bluuebunny/crossref_metadata_2025_split huggingface dataset:
An experimental survey of imbalanced learning algorithms for bankruptcy prediction
Authors: Gnip Peter , Kanász Róbert , Zoričak Martin , Drotár Peter 
Published: January 2025

Abstract
Information about imminent bankruptcy is crucial for financial institutions, decision-making managers, and state agencies. Since bankruptcy prediction is a prevalent research topic, many new methods have been continuously proposed. Bankruptcy prediction is frequently approached as a binary classification task. Since bankruptcy datasets are inherently imbalanced, bankruptcy classification is usually performed using class imbalance learning methods. The nature of these methods is very diverse, but they can usually be categorized as ensemble, cost-sensitive, sampling, and hybrid methods. In this paper, we provide a comprehensive experimental comparison of 45 methods. These methods were selected because they cover the approaches and algorithms frequently employed for bankruptcy prediction and imbalanced learning. Extensive experiments on 15 publicly available datasets with different imbalance ratios showed that the methods based on a combination of ensemble learning and undersampling are able to handle data imbalance and achieve the best results for bankruptcy classification.
Ability of dynamic chest radiography to identify left ventricular systolic dysfunction in heart failure
Authors: Hiraiwa Hiroaki , Nagai Shin , Ito Ryota , Kondo Kiyota , Kazama Shingo , Kondo Toru , Adachi Shiro , Furusawa Kenji , Tanaka Akihito , Morimoto Ryota , Okumura Takahiro , Murohara Toyoaki 
Published: January 2025

Abstract
Dynamic chest radiography (DCR) can estimate haemodynamic parameters in heart failure (HF). However, no studies have evaluated its ability to determine cardiac systolic function in HF. This experimental study investigates the correlation between left ventricular (LV) ejection fraction (LVEF) and DCR image parameters in HF. Ninety-one patients with acute HF (median age, 58 years; males, 75%) (cardiologist diagnosis using the Framingham criteria) underwent DCR and transthoracic echocardiography after treatment for the uncompensated phase of HF. The LV apex pixel value (PV) change was measured by DCR. Correlations between the PV change and LVEF, as well as sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of DCR, were evaluated. LVEF and LV apex PV change were correlated in all patients (R = 0.428, P < 0.001) and in patients with LVEF < 50% (n = 38; R = 0.355, P = 0.029), < 40% (n = 31; R = 0.343, P = 0.059), and < 30% (n = 23; R = 0.321, P = 0.135). There was no significant correlation for patients with LVEF ≥ 50% (n = 53; R = − 0.004, P = 0.980). The LV apex PV change rate cutoff values for identifying LVEF < 50%, < 40%, and < 30% were 9.3% (AUC: 0.761, sensitivity: 0.698, specificity: 0.789, P < 0.001), 5.5% (AUC: 0.765, sensitivity: 0.883, specificity: 0.645, P < 0.001), and 5.5% (AUC: 0.767, sensitivity: 0.838, specificity: 0.696, P < 0.001), respectively. DCR may be useful to identify LV systolic dysfunction based on LVEF in acute HF.

Graphical abstract
An Effective Investments System in the Optimal Portfolio Selection Intelligence (OPSI)
Authors: Loukeris Nikolaos , Eleftheriadis Iordanis , Livanis Efstratios 
Published: January 2025

