bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interest in anime and manga: relationship with (mental) health, social disconnectedness, social joy and subjective well-being
Authors: Hajek André , König Hans-Helmut 
Published: September 2024

Abstract
Aim
Our aim was to examine the association between interest in anime and manga and their relationship with (mental) health (in terms of depressive symptoms, anxiety symptoms, health-related quality of life, symptoms of hikikomori), social disconnectedness (in terms of preference for solitude, loneliness, objective social isolation, and perceived social isolation), subjective well-being (in terms of ikigai, life satisfaction, and happiness) and joy (frequency of laughter, and frequency of hugs).

Subjects and methods
Data were taken from a large sample of the general German adult population aged 18–74 years (n = 4,738 individuals, average age: 46.4 years). Established tools were used to quantify the outcomes. Multiple linear and ordered logistic regressions were used, as appropriate.

Results
Regressions showed that a higher interest in anime was associated with several adverse mental health and some social disconnectedness outcomes. Contrarily, a higher interest in anime was associated with favorable subjective well-being outcomes, and favorable joy outcomes. Similarly, regressions showed that a higher interest in manga was associated with several adverse (mental) health and some social disconnectedness outcomes. Contrary, it is associated with lower objective social isolation. Moreover, it is not significantly associated with subjective well-being outcomes, but significantly associated with the joy outcome frequency of hugs.

Conclusion
A higher interest in manga and anime was associated both with negative and positive outcomes. Particularly a higher interest in anime was associated with more favorable subjective well-being scores, laughing and hugging. In this respect, this topic needs to be approached in a very nuanced way.
The use of individual and collective selection, optimisation and compensation (SOC) strategies and their association with work ability among senior workers
Authors: Meng Annette , Sundstrup E. , Andersen Lars Louis 
Published: September 2024

AbstractBackground Selection, optimisation, and compensation (SOC) can be important strategies for maintaining work ability as we age. This study aimed to explore differences in self-reported individual and collective use of SOC strategies across job functions, as well as their association with self-rated work ability. Methods: In the third wave of the SeniorWorkingLife study, 10,798 workers aged 50 + , across the job function categories “Office work”, “work with people”, and “work in the field of production”, replied to questions about collective and individual SOC strategies and work ability. Using multiple regression, we modelled associations between SOC and work ability. Results: Associations between SOC and work ability were generally weaker among participants working in the field of production. Both individual and collective use of selection had much weaker associations with work ability in the job functions “office work” and “working with people”. In the job function “working in the field of production”, only collective compensation was positively associated with work ability while individual selection was significantly but negatively associated with work ability. Conclusions: The use of SOC may be particularly beneficial for older employees working with people. Optimisation and compensation may be the most important SOC strategies for maintaining the work ability of older employees working with people and doing office work. For older employees working in the field of production, collective optimisation may support the maintenance of work ability while reduced work ability may be associated with the use of individual selection as a “coping strategy”.
A survey of deep causal models and their industrial applications
Authors: Li Zongyu , Guo Xiaobo , Qiang Siwei 
Published: September 2024

AbstractThe notion of causality assumes a paramount position within the realm of human cognition. Over the past few decades, there has been significant advancement in the domain of causal effect estimation across various disciplines, including but not limited to computer science, medicine, economics, and industrial applications. Given the continous advancements in deep learning methodologies, there has been a notable surge in its utilization for the estimation of causal effects using counterfactual data. Typically, deep causal models map the characteristics of covariates to a representation space and then design various objective functions to estimate counterfactual data unbiasedly. Different from the existing surveys on causal models in machine learning, this review mainly focuses on the overview of the deep causal models based on neural networks, and its core contributions are as follows: (1) we cast insight on a comprehensive overview of deep causal models from both timeline of development and method classification perspectives; (2) we outline some typical applications of causal effect estimation to industry; (3) we also endeavor to present a detailed categorization and analysis on relevant datasets, source codes and experiments.
Metabolic rate does not scale with body size or activity in some tick species
Authors: Earls Kayla N. , Oyen Kennan J. 
Published: September 2024

