bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimizing Cold Spray Parameters for High Entropy Alloy Coatings Using Taguchi and Box–Behnken Design Approaches for Mechanically Alloyed Powder
Authors: Sharma Deepak , Boruah Dibakor , Ameen Ahamed , Bakir Ali Alperen , Paul Shiladitya 
Published: September 2024

AbstractThe present study focused on optimizing the cold spray (CS) process parameters for depositing Fe20Cr20Mn20Ni20Co20 (Cantor alloy) coatings using mechanically alloyed (MA) powder. A two-step design of experiments approach was employed, beginning with the initial screening of input variables using the L8 Taguchi method, followed by the refinement of process parameters through the Box–Behnken design of experiments. Key performance indicators included deposition efficiency (DE), coating thickness per pass, and microstructural parameters including porosity, cracks, and interfacial defects/delamination. The study identified process gas temperature as the primary factor influencing both DE and thickness per pass. Higher gas temperature and pressure, combined with increased scanning speed, resulted in higher DE. The DE of the MA Cantor alloy powder peaked at around 14-15%, with a deposit density greater than 99% achieved at the highest process gas temperature and pressure (1000 °C and 60 bar, respectively). The average hardness of the optimal CS coating deposited using MA powder was found to be 679 ± 17 HV0.1, which is approximately 90% greater than the average hardness reported for CS coatings deposited using atomized powder.
Wat is een gezond sociaal netwerk? Reflecties bij het sociaal-netwerkadvies
Authors: Machielse Anja , van Campen Crétien , Schoenmakers Eric , van Tilburg Theo 
Published: September 2024

SamenvattingEind 2023 lanceerde het ministerie van Volksgezondheid, Welzijn en Sport een advies over het sociaal netwerk dat mensen nodig hebben om zich niet eenzaam te voelen en gezond te blijven. Het advies benadrukt het belang van het sociaal netwerk voor de gezondheid en bevat suggesties om dit te versterken. In deze bijdrage wordt het sociaal-netwerkadvies gepresenteerd. Omdat er geen eenduidige kwantitatieve drempelwaarde voor een gezond sociaal netwerk is, is gekozen voor een kwalitatieve formulering. Het sociaal-netwerkadvies is geformuleerd door de Wetenschappelijke Adviescommissie (WAC) van het programma ‘Eén tegen Eenzaamheid’. De auteurs van dit artikel zijn lid van de WAC.
Evaluating the efficacy of Rose Bengal-PVA combinations within PCL/PLA implants for sustained cancer treatment
Authors: Demartis Sara , Picco Camila J. , Larrañeta Eneko , Korelidou Anna , Islam Rayhanul , Coulter Jonathan A. , Giunchedi Paolo , Donnelly Ryan F. , Rassu Giovanna , Gavini Elisabetta 
Published: September 2024

AbstractThe current investigation aims to address the limitations of conventional cancer therapy by developing an advanced, long-term drug delivery system using biocompatible Rose Bengal (RB)-loaded polyvinyl alcohol (PVA) matrices incorporated into 3D printed polycaprolactone (PCL) and polylactic acid (PLA) implants. The anticancer drug RB’s high solubility and low lipophilicity require frequent and painful administration to the tumour site, limiting its clinical application. In this study, RB was encapsulated in a PVA (RB@PVA) matrix to overcome these challenges and achieve a localised and sustained drug release system within a biodegradable implant designed to be implanted near the tumour site. The RB@PVA matrix demonstrated an RB loading efficiency of 77.34 ± 1.53%, with complete RB release within 30 min. However, when integrated into implants, the system provided a sustained RB release of 75.84 ± 8.75% over 90 days. Cytotoxicity assays on PC-3 prostate cancer cells indicated an IC50 value of 1.19 µM for RB@PVA compared to 2.49 µM for free RB, effectively inhibiting cancer cell proliferation. This innovative drug delivery system, which incorporates a polymer matrix within an implantable device, represents a significant advancement in the sustained release of hydrosoluble drugs. It holds promise for reducing the frequency of drug administration, thereby improving patient compliance and translating experimental research into practical therapeutic applications.
Orthogonal representations of $${{\,\textrm{SL}\,}}_2(q)$$ in defining characteristic
Authors: Braun Tobias , Nebe Gabriele 
Published: September 2024

AbstractThis paper determines the types of the invariant quadratic forms over their respective (finite) fields of definition for all irreducible modules of the groups $${{\,\textrm{SL}\,}}_2(q)$$

