bluuebunny/crossref_metadata_2025_split huggingface dataset:
No benefit of antidepressants in inpatient treatment of depression. A longitudinal, quasi-experimental field study
Authors: Maß Reinhard , Backhaus Kerstin , Lohrer Katharina , Szelies Michael , Unkelbach Bodo K. 
Published: August 2023

Abstract
Rationale
Antidepressants (AD) are mostly considered indispensable for the treatment of major depression. The vast majority of depressive inpatients are treated with AD. However, there is a growing body of studies indicating that the effectiveness of AD is greatly overestimated due to methodological issues with the AD efficacy studies (e.g., publication bias, unintentional unblinding, confusion between withdrawal symptoms and relapse).

Objectives
The benefit of the additional use of AD in the inpatient treatment of depression with intensive cognitive-behavioral therapy (CBT) has been investigated in a naturalistic design.

Methods
Depressiveness was assessed using the Beck Depression Inventory (BDI-II) during a preliminary interview (T0), at admission (T1), at discharge (T2), and at a 6-month follow-up (T3). Two study phases were compared: During Phase A, AD were recommended in accordance with the German guideline. In Phase B, AD were no longer recommended, and they were only prescribed upon explicit request from patients. In phase A (N = 574), 60.3% of all patients were taking AD at discharge. In Phase B (N = 424), 27.9% of patients were on AD at discharge. Apart from the difference in AD usage, the two treatment conditions were similar, and the samples did not significantly differ in terms of age, sex, diagnoses, history of suicide attempts, comorbid anxiety disorders, and unemployment.

Results
In both study phases, BDI-II scores were strongly decreased at T2 and T3, respectively, compared with T1. The BDI-II scores of the two phases did not differ at any of the measurement time points. Depression changes were similar in both phases. In sequential multiple regression analyses with the total sample, AD were no significant predictors for the reduction of depression at either T2 or T3.

Conclusions
The inpatient CBT was effective in depression. The effectiveness of CBT is not improved by the additional use of AD. The current prescribing practices of AD should be questioned.
A cross-sectional study on Chinese oncology nurses’ knowledge of bone health among cancer patients
Authors: Shan Jing , Lv Sumei , Chen Lu , Li Tianhua , Li Jingwen , Wang Shuangyan , Zhang Congcong 
Published: August 2023

Abstract
Objective
To understand the knowledge status, obstacle factors, and management confidence of oncology nurses on the bone health of cancer patients, and in addition to provide reference for establishing bone health knowledge training system for oncology nurses and guiding them to manage bone health of cancer patients.

Methods
A total of 602 nurses engaged in oncology nursing in 6 hospitals in Hebei Province were selected by cluster sampling, and an online anonymous survey was conducted by sending questionnaires to oncology nurses from the Hebei Cancer Prevention and Control Association. The questionnaire was developed by the study team. There are 4 parts, namely general information, nurses’ role and job responsibilities, knowledge of skeletal-related events (SREs) and cancer treatment–induced bone loss (CTIBL), and understanding and confidence in bone health management, for a total of 33 questions.

Results
Thirty-seven percent of oncology nurses received training on bone health and other related contents; 40.48% of oncology nurses used domestic and foreign guidelines when managing patients with bone metastases or CTIBL. Only approximately one-third of oncology nurses had confidence in managing the side effects of bone metastases and bone modification drugs and identifying patients at risk of CTIBL and fracture; only 33.04% of oncology nurses believed that weight-bearing exercise can prevent bone loss; less than 50% of oncology nurses believed that aromatase inhibitor therapy, ovarian suppression therapy, androgen deprivation therapy, and low body weight were risk factors for pathological fractures. The reasons that hindered oncology nurses from optimizing the management of patients with bone metastases and understanding the preventive measures and risk factors for bone loss mainly included lack of relevant knowledge training, lack of understanding of effective intervention measures, and lack of training and professionalism of specialized nurses, including insufficient development time and guidelines for clinical nursing practice.

Conclusion
Managers must continuously improve the training system of oncology nurses, enrich the content of training pertaining to bone health for cancer patients, formulate clinical nursing practice guidelines, and give oncology nurses more time for professional development.
Statistical modeling of three-dimensional redox architecture from non-colocated redox borehole and transient electromagnetic data
Authors: Wang Lijing , Kim Hyojin , Hansen Birgitte , Christiansen Anders V. , Vilhelmsen Troels N. , Caers Jef 
Published: August 2023

