bluuebunny/crossref_metadata_2025_split huggingface dataset:
A new framework for Physical Layer Security in HetNets based on Radio Resource Allocation and Reinforcement Learning
Authors: Marabissi Dania , Abrardo Andrea , Mucchi Lorenzo 
Published: August 2023

AbstractDensification of networks through heterogeneous cells deployment is considered a key technology to satisfy the huge traffic growth in future wireless systems. In addition to achieving the required communication capacity and efficiency, another significant challenge arises from the broadcast nature of wireless channels: vulnerability to wiretapping. Physical-layer security is envisaged as an additional level of security to provide confidentiality of radio communications. Typical characteristics of the wireless channel (noise, interference) can be exploited to keep a message confidential from potential eavesdroppers. In particular, heterogeneous networks (HetNet) have inherent security features: while the legitimate user can benefit of the HetNet architecture, the eavesdropper is strongly affected by the inter-cell interference. This paper presents an overview of HetNets intrinsic security benefits, mainly focusing on users association and resource allocation policies. In particular, allocation of radio resources is a poorly investigated topic when related to information security. However, in systems with a large radio resource reuse like HetNets, co-channel interference can be suitably exploited to resist to the eavesdropper. This paper presents a new framework for radio resources allocation using reinforcement learning (Q-learning) to increase the security level in HetNets. A coordinated scheduling among different cells using the same radio resources is proposed based on the exploitation of the spatial information. The goal is to optimize the security at physical layer. The reinforcement learning approach represents a feasible and efficient solution to the proposed problem.
View recommendation for multi-camera demonstration-based training
Authors: Biswas Saugata , Kruijff Ernst , Veas Eduardo 
Published: August 2023

AbstractWhile humans can effortlessly pick a view from multiple streams, automatically choosing the best view is a challenge. Choosing the best view from multi-camera streams poses a problem regarding which objective metrics should be considered. Existing works on view selection lack consensus about which metrics should be considered to select the best view. The literature on view selection describes diverse possible metrics. And strategies such as information-theoretic, instructional design, or aesthetics-motivated fail to incorporate all approaches. In this work, we postulate a strategy incorporating information-theoretic and instructional design-based objective metrics to select the best view from a set of views. Traditionally, information-theoretic measures have been used to find the goodness of a view, such as in 3D rendering. We adapted a similar measure known as the viewpoint entropy for real-world 2D images. Additionally, we incorporated similarity penalization to get a more accurate measure of the entropy of a view, which is one of the metrics for the best view selection. Since the choice of the best view is domain-dependent, we chose demonstration-based training scenarios as our use case. The limitation of our chosen scenarios is that they do not include collaborative training and solely feature a single trainer. To incorporate instructional design considerations, we included the trainer’s body pose, face, face when instructing, and hands visibility as metrics. To incorporate domain knowledge we included predetermined regions’ visibility as another metric. All of those metrics are taken into account to produce a parameterized view recommendation approach for demonstration-based training. An online study using recorded multi-camera video streams from a simulation environment was used to validate those metrics. Furthermore, the responses from the online study were used to optimize the view recommendation performance with a normalized discounted cumulative gain (NDCG) value of 0.912, which shows good performance with respect to matching user choices.
A new optimal root-finding iterative algorithm: local and semilocal analysis with polynomiography
Authors: Qureshi Sania , Argyros Ioannis K. , Soomro Amanullah , Gdawiec Krzysztof , Shaikh Asif Ali , Hincal Evren 
Published: August 2023

AbstractIn this work, a new optimal iterative algorithm is presented with fourth-order accuracy for root-finding of real functions. It uses only function as well as derivative evaluation. The algorithm is obtained as a combination of existing third-order methods by specifying a parameter involved. The algorithm is based on local and semilocal analysis and has been specifically designed to improve efficiency and accuracy. The proposed algorithm represents a significant improvement over existing iterative algorithms. In particular, it is tested on a range of polynomial functions and was found to produce accurate and efficient results, with improved performance over existing algorithms in terms of both speed and accuracy. The results demonstrate the effectiveness of the proposed algorithm and suggest that it has great potential for use in a wide range of applications in polynomiography and other areas of mathematical analysis.
Dividends, trust, and firm value
Authors: Kapons Martin , Kelly Peter , Stoumbos Robert , Zambrana Rafael 
Published: August 2023

