bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prognostic impact of fibrosclerotic changes in non-papillary, non-anaplastic, follicular cell-derived thyroid carcinomas
Authors: Orlando Giulia , Capella Giulia , Vocino Trucco Giulia , Vissio Elena , Metovic Jasna , Maletta Francesca , Volante Marco , Papotti Mauro 
Published: January 2025

Abstract
In non-papillary follicular cell-derived thyroid carcinomas, prognostic factors are scarce. Intratumoral fibrosis was identified as an adverse factor in papillary and medullary carcinomas, but it has not been investigated in other subtypes. We aimed at exploring the presence of intratumoral fibrosclerosis in a cohort of 132 non-papillary follicular cell-derived thyroid carcinomas (53 follicular and 31 oncocytic carcinomas, including 10 high grade differentiated thyroid carcinomas and 48 poorly differentiated carcinomas) and correlating its presence and extent with clinical and pathological features and survival. For each case, all available hematoxylin and eosin slides were reviewed, and the presence of fibrosclerosis was assessed as the percentage of tumor area and semi-quantitatively scored as absent, mild (≤ 10%) or extensive (> 10%). In addition, digital image analysis was applied in 65 cases. Scoring of intratumoral fibrosis showed a strong agreement between two observers and between observers and digital image quantification. The presence and extent of intratumoral fibrosis were significantly associated with poorly differentiated carcinoma histology, large tumor size, extent of vascular invasion, presence of necrosis, high mitotic index, positive nodal status, and aggressive clinical outcome, and with a shorter disease-free and disease-specific survival, the former also in follicular and oncocytic carcinomas analyzed separately. These data support the potential use of fibrosis in the clinical practice since it is both easily assessable and significantly associated with the presence of parameters of aggressiveness. In addition, fibrosis is correlated with decreased survival rate independently from the tumor histotypes, suggesting its potential role as novel prognostic factor in non-papillary follicular cell-derived thyroid carcinomas.
Set-Valued Recursions Arising from Vantage-Point Trees
Authors: Dong Congzao , Marynych Alexander , Molchanov Ilya 
Published: January 2025

Abstract
We study vantage-point trees constructed using an independent sample from the uniform distribution on a fixed convex body K in

$$(\mathbb {R}^d,\Vert \cdot \Vert )$$

(

R

d

,
‖
·
‖
)

, where

$$\Vert \cdot \Vert $$

‖
·
‖

is an arbitrary norm on

$$\mathbb {R}^d$$

R

d

. We prove that a sequence of sets, associated with the left boundary of a vantage-point tree, forms a recurrent Harris chain on the space of convex bodies in

$$(\mathbb {R}^d,\Vert \cdot \Vert )$$

(

R

d

,
‖
·
‖
)

. The limiting object is a ball polyhedron, that is, an a.s. finite intersection of closed balls in

$$(\mathbb {R}^d,\Vert \cdot \Vert )$$

(

R

d

,
‖
·
‖
)

of possibly different radii. As a consequence, we derive a limit theorem for the length of the leftmost path of a vantage-point tree.
Effects of surgical approach and downstaging in esophageal adenocarcinoma patients treated with neoadjuvant chemotherapy: a 2010–2020 National Cancer Database (NCDB) study
Authors: Canto Eduardo A. , Reilly Matthew , Hall Alexander , Walters Ryan W. , Nandipati Kalyana C. 
Published: January 2025

Abstract

Background
Neoadjuvant Chemoradiation (nCRT) has been shown to improve survival in patients with Esophageal Adenocarcinoma (EAC). The objective of this study is to assess the patient characteristics associated with tumor downstaging in a large national database. Additionally, we evaluated surgical approach and change in clinical versus pathological staging as predictors of patient survival.

Methods
Using the 2010–2020 National Cancer Database, we identified 6,400 patients with clinical stage 1B to 4A EAC who received nCRT and underwent esophagectomy. Multivariable logistic models were estimated to evaluate odds of downstaging, and complete downstaging. Multivariable marginal Cox proportional-hazard models were estimated to evaluate all-cause mortality hazard.