AbstractAgricultural nitrate pollutants infiltrate into the subsurface and contaminate groundwater. The redox environment in the subsurface is important for the natural removal of nitrate by denitrification. Detailed knowledge of the redox conditions is needed in order to make better-targeted nitrogen regulations for farmers. However, unveiling three-dimensional (3D) redox architectures is challenging because one only observes redox conditions in boreholes. Therefore, this work proposes a combination of towed transient electromagnetic resistivity (tTEM) geophysical surveys and redox boreholes to model 3D redox architecture stochastically. The tTEM survey reveals the geological structure in high resolution. However, the tTEM survey and redox boreholes are often non-colocated. To address this issue, geostatistical simulations are performed to generate multiple resistivity data colocated with redox boreholes. Then, a statistical learning method, namely multinomial logistic regression, is leveraged to predict multiple 3D redox architectures given the uncertain surrounding resistivity structures. In this way, the aggregated prediction of multiple redox architectures has a higher prediction accuracy than a redox prediction model with interpolated resistivity. The trained statistical model can also identify significant resistivity structures for redox predictions. An inverse problem has also been formulated to better match the redox borehole data. In summary, the proposed workflow models 3D resistivity and redox architecture jointly, aggregates to a highly accurate redox architecture, and provides important resistivity structures for domain experts. The highly accurate redox architecture supports a better agricultural regulation decision.
Probabilistic reconstruction via machine-learning of the Po watershed aquifer system (Italy)
Authors: Manzoni Andrea , Porta Giovanni Michele , Guadagnini Laura , Guadagnini Alberto , Riva Monica 
Published: August 2023

AbstractA machine-learning-based methodology is proposed to delineate the spatial distribution of geomaterials across a large-scale three-dimensional subsurface system. The study area spans the entire Po River Basin in northern Italy. As uncertainty quantification is critical for subsurface characterization, the methodology is specifically designed to provide a quantitative evaluation of prediction uncertainty at each location of the reconstructed domain. The analysis is grounded on a unique dataset that encompasses lithostratigraphic data obtained from diverse sources of information. A hyperparameter selection technique based on a stratified cross-validation procedure is employed to improve model prediction performance. The quality of the results is assessed through validation against pointwise information and available hydrogeological cross-sections. The large-scale patterns identified are in line with the main features highlighted by typical hydrogeological surveys. Reconstruction of prediction uncertainty is consistent with the spatial distribution of available data and model accuracy estimates. It enables one to identify regions where availability of new information could assist in the constraining of uncertainty. The comprehensive dataset provided in this study, complemented by the model-based reconstruction of the subsurface system and the assessment of the associated uncertainty, is relevant from a water resources management and protection perspective. As such, it can be readily employed in the context of groundwater availability and quality studies aimed at identifying the main dynamics and patterns associated with the action of climate drivers in large-scale aquifer systems of the kind here analyzed, while fully embedding model and parametric uncertainties that are tied to the scale of investigation.
Kinetic Energy Budget in Turbulent Flows of Dilute Polymer Solutions
Authors: Serafini Francesco , Battista Francesco , Gualtieri Paolo , Casciola Carlo Massimo 
Published: August 2023

AbstractDirect numerical simulation of a turbulent pipe flow of a realistic solution of $$10^8$$

10
8

polymers, modelled as finitely extensible nonlinear elastic (FENE) dumbbells, and directly momentum coupled with the incompressible Navier–Stokes equations, are performed by means of an Eulerian-Lagrangian approach. Besides the drag reduction, the polymers significantly modify mean and turbulent kinetic energy budgets. The polymer backreaction to the solvent reduces the Reynolds stress and thus decreases the turbulent production and, at large Weissenberg number, the polymers act as a source of turbulent kinetic energy for $$y^+> 40$$

y
+

>
40

, leading to an increase in the dissipation. This effect is peculiar to large Weissenberg polymers and it is particularly apparent at a small Reynolds number. At a smaller Weissenberg number, the effect of the polymers remains confined in the buffer layer, with the kinetic energy budget not significantly altered elsewhere.
What is meant by scientific literacy in the curriculum? A comparative analysis between Bolivia and Chile
Authors: Norambuena-Meléndez Mariela , Guerrero Gonzalo R. , González-Weil Corina 
Published: August 2023