SL

2

(
q
)

in defining characteristic. We prove that for $$q>2$$

q
>
2

any absolutely irreducible even dimensional orthogonal $${{\,\textrm{SL}\,}}_2(q)$$

SL

2

(
q
)

-module W in defining characteristic carries a split invariant quadratic form (i.e. it is of $$+$$
+
type) unless $$\dim (W) \equiv 4 \pmod {8}$$

dim
(
W
)
≡
4

(
mod

8
)

and the field of definition of W is the subfield of index 2 in $${\mathbb {F}}_q$$

F
q

; in the latter case the type of the invariant quadratic forms is −.
Modelling asymmetric and nonlinear features in the natural resource wealth-economic complexity nexus: empirical insights from Nigeria
Authors: Olaniyi Clement Olalekan , Odhiambo Nicholas Mbaya 
Published: September 2024

AbstractContrary to previous research, this study makes a unique contribution to the global discussion by incorporating asymmetric structure and nonlinearity into the analysis of how changes in natural resource wealth affect economic complexity. To achieve this objective, the study uses a nonlinear autoregressive distributed lag (ARDL) and a fully modified ordinary least squares estimator, utilizing data from Nigeria spanning the period 1984–2021. Unlike earlier studies, this study establishes robust evidence of nonlinearity and asymmetry in the sensitivity of economic complexity to changes in natural resource rents in the short and long run. The cumulative increases (positive shock components) in natural resource wealth provide strong stimuli and incentives that promote economic complexity in the short run, while the cumulative decreases (negative shock components) deteriorate economic complexity upgrades. Meanwhile, long-run estimates indicate that both positive and negative shock components are catalysts that impede Nigeria’s manufacturing structures’ ability to improve technological innovation and knowledge-based productive capacity for producing sophisticated and globally competitive exports. These findings imply that the resource curse phenomenon holds true regarding economic complexity in Nigeria in the long run. In conclusion, this study finds that Nigeria’s natural resource endowments breed complacency, racketeering, shrewdness, corrupt practices, and opportunistic behaviour, which impair innovative initiatives that spur economic complexity. This study outlines the policy implications and insights from the findings.
Transferring algebra structures on complexes
Authors: Miller Claudia , Rahmati Hamidreza 
Published: September 2024

AbstractWith the goal of transferring dg algebra structures on complexes along contractions, we introduce a new condition on the associated homotopy, namely a generalized version of the Leibniz rule. We prove that, with this condition, the transfer works to yield a dg algebra (with vanishing descended higher $$A_\infty $$

A
∞

products) and prove that it works also after an application of the Perturbation Lemma even though the new homotopy may no longer satisfy that condition. We also extend these results to the setting of $$A_\infty $$

A
∞

algebras. Then we return to our original motivation from commutative algebra. We apply these methods to find a new method for building a dg algebra structure on a well-known resolution, obtaining one that is both concrete and permutation invariant. The naturality of the construction enables us to find dg algebra homomorphisms between these as well, enabling them to be used as inputs for constructing bar resolutions.
Racial and Ethnic Disparities and the National Burden of COVID-19 on Inpatient Hospitalizations: A Retrospective Study in the United States in the Year 2020
Authors: Nguyen Amanda , Buhr Russell G. , Fonarow Gregg C. , Hsu Jeffrey J. , Brown Arleen F. , Ziaeian Boback 
Published: September 2024

Abstract
Background
Since January 2020, COVID-19 has affected more than 100 million people in the U.S. Previous studies on racial and ethnic disparities related to characteristics and outcomes of COVID-19 patients have been insightful. However, appropriate epidemiologic age-standardization of the disease burden and disparities for hospitalization data are lacking.

Objective
To identify and describe racial and ethnic disparities for primary COVID-19 hospitalizations in the U.S. in 2020.

Methods
In this nationally representative observational study, we use the National Inpatient Sample to quantify racial and ethnic disparities in COVID-19 hospitalizations. Descriptive statistics for patient characteristics, common comorbidities, age-standardized hospitalization rates, inpatient complications, and mortality among COVID-19 hospitalizations were contrasted by race and ethnicity.

