bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unravelling the influence of heterogeneities and abstraction on groundwater flow and solute transport in a fractured carbonate aquifer, Sicily, Italy
Authors: G. Pappalardo , I. Borsi , R. Rossetto , G. Tranchina , M. Bongiovanni , M. Farina , S. Mineo 
Published: May 2024

AbstractThe migration of a groundwater contaminant plume consisting of light nonaqueous phase liquids (LNAPLs) along the Ionian coastline of Sicily, Italy, has been reported to follow a trajectory that is inconsistent with the regional hydraulic gradient. The influence of several faults affecting the fractured carbonate bedrock aquifer, and groundwater abstraction from a well, were hypothesized to be responsible for the anomalous trajectory of the contaminant plume. A conceptual hydrogeological model was developed for the study area that incorporated structural information derived from geophysical surveys and the mapping of fractures in bedrock outcrops. This conceptual model was incorporated into numerical groundwater flow and solute transport models to simulate the groundwater transport of the light nonaqueous phase liquids. Four model scenarios representing different levels of complexity were tested to assess the relative influence of geological heterogeneity and groundwater abstraction on the migration of the contaminant plume. Results show that underground major discontinuity systems, invoking the presence of the faults in the model domain accounted for the observed migration of the contaminant plume, act as conduits for groundwater flow. Conversely, groundwater abstraction from a well was found to result in relatively minor, localized impacts to the migration of the contamination plume. This study demonstrates the importance of incorporating geological heterogeneity into groundwater modelling and environmental risk assessments associated with the storage of LNAPLs.
DTP: learning to estimate full-body pose in real-time from sparse VR sensor measurements
Authors: Zeng Qiang , Zheng Gang , Liu Qian 
Published: May 2024

AbstractFor virtual reality (VR) applications, estimating full-body pose in real-time is becoming increasingly popular. Previous works have reconstructed full-body motion in real time from an HTC VIVE headset and five VIVE Tracker measurements by solving the inverse kinematics (IK) problem. However, an IK solver may yield unnatural poses and shaky motion. This paper introduces Deep Tracker poser (DTP): a method for real-time full-body pose estimation in VR. This task is difficult due to the ambiguous mapping from the sparse measurements to full-body pose. The data obtained from VR sensors is calibrated, normalized and fed into the deep neural networks (DNN). To learn from sufficient data, we propose synthesizing a VR sensor dataset called AMASS-VR from the AMASS, a collection of various motion capture datasets. Furthermore, feet tracking loss is a common problem of VIVE Tracker. To improve the accuracy and robustness of DTP to the occlusion noise, we simulate the occlusion noise by Gaussian random noise. Then we synthesize an occlusion dataset AMASS-OCC and fine-tune DTP on that. We evaluate DTP by comparing with other popular methods in terms of the accuracy and computational cost. The results indicate that DTP outperforms others in terms of the positional error (1.04 cm) and rotational error (4.22 °). The quantitative and qualitative results show that DTP reconstructs accurate and natural full-body pose even under serious feet occlusion, which indicates the superiority of the DTP in modelling the mapping from sparse joint data to the full-body pose.
Human atherosclerotic plaque transcriptomics reveals endothelial beta-2 spectrin as a potential regulator a leaky plaque microvasculature phenotype
Authors: Rademakers Timo , Manca Marco , Jin Han , Orban Tanguy , Perisic Ljubica Matic , Frissen Hubertus J. M. , Rühle Frank , Hautvast Petra , van Rijssel Jos , van Kuijk Kim , Mees Barend M. E. , Peutz-Kootstra Carine J. , Heeneman Sylvia , Daemen Mat J. A. P. , Pasterkamp Gerard , Stoll Monika , van Zandvoort Marc A. M. J. , Hedin Ulf , Dequiedt Franck , van Buul Jaap D. , Sluimer Judith C. , Biessen Erik A. L. 
Published: May 2024