AbstractScientific literacy is still being identified and recognised as one of the main goals of science education. However, this concept has multiple interpretations and its definition changes continuously depending on its social, cultural, and political contexts. In this paper, scientific literacy is conceptualised through visions I, II and III. The first one is focused on the content and scientific processes for its subsequent application; the second, with a focus on understanding the usefulness of scientific knowledge in life and society; and the third one seeks to move towards a politicised scientific education to dialogic emancipation, attending social and eco-justice dimensions. The latter is also called critical scientific literacy. The research aimed at analysing how scientific literacy and these three visions are expressed in school curricula of Bolivia and Chile. Using a qualitative approach and thematic analysis, it is established that the Bolivian curriculum presents mainly a critical scientific literacy approach and the Chilean science curriculum presents mainly a vision II of scientific literacy. Findings of contrasting both school curricula show science education as non-neutral and profoundly political field, and therefore, we can see relevant opportunities for transformation and emancipation, understanding science curriculum as a social practice.
Subjective Well-being of Children Left Behind by Migrant Parents in Six European Countries
Authors: Bălțătescu Sergiu , Strózik Tomasz , Soo Kadri , Kutsar Dagmar , Strózik Dorota , Bacter Claudia 
Published: August 2023

AbstractThis paper presents a cross-national comparison of the influence of parental migration on children’s subjective well-being (SWB). While studies often focus on the economic implications of adult migration, research on its effects on children’s well-being is scarce, particularly in Europe. Data from surveys of over 13,500 school children in six European countries with a communist legacy were analysed. These were collected as part of Children’s Worlds - The International Study of Children’s Well-being (ISCWeB). The findings reveal that left-behind children generally have lower levels of SWB than non-left-behind children, with girls being more affected, and the gap in well-being increases with age. Left-behind status was also associated with lower family and school satisfaction. A hierarchical logistic regression model was used to explore the role of parental migration and family and school life satisfaction in predicting high SWB of children. While including family and school life satisfaction in the model weakened the association between parental migration and child SWB, the models’ explanatory power improved. This study emphasizes the need for further research in this area to better understand the complex dynamics between parental migration, children’s subjective well-being, and other factors. These insights are essential for developing targeted interventions and policies to support the well-being of left-behind children in migrant sending countries.
Is There Still a Policy Agenda for EU Copyright Law?
Authors: Sganga Caterina 
Published: August 2023

AbstractAlmost two decades after the last landmark act of EU copyright harmonization (InfoSoc Directive, 2001/29/EC), and after a number of narrow, targeted interventions on specific topics, the EU legislator has issued another historical directive touching key pillars of copyright law (2019/790/EU, CDSMD). It is still too early to evaluate the impact this act will have on the digital single market of protected works and the balance between conflicting interests at stake. However, commentators have already highlighted its strengths and flaws, underlined challenges and problems still affecting the system, and advanced specific reform proposals and, more generally, EU copyright law that have still remained unaddressed. This revived debate, also triggered by the interplay between EU copyright and the new regulatory interventions on platform regulation and the data economy, stand in stark contrast with the disappearance of copyright from the Union’s legislative agenda, which will likely be the case for some years to come. Building on the current state of the harmonization in the field, this Opinion maintains that a pressing EU copyright policy agenda still exists, and proposes a number of recommendations for future regulatory actions.
An Opportunity to See the Heart Defect Physically: Medical Student Experiences of Technology-Enhanced Learning with 3D Printed Models of Congenital Heart Disease
Authors: Luxford Jack C. , Cheng Tegan L. , Mervis Jonathan , Anderson Jennifer , Clarke Jillian , Croker Sarah , Nusem Erez , Bray Liam , Gunasekera Hasantha , Scott Karen M. 
Published: August 2023

AbstractThree-dimensional (3D) printing is increasingly used in medical education and paediatric cardiology. A technology-enhanced learning (TEL) module was designed to accompany 3D printed models of congenital heart disease (CHD) to aid in the teaching of medical students. There are few studies evaluating the attitudes and perceptions of medical students regarding their experience of learning about CHD using 3D printing. This study aimed to explore senior medical students’ experiences in learning about paediatric cardiology through a workshop involving 3D printed models of CHD supported by TEL in the form of online case-based learning. A mixed-methods evaluation was undertaken involving a post-workshop questionnaire (n = 94 students), and focus groups (n = 16 students). Focus group and free-text questionnaire responses underwent thematic analysis. Questionnaire responses demonstrated widespread user satisfaction; 91 (97%) students agreed that the workshop was a valuable experience. The highest-level satisfaction was for the physical 3D printed models, the clinical case-based learning, and opportunity for peer collaboration. Thematic analysis identified five key themes: a variable experience of prior learning, interplay between physical and online models, flexible and novel workshop structure, workshop supported the learning outcomes, and future opportunities for learning using 3D printing. A key novel finding was that students indicated the module increased their confidence to teach others about CHD and recommended expansion to other parts of the curriculum. 3D printed models of CHD are a valuable learning resource and contribute to the richness and enjoyment of medical student learning, with widespread satisfaction.
Rotation-equivariant transformer for oriented person detection of overhead fisheye images
Authors: Zhou You , Bai Yong , Chen Yongqing 
Published: August 2023

