bluuebunny/crossref_metadata_2025_split huggingface dataset:
Resource overload problems with tardiness penalty: structural properties and solution approaches
Authors: Wohlert Lena Sophie , Zimmermann Jürgen 
Published: January 2024

AbstractIn this paper, we consider a resource overload problem and add a tardiness penalty to the objective function when a prescribed project makespan is exceeded, which enables a trade-off between a balanced resource utilization and a project delay. For the tardiness penalty, we distinguish between a constant and variable delay cost variant. Based on the structural properties of the resource overload problem, we show that the search space of the resource overload problem with tardiness penalty can also be reduced utilizing quasistable schedules. In addition, we discuss the application of these findings to further problems, which include objectives composed of a locally concave and a concave function or a reward structure for an early project completion instead of a tardiness penalty. As solution approaches, we present mixed-integer linear model formulations as well as a novel genetic algorithm with a decoding procedure, which exploits the devised structural properties. The performance of the genetic algorithm is improved by implementing learning methods and utilizing lower bounds. Finally, we present results from experiments on small to medium sized problem instances.
Dynamic Return Scenario Generation Approach for Large-Scale Portfolio Optimisation Framework
Authors: Neděla David , Ortobelli Lozza Sergio , Tichý Tomáš 
Published: January 2024

Abstract
In this paper, we propose a complex return scenario generation process that can be incorporated into portfolio selection problems. In particular, we assume that returns follow the ARMA–GARCH model with stable-distributed and skewed t-copula dependent residuals. Since the portfolio selection problem is large-scale, we apply the multifactor model with a parametric regression and a nonparametric regression approaches to reduce the complexity of the problem. To do this, the recently proposed trend-dependent correlation matrix is used to obtain the main factors of the asset dependency structure by applying principal component analysis (PCA). However, when a few main factors are assumed, the obtained residuals of the returns still explain a non-negligible part of the portfolio variability. Therefore, we propose the application of a novel approach involving a second PCA to the Pearson correlation to obtain additional factors of residual components leading to the refinement of the final prediction. Future return scenarios are predicted using Monte Carlo simulations. Finally, the impact of the proposed approaches on the portfolio selection problem is evaluated in an empirical analysis of the application of a classical mean–variance model to a dynamic dataset of stock returns from the US market. The results show that the proposed scenario generation approach with nonparametric regression outperforms the traditional approach for out-of-sample portfolios.
Hidden Populations for Healthcare Financial Protection in the Super-Aging Society: Closing the Gap Between Policy and Practice
Authors: Sasaki Noriko , Rosenberg Megumi , Shin Jung-ho , Kunisawa Susumu , Imanaka Yuichi 
Published: January 2024

AbstractDespite the remarkable health achievements of Japan’s universal health coverage since 1961, along with numerous social programs to ensure financial protection, a growing proportion of the older population reportedly experiences financial hardship for essential health care. The socio-behavioral and economic situation of the households in need and the effective policy interventions remain unknown. To identify the reasons behind older persons’ financial hardship and the effective policy interventions, we performed a questionnaire survey of social workers in all hospitals, local government offices and social service agencies across six prefectures in Kansai region. Data from 553 respondents revealed that the financial difficulties related to health care are often closely intertwined with social and mental health hardships experienced by older people and their families. Notably, potentially helpful programs including ‘free/low-cost medical treatment program’ and the adult guardianship system for dementia were infrequently used. Moreover, male, social workers at local offices/agencies, and less than 10 years’ professional experience associated with infrequent use of key protective programs. To close the gap between policy and practice, policies should focus on clients’ daily living needs, and new frontline social workers should receive lifelong training that incorporates their own backgrounds, experiences, and values, including the use of anti-oppressive gerontological approaches.
First Partner Choice in a Native Minority: The Role of Own and Parental Ethnolinguistic Affiliation
Authors: Uggla Caroline , Saarela Jan 
Published: January 2024