AbstractThe presence of atherosclerotic plaque vessels is a critical factor in plaque destabilization. This may be attributable to the leaky phenotype of these microvessels, although direct proof for this notion is lacking. In this study, we investigated molecular and cellular patterns of stable and hemorrhaged human plaque to identify novel drivers of intraplaque vessel dysfunction. From transcriptome data of a human atherosclerotic lesion cohort, we reconstructed a co-expression network, identifying a gene module strongly and selectively correlated with both plaque microvascular density and inflammation. Spectrin Beta Non-Erythrocytic 1 (sptbn1) was identified as one of the central hubs of this module (along with zeb1 and dock1) and was selected for further study based on its predominant endothelial expression. Silencing of sptbn1 enhanced leukocyte transmigration and vascular permeability in vitro, characterized by an increased number of focal adhesions and reduced junctional VE-cadherin. In vivo, sptbn1 knockdown in zebrafish impaired the development of the caudal vein plexus. Mechanistically, increased substrate stiffness was associated with sptbn1 downregulation in endothelial cells in vitro and in human vessels. Plaque SPTBN1 mRNA and protein expression were found to correlate with an enhanced presence of intraplaque hemorrhage and future cardiovascular disease (CVD) events during follow-up. In conclusion, we identify SPTBN1 as a central hub gene in a gene program correlating with plaque vascularisation. SPTBN1 was regulated by substrate stiffness in vitro while silencing blocked vascular development in vivo, and compromised barrier function in vitro. Together, SPTBN1 is identified as a new potential regulator of the leaky phenotype of atherosclerotic plaque microvessels.
Stress testing for IInd pillar life-cycle pension funds using hidden Markov model
Authors: Kabašinskas Audrius , Kopa Miloš , Šutienė Kristina , Lakštutienė Aušrinė , Malakauskas Aidas 
Published: May 2024

AbstractThis paper presents a stress testing technique based on a hidden Markov regime switching model and scenario generations. Firstly, we assume that investor’s risk preferences and beliefs are primarily observed in main world indices and then transmitted to other markets such as IInd pillar life-cycle pension funds. This enables both regime (market state) identification and regime-switching detection. Second, we apply stress to the transition matrix by increasing probabilities of moving to a worse market state, i.e., we increase the transition probabilities on the upper-right side of the main diagonal and decrease the diagonal probabilities correspondingly. Third, future scenarios (evolution) of returns of pension funds are generated using stressed transition matrices and basic risk and performance measures of the final wealth are presented. Finally, three different strategies for pension managers are considered and compared to each other. The results show how the best strategy depends on the stress level.
Simulated plant-mediated oxygen input has strong impacts on fine-scale porewater biogeochemistry and weak impacts on integrated methane fluxes in coastal wetlands
Authors: Zhou Yongli , O’Meara Teri , Cardon Zoe G. , Wang Jiaze , Sulman Benjamin N. , Giblin Anne E. , Forbrich Inke 
Published: May 2024

AbstractMethane (CH4) emissions from wetland ecosystems are controlled by redox conditions in the soil, which are currently underrepresented in Earth system models. Plant-mediated radial oxygen loss (ROL) can increase soil O2 availability, affect local redox conditions, and cause heterogeneous distribution of redox-sensitive chemical species at the root scale, which would affect CH4 emissions integrated over larger scales. In this study, we used a subsurface geochemical simulator (PFLOTRAN) to quantify the effects of incorporating either spatially homogeneous ROL or more complex heterogeneous ROL on model predictions of porewater solute concentration depth profiles (dissolved organic carbon, methane, sulfate, sulfide) and column integrated CH4 fluxes for a tidal coastal wetland. From the heterogeneous ROL simulation, we obtained 18% higher column averaged CH4 concentration at the rooting zone but 5% lower total CH4 flux compared to simulations of the homogeneous ROL or without ROL. This difference is because lower CH4 concentrations occurred in the same rhizosphere volume that was directly connected with plant-mediated transport of CH4 from the rooting zone to the atmosphere. Sensitivity analysis indicated that the impacts of heterogeneous ROL on model predictions of porewater oxygen and sulfide concentrations will be more important under conditions of higher ROL fluxes or more heterogeneous root distribution (lower root densities). Despite the small impact on predicted CH4 emissions, the simulated ROL drastically reduced porewater concentrations of sulfide, an effective phytotoxin, indicating that incorporating ROL combined with sulfur cycling into ecosystem models could potentially improve predictions of plant productivity in coastal wetland ecosystems.
Selling Who You Know: How We Justify Sharing Others’ Data
Authors: Ruckelshausen Susanne , Kamleitner Bernadette , Mitchell Vincent 
Published: May 2024

