bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transition from hospital to nursing home: Discharge planners as a potential lever for quality improvements?
Authors: Kast Kristina , Carl Lukas 
Published: July 2024

Abstract
Background
Public reporting is supposed to be helpful in differentiating between well and poorly performing nursing homes; however, hospital patients often have difficulties to deal with quality information. Discharge planners (DP) can support them in comparing quality and, by influencing patients’ decision, lead to better provision of care in nursing homes.

Objective
This study investigated the choice behavior of DP, their use of quality information and the potential to impact the decision-making of patients.

Material and methods
A total of 70 DP from German hospitals with a geriatric department participated in an online survey. They were asked about information preferences and tools used for nursing home searches. In addition, they assessed quality information items from the new German quality reporting on a Likert scale. To test their comprehension participants were given a case scenario of a typical patient, were shown nursing homes displayed based on a medical comparison portal navigator (AOK-Pflegenavigator) and were asked to select nursing homes in a 3-round experiment.

Results
When looking for a nursing home, DP primarily rely on internal nursing home directories (n = 62; 92.5%). The 3 preferred criteria for decision are: distance to the family (n = 55; 28.80%), bed availability (n = 51; 26.7%) and wishes of patients/relatives (n = 41; 21.47%). The consent score for public reporting was 46.28% and the comprehension ratio was 82.24%.

Discussion
The DP do not advise hospital patients on the performance of nursing homes and rely on the decision-making of patients. This results in a lack of impact on patients’ decisions and consequently in a loss of potential for public reporting to lead to better care in nursing homes.
Regularized Stein Variational Gradient Flow
Authors: He Ye , Balasubramanian Krishnakumar , Sriperumbudur Bharath K. , Lu Jianfeng 
Published: July 2024

AbstractThe stein variational gradient descent (SVGD) algorithm is a deterministic particle method for sampling. However, a mean-field analysis reveals that the gradient flow corresponding to the SVGD algorithm (i.e., the Stein Variational Gradient Flow) only provides a constant-order approximation to the Wasserstein gradient flow corresponding to the KL-divergence minimization. In this work, we propose the Regularized Stein Variational Gradient Flow, which interpolates between the Stein Variational Gradient Flow and the Wasserstein gradient flow. We establish various theoretical properties of the Regularized Stein Variational Gradient Flow (and its time-discretization) including convergence to equilibrium, existence and uniqueness of weak solutions, and stability of the solutions. We provide preliminary numerical evidence of the improved performance offered by the regularization.
Macro-micro decomposition for consistent and conservative model order reduction of hyperbolic shallow water moment equations: a study using POD-Galerkin and dynamical low-rank approximation
Authors: Koellermeier Julian , Krah Philipp , Kusch Jonas 
Published: July 2024

AbstractGeophysical flow simulations using hyperbolic shallow water moment equations require an efficient discretization of a potentially large system of PDEs, the so-called moment system. This calls for tailored model order reduction techniques that allow for efficient and accurate simulations while guaranteeing physical properties like mass conservation. In this paper, we develop the first model reduction for the hyperbolic shallow water moment equations and achieve mass conservation. This is accomplished using a macro-micro decomposition of the model into a macroscopic (conservative) part and a microscopic (non-conservative) part with subsequent model reduction using either POD-Galerkin or dynamical low-rank approximation only on the microscopic (non-conservative) part. Numerical experiments showcase the performance of the new model reduction methods including high accuracy and fast computation times together with guaranteed conservation and consistency properties.
Assessment of bio-medical waste disposal techniques using interval-valued q-rung orthopair fuzzy soft set based EDAS method
Authors: Zulqarnain Rana Muhammad , Naveed Hamza , Askar Sameh , Deveci Muhammet , Siddique Imran , Castillo Oscar 
Published: July 2024