Abstract
Despite increasing diversity within many societies, ethnically endogamous unions remain common. In contexts where one ethnic minority has lived alongside the majority for centuries, understanding who partners with whom is central to understanding how ethnic boundaries are maintained or dissolved. This study examines the role of own and parental ethnolinguistic affiliation for the first partner choice in Finland. We provide a unique test of the relevance of ethnic endogamy across two generations, in a context where both groups are native, but one (Finnish speakers) overwhelmingly outnumbers the other (Swedish speakers). Using register data on the total population, we examine how a person’s ethnolinguistic affiliation and background affect the choice of the first cohabiting partner in terms of the partner’s ethnolinguistic affiliation and background. We apply discrete-time competing risk models for men and women born 1970–1983. Results indicate that Swedish-registered individuals with two Swedish-registered parents are, by far, the most likely to partner with another Swedish-registered person with endogamous background. Partnering with a Swedish-registered person with exogamous background is most likely among individuals who themselves come from mixed unions. Patterns are remarkably consistent across gender, and adjustments for education and residential area only marginally alter the results.
Exploring Archaeological Sites and the Transformative Power of Local Practices of Heritage in the Caribbean: A Haitian Case
Authors: Jean Joseph Sony 
Published: January 2024

AbstractThis article combines ethnographic and anthropological research with archaeology to explore the significance of archaeological sites as historical elements and their continuous reinterpretation in Haiti. By examining the connection of people with traces of colonial plantations, caves, and Indigenous rock art, this study contextualizes archaeology and heritage within the current social context. The research reveals archaeological sites are characterized by contemporary traces of uses by individuals today. These traces are associated with stories tied to renegotiations of meaning to places, and their contestation, construction of belonging, and memories are among the elements that make sense of heritage-making. The study emphasizes the importance of place meaning and heritage, offering valuable perspectives for future archaeological investigations and contributing to broader discourses on material history in the Caribbean.
Neuropeptide W facilitates chronic gastric ulcer healing by the regulation of cyclooxygenase and NF-κB signaling pathways
Authors: Arabacı Tamer Sevil , Mermer Kadriye Sezen , Erdoğan Ömer , Çevik Özge , Ercan Feriha , Bağcı Cahit , Yeğen Berrak Ç. 
Published: January 2024

Abstract
Aims
Putative beneficial effects of neuropeptide W (NPW) in the early phase of gastric ulcer healing process and the involvement of cyclooxygenase (COX) enzymes were investigated in an acetic acid-induced gastric ulcer model.

Main methods
In anesthetized male Sprague–Dawley rats, acetic acid was applied surgically on the serosa and then a COX-inhibitor (COX-2-selective NS-398, COX-1-selective ketorolac, or non-selective indomethacin; 2 mg/kg/day, 3 mg/kg/day or 5 mg/kg/day; respectively) or saline was injected intraperitoneally. One h after ulcer induction, omeprazole (20 mg/kg/day), NPW (0.1 μg/kg/day) or saline was intraperitoneally administered. Injections of NPW, COX-inhibitors, omeprazole or saline were continued for the following 2 days until rats were decapitated at the end of the third day.

Key findings
NPW treatment depressed gastric prostaglandin (PG) I2 level, but not PGE2 level. Similar to omeprazole, NPW treatment significantly reduced gastric and serum tumor necrosis factor-alpha and interleukin-1 beta levels and depressed the upregulation of nuclear factor kappa B (NF-κB) and COX-2 expressions due to ulcer. In parallel with the histopathological findings, treatment with NPW suppressed ulcer-induced increases in myeloperoxidase activity and malondialdehyde level and replenished glutathione level. However, the inhibitory effect of NPW on myeloperoxidase activity and NPW-induced increase in glutathione were not observed in the presence of COX-1 inhibitor ketorolac or the non-selective COX-inhibitor indomethacin.