Results
3285 (51%) patients downstaged (of which 292 [5% of total] completely downstaged), 2430 (38%) had no change in stage, and 685 (11%) progressed. Generally, higher covariate values such as Clinical T, Clinical N, age, and Charlson-Deyo score were associated with higher odds of downstaging and lower odds of complete downstaging. Downstaging was associated with 31% lower risk of death compared to progression (p < .001) and 17% lower risk of death compared to no change (p < .001). Regarding surgical approach, when compared with open esophagectomy (OE), robotic-assisted minimally invasive esophagectomy (RAMIE) was associated with 17% lower adjusted risk of death (p = .002) while minimally invasive esophagectomy (MIE) was associated with a 10% decrease in adjusted risk of death (p = .009).

Conclusion
In patients with EAC who underwent nCRT, pathological downstaging was associated with increased survival compared to no change or progression. Additionally, RAMIE and MIE were associated with lower risk of death compared to OE.

Graphical Abstract
Wound Segmentation with U-Net Using a Dual Attention Mechanism and Transfer Learning
Authors: Niri Rania , Zahia Sofia , Stefanelli Alessio , Sharma Kaushal , Probst Sebastian , Pichon Swann , Chanel Guillaume 
Published: January 2025

Abstract
Accurate wound segmentation is crucial for the precise diagnosis and treatment of various skin conditions through image analysis. In this paper, we introduce a novel dual attention U-Net model designed for precise wound segmentation. Our proposed architecture integrates two widely used deep learning models, VGG16 and U-Net, incorporating dual attention mechanisms to focus on relevant regions within the wound area. Initially trained on diabetic foot ulcer images, we fine-tuned the model to acute and chronic wound images and conducted a comprehensive comparison with other state-of-the-art models. The results highlight the superior performance of our proposed dual attention model, achieving a Dice coefficient and IoU of 94.1% and 89.3%, respectively, on the test set. This underscores the robustness of our method and its capacity to generalize effectively to new data.
Nonlinear forecasting with many predictors using mixed data sampling kernel ridge regression models
Authors: Dai Deliang , Javed Farrukh , Karlsson Peter , Månsson Kristofer 
Published: January 2025

Abstract
Policy institutes such as central banks need accurate forecasts of key measures of economic activity to design stabilization policies that reduce the severity of economic fluctuations. Therefore, this paper develops a kernel ridge regression estimator in a mixed data sampling framework. Kernel ridge regression can handle many predictors with a nonlinear relationship to the target variable. Consequently, it has potential to improve the currently used principal component-based methods when the economic data follow a nonlinear factor structure. In a Monte Carlo study, we show that the kernel ridge regression approach is superior in terms of mean square error and is more robust than principal component-based methods to different nonlinear data generating processes. By using a dataset consisting of 24 economic indicators, we forecast Swedish gross domestic production. The results confirm the superiority of the kernel ridge regression approach. Therefore, we suggest that policy institutes consider the use of kernel-based approaches when forecasting key measures of economic activity.
Fake advertisements detection using automated multimodal learning: a case study for Vietnamese real estate data
Authors: Nguyen Duy , Nguyen Trung T. , Nguyen Cuong V. 
Published: January 2025

Abstract
The popularity of e-commerce has given rise to fake advertisements that can expose users to financial and data risks while damaging the reputation of these e-commerce platforms. For these reasons, detecting and removing such fake advertisements are important for the success of e-commerce websites. In this paper, we propose FADAML, a novel end-to-end machine learning system to detect and filter out fake online advertisements. Our system combines techniques in multimodal machine learning and automated machine learning to achieve a high detection rate. As a case study, we apply FADAML to detect fake advertisements on popular Vietnamese real estate websites. Our experiments show that we can achieve 91.5% detection accuracy, which significantly outperforms three different state-of-the-art fake news detection systems.
Modeling impairment of ionic regulation with extended Adaptive Exponential integrate-and-fire models
Authors: Depannemaecker Damien , Tesler Federico , Desroches Mathieu , Jirsa Viktor , Destexhe Alain 
Published: January 2025