AbstractWe find evidence that investors value dividends differently depending on their level of trust. Our tests indicate that investor demand for dividend-paying stocks increases as trust decreases, and that this relationship affects market values. We begin with survey evidence showing that people think accounting fraud is less likely among dividend payers and that people with low trust are more likely to hold dividend-paying stocks. We then empirically exploit accounting fraud discoveries within a mutual fund’s portfolio as a shock to trust. In response to these shocks, we show that mutual funds tilt their portfolios toward dividend-paying stocks. This result is not explained by a shift in risk preferences, indicating that these institutional investors are seeking dividends in particular rather than stable firms that just happen to pay dividends. Finally, we provide evidence that dividend payers experience a premium in their market values relative to non-payers when their investor base becomes less trusting.
Adsorptive Removal of Rhodamine B Dye from Aqueous Solutions Using Mineral Materials as Low-Cost Adsorbents
Authors: Kuśmierek Krzysztof , Fronczyk Joanna , Świątkowski Andrzej 
Published: August 2023

AbstractIn this work, the potential adsorption abilities of mineral materials such as zeolite (Ze), halloysite (Ha), chalcedonite (Ch), and Devonian sand (DS) used as low-cost resources for the removal of Rhodamine B (RhB) from aqueous solutions were investigated in batch conditions. Adsorption kinetics and equilibrium and the effect of solution reaction (pH) were studied. Adsorption kinetic data were analyzed using two kinetic models: pseudo-first-order and pseudo-second-order models. Adsorption kinetics was better represented by the pseudo-second-order model. Equilibrium data were analyzed by the Freundlich, Langmuir, and Sips isotherms. The results show that equilibrium data fit well with the Freundlich equilibrium. Monolayer maximum adsorption capacities of RhB were assumed at 6.964, 4.252, 2.701, and 0.349 mg/g for Ze, Ha, Ch, and DS, respectively. Adsorption was strongly pH-dependent. The maximum RhB adsorption on all tested materials was observed at pH = 2.2 and decreased with further pH increase. The results of these investigations suggest that natural materials represented by certain minerals have a good potential for the removal of Rhodamine B from aqueous solutions.
Graphical Abstract
Neural-network-based parameter tuning for multi-agent simulation using deep reinforcement learning
Authors: Hirano Masanori , Izumi Kiyoshi 
Published: August 2023

AbstractThis study proposes a new efficient parameter tuning method for multi-agent simulation (MAS) using deep reinforcement learning. MAS is currently a useful tool for social sciences, but is hard to realize realistic simulations due to its computational burden for parameter tuning. This study proposes efficient parameter tuning to address this issue using deep reinforcement learning methods. To improve compatibility with the tuning task, our proposed method employs actor-critic-based deep reinforcement learning, such as deep deterministic policy gradient (DDPG) and soft actor-critic (SAC). In addition to the customized version of DDPG and SAC for our task, we also propose three additional components to stabilize the learning: an action converter (DDPG only), a redundant full neural network actor, and a seed fixer. For experimental verification, we employ a parameter tuning task in an artificial financial market simulation, comparing our proposed model, its ablations, and the Bayesian estimation-based baseline. The results demonstrate that our model outperforms the baseline in terms of tuning performance, indicating that the additional components of the proposed method are essential. Moreover, the critic of our model works effectively as a surrogate model, that is, as an approximate function of the simulation, which allows the actor to tune the parameters appropriately. We have also found that the SAC-based method exhibits the best and fastest convergence, which we assume is achieved by the high exploration capability of SAC.
Sex-specific preservation of neuromuscular function and metabolism following systemic transplantation of multipotent adult stem cells in a murine model of progeria
Authors: Thompson Seth D. , Barrett Kelsey L. , Rugel Chelsea L. , Redmond Robin , Rudofski Alexia , Kurian Jacob , Curtin Jodi L. , Dayanidhi Sudarshan , Lavasani Mitra 
Published: August 2023