Significance
In conclusion, NPW facilitated the healing of gastric injury in rats via the inhibition of pro-inflammatory cytokine production, oxidative stress and neutrophil infiltration as well as the downregulation of COX-2 protein and NF-κB gene expressions.
On the effects of intergovernmental grants: a survey
Authors: Lago Manuel E. , Lago-Peñas Santiago , Martinez-Vazquez Jorge 
Published: January 2024

AbstractThis paper offers a comprehensive and updated review of the effects of intergovernmental grants. We focus on the main findings in the existing literature on the effects of intergovernmental grants on tax policy and choices, expenditure decisions, fiscal stability and behavioral choices, and political economy. The intricate nature of the subject, intrinsically, does not allow for an all-inclusive survey, but we aim to provide a thorough examination and update of the most salient effects of intergovernmental grants, while indicating areas for further research.
Electrocatalytic performance of a nickel(II) phthalocyanine-carbon nanotube composite towards the detection of Hg2+ ions
Authors: Ngwenya Vuyelwa , Nelson Peter Nattaniel , Rhyman Lydia , Ramasami Ponnadurai , Booysen Irvin Noel , Mambanda Allen 
Published: January 2024

AbstractA composite film of Ni(II) phthalocyanine bearing four benzothiazole (bs) substituents (2) and carboxylic-functionalised multi-walled carbon nanotubes (2-f-MWCNTs) was drop cast on an Au electrode and heated at 50 °C to form a new Au|2-f-MWCNTs sensor for detection of Hg(II) ions. The redox potentials of 2 were measured by cyclic voltammetry, and the processes were affirmed spectroelectrochemically. The nanocomposite of the 2-f-MWCNTs was characterised by Fourier transform Infrared and Raman spectroscopies, and Scanning electron Microscopy. Its electrocatalysis towards Hg(II) was probed by various voltammetric techniques showing higher Faradaic currents in standard redox solutions than the bare or SAMs of 2. Anodic stripping voltammgrams of Hg2+ ions at the Au|2-f-MWCNTs showed good electrocatalytic activity with a linear range spanning 14.4 μM and 1000 μM, and a precision of ± 4.2%. Electrode selectively detected Hg2+ ions in the presence of Pb2+ and Zn2+ ions, while its SWV scan for a mixture of Hg2+ and Cd2+ showed high background noise.
Graphic abstract
Mining Bodily Cues to Deception
Authors: Poppe Ronald , van der Zee Sophie , Taylor Paul J. , Anderson Ross J. , Veltkamp Remco C. 
Published: January 2024

AbstractA significant body of research has investigated potential correlates of deception and bodily behavior. The vast majority of these studies consider discrete, subjectively coded bodily movements such as specific hand or head gestures. Such studies fail to consider quantitative aspects of body movement such as the precise movement direction, magnitude and timing. In this paper, we employ an innovative data mining approach to systematically study bodily correlates of deception. We re-analyze motion capture data from a previously published deception study, and experiment with different data coding options. We report how deception detection rates are affected by variables such as body part, the coding of the pose and movement, the length of the observation, and the amount of measurement noise. Our results demonstrate the feasibility of a data mining approach, with detection rates above 65%, significantly outperforming human judgement (52.80%). Owing to the systematic analysis, our analyses allow for an understanding of the importance of various coding factor. Moreover, we can reconcile seemingly discrepant findings in previous research. Our approach highlights the merits of data-driven research to support the validation and development of deception theory.
“We Never Stop Singing”: The Dynamics of the Mental and Physical Health of Czech Religious Pastors during the COVID-19 Pandemic
Authors: Kotherová Silvie , Müller Michal , Jedličková Lenka , Havlíček Jakub , Bubík Tomáš 
Published: January 2024

AbstractThis study explores the dynamics of coping strategies of Czech religious leaders during a peak of the COVID-19 pandemic. An interpretative phenomenological analysis reveals that mental health among pastors is closely linked to a need to maintain community and social contact, while physical health is related to limitations upon ritual elements. In all narratives, the lived experience of mental health in the form of prosocial behavior is significantly prioritized despite the possibility of spreading infection. The analysis also shows that maintaining the community is closely linked to risky behaviors, which positively affected group and individual well-being.
A Dynamic Logic of Data-Informed Knowledge
Authors: Deuser Kaya , Jiang Junli , Naumov Pavel , Zhang Wenxuan 
Published: January 2024