Abstract
To model the dynamics of neuron membrane excitability many models can be considered, from the most biophysically detailed to the highest level of phenomenological description. Recent works at the single neuron level have shown the importance of taking into account the evolution of slow variables such as ionic concentration. A reduction of such a model to models of the integrate-and-fire family is interesting to then go to large network models. In this paper, we introduce a way to consider the impairment of ionic regulation by adding a third, slow, variable to the adaptive Exponential integrate-and-fire model (AdEx). We then implement and simulate a network including this model. We find that this network was able to generate normal and epileptic discharges. This model should be useful for the design of network simulations of normal and pathological states.
Development and Validation of the Satisfaction with the Intervention for Intimate Partner Violence Perpetrators Scale (SIIPVS)
Authors: Roldán-Pardo Manuel , Santirso Faraj A. , Tomás José Manuel , Gracia Enrique , Lila Marisol 
Published: January 2025

Abstract

Purpose
Although research in the intimate partner violence (IPV) field has significantly advanced in recent decades, important challenges remain in intervention effectiveness terms. Some authors point out that satisfaction with intervention could be an indicator of effectiveness. However, this variable has not been thoroughly explored in the scientific literature. This study aimed to develop and validate a scale to measure the satisfaction with the intervention of participants attending an intervention program for IPV perpetrators.

Methods
A panel of experts developed the Satisfaction with the Intervention for Intimate Partner Violence Perpetrators Scale (SIIPVS) items. A sample of 646 male perpetrators was employed. Exploratory and confirmatory factor analyses, and a reliability analysis, were conducted. Scale validity was examined in relation to other relevant variables to the intervention, such as recidivism, working alliance, motivation to change and state of change.

Results
The findings indicate that the factor structure with the best fit consisted of three factors: Satisfaction with the facilitators and program delivery, Satisfaction with the learning-process, and Satisfaction with the peer group. All the factors demonstrated adequate internal consistency. Participant satisfaction with various intervention elements was associated with the key variables of these interventions.

Conclusions
The validation analysis results indicated that the SIIPVS is a suitable scale to analyze the satisfaction of the participants attending an intervention program for IPV perpetrators due to its adequate psychometric properties. Understanding participant satisfaction could provide a more comprehensive approach to evaluate the effectiveness of these interventions.
Multi-professional healthcare teams, medical dominance, and institutional epistemic injustice
Authors: Bueter Anke , Jukola Saana 
Published: January 2025

Abstract
Multi-professional teams have become increasingly common in healthcare. Collaboration within such teams aims to enable knowledge amalgamation across specializations and to thereby improve standards of care for patients with complex health issues. However, multi-professional teamwork comes with certain challenges, as it requires successful communication across disciplinary and professional frameworks. In addition, work in multi-professional teams is often characterized by medical dominance, i.e., the perspective of physicians is prioritized over those of nurses, social workers, or other professionals. We argue that medical dominance in multi-professional teams can lead to institutional epistemic injustice, which affects both providers and patients negatively. Firstly, it codifies and promotes a systematic and unfair credibility deflation of the perspectives of professionals other than physicians. Secondly, it indirectly promotes epistemic injustice towards patients via leading to institutional opacity; i.e., via creating an intransparent system of credibility norms that is difficult to navigate. To overcome these problems, multi-professional teamwork requires institutional settings that promote epistemic equity of team members.
Root growth and biomass partitioning of nine juvenile Sahelian agroforestry tree species under drought and irrigation treatments
Authors: Gning Fatou , Jourdan Christophe , Marone Diatta , Ngom Daouda , Ræbild Anders 
Published: January 2025

Abstract

Background and aims
Root traits of tree species are of great importance for selection of trees in dry zone agroforestry systems. Climate models predict increased frequency and severity of drought in the Sahel but our understanding on the strategies of root growth of tree species under drought is limited. To increase our knowledge of species differences in rooting patterns we investigated root growth of nine dryland tree species in West Africa during one year when exposed to drought stress.