AbstractOnset and rates of sarcopenia, a disease characterized by a loss of muscle mass and function with age, vary greatly between sexes. Currently, no clinical interventions successfully arrest age-related muscle impairments since the decline is frequently multifactorial. Previously, we found that systemic transplantation of our unique adult multipotent muscle-derived stem/progenitor cells (MDSPCs) isolated from young mice—but not old—extends the health-span in DNA damage mouse models of progeria, a disease of accelerated aging. Additionally, induced neovascularization in the muscles and brain—where no transplanted cells were detected—strongly suggests a systemic therapeutic mechanism, possibly activated through circulating secreted factors. Herein, we used ZMPSTE24-deficient mice, a lamin A defect progeria model, to investigate the ability of young MDSPCs to preserve neuromuscular tissue structure and function. We show that progeroid ZMPST24-deficient mice faithfully exhibit sarcopenia and age-related metabolic dysfunction. However, systemic transplantation of young MDSPCs into ZMPSTE24-deficient progeroid mice sustained healthy function and histopathology of muscular tissues throughout their 6-month life span in a sex-specific manner. Indeed, female—but not male—mice systemically transplanted with young MDSPCs demonstrated significant preservation of muscle endurance, muscle fiber size, mitochondrial respirometry, and neuromuscular junction morphometrics. These novel findings strongly suggest that young MDSPCs modulate the systemic environment of aged animals by secreted rejuvenating factors to maintain a healthy homeostasis in a sex-specific manner and that the female muscle microenvironment remains responsive to exogenous regenerative cues in older age. This work highlights the age- and sex-related differences in neuromuscular tissue degeneration and the future prospect of preserving health in older adults with systemic regenerative treatments.
Instrumented column testing on long-term consolidation and desiccation behaviour of coal tailings under natural weather conditions
Authors: Zhang Wenqiang , Zhang Chenming , Lei Ximing , Quintero Olaya Sebastian , Zhu Yuyang , Zhao Zicheng , Jensen Steve , Williams David John 
Published: August 2023

AbstractThe sedimentation, consolidation and desiccation behaviour of sub-aerially deposited tailings in tailings storage facilities, despite occurring simultaneously and being essential to maximise tailings dry density and dewatering efficiency, are usually analysed in laboratories using distinctive testing equipment, which is unable to reveal their interactions. A large instrumented column was constructed to test the three processes of tailings in a single apparatus, capable of monitoring the changes in the hydrological parameters of coal tailings with depth and surface settlement under natural weather conditions. The column was initially filled with coal tailings slurry and exposed to natural weather for two years, during which five wetting–drying periods were identified. The monitored results indicate that exposing the slurry tailings for one month would lead to the formation of an unsaturated tailings layer with a thickness of 150 mm, likely representing the optimised tailings deposition cycle and thickness, respectively, under the given tailings characteristics and semi-arid climates. Settlement mainly occurred after major rainfall events due to the collapse of cracks and cavities formed during the preceding desiccation. The maximum thickness of the unsaturated tailings increased over the first four periods as the predominant desiccation and settlement strengthened the evaporative capillary forces, despite it decreasing greatly in the last period due to insufficient desiccation. An empirical model was proposed to consecutively estimate the surface moisture content of deformable tailings and validated by achieving a good agreement in the water mass estimated by two methods during wetting–drying cycles.
Experimental and Numerical Investigation of a Solidification-Based Aluminum-Cooled Finger Refinement Process From Micro to Macro-Scale
Authors: Curtolo Danilo , Schubert Christian , Viardin Alexandre , Friedrich Semiramis , Eickhoff Moritz , Böttger Bernd , Friedrich Bernd , Pfeifer Herbert , Apel Markus 
Published: August 2023