AbstractSelecting an optimum technique for disposing of biomedical waste is a frequently observed obstacle in multi-attribute group decision-making (MAGDM) problems. The MAGDM is commonly applied to tackle decision-making states originated by obscurity and vagueness. The interval-valued q-rung orthopair fuzzy soft set is a novel variant of fuzzy sets. The main objective of this study is to introduce the interval-valued q-rung orthopair fuzzy soft Einstein-ordered weighted and Einstein hybrid weighted aggregation operators. Based on developed aggregation operators, a novel decision-making approach, the Evaluation based on the Distance from the Average Solution introduced to solve the MAGDM problem. The execution of the proposed approach demonstrates the significant impact of determining the most effective strategy to handle biomedical waste. Our proposed approach's practicality is confirmed by a case study focusing on selecting the most effective technique for Biomedical Waste (BMW) treatment. This study shows that autoclaving is the most effective method for the disposal of BMW. Comparative and sensitivity analysis confirms the consistency and effectiveness of our methodology. The comparative study indicates the effects of the proposed strategy are more feasible and realistic than the prevailing techniques.
HRM’s Response to Workplace Bullying: Complacent, Complicit and Compounding
Authors: Boddy Clive R. , Boulter Louise 
Published: July 2024

AbstractPerceptions of human resource (HRM) management’s response to worker bullying were investigated through a netnographic analysis of written comments concerning an online ‘TEDx’ talk called “Bullying and Corporate Psychopaths at Work” to help determine whether HRM are seen as supportive of bullied workers. This research utilized a qualitative, ethnographic approach deemed to be highly valid in researching sensitive areas such as that of workplace bullying. Findings align with, deepen, and extend previous theory and knowledge in that a key finding that emerges is that HRM is deemed by workers to be capable of, but unwilling to deal effectively with, bullying managers. HRM are seen as complacent in that they do little about psychopathic bullies, complicit in that they support managerial bullies and compounding in that they worsen outcomes from workers’ point of view. It appears that HRM has therefore lost the trust of this sample of bullied workers. The paper is a first to apply a netnographic analysis to the problem of workplace bullying and reveals HRM fails to deal with it to worker’s satisfaction. Implications include that the ubiquitous prevalence of workplace bullying around the world could continue unabated unless strict, clear codes of conduct are established and policed by HRM or non-HRM related forms of intervention are mobilized.
What Drives Carbon Emissions in German Manufacturing: Scale, Technique or Composition?
Authors: Rottner Elisa , von Graevenitz Kathrine 
Published: July 2024

AbstractEmissions of local pollutants from industry have declined across many developed countries over the last decades. For carbon emissions such reductions have yet to materialize. Using German administrative micro-data at the product level, we apply the workhorse model for decomposing emission changes into scale, composition (changes in the mix of goods produced) and technology (emission factors of production) effects. We find that the production composition in German manufacturing shifted towards less CO2 intensive goods, while emission intensities of production increased. We show that data aggregation matters. Both effects are substantially underestimated when using data at the sector level as compared to the product level. A complementary plant level decomposition reveals that emission intensities of production increased both within plant, and due to a reallocation of production to more emission intensive plants.
A Hidden Convexity of Nonlinear Elasticity
Authors: Singh Siddharth , Ginster Janusz , Acharya Amit 
Published: July 2024

AbstractA technique for developing convex dual variational principles for the governing PDE of nonlinear elastostatics and elastodynamics is presented. This allows the definition of notions of a variational dual solution and a dual solution corresponding to the PDEs of nonlinear elasticity, even when the latter arise as formal Euler–Lagrange equations corresponding to non-quasiconvex elastic energy functionals whose energy minimizers do not exist. This is demonstrated rigorously in the case of elastostatics for the Saint-Venant Kirchhoff material (in all dimensions), where the existence of variational dual solutions is also proven. The existence of a variational dual solution for the incompressible neo-Hookean material in 2-d is also shown. Stressed and unstressed elastostatic and elastodynamic solutions in 1 space dimension corresponding to a non-convex, double-well energy are computed using the dual methodology. In particular, we show the stability of a dual elastodynamic equilibrium solution for which there are regions of non-vanishing length with negative elastic stiffness, i.e. non-hyperbolic regions, for which the corresponding primal problem is ill-posed and demonstrates an explosive ‘Hadamard instability;’ this appears to have implications for the modeling of physically observed softening behavior in macroscopic mechanical response.
Harmonious environmental passion and voluntary pro-environmental behavior at home and at work: a moderated mediation model to examine the role of cultural femininity
Authors: Saifulina Nailya , Carballo-Penela Adolfo , Ruzo-Sanmartín Emilio 
Published: July 2024

