bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Study of Fractional Order Financial Crime Model Using the Gegenbauer Wavelet Collocation Method
Authors: G Manohara , S Kumbinarasaiah 
Published: December 2024

AbstractThe manuscript investigates the numerical approximation of the fractional mathematical model of the financial crime population dynamics by the Gegenbauer wavelet collocation method. The study aims to enhance the accuracy and efficiency of solving the underlying differential equations that describe these phenomena by utilizing the proposed technique. The financial crime model is a nonlinear coupled system of ordinary differential equations. Using the Gegenbauer wavelets, the novel operational matrices of integration are created. A nonlinear system of ordinary differential equations are transformed into a system of algebraic equations using the characteristics of the Gegenbauer wavelet expansions and the operational matrix of integration, which speeds up processing. Then, this system of algebraic equations is solved using the Newton‐iterative technique to find the unknown Gegenbauer coefficients that help to obtain the approximate solution for the system. A numerical illustration is presented to show the efficacy and precision of the approach. The numerical results obtained from the projected approach are compared with the existing methods, such as NDSolve and Runge Kutta methods. These results show that the projected scheme is simple, reliable, and resilient. The findings suggest that this approach can be a powerful tool for researchers and practitioners in the financial sector, aiding in developing crime prevention and intervention strategies. The study concludes with suggestions for future research directions.
Comparing kinetic methods for ball‐mill grinding: Molecular weight versus refractive index‐based methods
Authors: Cha Somin , Park Byeongyeol , Kim Tae‐Hyun , Peterson Gregory I. 
Published: December 2024

AbstractPolymers are commonly subjected to ball‐mill grinding (BMG) to induce chain scission. Milling and polymer parameters can influence the kinetics of degradation, and various kinetic methods have been employed to study this process. The most common methods include molecular weight models (fitting the decrease in molecular weight with milling time) and refractive index (RI)‐based methods (such as the Florea method, which fits the decrease in RI signal with milling time). In this report, we compare the rate constant trends obtained from three different molecular weight models and the Florea method to provide a deeper understanding of how the kinetic method employed in kinetic studies influences the observed reactivity trends. Specifically, each kinetic method was applied to BMG‐induced degradation data from polystyrene (PS) and poly(lactide) (PLA) of varying initial molecular weight. Each kinetic method produced different rate constant trends (e.g., initial molecular weight vs. rate constant), which could also be influenced by changing the milling duration. Molecular weight models or the Florea method were better suited with longer or shorter milling durations, respectively. Furthermore, the rate constant trends for PS and PLA were relatively consistent if compared with the same kinetic method. We expect that this work will help guide future BMG‐based degradation kinetics studies.
MARVEL Analysis of High‐Resolution Rovibrational Spectra of 16O13C18O
Authors: Azzam Ala'a A. A. , Tennyson Jonathan , Yurchenko Sergei N. , Furtenbacher Tibor , Császár Attila G. 
Published: December 2024

ABSTRACTA large set of validated experimental transitions and empirical rovibrational energy levels are reported for the fifth most abundant carbon dioxide isotopologue, 16O13C18O (in a shorthand notation, 638). Validation of the transitions and determination of the empirical energy levels are based on a compiled and carefully checked dataset, collected from 35 literature sources, containing 12 348/7432 measured/unique lines in the wavenumber range of 578–9318 cm−1. The MARVEL (Measured Active Rotational‐Vibrational Energy Levels) protocol, built upon the theory of spectroscopic networks, not only validates the vast majority of the measured transitions, but also yields 3975 empirical rovibrational energy levels, with uncertainty estimates compliant with the experimental uncertainties of the transitions.
Analysis of the Ocean–Atmosphere Interface in the Brazil Current Region
Authors: Machado Raquel Machado , da Silva Lindemann Douglas , de Mendonça Luís Felipe Ferreira , de Freitas Rose Ane Pereira , Reis Ítalo Seilhe , Alonso Marcelo Felix 
Published: December 2024