AbstractThe interest in ultra-pure metals is steadily growing due to the increasing demand for these materials in modern technology. To be able to meet the increasing demand in the future, it is necessary to implement more efficient and productive processes. As a fractional crystallization method in this application area, the cooled finger method exhibits higher productivity and lower energy requirements when compared to industry well-established methods like zone melting. In this study, the mechanisms and relevant phenomena crucial for a successful implementation of a cooled finger process were investigated using a multidisciplinary approach. With carefully selected process parameters, we present here an experimental setup with a purification potential of approximately 80 pct. Additional micro- and macro-scale simulations demonstrate that the process is sensitive to parameters such as rotation rate, cooling rate, and temperature gradient within the melt, which explains the difficulty in optimizing this process in practice. An analysis and description of various phenomena that characterize the behavior of the cooled finger process are presented within this multi-scale approach. As a result, these approaches can also be transferred to the description of processes for other metals, opening application areas outside of the purification of aluminum.
Team-Based Approach to Reduce Malignancies in People with Diabetes and Obesity
Authors: Zhu Ziyue , Wong Samuel Yeung Shan , Sung Joseph Jao Yiu , Lam Thomas Yuen Tung 
Published: August 2023

Abstract
Purpose of Review
Numerous observations have indicated an increased risk of developing various types of cancers, as well as cancer-related mortality, among patients with diabetes and obesity. The purpose of this review is to outline multiple-cancer screening among these patients through a team-based approach and to present the findings of a pioneering integrated care program designed for patients with obesity with a specific emphasis on cancer prevention.

Recent Findings
A community-based multi-cancer prevention program, which provides all services in one location and utilizes team-based approaches, is reported to be feasible and has the potential to enhance the uptake rate of multiple cancers screening among patients with diabetes and obesity.

Summary
The team-based approach is a commonly utilized method for managing patients with diabetes, obesity, and cancer, and has been shown to be efficacious. Nevertheless, research on team-based cancer screening programs for patients with diabetes and obesity remains limited. Providing a comprehensive screening for colorectal, prostate, and breast cancer, as well as metabolic syndrome, during a single clinic visit has been proven effective and well-received by participants.
Digitale Kompetenzen angehender Sportlehrkräfte
Authors: Mödinger Moritz , Wohlfart Olivia , Woll Alexander , Wagner Ingo 
Published: August 2023

ZusammenfassungDa internationale Vergleichsstudien zu digitalen Kompetenzen im Hinblick auf eine föderalistisch geprägte Bildungslandschaft zum Ausbildungsstand angehender Lehrkräfte nur eingeschränkt aussagekräftig sein können, bedarf es im Hinblick auf eine zielgerichtete Ausbildung bundesland- und fachspezifischer Untersuchungen unter Verwendung eines zielgruppenadäquaten Erhebungsinstruments. Zu diesem Zweck wurden die Kompetenzen von 185 angehenden Sportlehrkräften zu Beginn des Referendariats in Baden-Württemberg (Rücklaufquote: 44,4 %) anhand des TPACK-Modells mittels eines Online-Fragebogens erhoben, der auf einer Selbsteinschätzung beruht und fachspezifisch inhaltlichen Besonderheiten Rechnung trägt. Die Ergebnisse zeigen, dass sich die angehenden Sportlehrkräfte inhaltlich gut (CK) und besser als pädagogisch (PK) auf eine zunehmend digitale Bildungslandschaft vorbereitet fühlen. Auch trauen sie sich zu, inhaltliches Wissen pädagogisch zu vermitteln (PCK), allerdings stellt die Berücksichtigung von Informations- und Kommunikationstechnologien (IKT) im Unterricht (TK, TCK, TPK, TPACK) vermeintlich noch eine Barriere dar. Eine gezielte Förderung der pädagogischen Implementierung von IKT (TPK) könnte hingegen die Entwicklung von TPACK – auch fächerübergreifend – positiv beeinflussen. Mit Blick auf die Stärkung von Kompetenzen sollte darüber hinaus der Fachspezifität größere Aufmerksamkeit zuteilwerden, um mögliche Defizite zu identifizieren und diesen konstruktiv entgegenwirken zu können. Auch sollte der schulische Kontext bei der Vermittlung theoretischen Wissens noch stärker berücksichtigt werden und die Ausbildung die methodische Einbindung technologischer Aspekte im Hinblick auf das Bewegungskönnen stärker in den Blick nehmen, um TPACK bei angehenden Sportlehrkräften wirksam(er) zu fördern.
Fibration theorems à la Milnor for analytic maps with non-isolated singularities
Authors: Cisneros-Molina José Luis , Menegon Aurélio , Seade José , Snoussi Jawad 
Published: August 2023