Methods
Seedlings were planted in 2 m tubes inserted into the soil and subjected to irrigation and drought (no irrigation during the dry season). After 4, 8 and 12 months, we assessed root growth and root biomass, supplemented with assessments of water potential, leaf phenology, and above-ground growth.

Results
Tree species showed significant differences in rooting profile. Drought induced deeper root growth, especially in deciduous species. Adansonia digitata, Sterculia setigera and Anacardium occidentale had shallow roots when irrigated. Acacia senegal, Acacia nilotica and Faidherbia albida had deeper root growth and showed clear differences in leaf water potential between treatments while A. digitata and S. setigera appeared to be water conserving under drought.

Conclusions
Our results link root growth with phenology, physiology and above-ground growth and provide an attempt to group dryzone tree species in functional types based on their root growth.
A Comprehensive Framework for Water Affordability Analysis
Authors: Fagundes T. S. , Marques R. C. , Malheiros T. F. 
Published: January 2025

Abstract
Water and sanitation affordability has emerged as a significant concern in recent years due to economic crises and the increasing reliance on tariffs to finance public services. Governments have often depended on inadequate affordability analyses, if any, to identify constraints faced by vulnerable families in accessing water supply and sanitation services. This paper proposes a comprehensive affordability analysis framework, considering six key dimensions: coverage rates, conventional affordability ratio, community poverty conditions, affordability ratio for poorer households, access to water social programs, and the burden of connection fees. The framework was applied to Brazil, focusing on its state-owned providers, which serve more than 70% of the population. The results demonstrate that the proposed framework offers a simple yet robust tool for decision-makers globally, with the flexibility to adapt to various contexts. The case study revealed that the Brazil’s conventional affordability ratio masks affordability issues faced by poorer families, along with low access to social tariffs, high incidence of poverty, and low coverage in several areas. These findings provide critical insights for stakeholders, enabling the development of targeted public policies and the design of appropriate subsidy mechanisms.
Efficient automatic estimation of soil constitutive model parameters via particle swarm optimization
Authors: Sakai Takayuki , Nakano Masaki 
Published: January 2025

Abstract
In this study, we automatically estimated the parameters of the modified Cam-Clay model, a representative constitutive model for soil. The estimation was carried out by minimizing the objective function using the dynamic multiswarm particle swarm optimization (DMS-PSO) algorithm, which is an improvement over the original PSO. The objective function was newly defined by quantifying the discrepancy between the targeted results and the model calculations in q-p′-v space. DMS-PSO divides particles into several islands to search globally and prevent local solutions, and even particles that fall into a local solution can be relocated. To evaluate the automatic estimation performance of DMS-PSO, we examined whether model parameters could be correctly estimated from the calculation results (Consideration (1)) and whether the DMS-PSO algorithm could consistently obtain the same parameter values when reproducing the experimental results (Consideration (2)). Regarding Consideration (1), the objective function was consistently smaller than 1.0 × 10–6 when the number of particles was greater than 400 and the number of islands was greater than 40. At this time, the parameter values could be estimated to the fifth decimal place. When two experiments were conducted, the estimation was obtained approximately 1.5 times faster than when only one was conducted. Regarding Consideration (2), the coefficient of variation of the parameters obtained from 100 estimations was at most 1%, and the parameter values were estimated to be approximately the same each time. In addition, narrowing the solution search range based on soil physical properties could reduce the variation in parameters by approximately 10%. Additionally, the parameters could be accurately estimated by data from at least two mechanical experiments.
Relationships Between Social Media Addiction, Social Media Use Metacognitions, Depression, Anxiety, Fear of Missing Out, Loneliness, and Mindfulness
Authors: Meynadier Jai , Malouff John M. , Schutte Nicola S. , Loi Natasha M. , Griffiths Mark D. 
Published: January 2025