ABSTRACTThe Brazil current (BC) is a westerly current that flows south along the Brazilian coast, being part of the Southern Brazilian Continental Shelf (SBCS). Recent studies have indicated a trend towards intensification and a shift to the south of the region where this current predominates. We analysed the seasonality of the relationship between atmospheric variables and sea surface temperature (SST) with potential trends and changes in the spatio‐temporal pattern of these variables from 1980 to 2020 over the BCs area in the South Atlantic Ocean. For this purpose, monthly data on SST, air temperature at 2 m above the surface (T2M), mean sea level pressure (MSLP), zonal wind (U10) and meridional wind (V10), obtained from ERA5 reanalysis, were used. Descriptive statistical analyses, trends using the Mann‐Kendall test, correlation matrices and Pettitt's test revealed a significant spatial correlation between the variables, with temporal trends of variation, especially over the BCs area. The meridional (zonal) wind predominantly exhibited a north–south (west–east) direction, supporting the hypothesis that the study region was displaced. Additionally, statistically significant positive trends were observed for SST (0.02°C ∙ dec−1 in austral autumn, winter and spring and 0.01°C ∙ dec−1 in austral summer), T2M (0.02°C ∙ dec−1 in austral winter and spring), MSLP (0.05°C ∙ dec−1 in austral autumn) and negative for U10 (−0.01°C ∙ dec−1 in austral spring). Pettitt's test results confirm significant changes in the behaviour of most analysed variables from the late 1990s to the early 2000s. The post‐breakpoint periods of the variables consistently showed above‐average values compared to the pre‐breakpoint periods, supporting positive upward trends consistent with literature findings. In particular, they highlight the notable upward slope in SST in the BC region.
Growth Analysis of Glyphosate‐Resistant and Susceptible Amaranthus palmeri Biotypes
Authors: de Souza Rodrigues Juliana , Basinger Nicholas T. , Leon Ramon G. , Bacha Allan L. , da Silva Santos Renata Thaysa , Eason Kayla M. , Shilling Donn , Grey Timothy L. 
Published: December 2024

ABSTRACTThis study examined the growth parameters of both glyphosate‐susceptible and glyphosate‐resistant biotypes of Amaranthus palmeri, designated as GA2005 and GA2017, respectively. A two‐year microplot field study was conducted to assess their growth characteristics. Scheduled destructive harvests on named harvest days (HD) were conducted to collect measurements for further calculation of net assimilation rate (NAR; g m−2 day−1), specific leaf area (SLA), leaf weight ratio (LWR), stem‐to‐leaf ratio (SLR), leaf area index (LAI), leaf area ratio (LAR; cm2 g−1), leaf area duration (LAD; days), relative growth rate (RGR; g.g−1 day−1) and plant volume (m3). In addition, stem diameter, number of leaves, and Chlorophyll content (μmol m2) were determined. The main objective was to identify growth parameters that differentiate biotypes along the plant life cycle. While certain growth parameters showed no variation among biotypes, differences in leaf area index (LAI) over HD and chlorophyll content and leaf area duration (LAD) were observed as the main effects. Glyphosate‐resistant biotypes exhibited higher LAD and chlorophyll content, potentially conferring a competitive advantage, especially in heavily used glyphosate environments. The study highlights the complexity of intraspecific genetic differentiation, adaptation, and environmental factors affecting A. palmeri. It may offer insights into biotype distinction and resistance spread while advancing our comprehension of species adaptation and growth strategies for enhanced control.
Effects of polyol plasticizers on morphological characteristics and performance of injection‐molded polylactide/thermoplastic starch blends
Authors: Inta Orathai , Yoksan Rangrong 
Published: December 2024