Results
There were 1,058,815 primary COVID-19 hospitalizations in 2020. Of those, 47.2% were female, with median age of 66 (IQR, 54, 77). Overall inpatient mortality rate was 11.1%. When compared to White patients, Black, Hispanic, and Native American patients had higher age-standardized hospitalization rate ratios of 2.42 (95% CI 2.40–2.43), 2.26 (2.25–2.28), and 2.51 (2.46–2.56), respectively. Non-White patients had increased age-adjusted rates for procedures and complications. Factors associated with inpatient mortality include age, male sex, Hispanic or Native American race or ethnicity, lower income, Medicaid, heart failure, arrhythmias, coagulopathy, and chronic liver disease.

Conclusions
Marginalized populations in the U.S. had over twice the COVID-19 hospitalization rate relative to White patients. Age-adjusted mortality rates were highest for Black, Hispanic, and Native American patients. Careful consideration for vulnerable populations is encouraged during highly communicable respiratory pandemics.
Developing a water budget for the Amman-Zarqa basin using water accounting plus and the pixel-based soil water balance model
Authors: Amdar Nafn , Seyoum Solomon , Al-Bakri Jawad , Rutten Martine , Jewitt Graham , Mul Marloes 
Published: September 2024

AbstractWater resources assessments are essential for effective planning in water-scarce regions such as Jordan. Such assessments require sufficient data in space and time. The WaPOR-based Water Accounting Plus (WA +) framework is relevant as it integrates remote sensing data and the Pixel-Based Soil Water Balance model to simulate a basin’s water balance. However, since it relies on remote sensing, this framework only tracks water consumption in irrigated agriculture and does not consider non-irrigation water use and its return flow. This paper modifies the WaPOR-based WA + framework to include non-irrigation manmade consumption and its return flows. The modified framework provides a more comprehensive water budget for the Amman-Zarqa (AZ) basin, presented in a modified WA + resource base sheet for 2018 through 2021. The results show that water availability in the AZ basin is highly responsive to precipitation changes. Average precipitation was approximately 926 Mm3/year between 2018 and 2020, corresponding to an average available water of 485 Mm3/year. However, a reduction in average precipitation by 28% in 2021 corresponded to a reduction in available water to 243 Mm3/year. Nevertheless, substantial groundwater outflows to neighbouring basins may indicate that available water is being overestimated. Manmade consumption increased by 18% from 2018 to 2021, and the total demand exceeded the available supply by 150%. This underscores the pressing need to investigate supply augmentation and conservation methods. Future studies could focus on improving the representation of groundwater dynamics in the modified framework by improving groundwater dynamics in PixSWAB and testing the modified framework with other remote sensing datasets.
Investigation of human interaction with an augmented remote operating system for scaling in mining applications
Authors: Rafiei Shirin , Brunnström Kjell , Andersson Jonas , Sjöström Mårten 
Published: September 2024

AbstractThanks to the advent of telepresence applications, we can remotely take control and operate industrial machinery. Teleoperation removes operators from hazardous workplaces such as mining and plays an essential role in the safety of workers. In addition, augmented telepresence can introduce information that helps the user understand the remote scene. However, remote operation presents challenges since the information received is more limited than what could be perceived by being physically present, such as accurately judging depth. This study investigates how well operators interact with an augmented remote operation scaling system (AROSS) in a mining context when different computer-generated visual interfaces are provided. The system can achieve five visual interfaces: Disocclusion Augmentation view using selective content removal, Novel Perspective view generation, Lidar view, Right (Original) view, and Left (Original) view. We performed two experiments in a mine-like laboratory to analyze human interaction with the designed prototype by applying a mixed research methodology that used questionnaires, interviews, and observations. This mixed methodology consisted of quality of experience methods to discover the users’ requirements from a technological standpoint and user experience methods (i.e., user-centric approaches). We investigated 10 and 11 users’ interactions in two experimental studies. The first experiment focused on identifying small patterns (e.g., cracks in the mine wall), and the second focused on depth and three-dimensional understanding. We considered the first experiment a feasibility test to understand how to conduct the second experiment. Therefore, we designed the second test to assess the technical readiness of AROSS from the users’ perspective. The overall conclusion yields a comprehensive understanding of users’ perceptions and experiences. The quality of experience results favored Left and Right (Original) views for remote control, indicating a preference among remote operators using natural (Original) views due to their facilitation of environmental comprehension. User experience analysis revealed the reason why other views were less favored and what their potential benefits are. Specifically, Novel Perspective and Lidar views were found helpful for depth perception, and Disocclusion Augmentation view functionality could be enhanced if robot arm position tracking is enabled. These insights inform design recommendations, emphasizing the value of incorporating Disocclusion Augmentation and Novel Perspective views and suggesting improvements to enhance system usability.
Artificial Intelligence Tools Usage: A Structural Equation Modeling of Undergraduates’ Technological Readiness, Self-Efficacy and Attitudes
Authors: Falebita Oluwanife Segun , Kok Petrus Jacobus 
Published: September 2024