AbstractEmployees’ pro-environmental behavior can contribute to reduce organizations environmental impact, improving organizational sustainability. The primary objective of this work is to highlight the mechanisms that stimulate employees’ voluntary pro-environmental behavior at work (Wpeb), paying attention to the role of harmonious environmental passion, private life voluntary pro-environmental behavior (PLpeb) and contextual factors as national culture. The model was analysed empirically by collecting data from 331 Kazakhstani and Ecuadorian bank employees. Covariance-based structural equation modelling (CB_SEM) is used to test the proposed relationships. Our findings demonstrate that harmonious environmental passion is positively related to Wpeb, and this relationship is mediated by PLpeb. In addition, the results show that cultural femininity strengthens the direct effects of harmonious environmental passion on PLpeb and Wpeb. These findings will help managers to promote such pro-environmental behaviors at work in different cultural contexts through the implementation of various practices inducing the atmosphere that stimulates the development of environmental passion.
A physically-informed machine learning model for freeform bending
Authors: Lechner Philipp , Scandola Lorenzo , Maier Daniel , Hartmann Christoph , Rizaiev Yevgen , Lieb Mona 
Published: July 2024

AbstractThis work aims at a fast computational process model of the free-form bending process. It proposes a novel physically-informed machine learning model, which is trained with experimental data of bending constant radii and utilizes additional physical bending knowledge by integrating Timoshenko’s beam theory. The model is able to predict the resulting plastic deformation of the tube after exiting the die by computing an elastic representation of the tube’s deformation with beam theory at each time step. This elastic representation serves as input for a regression model similar to a partially connected neural network. This physically-informed machine learning model generalizes the constant training radii to complex bend geometries consisting of transitional sections and true spline geometries. It is compared to a benchmark finite element simulation and has an improved prediction quality for complex kinematics while reducing the computation time by four orders of magnitude.
Sustainable and multifunctional polyurethane green composites with renewable materials
Authors: Bartczak Przemysław , Szylińczuk Kacper , Tomaszczak Maciej , Borysiak Sławomir 
Published: July 2024

AbstractPolyurethane materials are characterised by an ever-expanding range of application possibilities due to their versatility. Currently, the management of leftovers as well as post-production and post-consumer waste for the production of biocomposites is one of the most obvious, effective and profitable solutions. Due to the renewable nature of biofillers such as cellulose, lignin, and chitin, their use to obtain composite polyurethane elastomers is a real perspective for the dissemination of more environmentally friendly materials and, at the same time, contributes to additional economic profit. The key aspect for further development of the polyurethane/biopolymer biocomposite concept is to fulfil of a number of currently functioning industry standards, mainly those regarding functional properties. In the presented research, an attempt to obtain advanced polyurethane elastomers with the addition of biopolymers (cellulose, lignin, and chitin) was conducted for the first time. The innovative biocomposites obtained in this way were characterised by good processing parameters (processing times, density) and improved functional properties compared to the standard without the addition of fillers (abrasion resistance, tensile strength, contact angle, hardness). Due to the above-mentioned facts, the described biocomposites can be successfully used for the production of multifunctional elastomeric materials with a wide range of potential applications. Moreover, it is worth noting that the management of waste materials in this way will reduce production costs while indirectly contributing to the protection of the natural environment.
Graphical abstract
Zinc-doped hexaferrite exhibits altered physical properties in the presence of both Dy and Zn ions
Authors: Ramadan Rania 
Published: July 2024