Abstract
The optimal portfolio selection problem is investigated in fundamentals of higher order moments. The returns behavior frequently skewed and in excess kurtosis, along with investors’ preferences set new grounds of discussion. Higher order moments, than the kurtosis, will offer further information on investors. A more complex problem arises, of higher flexibility, non-convexity, in unlimited scale fitted to portfolio optimization. The principal problem of Free Will is thus answered, with emphasis on investors. We discuss the OPSI model introducing three hybrid neuro-genetic models of numerous topologies and one regression. Firstly the Radial Basis Function Networks-RBF are in 40 hybrid forms and 10 RBF Neural Nets whilst the results are compared to 50 Time-Lag Recurrent Network-TLRN Hybrids topologies, 10 on the MultiLayer Perceptron-MLP Neural Nets, and the Bayesian Logistic Regression-BLR, to define the most competitive methods in asset allocation and corporate evaluation. New solutions are offered under specific hybrids whilst portfolio efficiency is either evolutionary or intelligent. Introducing the parameters of financial health, we propose the advanced expected utility function filtering noise. The problem of wealth maximisation is transformed to a preferential combination on gain and loss. The TLRN hybrid networks are a very efficient and reliable model on portfolio selection. The OPSI model offers a competitive approach in efficient portfolio selection, protecting the investor from systematic exposure. In the investors Free Will problem, the answer is that Logic is dynamic linearly but adjusting to the environment overrides new challenges of superior potentials than the linear series of events. It is consistent to the maximisation of utility and investors’ welfare.
The use of ICT in classrooms: The effect of the pandemic
Authors: Pérez Echeverría María del Puy , Cabellos Beatriz , Pozo Juan-Ignacio 
Published: January 2025

Abstract
Although various studies advocate for the integration of information and communication technologies in education, the forced digitization caused by the pandemic has yielded contradictory results on student learning. Conversely, research has shown that when students manage ICT, they achieve better learning outcomes but when teacher-centered approaches are employed, their effects on learning tend to be negative. Has the pandemic crisis served to promote or hinder the integration of ICT in classrooms? Have the uses of ICT changed? This article focuses on whether changes after the mandatory use of ICT in classrooms during the pandemic have favored the integration of digital technologies in classrooms. The analysis of these results has not only practical implications but also theoretical, since they allow us to test the influence of different variables on the change in teaching conceptions and practices. 731 primary and secondary Spanish teachers responded to a questionnaire investigating the frequency with which they used ICT in their classrooms, the type of use they made, and the learning outcomes they promoted. The results showed that teachers reported a higher use of ICT than in previous periods. Also, similar to studies before and during the pandemic, these results indicated a higher frequency of teacher-centered activities, mainly oriented towards the transmission of verbal content. However, this effect seems to have been moderated after the pandemic. There were, however, different teacher profiles reflecting different styles in the educational use of ICT. A critical variable for making student-centered use of ICT seems to be the frequency of use. Those teachers more familiar with ICT tended to make more complex and varied uses, suggesting that their inclusion in teacher training should be an essential step to promote the integration of ICT in classrooms.
Personalization capabilities of current technology chatbots in a learning environment: An analysis of student-tutor bot interactions
Authors: Looi Chee-Kit , Jia Fenglin 
Published: January 2025

Abstract
Since the advent of chatbots enabled by Generative AI such as ChatGPT, their application in the domain of education has been linked to promises of personalizing learning (PL). Through a study of conversational interactions of graduate students with such chatbots, this paper provides an empirical study of how current ChatGPT technologies can enable PL. We introduce a framework of levels of PL affordances enabled by the current state of ChatGPT technology. The case study uses multi-methods to analyze graduate student interactions with a ChatGPT tutor bot in discussions about the topic of educational reforms. Tutoring conversations of 51 students with the tutor bot are collected, and then analyzed to probe whether and how ChatGPT creates an individualized growth area for students, tailoring interactions to individual needs and supporting students to have a deeper understanding of the topic. This study contributes to the limited body of research on the evidence-based application of Generative AI to PL.
Assessing the speed of individual bacteria dispersing on mycelial networks
Authors: Buffi Matteo , Kuhn Thierry , Gonzalez Diego , Bindschedler Saskia , Chain Patrick S. , Richter Xiang-Yi Li , Junier Pilar 
Published: January 2025