AbstractThis study investigates the relationship between undergraduates’ technological readiness, self-efficacy, attitude, and usage of artificial intelligence (AI) tools. The study leverages the technology acceptance model (TAM) to explore the relationships among the study’s variables. The study’s participants are 176 undergraduate students from a public university in southwestern Nigeria. The Partial Least Square Structural Equation Modeling (PLS-SEM) was used to analyze the responses from the participants. The questionnaire has six constructs measured on a 5-point Likert scale. The results show that undergraduates’ technological self-efficacy determines their usage of AI tools and perception of AI tools’ ease of use, but this does not determine their perception of the AI tools’ usefulness and attitude towards AI tools usage. Also, technological readiness was found to determine the perception of the AI tools’ usefulness, perception of AI tools’ ease of use, and technological self-efficacy among undergraduates but does not determine their usage of AI tools and attitude towards AI tools usage. In addition, undergraduates’ attitude towards AI tools was considered the primary determinant of the usage of AI tools. It was concluded that some factors determine the adoption of AI tools, which are interrelated. Educators can play a pivotal role in empowering students to harness the power of AI tools by encouraging their usage under well-coordinated guidance rather than imposing outright restrictions. By fostering AI literacy and equipping students with the knowledge and skills to navigate these innovative technologies, educators can instil the confidence and competency needed to integrate AI tools into various academic activities seamlessly.
Utility of classical insurance risk models for measuring the risks of cyber incidents
Authors: Shimizu Yasutaka , Takagami Yutaro 
Published: September 2024

AbstractWe demonstrate that the classical insurance risk models yield significant advantages in the context of cyber risk analysis. This model exhibits commendable attributes in terms of both computational efficiency and predictive capabilities. Utilizing several compound point risk models, we derive the conditional Value-at-Risk and Tail Value-at-Risk predictions for the cumulative breach size within specified time intervals. To verify the reliability of our method, we conduct backtesting exercises, comparing our predictions with actual breach sizes.
The safe-and-sustainable-by-design concept: innovating towards a more sustainable future
Authors: Soeteman-Hernández Lya G. , Apel Christina , Nowack Bernd , Sudheshwar Akshat , Som Claudia , Huttunen-Saarivirta Elina , Tenhunen-Lunkka Anna , Scheper Johanna , Falk Andreas , Valsami-Jones Eugenia , Rocca Cris , Brennan Maurice , Igartua Amaya , Mendoza Gemma , Midander Klara , Strömberg Emma , Kümmerer Klaus 
Published: September 2024

AbstractSafe-and-Sustainable-by-Design (SSbD) is a new concept proposed by the European Commission to support the urgent need to transition towards a more preventive and proactive approach in chemical and material innovation which supports a more sustainable future and in meeting the UN’s Sustainable Development Goals. SSbD provides orientation and guidance by taking a system approach. SSbD building blocks were developed: regenerative corporate and societal strategic needs (considering service and function), risk and sustainability governance, competencies, and data management. This viewpoint brings these building blocks together in a holistic way to create an innovation landscape ensuring safer and more sustainable chemicals, materials, production processes and products in science, technology, and industry; starting from ‘design’ and that is fit for supporting a sustainable future.
Estimating the parameters of epidemic spread on two-layer random graphs: a classical and a neural network approach
Authors: Backhausz Ágnes , Bognár Edit , Csiszár Villő , Tárkányi Damján , Zempléni András 
Published: September 2024