AbstractRespiration in ticks is highly efficient and exceptionally low. Ticks can survive years between bloodmeals by having low activity and respiration to conserve energetic resources. Our objective was to compare metabolic (VCO2) and activity rates across 6 tick species. We predicted that VCO2 would be different among species and scale linearly with activity and body mass. Activity and CO2 production were measured for 32 h in 6 tick species: Dermacentor andersoni, D. variabilis, Haemaphysalis longicornis, Rhipicephalus appendiculatus, R. microplus, and R. sanguineus. Individual ticks were measured for 30 min three times to ensure breathing occurred. Absolute and mass-specific VCO2, total activity, body mass, and ventilation patterns were compared among species. As expected, ticks did not always breathe during the 30-minute measurements, especially R. sanguineus. Ventilation patterns differed among species with R. microplus having primarily cyclic patterns and R. appendiculatus having discontinuous gas exchange. VCO2 did not scale with body mass in most species. Haemaphysalis longicornis and R. sanguineus had the lowest VCO2; however, H. longicornis was the second most active species. Life history, including questing behavior and range expansion, could be contributing to differences between species. For instance, H. longicornis had exceptionally low metabolic rates despite above average activity levels, suggesting an energetic advantage which may underlie recently documented range expansions in North America. Our results demonstrate how ticks utilize energetic resources to maximize longevity. Future research describing questing behavior and distribution modeling may help explain differences in metabolic rates and activity and impacts on life history traits.
Natural killer cells in neuroblastoma: immunological insights and therapeutic perspectives
Authors: Rados Magdalena , Landegger Anna , Schmutzler Lukas , Rabidou Kimberlie , Taschner-Mandl Sabine , Fetahu Irfete S. 
Published: September 2024

AbstractNatural killer (NK) cells have multifaceted roles within the complex tumor milieu. They are pivotal components of innate immunity and shape the dynamic landscape of tumor-immune cell interactions, and thus can be leveraged for use in therapeutic interventions. NK-based immunotherapies have had remarkable success in hematological malignancies, but these therapies are met with many challenges in solid tumors, including neuroblastoma (NB), a childhood tumor arising from the sympathetic nervous system. With a focus on NB, this review outlines the mechanisms employed by NK cells to recognize and eliminate malignant cells, delving into the dynamic relationship between ligand-receptor interactions, cytokines, and other molecules that facilitate the cross talk between NK and NB cells. We discuss the immunomodulatory functions of NK cells and the mechanisms that contribute to loss of this immunosurveillance in NB, with a focus on how this dynamic has been utilized in recent immunotherapy advancements for NB.
Navigating Transnational Separation and Reunification: Resilience in Low-Income Chinese Immigrant Mothers
Authors: Ma Pei-Wen Winnie , Hsu Pei-Chen , Grenier Nuutari , Becher Chana B. , Smith-Cordice Avianne O. , Desai Uttara , Zehner Melissa 
Published: September 2024

AbstractThe present study examines the experience of low-income Chinese immigrant mothers managing the reunification process with their young children after a prolonged transnational separation—either due to reverse migration separation (children born in the US but sent to live in China, then returned to the US later) or serial migration (the mother came to the US first, and the children followed years later). Grounded in a feminist family therapy and resilience framework, this qualitative study aims to understand the mothers’ experience through a strength-based perspective and a cultural lens. A phenomenological approach was used in this study to obtain qualitative data from interviews with nine Chinese immigrant mothers. Data were analyzed using the deductive approach of thematic analysis. Results highlighted mothers’ resilience in providing for the families’ needs, utilizing familial and community support, and their strategies to overcome adversities and parenting challenges. The participants demonstrate motivation to improve their children’s well-being by utilizing a range of public, school, and community resources and support from other Chinese parents. Areas where these mothers still needed support were also identified. Lastly, implications for clinical service with Chinese immigrant families are discussed.
Designs in finite classical polar spaces
Authors: Kiermaier Michael , Schmidt Kai-Uwe , Wassermann Alfred 
Published: September 2024

AbstractCombinatorial designs have been studied for nearly 200 years. 50 years ago, Cameron, Delsarte, and Ray-Chaudhury started investigating their q-analogs, also known as subspace designs or designs over finite fields. Designs can be defined analogously in finite classical polar spaces, too. The definition includes the m-regular systems from projective geometry as the special case where the blocks are generators of the polar space. The first nontrivial such designs for $$t > 1$$

t
>
1

were found by De Bruyn and Vanhove in 2012, and some more designs appeared recently in the PhD thesis of Lansdown. In this article, we investigate the theory of classical and subspace designs for applicability to designs in polar spaces, explicitly allowing arbitrary block dimensions. In this way, we obtain divisibility conditions on the parameters, derived and residual designs, intersection numbers and an analog of Fisher’s inequality. We classify the parameters of symmetric designs. Furthermore, we conduct a computer search to construct designs of strength $$t=2$$

t
=
2

, resulting in designs for more than 140 previously unknown parameter sets in various classical polar spaces over $$\mathbb {F}_2$$

F
2

and $$\mathbb {F}_3$$

F
3

.
Different mulch films, consistent results: soil fauna responses to microplastic
Authors: Weltmeyer Antonia , Roß-Nickoll Martina 
Published: September 2024