Abstract
Many apps request access to users’ contacts or photos and many consumers agree to these requests. However, agreeing is ethically questionable as it also gives apps access to others’ data. People thus regularly infringe each other’s information privacy. This behavior is at odds with offline practices and still poorly understood. Introducing a novel application of the theory of neutralization, we explore how people justify the giving away of others’ data and the emerging norms surrounding this behavior. To obtain a deeper understanding of the potentially ambiguous norms surrounding the behavior, we investigate how people justify, i.e., neutralize, the behavior from both offender and victim perspectives. Across four studies, offenders appear more likely to admit to moral wrongdoing than victims assume. This suggests moral disagreement between offenders and victims. The discrepancy appears to be reasonably robust across different samples, apps and whether the other is identified, but diminishes when people learn how easily others’ data could be protected. These insights offer suggestions for businesses, consumers and public policy.
Climate change, corporate risk-taking, and financialization: evidence from Chinese A-share non-financial listed companies
Authors: Zheng Lin , An Qiguang , Yang Mu 
Published: May 2024

AbstractClimate change-induced risks, such as global warming, can affect the economic development of entities and, consequently, the stability of financial markets. Businesses are progressively making the transition to green in order to lessen the negative consequences of climate threats. This study examines the relationship between corporate risk-taking (CRISK) and financialization (FIN) in light of climate change. The impact of business risk-taking on financialization is experimentally investigated through the transmission chain of “CRISK - enterprise value – FIN” using a fixed-effects model. The study also analyzes the moderating effect of climate change on the direct and indirect channels of climate change by using “temperature” and “investors’ concern about climate,” respectively. In addition, the empirical results are tested for robustness using propensity score matching and an instrumental variable method. This study’s findings reveal the following key insights. First, CRISK significantly enhances FIN by improving firm value. Second, enterprises with high financing constraints and manufacturing enterprises are more likely to have a positive correlation between CRISK and FIN. Third, the relationship between CRISK and FIN is enhanced by the direct transmission channel of increasing climate risk, but the indirect transmission channel is not significant. This study proposes policy recommendations to address the effect of climate risk on CRISK and FIN. Among these suggestions are the prudent distribution of financial resources among enterprises according to their level of risk-taking and the reinforcement of regulatory authorities’ financial oversight of businesses with high financing constraints and the manufacturing sector. By implementing these policies, companies can better manage climate-related risks and contribute to financial stability.
The best linear unbiased prediction (BLUP) method as a tool to estimate the lifetime risk of pancreatic ductal adenocarcinoma in high-risk individuals with no known pathogenic germline variants
Authors: Cristina-Marianini-Rios  , Sanchez María E. Castillo , de Paredes Ana García García , Rodríguez Mercedes , Barreto Emma , López Jorge Villalón , Fuentes Raquel , Beltrán María Muñoz , Sanjuanbenito Alfonso , Lobo Eduardo , Caminoa Alejandra , Ruz-Caracuel Ignacio , Durán Sergio López , Olcina José Ramón Foruny , Blázquez Javier , Sequeros Enrique Vázquez , Carrato Alfredo , Ávila Jose Carlos Martínez , Earl Julie 
Published: May 2024

AbstractPancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related death in the Western world. The number of diagnosed cases and the mortality rate are almost equal as the majority of patients present with advanced disease at diagnosis. Between 4 and 10% of pancreatic cancer cases have an apparent hereditary background, known as hereditary pancreatic cancer (HPC) and familial pancreatic cancer (FPC), when the genetic basis is unknown. Surveillance of high-risk individuals (HRI) from these families by imaging aims to detect PDAC at an early stage to improve prognosis. However, the genetic basis is unknown in the majority of HRIs, with only around 10–13% of families carrying known pathogenic germline mutations. The aim of this study was to assess an individual’s genetic cancer risk based on sex and personal and family history of cancer. The Best Linear Unbiased Prediction (BLUP) methodology was used to estimate an individual’s predicted risk of developing cancer during their lifetime. The model uses different demographic factors in order to estimate heritability. A reliable estimation of heritability for pancreatic cancer of 0.27 on the liability scale, and 0.07 at the observed data scale as obtained, which is different from zero, indicating a polygenic inheritance pattern of PDAC. BLUP was able to correctly discriminate PDAC cases from healthy individuals and those with other cancer types. Thus, providing an additional tool to assess PDAC risk HRI with an assumed genetic predisposition in the absence of known pathogenic germline mutations.
Top degree $$\ell ^p$$-homology and conformal dimension of buildings
Authors: López Neumann Antonio 
Published: May 2024

