we adopt teacher noticing in the context of three components of rationality (epistemic, teleological, and communicative) and demonstrate the potential of ChatGPT to monitor teachers’ noticing the rationality. In this context, we conducted scenario-based training with three in-service mathematics teachers using ChatGPT. Participants were presented with a scenario involving a common difficulty related to the concept of slope and were asked to engage in an interactive session with ChatGPT. We then conducted individual interviews to gain insight into their noticing the rationality. Our findings clearly pointed to a tendency among the teachers to focus on the epistemic and teleological aspects of ChatGPT’s response, with no engagement in communicative decision-making. ChatGPT provided the opportunity to determine the cases in which the teacher could not attend and interpret the rationality and decide for rational questioning. Based on these findings, we suggest that ChatGPT could be used as a tool for monitoring teacher noticing the rationality in teacher education.
Percutaneous laser ablation vs. radical nephroureterectomy: a comparative study on renal pelvic tumors
Authors: Li Gao , Chen Yuanhao , Zhang Xin 
Published: February 2025

Abstract

Purpose
To compare the safety and efficacy of percutaneous laser ablation and radical nephroureterectomy for renal pelvic tumors.

Methods
This prospective cohort study included 30 patients diagnosed with renal pelvic tumors who met the established selection criteria. The cohort was divided into two groups: Group I, consisting of 15 patients who underwent percutaneous laser ablation, and Group II, comprising 15 patients who received radical nephroureterectomy. Comprehensive data collection encompassed demographic information, intraoperative and postoperative outcomes, and disease-free survival.

Results
The analysis revealed that percutaneous laser ablation offered modest benefits over radical nephroureterectomy in terms of reduced surgical duration (P < 0.01) and shorter hospital stays (P = 0.03). However, in evaluating long-term oncologic outcomes, percutaneous laser ablation did not achieve parity with radical nephroureterectomy. Although the differences in long-term outcomes were not statistically significant (HR: 0.48; 95% CI 0.05–4.92, P = 0.54), radical nephroureterectomy exhibited a slight advantage in disease-free survival.

Conclusion
Percutaneous laser ablation presents a safe and effective, less invasive treatment alternative, rendering it a feasible option for patients who are either unable or unwilling to undergo radical nephroureterectomy due to comorbid conditions or personal preferences.
An artificial intelligence-supported GFCA learning model to enhance L2 students’ role-play performance, English speaking and interaction mindset
Authors: Darmawansah Darmawansah , Hwang Gwo-Jen , Lin Chi-Jen , Febiyani Febiyani 
Published: February 2025

Abstract
Role-play tasks have long been used by researchers and practitioners to observe L2 (Second language) speaking performance. This social-situated simulation allows students to employ their language skills to converse about real-life themes. While role-plays are highly plausible to actively engage students in interactive learning environments, it has been challenging to determine whether students perform at an adequate level of speaking proficiency with an appropriate learning approach. Nevertheless, the emerging technology-supported role-play tasks employing AI (artificial intelligence) could enhance competencies, enabling students to perform better in role-plays. Therefore, to enhance and support students’ performance in role-plays, English speaking skills, and their interaction mindset, we integrated an AI-based speaking learning app in the Generalization, Formulation, Correction, Appreciation (AI-GFCA) learning model. A quasi-experiment was conducted in a university with a total of 45 students. One class was randomly assigned to apply the AI-GFCA learning model as the experimental group, while the other was the control group (AI-C). The findings indicated that the AI-GFCA learning model could significantly enhance students’ role-play performance, English speaking skills, and interaction mindset. Furthermore, students produced fewer L2 errors and perceived a better learning experience than the AI-C group. It is noted that with the support of AI learning speaking through role-play tasks, students received sufficient corrective feedback, which encouraged them to establish a positive and motivating learning interaction, thus benefiting their academic performance.
Multi-product Newsvendor problem with dynamic pricing: a decision interpolation approximation
Authors: Sprenkels Laura , Atan Zümbül , Adan Ivo 
Published: February 2025

Abstract
In this paper we present an approximation for the finite horizon, finite inventory multi-product dynamic pricing problem. We consider both price- and stock-out- based substitutions. The computation time of the optimal solution grows exponentially in the number of products, while computation time of the proposed approximation is linear in the number of products. We compare the approximation with existing methods.
Elevated vascular endothelial growth factor a is associated with disruption of default network connectivity in older adults
Authors: Kapoor Arunima , Jang Jung Yun , Engstrom Allison C. , Lohman Trevor , Dutt Shubir , Alitin John Paul M. , Sible Isabel J. , Marshall Anisa , Shenasa Fatemah , Gaubert Aimee , Nguyen Amy , Bradford David Robert , Rodgers Kathleen , Han S. Duke , Nation Daniel A. 
Published: February 2025