AbstractThe nanosized M-type hexaferrites SrFe11.5Zn0.5O19, Sr0.95Dy0.05Fe12O19, and Sr0.95Dy0.05Fe11.5Zn0.5O19 were produced by auto combustion utilizing citric acid. The impacts of substituting Zn2+ as well as Dy3+ ions upon the structural, electrical, magnetic, and optical properties of SrFe11.5Zn0.5O19, Sr0.95Dy0.05Fe12O19 and Sr0.95Dy0.05Fe11.5Zn0.5O19 nanoferrites have been studied using XRD, FTIR, UV–Visible, FESEM, VSM, and LCR meter. The formation of a single-phase lattice was confirmed by the XRD analyses. For the investigated samples, the crystallite size rose from 36 nm for SrFe11.5Zn0.5O19 to 37 and 33 nm, for Sr0.95Dy0.05Fe12O19, and Sr0.95Dy0.05Fe11.5Zn0.5O19 respectively. In FTIR spectra, a couple of absorption bands have been seen. The prepared samples possess a strong tendency to clump together into large masses, according to FSEM. The samples’ band gap values vary from 1.8 to 2.4 eV. Additionally, the dielectric parameters based on a Maxwell–Wagner two-layer approach have also been described. The results reveal that the dielectric constant (ε’) as well as dielectric loss (ε’’) decrease with increasing applied field frequency, whereas the AC conductivity (σac) increases. The VSM results show that all the investigated materials are referred to as hard magnetic materials.
Do Social Sciences Threaten the Autonomy of Ethics? Reconstructing the Marxian Metaethical Response
Authors: Dimitrakos Thodoris 
Published: July 2024

AbstractIn the present paper, I attempt to provide a reconstructed Marxian response to the question of whether the social (and behavioral) sciences constitute a philosophical threat to the autonomy of ethics. I suggest that shedding light on some aspects of the Marxian work (especially the Theses on Feuerbach), from the standpoint of the debate on naturalism in contemporary analytic philosophy, can offer valuable philosophical insights against the framework of scientific naturalism. This framework is responsible for presenting the social sciences as a philosophical threat to the autonomy of ethics. I argue that Marx detects and rejects three fundamental presuppositions of scientific naturalism: empiricism, ‘God’s point of view,’ and methodological individualism. I conclude that the Marxian view is a liberal naturalist perspective which allows both the scientific comprehension of the social world and the autonomy of ethics.
Effects of Defects on the Properties of Polymer Nanocomposites: A Brief Review
Authors: Folorunso Oladipo , Hamam Yskandar , Sadiku Rotimi , Kupolati Williams 
Published: July 2024

AbstractPolymer nanocomposites are promising materials for various applications in the electronics, biomedicine, and aerospace industries. However, the fabrication errors or defects, e.g., induced porosity, significantly impact the performance and the reliability of devices fabricated from polymer nanocomposites. Hence, this study has comprehensively carried out an investigation into the effects of defects on the properties of photovoltaic active cells, biomimetic scaffold, and aircraft structures that are fabricated by using polymer nanocomposites. Agglomeration is another defect that degrades the intended properties of polymer nanocomposite devices. For photovoltaic devices, defects can be controlled by the selective modification of organic semiconductor molecular structures. In addition, proper optimization of the process parameters and the material selection, are effective approaches for obtaining excellent photovoltaic cells. Furthermore, the presence of impurities, a non-homogeneous mixture of organic and inorganic materials, and the incomplete solubility of nanoparticles, are detrimental factors that affect the cell proliferation performance of biomimetic scaffolds. These technological imperfections must be also avoided when producing parts for aircraft structures. In other words, impurities introduced during the synthesis or processing stages can lead to irregularities in the material structure, which often affect its mechanical, electrical, biomedical, and optical properties. The understanding and mitigating of these factors are crucial for the optimization of the properties and performance of polymer nanocomposites in various applications.
Theoretical Studies on Off-Axis Phase Diagrams and Knight Shifts in UTe$$_2$$: Tetra-Critical Point, d-Vector Rotation, and Multiple Phases
Authors: Machida Kazushige 
Published: July 2024