AbstractAgricultural activities contribute to plastic pollution, with unintentional introduction and intentional use of plastic mulch films leading to the accumulation of microplastic particles in soils. The lack of removal techniques and scarce information on the effects on soil organisms, especially for biodegradable mulch films, necessitate an assessment of potential effects. This study aimed to elucidate the effects of mulch film microplastic on soil fauna by investigating reproduction output and subcellular responses before and after recovery from exposure. Two common soil organisms, Folsomia candida and Eisenia fetida, were exposed to petroleum-based polyethylene (PE) and biodegradable polylactic acid/polybutylene adipate terephthalate (PLA/PBAT) microplastic for 28 days, according to OECD guidelines 232 and 222, respectively. Juvenile numbers revealed no polymer- or concentration-dependent effects on E. fetida and F. candida reproduction after exposure to up to 5 and 10 g/kgdw soil, respectively. To provide a more sensitive and early indication of sublethal effects, subcellular responses in E. fetida were analyzed. Glutathione S-transferase (GST) activity increased with rising microplastic concentration; however, catalase (CAT), acetylcholine esterase (AChE) activity, and reactive oxygen species (ROS) did not differ from control levels. Further, the more environmentally relevant PE polymer was chosen for in-depth assessment of subcellular response after 28-day microplastic exposure and subsequent 28 days in uncontaminated soil with E. fetida. No significant differences in biomarker activity and stress levels were observed. We conclude that mulch film–derived microplastic did not adversely affect earthworm and collembolan species in this scenario, except for a slight induction in the detoxification enzyme glutathione S-transferase.
Requirements for water data ecosystems: results from a business ecosystem case study
Authors: Palviainen Marko , Soininen Juha-Pekka , Arnold Mona 
Published: September 2024

AbstractThis paper studies the factors that affect the emergence of water data ecosystems using a case study as a research method. The study is based on interviews conducted with partners in a comprehensive business ecosystem focused on the development of smart water network management. Eleven representatives from six private companies, the waterworks of a city, and three organizations that provide water supply management services for municipalities were interviewed. The paper presents analysis of the interview results focusing on the interviewees’ thoughts on the state of water data systems in Finland and on the factors that affect the emergence of water data ecosystems in Finland.The interview results indicate a clear need for water data ecosystems but also obstacles preventing their emergence. Inadequate understanding on the part of customer, a lack of water data, regulations, and underdeveloped agreements were seen to hinder the development of water data solutions. In addition to ecosystem development, the emergence of water data ecosystems requires investment and the development of water data solutions, solution concepts, and demonstrations to show the value of the ecosystem. The results show that ecosystems need a clear rationale and vision, effective management of water data sharing, and mechanisms to ensure the scalability of water data ecosystems.
Web tension AI modeling and reconstruction for digital twin of roll-to-roll system
Authors: Gafurov Anton Nailevich , Kim Jaeyoung , Kim Inyoung , Lee Taik-Min 
Published: September 2024

AbstractDigital twins (DT) are gaining attention as an emerging technology in Smart manufacturing systems. These DTs comprise various units that enable simulation, monitoring, and prediction of the manufacturing process. This study introduces a predictive model for web tension and a tension reconstruction algorithm for the DT of the roll-to-roll (R2R) system. The observed web tension signals from tension sensors decomposed into a mean component, a sinusoidal wave, and a random noise. Utilizing deep neural networks, the predictive model integrated various sub-models to forecast statistical (mean, standard deviation) and frequency domain (main frequency, signal-to-noise ratio) features of the web tension signal. Through fivefold cross-validation, 23 model architectures were optimized, with selected architectures ranging from 16-32-32-1 to 16-32-64-32-1 nodes per layer. Overall, R2 scores on the test set ranged from approximately 52 to 100%. The proposed reconstruction algorithm generated tension signals from the model’s predictions that closely resemble the original tension signals, indicating credible reconstructions. The proposed predictive model and reconstruction algorithm were integrated into the DT of the R2R system, offering a valuable tool for monitoring and optimizing the R2R process.
On the size- and shape-dependence of integral and partial molar Gibbs energies, entropies, enthalpies and inner energies of solid and liquid nano-particles
Authors: Kaptay George 
Published: September 2024