AbstractWe study the topology of real analytic maps in a neighborhood of a (possibly non-isolated) critical point. We prove fibration theorems à la Milnor for real analytic maps with non-isolated critical values. Here we study the situation for maps with arbitrary critical set. We use the concept of d-regularity introduced in an earlier paper for maps with an isolated critical value. We prove that this is the key point for the existence of a Milnor fibration on the sphere in the general setting. Plenty of examples are discussed along the text, particularly the interesting family of functions $$(f,g):{\mathbb {R}}^n \rightarrow {\mathbb {R}}^2$$

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Detecting and generating overlapping nested communities
Authors: Gera Imre , London András 
Published: August 2023

AbstractNestedness has been observed in a variety of networks but has been primarily viewed in the context of bipartite networks. Numerous metrics quantify nestedness and some clustering methods identify fully nested parts of graphs, but all with similar limitations. Clustering approaches also fail to uncover the overlap between fully nested subgraphs, as they assign vertices to a single group only. In this paper, we look at the nestedness of a network through an auxiliary graph, in which a directed edge represents a nested relationship between the two corresponding vertices of the network. We present an algorithm that recovers this so-called community graph, and finds the overlapping fully nested subgraphs of a network. We also introduce an algorithm for generating graphs with such nested structure, given by a community graph. This algorithm can be used to test a nested community detection algorithm of this kind, and potentially to evaluate different metrics of nestedness as well. Finally, we evaluate our nested community detection algorithm on a large variety of networks, including bipartite and non-bipartite ones, too. We derive a new metric from the community graph to quantify the nestedness of both bipartite and non-bipartite networks.
Unpaid caregiving for people following hip fracture: longitudinal analysis from the English Longitudinal Study of Ageing
Authors: Smith Toby O. , Langford S. , Ward K. , Gray R. 
Published: August 2023

Abstract
Purpose
To determine the provision and its change over time in unpaid care for people following hip fracture.

Methods
Data were sought from the English Longitudinal Study of Ageing (ELSA) cohort. We identified participants who self-reported experiencing a hip fracture, who had clinical and caregiving data in the previous and subsequent two data collection waves. Demographic and clinical data were collected in addition to data on provision of unpaid care, who provided care and the frequency of needs being met.

Results
The analysed cohort consisted of 246 participants [150 females (61%), mean age 78.9 years (standard deviation: 8.6)]. There was an increase in the number of participants requiring unpaid care between the Pre-Fracture and Fracture Wave (29% vs. 59%), which plateaued in the subsequent two waves (56%; 51%). Although both spouse and daughters provided the most unpaid care to participants over this study period, there was an increase in support provided during the Fracture Wave by both sons and daughters. This increased support offered by spouses continued until Post-Fracture Wave 2 when this plateaued. Support provided by friends increased from 3 to 8% and brothers and sisters increased from 0 and 1% Pre-Fracture to 8% by Post-Fracture Wave 2.

Conclusion
These findings provide insights into who, what and how unpaid carers support people following hip fracture over time. Given the level of support unpaid carers offer, and previously reported carer stress and burden, undertaking clinical trials to assess the effectiveness of carer–patient support interventions would be valuable.