AbstractInspired by recent remarkable sets of experiments on UTe$$_2$$

2

: discoveries of the fourth horizontal internal transition line running toward a tetra-critical point (TCP) at H = 15 T, the off-axis high-field phases, and abnormally large Knight shift (KS) drop below $$T_\textrm{c}$$

T
c

for $$H \parallel a$$

H
‖
a

-magnetic easy axis, we advance further our theoretical work on the field (H)-temperature (T) phase diagram for $$H \parallel b$$

H
‖
b

-magnetic hard axis which contains a positive sloped $$H_\textrm{c2}$$

H
c2

departing from TCP. A nonunitary spin-triplet pairing with three components explains these experimental facts simultaneously and consistently by assuming that the underlying normal electron system with a narrow bandwidth characteristic to the Kondo temperature $$\sim$$
∼
30 K unsurprisingly breaks the particle-hole symmetry. This causes a special invariant term in Ginzburg–Landau (GL) free energy functional which couples directly with the 5f magnetic system, giving rise to the $$T_\textrm{c}$$

T
c

splitting and ultimately to the positive sloped $$H_\textrm{c2}$$

H
c2

and the horizontal internal transition line connected to TCP. The large KS drop can be understood in terms of this GL invariance whose coefficient is negative and leads to a diamagnetic response where the Cooper pair spin is antiparallel to the applied field direction. The present scenario also accounts for the observed d-vector rotation phenomena and off-axis phase diagrams with extremely high $$H_\textrm{c2}$$

H
c2

$$\gtrsim$$
≳
70 T found at angles in between the b- and c-axes and between the bc-plane and a-axis, making UTe$$_2$$

2

a fertile playground for a possible topological superconductor.
Identification and Design of Novel Potential Antimicrobial Peptides Targeting Mycobacterial Protein Kinase PknB
Authors: Deka Hemchandra , Pawar Atul , Battula Monishka , Ghfar Ayman A. , Assal Mohamed E. , Chikhale Rupesh V. 
Published: July 2024

AbstractAntimicrobial peptides have gradually gained advantages over small molecule inhibitors for their multifunctional effects, synthesising accessibility and target specificity. The current study aims to determine an antimicrobial peptide to inhibit PknB, a serine/threonine protein kinase (STPK), by binding efficiently at the helically oriented hinge region. A library of 5626 antimicrobial peptides from publicly available repositories has been prepared and categorised based on the length. Molecular docking using ADCP helped to find the multiple conformations of the subjected peptides. For each peptide served as input the tool outputs 100 poses of the subjected peptide. To maintain an efficient binding for relatively a longer duration, only those peptides were chosen which were seen to bind constantly to the active site of the receptor protein over all the poses observed. Each peptide had different number of constituent amino acid residues; the peptides were classified based on the length into five groups. In each group the peptide length incremented upto four residues from the initial length form. Five peptides were selected for Molecular Dynamic simulation in Gromacs based on higher binding affinity. Post-dynamic analysis and the frame comparison inferred that neither the shorter nor the longer peptide but an intermediate length of 15 mer peptide bound well to the receptor. Residual substitution to the selected peptides was performed to enhance the targeted interaction. The new complexes considered were further analysed using the Elastic Network Model (ENM) for the functional site’s intrinsic dynamic movement to estimate the new peptide’s role. The study sheds light on prospects that besides the length of peptides, the combination of constituent residues equally plays a pivotal role in peptide-based inhibitor generation. The study envisages the challenges of fine-tuned peptide recovery and the scope of Machine Learning (ML) and Deep Learning (DL) algorithm development. As the study was primarily meant for generation of therapeutics for Tuberculosis (TB), the peptide proposed by this study demands meticulous invitro analysis prior to clinical applications.
Graphical Abstract