Abstract
The movement of bacteria on the hyphae of fungi and other mycelial-forming organisms is an important process that determines their ability to actively disperse in water-unsaturated habitats. However, direct observation and characterization of bacterial cell movement on mycelial networks have been difficult to achieve. In this study, we developed a new method that uses high-speed video recording to track the dispersal of individual fluorescently tagged cells of two closely related strains of Pseudomonas putida (UWC1 and KT2440) over the mycelial network of the oomycete Pythium ultimum. We found high intra-population heterogeneity and between-population differences in dispersal speeds for the two bacterial strains. The fitting of the speed distribution functions led to the separation of speeds into two ranges (fast/slow) at an intersection of the fitted curves. In the lower speed range, the UWC1 strain dispersed faster, while the KT2440 strain moved faster in the higher speed range. This finding helps explain conflicting competition outcomes revealed in previous studies and suggests that population mean speed alone does not capture key aspects of bacterial dispersal in mycelial networks. Our new method opens the possibility of studying bacterial dispersal, competition, and other social interactions in spatially heterogeneous environments, such as soils.
Feature selection for high-dimensional data using a multivariate search space reduction strategy based scatter search
Authors: Garcia-Torres Miguel 
Published: January 2025

Abstract
In feature selection, the increasing of the dimensionality and the complexity of feature interactions make the problem challenging. Furthermore, searching for an optimal subset of features from a high-dimensional feature space is known to be an

$$\mathcal{N}\mathcal{P}$$

N
P

-hard problem. To improve the efficiency and effectiveness of the search algorithm, feature grouping has emerged as a way to reduce the search space by clustering features according to a measure. In this work we propose to reduce the search space by applying a greedy algorithm, called Multivariate Greedy Predominant Groups Generator (MGPGG). MGPGG extends the idea of the Greedy Predominant Groups Generator (GPGG) algorithm by taking into account feature interaction among three or more features. For this purpose, MGPGG uses the Multivariate Symmetrical Uncertainty (MSU) to group features that share information about the class label. We also propose a Scatter Search strategy that integrates MGPGG to find small subsets of features with high predictive power. The proposed algorithm, called Multivariate Predominant Group-based Scatter Search (MPGSS), is tested on high-dimensional data from biomedical and text-mining fields. The proposal is compared with state-of-the-art feature selection strategies. Results show that MPGSS is competitive since it is capable of finding small subsets of features while keeping high predictive classification models.
Left atrial shunting devices: why, what, how, and… when?
Authors: De Lorenzo Leila Anna , Baratto Claudia , Sala Davide , Perego Giovanni Battista , Caravita Sergio 
Published: January 2025

Abstract
Left atrial (LA) hypertension is central in the pathophysiology of heart failure (HF) in general and of HF with preserved ejection fraction (HFpEF) in particular. Despite approved treatments, a number of HF patients continue experiencing disabling symptoms due to LA hypertension, causing pulmonary congestion, pulmonary hypertension, and right heart dysfunction, at rest and/or during exercise. LA decompression therapies, i.e., left atrial shunting through a specifically designed device (either implant-based or implant-free), are being studied in various forms of HF to alleviate LA hypertension and patients’ symptoms. Despite a solid background and favorable signals from initial non-randomized clinical trials, the quest for the optimal HF candidate for interatrial shunt devices is still an area of active research that at the same time is helping to better elucidate the intricate pathophysiology of HF(pEF).
“When People Reach Out that is When They’re Desperate”: Understanding Informal and Formal Help-Seeking Practices for Gambling among Aboriginal Peoples in the Northern Territory, Australia
Authors: Gupta Himanshu , Tari-Keresztes Noemi , Aanundsen David , Smith James A. 
Published: January 2025