AbstractIn this paper the size- and shape dependences of 8 different integral and partial molar thermodynamic quantities are derived for solid and liquid nano-phases, starting from the fundamental equation of Gibbs: i) The integral molar Gibbs energies of nano-phases and the partial molar Gibbs energies of components in those nano-phases, ii) The integral molar enthalpies of nano-phases and the partial molar enthalpies of components in those nano-phases, iii) The integral molar entropies of nano-phases and the partial molar entropies of components in those nano-phases, and iv). The integral molar inner energies of nano-phases and the partial molar inner energies of components in those nano-phases. All these 8 functions are found proportional to the specific surface area of the phase, defined as the ratio of its surface area to its volume. The equations for specific surface areas of phases of different shapes are different, but all of them are inversely proportional to the characteristic size of the phase, such as the diameter of a nano-sphere, the side-length of a nano-cube or the thickness of a thin film. Therefore, the deviations of all properties discussed here from their macroscopic values are inversely proportional to their characteristic sizes. The 8 equations derived in this paper follow strict derivations from the fundamental equation of Gibbs. Only the temperature dependent surface energy of solids and surface tension of liquids will be considered as model equations to simplify the final resulting equations. The theoretical equations are validated for the molar Gibbs energy against the experimental values of liquidus temperatures of pure lead. The theoretical equations for the molar enthalpy are validated i). Against the experimental values of dissolution enthalpy differences between nano- and macro cobalt particles in the same liquid alloy and ii). Against the size dependent melting enthalpy of nano-indium particles. In this way, also the theoretical equations for the molar entropy and molar inner energy are validated as they are closely related to the validated equations for the molar Gibbs energy and molar enthalpy.
The Unhappy Beliefs of Happiness: Investigating the Mechanisms Underlying the Links Between Negative Hedonic Beliefs and Diminished Well-Being
Authors: Kwon Yuri , Choi Jongan , Choi Incheol 
Published: September 2024

AbstractIn spite of extensive research that links the absence of pain with happiness, it remains puzzling why possessing beliefs equating the absence of pain with happiness (negative hedonic beliefs) undermine experienced happiness and what underlying mechanisms can explain this paradox. We conducted five studies to address these questions. The participants who had more negative hedonic beliefs exhibited decreased well-being, including subjective well-being and psychological well-being, alongside heightened depression and physical symptoms (Study 1a), an effect that persisted after controlling for behavioral inhibition/activation systems (Study 1b). Hypersensitivity to negative experiences, which reflects a reduced inclination to engage in negative experiences, even when positives exist, mediated the links between negative hedonic beliefs and poor well-being both cross-sectionally (Study 2) and longitudinally (Study 3). Moreover, the propensity to avoid negative experiences was observed in behavioral intention, primarily due to heightened anticipated negative affect when an event was manipulated to include negative aspects (Study 4). Together, the effort to eliminate negative experiences, as adhered to by individuals with negative hedonic beliefs, tends to prevent them from recognizing the potential benefits of unpleasant experiences, inadvertently depriving themselves of opportunities for the enhancement of their well-being.
Equivariant Divergence Formula for Hyperbolic Chaotic Flows
Authors: Ni Angxiu , Tong Yao 
Published: September 2024

AbstractWe prove the equivariant divergence formula for axiom A flow attractors. It is a pointwisely-defined and recursive formula for perturbation of SRB measures along center-unstable manifolds. It depends on only the zeroth and first order derivatives of the map, the observable, and the perturbation. Hence, the linear response acquires an ‘ergodic theorem’, which means that it can be sampled by recursively computing a few vectors on one orbit.
On metafeatures’ ability of implicit concept identification
Authors: Komorniczak Joanna , Ksieniewicz Paweł 
Published: September 2024

AbstractConcept drift in data stream processing remains an intriguing challenge and states a popular research topic. Methods that actively process data streams usually employ drift detectors, whose performance is often based on monitoring the variability of different stream properties. This publication provides an overview and analysis of metafeatures variability describing data streams with concept drifts. Five experiments conducted on synthetic, semi-synthetic, and real-world data streams examine the ability of over 160 metafeatures from 9 categories to recognize concepts in non-stationary data streams. The work reveals the distinctions in the considered sources of streams and specifies 17 metafeatures with a high ability of concept identification.
Pricing and Hedging Contingent Claims by Entropy Segmentation and Fenchel Duality
Authors: Vilar-Zanón José L. , Rogo Barbara 
Published: September 2024

AbstractWe present a new approach to the problem of characterizing and choosing equivalent martingale pricing measures for a contingent claim, in a finite-state incomplete market. This is the entropy segmentation method achieved by means of convex programming, thanks to which we divide the claim no-arbitrage prices interval into two halves, the buyer’s and the seller’s prices at successive entropy levels. Classical buyer’s and seller’s prices arise when the entropy level approaches 0. Next, we apply Fenchel duality to these primal programs to characterize the hedging positions, unifying in the same expression the cases of super (resp. sub) replication (arising when the entropy approaches 0) and partial replication (when entropy tends to its maximal value). We finally apply linear programming to our hedging problem to find in a price slice of the dual feasible set an optimal partial replicating portfolio with minimal CVaR. We apply our methodology to a cliquet style guarantee, using Heston’s dynamic with parameters calibrated on EUROSTOXX50 index quoted prices of European calls. This way prices and hedging positions take into account the volatility risk.