Abstract
Recent research has suggested that metacognitions about social media use may play a role in social media addiction. The aim of the present study was to investigate (a) the contribution of positive and negative social media use metacognitions in explaining social media addiction after accounting for a range of risk factors related to negative affect and (b) the mediating roles of positive and negative social media use metacognitions in associating depression, anxiety, fear of missing out (FoMO), loneliness, and low trait mindfulness with social media addiction. A sample of 810 Australians (M
age = 66.39 years; 63.6% female) completed an anonymous online survey. Both positive and negative social media use metacognitions accounted for a significant proportion of unique variance in social media addiction after controlling for age, sex, social media engagement, depression, anxiety, FoMO, loneliness, and mindfulness. Serial mediation models indicated that depression, anxiety, FoMO, loneliness, and mindfulness had a direct effect on social media addiction, as well as an indirect effect that was mediated by positive and negative metacognitions. The present study’s findings show the mediating role of social media use metacognitions in the relationship between negative affect and social media addiction.
Weathering the Pain: Ambient Temperature’s Role in Chronic Pain Syndromes
Authors: Jevotovsky David S. , Oehlermarx Whitman , Chen Tommy , Ortiz Christopher Chiodo , Liu Annie , Sahni Sidharth , Kessler Jason L. , Poli Joseph J. , Lau Richard 
Published: January 2025

Abstract

Purpose of Review
Chronic pain is highly prevalent and involves a complex interaction of sensory, emotional, and cognitive processes, significantly influenced by ambient temperature. Despite advances in pain management, many patients continue to experience inadequate pain relief. This review aims to consolidate and critically evaluate the current evidence on the impact of ambient temperature on chronic pain conditions such as fibromyalgia (FM), multiple sclerosis (MS), complex regional pain syndrome (CRPS), and osteoarthritis (OA).

Recent Findings
Patients with FM often report pain exacerbations due to temperature changes, with studies showing lower thresholds for heat and cold-induced pain compared to healthy controls. In MS, the Uhthoff phenomenon, characterized by temperature-induced neurological deterioration, underscores the significance of ambient temperature in pain management. CRPS patients exhibit heightened pain sensitivity to temperature changes, with both warm and cold stimuli potentially aggravating symptoms. OA patients frequently report increased pain and rigidity associated with lower temperatures and higher humidity.

Summary
Understanding the mechanisms through which temperature influences pain can enhance pain management strategies. This review highlights the need for further research to elucidate these mechanisms and develop targeted interventions, ultimately improving the quality of life for individuals with chronic pain conditions.
Palliative Care Spiritual Assessment and Goals-of-Care Discussions in the Neurocritical Care Unit: Collaborating with Chaplains
Authors: Kestenbaum Allison , Gilchrist Danielle , Dunlop Brian C. 
Published: January 2025

Abstract

Introduction
Neuropalliative care is an emerging subspecialty of palliative care designed to address the unique supportive care needs of patients with serious neurological illness, including those receiving neurocritical care in intensive care units. Spiritual care is a vital component in the provision of holistic and humanized care to these patients. A chaplain who is specially trained and credentialed in care for those with serious illness is the health care professional responsible for making spiritual assessments and contributes to the plan of care, facilitating decision making, and guiding other clinicians in the provision of generalist spiritual care.

Methods
This article illustrates the role of chaplains in supporting neurocritical care patients and highlights two fundamental aspects of spiritual care: (1) spiritual screening/assessment and (2) assistance with goals-of-care conversations.

Results
These cases clarify the role of professionally trained and credentialed chaplains with experience in both neurocritical and palliative care and the value added to the interprofessional team.