Abstract
This study provides an in-depth qualitative exploration of Aboriginal peoples’ experiences with seeking help for gambling-related issues in the Northern Territory (NT), Australia. Through semi-structured interviews with 29 participants, including regular and occasional gamblers as well as those affected by others’ gambling, the research highlights key barriers to seeking formal help. These barriers included the normalisation of gambling within Aboriginal communities, denial of gambling problems, feelings of shame, privacy concerns, and a lack of trust in mainstream services. Additionally, past negative experiences with services, fear of judgment, and logistical challenges, such as long waiting times and transportation difficulties in remote areas, contributed to the low uptake of professional services. Instead, informal support from family and friends was occasionally sought, reflecting the collectivist nature of Aboriginal cultures. Participants also reported employing self-help strategies and offered practical suggestions for minimising gambling harm. This research underscores the complexity of gambling behaviours within Aboriginal communities and the cultural, social, and systemic factors that deter access to formal support services. It calls for the integration of Indigenous knowledge and practices into gambling prevention and intervention programs, which may improve the relevance and effectiveness of these strategies. By addressing both cultural norms and access barriers, such targeted approaches may reduce the need for reactive interventions and better support the health and wellbeing of Aboriginal people affected by gambling in the NT. To improve relevant policies and practices, we also consider these findings to contribute to the broader Indigenous-specific gambling prevention evidence-base contexts nationally and globally.
Development of Attention-based Prediction Models for All-cause Mortality, Home Care Need, and Nursing Home Admission in Ageing Adults in Spain Using Longitudinal Electronic Health Record Data
Authors: Carrasco-Ribelles Lucía A. , Cabrera-Bean Margarita , Khalid Sara , Roso-Llorach Albert , Violán Concepción 
Published: January 2025

Abstract
Predicting health-related outcomes can help with proactive healthcare planning and resource management. This is especially important on the older population, an age group growing in the coming decades. Considering longitudinal rather than cross-sectional information from primary care electronic health records (EHRs) can contribute to more informed predictions. In this work, we developed prediction models using longitudinal EHRs to inform resource allocation. In this study, we developed deep-learning-based prognostic models to predict 1-year and 5-year all-cause mortality, nursing home admission, and home care need in people over 65 years old using all the longitudinal information from EHRs. The models included attention mechanisms to increase their transparency. EHRs were drawn from SIDIAP (primary care, Catalonia (Spain)) from 2010-2019. Performance on the test set was compared to that from baseline models using cross-sectional one-year history only. Data from 1,456,052 individuals over 65 years old were considered. Cohen’s kappa obtained using longitudinal data was 3.4-fold (1-year all-cause mortality), 10.3-fold (5-year all-cause mortality), 1.1-fold (5-year nursing home admission), and 1.2-fold (5-year home care need) higher than that obtained by the one-year history baseline models. Our models performed better than those not considering longitudinal data, especially when predicting further into the future. However, nursing home admission and home care need in the long term were harder to predict, suggesting their dependence on more abrupt changes. The attention maps helped to understand the predictions, enhancing model transparency. These prediction models can contribute to improve resource allocation in the general population of aging adults.
High-Level Moving Excursions for Spatiotemporal Gaussian Random Fields with Long Range Dependence
Authors: Leonenko Nikolai , Ruiz-Medina M. Dolores 
Published: January 2025

Abstract
The asymptotic behavior of an extended family of integral geometric random functionals, including spatiotemporal Minkowski functionals under moving levels, is analyzed in this paper. Specifically, sojourn measures of spatiotemporal long-range dependence (LRD) Gaussian random fields are considered in this analysis. The limit results derived provide general reduction principles under increasing domain asymptotics in space and time. The case of time-varying thresholds is also studied. Thus, the family of morphological measures considered allows the statistical and geometrical analysis of random physical systems displaying structural changes over time. Motivated by cosmological applications, the derived results are applied to the context of sojourn measures of spatiotemporal spherical Gaussian random fields. The results are illustrated for some families of spatiotemporal Gaussian random fields displaying complex spatiotemporal dependence structures.
Plasticity and neoplasticity in Malabou's the future of Hegel: addressing the concept’s ambiguity
Authors: Quiñonez Omar 
Published: January 2025