AbstractWith agents relying more and more on information from central servers rather than their own sensors, knowledge becomes property not of a specific agent but of the data that the agents can access. The article proposes a dynamic logic of data-informed knowledge that describes an interplay between three modalities and one relation capturing the properties of this form of knowledge. The main technical results are the undefinability of two dynamic operators through each other, a sound and complete axiomatisation, and a model checking algorithm.
On the effects of biased quantum random numbers on the initialization of artificial neural networks
Authors: Heese Raoul , Wolter Moritz , Mücke Sascha , Franken Lukas , Piatkowski Nico 
Published: January 2024

AbstractRecent advances in practical quantum computing have led to a variety of cloud-based quantum computing platforms that allow researchers to evaluate their algorithms on noisy intermediate-scale quantum devices. A common property of quantum computers is that they can exhibit instances of true randomness as opposed to pseudo-randomness obtained from classical systems. Investigating the effects of such true quantum randomness in the context of machine learning is appealing, and recent results vaguely suggest that benefits can indeed be achieved from the use of quantum random numbers. To shed some more light on this topic, we empirically study the effects of hardware-biased quantum random numbers on the initialization of artificial neural network weights in numerical experiments. We find no statistically significant difference in comparison with unbiased quantum random numbers as well as biased and unbiased random numbers from a classical pseudo-random number generator. The quantum random numbers for our experiments are obtained from real quantum hardware.
Triphenyltin isoselenocyanate: a novel nuclear retinoid X receptor ligand with antiproliferative and cytotoxic properties in cell lines derived from human breast cancer
Authors: Macejova Dana , Kollar Jakub , Bobal Pavel , Otevrel Jan , Schuster Daniela , Brtko Julius 
Published: January 2024

AbstractSeveral commercially available triorganotin compounds were previously found to function as agonist ligands for nuclear retinoid X receptor (RXR) molecules. Triphenyltin isoselenocyanate (TPT-NCSe), a novel selenium atom containing a derivative of triorganotin origin, was found to represent a new cognate bioactive ligand for RXRs. TPT-NCSe displayed a concentration- and time-dependent decrease in the cell viability in both human breast carcinoma MCF-7 (estrogen receptor positive) and MDA‑MB‑231 (triple negative) cell lines. Reactive oxygen species levels generated in response to TPT-NCSe were significantly higher in both carcinoma cell lines treated with TPT-NCSe when compared to mock-treated samples. Treatment with 500 nM TPT-NCSe caused a decrease in SOD1 and increased SOD2 mRNA in MCF-7 cells. The levels of SOD2 mRNA were more increased following the treatment with TPT-NCSe along with 1 μM all-trans retinoic acid (AtRA) in MCF-7 cells. An increased superoxide dismutase SOD1 and SOD2 mRNA levels were also detected in combination treatment of 500 nM TPT-NCSe and 1 μM AtRA in TPT-NCSe-treated MDA-MB-231 cells. The data have also shown that TPT-NCSe induces apoptosis via a caspase cascade triggered by the mitochondrial apoptotic pathway. TPT-NCSe modulates the expression levels of apoptosis‑related proteins, Annexin A5, Bcl‑2 and BAX family proteins, and finally, it enhances the expression levels of its cognate nuclear receptor subtypes RXRalpha and RXRbeta.
The Clinical Evolutions of Surveillance and Violence During Three Contemporary US Crises: Opioid Overdose, COVID-19, and Racial Reckoning
Authors: Knight Kelly Ray 
Published: January 2024