AbstractOverhead fisheye images can be used for person detection in intelligent monitoring systems. Unlike horizontal images, people in fisheye cameras are generally distributed in any orientation. When the object is rotated, the feature maps from convolutional neural networks have nonlinear variations and lose many orientation features. Transformer can learn the orientation relationship between features. However, a transformer cannot directly extract orientation features and the effectiveness of detecting small objects needs to be improved. In this paper, We propose a novel rotation-equivariant transformer backbone network, which combines group-equivariant convolution with swin transformer to solve these problems. In our proposed model, the rotation-equivariant feature map extracted by group-equivariant convolution contains a large number of orientation features in multiple directions. Aggregates feature in different directions to enhance the communication of orientation features before computing window self-attention. We propose the equivariant-group relation module for evaluating the similarity of the equivariant-group and calculating the aggregation weights. Our network architecture for multi-level receptive field structure can expand the local receptive field to enhance the detection of small objects. The experiments validate that our model achieves state-of-the-art performance on fisheye image datasets MW-R, HABBOF, and CEPDOF. Compared with the swin transformer, the accuracy of our model is improved by 0.3$$\%$$
%
, 0.5$$\%$$
%
, and 1.3$$\%$$
%
, and the accuracy of small object detection in the CEPDOF dataset is improved by 0.73$$\%$$
%
.
Diagonals Separating the Square of a Continuum
Authors: Illanes Alejandro , Martínez-de-la-Vega Verónica , Martínez-Montejano Jorge M. , Michalik Daria 
Published: August 2023

AbstractA metric continuum X is indecomposable if it cannot be put as the union of two of its proper subcontinua. A subset R of X is said to be continuumwise connected provided that for each pair of points $$p,q\in R$$

p
,
q
∈
R

, there exists a subcontinuum M of X such that $$\{p,q\}\subset M\subset R$$

{
p
,
q
}
⊂
M
⊂
R

. Let $$X^{2}$$

X
2

denote the Cartesian square of X and $$\Delta $$
Δ
the diagonal of $$X^{2}$$

X
2

. Recently, H. Katsuura asked if for a continuum X, distinct from the arc, $$X^{2}\setminus \Delta $$

X
2

\
Δ

is continuumwise connected if and only if X is decomposable. In this paper, we show that no implication in this question holds. For the proof of the non-necessity, we use the dynamical properties of a suitable homeomorphism of the Cantor set onto itself to construct an appropriate indecomposable continuum X.
Some Conditions Concerning the Shape Operator of a Real Hypersurface in Complex Projective Space
Authors: Pérez Juan de Dios , Pérez-López David 
Published: August 2023

AbstractLet M be a real hypersurface of a complex projective space. For any operator B on M and any nonnull real number k, we can define two tensor fields of type (1,2) on M, $$B_F^{(k)}$$

B
F

(
k
)

and $$B_T^{(k)}$$

B
T

(
k
)

. We will classify real hypersurfaces in complex projective space for which $$B_F^{(k)}$$

B
F

(
k
)

and $$B_T^{(k)}$$

B
T

(
k
)

either take values in the maximal holomorphic distribution $$\mathbb {D}$$
D
or are parallel to the structure vector field $$\xi $$
ξ
, in the particular case of $$B=A$$

B
=
A

, where A denotes the shape operator of M. We also introduce the concept of $$A_F^{(k)}$$

A
F

(
k
)

and $$A_T^{(k)}$$

A
T

(
k
)

being $$\mathbb {D}$$
D
-recurrent and classify real hypersurfaces such that either $$A_F^{(k)}$$

A
F

(
k
)

or $$A_T^{(k)}$$

A
T

(
k
)

are $$\mathbb {D}$$
D
-recurrent.
Approach to provide interpretability in machine learning models for image classification
Authors: Stadlhofer Anja , Mezhuyev Vitaliy 
Published: August 2023

AbstractOne of the main reasons why machine learning (ML) methods are not yet widely used in productive business processes is the lack of confidence in the results of an ML model. To improve the situation, interpretability methods may be used, which provide insight into the internal structure of an ML model, and criteria, based on which the model makes a certain prediction. This paper aims to consider the state of the art in interpretability methods and apply the selected methods to an industrial use case. Two methods, called LIME and SHAP, were selected from the literature and next implemented in the use case for image classification using a convolutional neural network. The research methodology consists of three parts, the first is the literature analysis, followed by the practical implementation of an ML model for image classification and the subsequent application of the interpretability methods, and the third part is a multi-criteria comparison of selected LIME and SHAP methods. This work enables companies to select the most effective interpretability method according to their use case and also to increase companies’ motivation for using ML.