AbstractFor a non-compact finite thickness building whose Davis apartment is an orientable pseudomanifold, we compute the supremum of the set of $$p>1$$

p
>
1

such that its top dimensional reduced $$\ell ^p$$

ℓ
p

-cohomology is nonzero. We adapt the non-vanishing assertion of this result to any finite thickness building using the Bestvina realization. Using similar techniques, we generalize bounds obtained by Clais on the conformal dimension of some Gromov-hyperbolic buildings to any such building.
Screening protocol for freshwater filamentous macroalgae bioremediation of primary municipal wastewater
Authors: Novak Indira N. , Magnusson Marie , Craggs Rupert J. , Lawton Rebecca J. 
Published: May 2024

AbstractA screening protocol was developed and applied to isolate and select cultivars of freshwater filamentous macroalgae for year-round monoculture cultivation and nutrient bioremediation of primary municipal wastewater. The screening protocol is a step-by-step guide to identify robust cultivars which possess key attributes of competitive dominance, high biomass productivity and bioremediation performance under local seasonal and extreme conditions. Forty-four mixed samples of freshwater filamentous macroalgae were collected during summer and winter from a range of local aquatic environments. Eleven isolated cultivars were grown in primary treated municipal wastewater and their biomass productivity and bioremediation performance under local ambient (summer and winter), extreme summer (max. summer) and winter (min. winter) conditions were assessed. Extreme conditions proved to be an important determining factor for cultivar selection as biomass productivity and bioremediation performance significantly declined under min. winter conditions. However, biomass productivity was not directly related to bioremediation performance, as cultivars with low growth rates maintained high nutrient removal rates under min. winter conditions. Top performing cultivars were Klebsormidium sp. (KLEB B) which reduced total ammoniacal-N concentrations by 99.9% to 0.01 mg L-1 (± 0.01 SE), Oedogonium sp. (OEDO D) which reduced nitrate-N concentrations by 90.2% to 0.08 mg L-1 (± 0.7 SE) and Rhizoclonium sp. which reduced phosphate concentrations by 98.7% to 0.02 mg L-1 (± 0.01 SE). Based on overall biomass productivity and bioremediation performance across seasonal and extreme conditions Klebsormidium sp. (KLEB B), Stigeoclonium sp. (STIG A) and Ulothrix sp. were identified as top performing cultivars suitable for the nutrient bioremediation of primary municipal wastewater.
Flexible and robust detection for assembly automation with YOLOv5: a case study on HMLV manufacturing line
Authors: Simeth Alexej , Kumar Atal Anil , Plapper Peter 
Published: May 2024

AbstractAutomating assembly processes in High-Mix, Low Volume (HMLV) manufacturing remains challenging, especially for Small and Medium-sized Enterprises (SMEs). Consequently, many companies still rely on a significant amount of manual operations with an overall low degree of automation. The emergence of artificial intelligence-based algorithms offers potential solutions, enabling assembly automation compatible with multiple products and maintaining overall production flexibility. This paper investigates the application of the YOLO (You Only Look Once) object detection algorithm in an HMLV production line within an SME. The performance of the algorithm was tested for different cases, namely, (a) on different products having similar product features, (b) on completely new products, and (c) under different lighting conditions. The algorithm achieved precision and recall greater than 98$$\%$$
%
and mAP50:95 greater than 97$$\%$$
%
.
Effects of Initial versus Frequent Preference Assessments on Skill Acquisition
Authors: León Yanerys , Campos Claudia , Baratz Stephania , Gorman Courtney , Price Amanda , DeLeon Iser 
Published: May 2024