AbstractIn 2020, three crises coalesced to transform the clinical care landscape of addiction medicine in the United States (US). The opioid overdose crisis (crisis #1), which had been contributing to excess US mortality for over two decades, worsened during the COVID-19 pandemic (crisis #2). The racial reckoning (crisis #3) spurred by the murder of George Floyd at the hands of police impacted clinical care, especially in safety net clinical settings where the majority of people targeted by police violence, and other forms of structural violence, receive healthcare to mend both physical and psychological wounds. Collectively, the three crises changed how providers and patients viewed their experiences of clinical surveillance and altered their relationships to the violence of US healthcare. Drawing from two different research studies conducted during the years preceding and during the COVID-19 pandemic (2017–2022) with low income, safety net patients at risk for opioid overdose and their care providers, I analyze the relationship between surveillance and violence in light of changes wrought by these three intersecting health and social crises. I suggest that shifting perceptions about surveillance and violence contributed to clinical care innovations that offer greater patient autonomy and transform critical components of addiction medicine care practice.
Noise signature identification using mobile phones for indoor localization
Authors: King Sayde , Pinder Samann , Fernandez-Lanvin Daniel , González García Cristian , De Andrés Javier , Labrador Miguel 
Published: January 2024

AbstractIndoor localization is still nowadays a challenge with room to improve. Even though there are many different approaches that have evidenced as effective, most of them require specific hardware or infrastructure deployed along the building that can be discarded in many potential scenarios. Others that do not require such on-site infrastructure, like inertial navigation-based systems, entail certain accuracy problems due to the accumulation of errors. However, this error-accumulation can be mitigated using beacons that support the recalibration of the system. The more frequently beacons are detected, the smaller will be the accumulated error. In this work, we evaluate the use of the noise signature of the rooms of a building to pinpoint the current location of a low-cost Android device. Despite this strategy is not a complete indoor localization system (two rooms could share the same signature), it allows us to generate beacons automatically. The noise recorded by the device is preprocessed performing audio filtering, audio frame segmentation, and feature extraction. We evaluated binary (determining if the ambient sound recording belonged to a specific room) and multi-class (identifying which room an ambient noise recording belonged to by comparing it amongst the remaining 18 rooms from the original 19 rooms sampled) classification methods. Our results indicate that the two Stacking techniques and K-Nearest Neighbor (KNN) machine learning classifier are the most successful methods in binary classification with an average accuracy of 99.19%, 99,08%, and 99.04%. In multi-class classification the average accuracy for KNN is 90.77%, and 90.52% and 90.15% for both Voting techniques.
A History Matching Study for the FluidFlower Benchmark Project
Authors: Tian Xiaoming , Wapperom Michiel , Gunning James , Jackson Samuel , Wilkins Andy , Green Chris , Ennis-King Jonathan , Voskov Denis 
Published: January 2024

AbstractIn this study, we conduct a comprehensive history matching study for the FluidFlower benchmark model. This benchmark was prepared and organized by the University of Bergen, the University of Stuttgart, and Massachusetts Institute of Technology, for promoting understanding of the complex physics of geological carbon storage (GCS) through in-house experiments and numerical simulations. This paper synthesizes the experiences of history matching the benchmark data encountered by the Delft-DARTS and CSIRO participants. History matching is first performed based on a low-dimensional-zonated structured model using a simple Poisson-like solver. The permeability of six facies and two faults is inferred in this stage to match the digitized concentration data. The history matching is then further enhanced to richer spatial and physical models to capture the spatial variation of permeability and buoyancy effects, using an unstructured grid. Efficient adjoint methods are used to evaluate the gradient used in the optimization of data misfits or equivalent Bayesian log-likelihoods. With efficient optimization methods available for both maximum a posteriori model inference and Randomized Maximum Likelihood methods for model uncertainty, we perform history matching using both binary and continuous concentration observations. The results show that the tracer plumes in the enriched model match the experimental plumes more accurately compared with the results from the parsimonious-zonated model. The history matching results based on the concentration observations provide more similar plume shapes compared with the case based on the binary observations. The permeability difference between the model before and after history matching reveals that the tracer plume zone and the high permeable zone are the regions of high sensitivity in terms of data misfit between the model response and observations. Surprisingly, CO$$_2$$

2

concentration plume forecasts based on these history-matched models were not especially sensitive to the improvements observed in the enhanced model.