Abstract
The influence of Catherine Malabou’s concept of plasticity has grown considerably. However, recent commentaries increasingly trace disagreements in the literature to Malabou’s own ambiguous uses of the concept. This paper weaves together these criticisms and places them in the Hegelian context out of which Malabou developed her views. Plasticity is Malabou’s argument for reimagining Hegel’s Aufhebung as a non-teleological view of change in which the “suppleness” of material plays an important role. As presented in The Future of Hegel, Malabou lays out her view of plasticity through the very Hegelian process of aufheben she is actively rethinking. Original lessons about change drawn from examples of material transformation are developed into an ontology of “becoming.” I argue that the charge of ambiguity in the literature stems from the lack of appreciation of this move from limited examples to novel ontology, something Malabou later acknowledged. I suggest distinguishing between plasticity and what I call “neoplasticity.” The former refers to concrete examples of material change, inspired by the plastic arts, in which the role of material suppleness is explicit. The latter refers to cases of transformation in which the role of malleability in the process of change is implicit and requires being considered in light of her ontology of non-teleological change.
Restoration and reactivation approaches in computer music and time-based media art
Authors: Russo Alessandro , Fiordelmondo Alessandro , Franceschini Andrea , Canazza Sergio 
Published: January 2025

Abstract
This paper presents the work carried out by the Centro di Sonologia Computazionale (CSC) of the University of Padua, regarding the reactivation and preservation of time-based media artworks, including computer music, live electronics, performances, and multimedia art installations. During the last few years, the CSC has been developing a specific approach for archiving, documenting, and reactivating time-based media artworks, which led to the definition of the Multilevel Dynamic Preservation (MDP) model. Through in-depth analysis, various approaches are examined in the reactivation of several case studies, including digitisation, restoration, migration, and virtualisation of the artworks. The selected case studies involve various forms of art expression, such as video art, computer music, expanded cinema, and interactive performance. This contribution offers a comprehensive overview of the challenges encountered in the process of reactivating and preserving multimedia art, investigating the possible solutions offered by new technologies in preserving, digitising and virtualizing some of its forms, such as multimedia installations, expanded cinema, and video art performances.
Induced Orthogonality in Semilattices with 0 and in Pseudocomplemented Lattices and Posets
Authors: Chajda Ivan , Kolařík Miroslav , Länger Helmut 
Published: January 2025

Abstract
On an arbitrary meet-semilattice

$$\textbf{S}=(S,\wedge ,0)$$

S
=
(
S
,
∧
,
0
)

with 0 we define an orthogonality relation and investigate the lattice

$${{\,\mathrm{{\textbf {Cl}}}\,}}({\textbf {S}})$$

Cl

(
S
)

of all subsets of S closed under this orthogonality. We show that if

$$\textbf{S}$$

S

is atomic then

$${{\,\mathrm{{\textbf {Cl}}}\,}}(\textbf{S})$$

Cl

(
S
)

is a complete atomic Boolean algebra. If

$$\textbf{S}$$

S

is a pseudocomplemented lattice, this orthogonality relation can be defined by means of the pseudocomplementation. Finally, we show that if

$$\textbf{S}$$

S

is a complete pseudocomplemented lattice then

$${{\,\mathrm{{\textbf {Cl}}}\,}}(\textbf{S})$$

Cl

(
S
)

is a complete Boolean algebra. For pseudocomplemented posets a similar result holds if the subset of pseudocomplements forms a complete lattice satisfying a certain compatibility condition.
Sheehan syndrome: a current approach to a dormant disease
Authors: Karaca Zuleyha , Kelestimur Fahrettin 
Published: January 2025

Abstract
Sheehan syndrome (SS) is postpartum pituitary necrosis leading to severe hypopituitarism. Severe bleeding during delivery and postpartum period results in ischemic necrosis of the enlarged pituitary gland during pregnancy. The improved obstetrical care decreased the incidence of SS significantly, however SS should always be kept in mind in the etiologies of hypopitutarism in women which can be easily recognized by medical history of the patient. The nonspecific signs and symptoms of hypopituitarism result in significant delay in diagnosis and treatment. The diagnostic delay makes the patients to expose hypopituitarism without essential replacement therapies leading to increased morbidity and mortality of the patients. Awareness of physicians about SS is critical for the diagnosis of the disease. In this review, the epidemiology, pathophysiology, clinical manifestations and treatment of SS are discussed in the light of recent studies.