AbstractPrevious researchers have demonstrated that using stimuli identified via daily brief preference assessments may produce more responding under concurrent-schedule arrangements than using stimuli identified via lengthy, pre-treatment preference assessments (DeLeon et al., 2001). To date, this has not been evaluated within the context of skill acquisition. Thus, the extent to which conducting daily brief preference assessments impacts the rate of skill acquisition during discrete trial instruction (DTI) remains unknown. The purpose of this study was to evaluate how frequent, pre-session preference assessments, influence the rate of skill acquisition relative to an initial preference assessment during DTI sessions for three children with autism spectrum disorder (ASD). Two of the three children acquired the targeted skills faster in the frequent preference assessment condition. The third participant showed no difference in the rate of skill acquisition.
Sorption Behavior of Zirconium Ions from Aqueous Solutions Using Different Inorganic Sorbents Based on Titanate
Authors: Abass M. R. , Ibrahim A. B. , Abou-Mesalam M. M. 
Published: May 2024

AbstractIn this article, we explore the sorption behavior of Zr(IV) ions by lithium titanate (LiTi), magnesium titanate (MgTi), and lithium magnesium titanate (LiMgTi) sorbents. These sorbents, fabricated using the precipitation method, were used for the Zr(IV) sorption from aqueous solutions. We employed various analytical tools, including XRD, FT-IR, BET, SEM, and EDX, to examine the prepared sorbents’ structure, morphology, and functional groups. We also studied the effect of pH, time, initial metal concentrations, temperature, and interfering species on sorption. The kinetic data obey pseudo-first-order. Many isotherm models were utilised to investigate equilibrium data. The results of thermodynamic functions show an endothermic and spontaneous sorption process. Finally, the influence of the interfering species reveals that as the concentration of CaCl2, MgCl2, and NaCl increases, the Zr(IV) adsorption rate decreases. The investigation demonstrated that LiMgTi is suitable for retaining Zr(IV) from aqueous solutions and could purify effluent polluted with Zr(IV) ions.
14N break-up α emission with 59Co, 93Nb, and 197Au targets at an incident energy of 250 MeV
Authors: Bhuptani C. , Patel D. , Ojha V. K. , Mukherjee S. 
Published: May 2024

AbstractThe emission of α particles has been analyzed using a 14N projectile beam on 59Co, 93Nb, and 197Au targets at an incident energy of 250 MeV, in the angular range from 8° to 40°. The estimated α particles from the break-up channel and the pre-equilibrium mode were compared with the experimentally measured inclusive double differential cross sections at various angles at 250 MeV beam energy. The present results indicate that at such a high incident energy, a significant contribution to the α-particle emission comes from direct reactions, which are dominant at forward angles. At larger emission angles, non-equilibrium and evaporation processes increase and compete with direct reactions.
Lessons learned from four recent Turkish earthquakes: Sivrice-Elazığ, Aegean Sea, and Dual Kahramanmaraş
Authors: Tunç Gökhan , Mertol Halit Cenan , Akış Tolga 
Published: May 2024

AbstractTürkiye is located in an earthquake-prone region where almost all of its population resides in risky areas. In the past 100 years, there has been a strong earthquake every two years and a major one every 3 years. This study investigates the impact of four recent earthquakes, that occurred between 2020 and 2023, on reinforced concrete (RC) buildings. The first, Sivrice-Elazığ, struck the eastern part of Türkiye on January 24, 2020, with a moment magnitude of Mw = 6.8. The second, the Aegean Sea, hit the western part of the country on October 30, 2020, with an Mw of 6.6. The third and fourth are the February 6, 2023 dual Kahramanmaraş earthquakes with Mws of 7.7 and 7.6, which struck the eastern part of Türkiye approximately 9 h apart. Immediately following these earthquakes, a technical team investigated each of the damaged areas. This study summarizes their findings on RC buildings. It was discovered that the majority of the collapsed or severely damaged RC buildings were constructed before 2000. The main reasons for this included technological limitations, specifically on producing high-quality concrete, as well as a lack of public policies and enforced laws in the construction sector to maintain an acceptable international standard. Furthermore, the damage patterns of buildings from these four earthquakes indicated poor workmanship, low material quality, improper structural framing, a common appearance of soft and weak stories, the inadequate use of shear walls, and defective reinforcement configuration. The significance of soil studies and the enforcement of building inspections are also discussed, along with the earthquake codes. The study concludes that the maximum peak ground accelerations from the dual Kahramanmaraş earthquakes were almost triple the code-prescribed values. Therefore, it is recommended that the current mapped spectral acceleration values be revised and that buildings constructed before 2000 should be prioritized while determining their structural performances.