Abstract
Vascular Endothelial Growth Factor A (VEGF-A) is an angiogenic signaling protein involved in the maintenance of the cerebral vasculature. No prior study has explored whether plasma VEGF-A levels may be associated with brain functional connectivity changes, such as disruption of the default mode network (DMN), which often precedes the development of cognitive changes in aging. Seventy-six independently living older adults (mean age = 70.3 years; SD = 7.5; 31.6% male) free of dementia or clinical stroke underwent venipuncture and brain MRI. Plasma was assayed for VEGF-A. Using resting state functional MRI, region of interest (ROI) to ROI connectivity and graph theory analysis were conducted to determine average connectivity and global efficiency between each of the following ROIs comprising the DMN: medial prefrontal cortex, lateral parietal cortex and precuneus cortex. Multiple linear regression analysis revealed a significant negative association between VEGF-A levels and DMN connectivity (B = − 0.14, 95% CI (-0.26, − 0.01), p =.038), accounting for age, sex, education, and vascular risk factors. Graph theory analysis similarly revealed that VEGF-A levels are associated with global efficiency of the entire network (B = − 0.18, p =.004). These findings suggest that VEGF-A may be elevated early in the progression of neurocognitive disorders. Whether higher levels of VEGF-A contribute to the pathogenesis of neurocognitive disorders or play a protective role in preserving cognitive function warrants further investigation. Clinical Trial Number: N/A; None.
Enhancing streamflow drought prediction: integrating wavelet decomposition with deep learning and quantile regression neural network models
Authors: Mohammadi Babak , Abdallah Mohammed , Oucheikh Rachid , Katipoğlu Okan Mert , Cheraghalizadeh Majid 
Published: February 2025

Abstract
Drought is a significant natural hazard that severely challenges water resource management and agricultural sustainability. This study aims to propose a novel approach for predicting streamflow drought indices (SDI-3, SDI-6, and SDI-12) in humid continental (Stockholm) and semi-arid (ELdiem) climates at different time-steps. The approach utilizes a Quantile Regression Neural Network (QRNN) coupled with wavelet decomposition (WD) techniques. Six mother wavelets (haar, sym8, coif5, bior6.8, demy, and db10) were used to decompose the SDI time series into different frequency bands, helping to identify patterns and trends in drought signals. The QRNN was compared with a tree-based machine learning (ML) model and two deep learning models: Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN). Results from stand-alone models showed that the LSTM model outperformed others in predicting SDI-3, while the QRNN model performed best in predicting SDI-6 and SDI-12 in both study regions. In the Stockholm station, the hybrid models achieved acceptable accuracy with bior6.8-LSTM2 (Nash–Sutcliffe efficiency (NSE) = 0.927), bior6.8-QRNN2 (NSE = 0.962), and demy-QRNN2 (NSE = 0.984) performing best for SDI-3, SDI-6, and SDI-12 predictions during the test phase, respectively. For the ELdiem station, the db10-QRNN3 (NSE = 0.926), demy-QRNN3 (NSE = 0.934), and demy-QRNN2 (NSE = 0.981) models demonstrated superior performance during the test phase in predicting SDI-3, SDI-6, and SDI-12, highlighting the robust capability of hybrid models across two case studies. The results indicate that combining WD with ML models can produce more accurate hydrological drought predictions than traditional models.
The Choice of Local or Imported Building Stone in English Medieval Churches; A South Cambridgeshire Case Study
Authors: Woodcock Nigel H. 
Published: February 2025

Abstract
External building stone has been recorded in 124 medieval churches in a 1200 km2 area in south Cambridgeshire, UK. Each component (e.g. walling, windows, doors) in each architectural part (e.g. tower, nave, aisles, chancel) of each church has been separately recorded, generating over 2000 records of construction or repair projects. Every project has been dated from documentary records or architectural style, allowing analysis of stone use in both space and time. The pre-Reformation churches of the area mostly have rubble walls of local Fieldstone and Clunch (Cretaceous Chalk), and imported Jurassic limestone from Barnack, 60 km to the northwest. Less common are ashlar walls of Clunch or Barnack. The medieval dressings clearly show the use of local Clunch in less exposed positions but of the weather-resistant imported Barnack stone for exposed locations. This use of Barnack was despite the transport costs for the circuitous inland waterway journey of about 110 km. The amount of imported Barnack stone in windows and doors is probably a good indicator of a church’s medieval wealth. Dressings of Clunch were much repaired or wholly replaced during the nineteenth century church ‘restorations.’ The replacement stone came mostly from the Jurassic Lincolnshire Limestone belt, not from Barnack but from other quarries along its outcrop from Weldon to Ancaster. The methodology of data collection, analysis and presentation in the Cambridgeshire study should prove useful for other heritage buildings nationally and internationally.