AbstractIn this paper, we propose and analyse various methods for estimating the infection parameter $$\tau $$
τ
in an SIR (susceptible-infected-recovered) epidemic spread model simulated on two-layer random graphs with a preferential attachment component. The statistics that can be used for the estimates is the number of susceptible and infected vertices. Our classical approach is based on the maximum likelihood method, while the machine learning approach uses a graph neural network (GNN). The underlying graph has a layer consisting of disjoint cliques (representing e.g. households) and a random second layer with a preferential attachment structure. Our simulation study reveals that the estimation is poorer at the beginning of the epidemic, for larger preferential attachment parameter of the graph, and for larger $$\tau $$
τ
. As for the neural networks, we find that dense networks offer better training datasets. Moreover, GNN perfomance is measured better using the $$l_2$$

l
2

loss function rather than cross-entropy.
Elevated efficiency in tartrazine removal from wastewater through boron-doped biochar: enhanced adsorption and persulfate activation
Authors: Chen Xiaojuan , Zhou Yu , He Juhua , Pillai Suresh C. , Li Ning , Xu Song , Li Jiesen , Chen Xin , Wang Hailong 
Published: September 2024

AbstractBoron-doped biochar (B-BC) was synthesized by pyrolysis using solid waste of sorghum straw as raw material. The specific surface area of B-BC increased significantly by 2.38 times compared to that of pure BC. This enhancement allowed B-BC (0.3 g L−1) to achieve complete adsorption of 10 mg L−1 tartrazine (TTZ) within 40 min. Moreover, acidic conditions were more favorable for TTZ adsorption, achieving complete removal of TTZ in only 15 min at a pH of 3.0. Interestingly, the adsorption rate of TTZ by B-BC in the presence of 0.05 M Cl− was approximately 2.12 times higher than that in the absence of Cl−. When other background electrolytes were present, excluding PO43−, complete adsorption of TTZ could also be achieved within 60 min. Thermodynamic analysis and DFT calculations described the parameters of B-BC for TTZ adsorption, including $$\Delta {\text{G}}^{\Theta }$$

Δ

G

Θ

(< 0 kJ mol−1), $$\Delta {\text{H}}^{\Theta }$$

Δ

H

Θ

(− 2.199 kJ mol−1), $$\Delta {\text{S}}^{\Theta }$$

Δ

S

Θ

(− 6.068 J mol−1 K−1), and the adsorption energy (Eads = − 0.6919 eV), indicating a tendency towards a spontaneous adsorption process. Moreover, the strong electron transfer ability of B-BC and the oxygen-containing groups promoted the activation of PDS and generation of active substances such as 1O2, O2•−, and SO4•−, thereby degrading TTZ into products with lower biological toxicity. When the added PDS was only 0.1 mM, the degradation rate constant of TTZ could reach 0.1481 min−1. Furthermore, boron doping enhanced the stability of biochar, enabling the complete removal of 10 mg L−1 TTZ even after recycling and regeneration. In summary, this study offers a practical solution for the resource utilization of solid waste sorghum straw and the treatment of TTZ-polluted wastewater.
Graphical Abstract
Effects of polymer sealant interlayer on quality of EN AW-2024-T3 aluminum alloy lap joint prepared by friction stir welding
Authors: Kubit Andrzej , Derazkola Hamed Aghajani , Myśliwiec Piotr , Szawara Paulina , Slota Ján , Macek Wojciech 
Published: September 2024

AbstractThis study investigates the influence of polymer interlayers on the mechanical properties and fracture behavior of friction stir welded EN AW-2024-T3 aluminum alloy joints. Aqualock AL 6002 (Adhesive_1) and 3M Adhesion Promoter 86A (Adhesive_2) were selected as polymeric sealants for EN AW-2024-T3 aluminum alloy interfaces. Force analysis revealed that the choice of polymer interlayer significantly affects the axial force during welding, with Adhesive_1 joints showing a significant reduction in force compared to other variants. The axial force during FSW in Adhesive_1 was 18% less than in Adhesive_2. Cross-sectional analysis revealed distinct features in joint morphology and defects, with Adhesive_1 joints exhibiting favorable thermal stability and minimal defects compared to Adhesive_2 joints. Tensile strength analysis showed a significant increase in load capacity for the Adhesive_1 (9470N) joint, while the Adhesive_2 (5030N) joint exhibited reduced strength due to inadequate heat flow. The Adhesive_1 joint showed a 93% increase in tensile strength compared to Adhesive_2. The mixing of Adhesive_2 with the joint area produced hard complex particles that reduced the strength of the final joint. Fracture analysis revealed complex fracture mechanisms, with Adhesive_1 joints exhibiting ductile fracture zones and Adhesive_2 joints exhibiting quasi-cleavable intergranular cracking. Microhardness distribution analysis showed variation between the joint variants, with Adhesive_2 joints showing higher microhardness in the weld nugget.