AbstractThermoplastic starch (TPS)‐based blends have attracted increased attention as a substitute for imperishable and non‐renewable plastics in various applications including packaging due to price competitiveness and being environmentally benign. However, the plasticizer type and quantity used to prepare TPS affect both the processability and performance of the final blends. Herein, TPS materials plasticized with both single (glycerol, xylitol, and sorbitol) and mixed polyol plasticizers (glycerol/xylitol and glycerol/sorbitol) were prepared and then blended with polylactide with a PLA:TPS weight fraction of 60:40. The effects of polyol plasticizers on the morphology and performance of injection‐molded PLA/TPS blends were discussed. Melt flowability and elongation of the glycerol‐plasticized PLA/TPS blend were much higher than those of other blends. In contrast, the blends plasticized with xylitol or sorbitol showed augmented tensile strength and Young's modulus, improved thermal stability, and reduced starch retrogradation. The reduction of TPS phase size and narrower size distribution were observed for blends plasticized with a higher fraction of xylitol or sorbitol. Crystallinity and cold crystallization temperature of PLA in the blends increased with increasing xylitol or sorbitol fraction. The obtained PLA/TPS blends have great potential for manufacturing renewable and biodegradable injection‐molded articles with tunable properties by incorporating appropriate polyol plasticizers.Highlights
Injection‐molded polylactide/thermoplastic starch (PLA/TPS) blends are prepared.
Glycerol (G), xylitol (X), sorbitol (S), and their mixtures are used as plasticizers.
Higher X or S fraction increases strength, modulus, and thermal stability of blends.
Higher X or S fraction decreases TPS phase size and starch retrogradation in blends.
Higher X or S fraction increases PLA's Tcc and crystallinity in the blends.
An investigation of the owner‐ and pet‐related factors that may affect the use of alternative feeding practices in dogs and cats in Hungary
Authors: Vékony Blanka , Bodor Zsanett , Veres Dániel Sándor , Vajdovich Péter , Mák Erzsébet 
Published: December 2024

AbstractBackgroundAlternative feeding practices have become increasingly popular among companion animal owners. We sought to identify possible factors behind the choice of alternative feeding types.MethodsA cross‐sectional study was performed with Hungarian pet owners. Descriptive data analysis and logistic regression models were undertaken to determine factors that may increase the likelihood of adopting alternative feeding practices.ResultsIn total, 1007 pet owners completed the questionnaire, of which 789 were dog owners and 218 were cat owners. The type of settlement was identified as a possible factor influencing the choice of application of alternative feeding patterns for dogs and cats. In the case of dogs, the owner's diet variable showed significantly increased odds of choosing an alternative feeding pattern where the owner followed an alternative diet. For cats, the owner's diet did not have a significant effect on choosing alternative feeding practices for these pets.ConclusionsOwners who followed an alternative diet were more likely to choose an alternative feeding pattern for their dogs but not for their cats. Further study is required to identify additional factors that may influence the owners’ choice of feeding practices and to more widely investigate the feeding habits of cat owners.
Psychosocial predictors of short-term glucose among people with diabetes: A narrative review
Authors: Horner Fiona S. , Helgeson Vicki S. 
Published: December 2024

AbstractType 1 and type 2 diabetes are metabolic disorders that require one to manage one’s blood glucose levels on a daily basis through a series of behaviorally complex tasks. Research shows that psychosocial factors, including mood, stress, and social relationships, have a significant influence on one’s ability to maintain these disease management routines and achieve healthy blood glucose levels. However, researchers have typically approached these questions from a between-person perspective. Here, we argue for greater consideration of short-term, within-person links of psychosocial factors—including mood, stress, and social interactions—to glucose outcomes. Drawing from existing social and health psychology theories, we put forth an organizing theoretical framework describing how psychosocial experiences may operate on glucose outcomes over subsequent hours. We then review the small but burgeoning literature of intensive longitudinal studies that have examined the short-term effects of negative affect, positive affect, stress, and social interactions on glucose outcomes. Findings showed somewhat stronger links for negative affect and stress compared to positive affect and social interactions, but studies varied greatly in their methodologies, making direct comparisons challenging. A number of findings, particularly in the social interaction literature, depended on dispositional or contextual factors, further complicating interpretation. There was little investigation of the mechanistic pathways that may connect psychosocial factors to glucose outcomes, and few studies conducted lagged analyses to probe the directionality of these links. We conclude by proposing best practices for future research that will address the key weaknesses in the extant literature.
Soil Erosion Prediction in Western Kazakhstan Through Deep Learning with a Neural Network Approach to LS-Factor Analysis
Authors: Seitkazy Moldir , Beisekenov Nail , Rakhimova Moldir , Tokbergenova Aigul , Zulpykharov Kanat , Kaliyeva Damira , Taukebayev Omirzhan , Levin Eugene 
Published: December 2024

AbstractWith the rapid shifts in environmental conditions, accurately predicting soil erosion has become crucial for the sustainable management of land resources. This study introduces a deep learning-based approach to forecast soil erosion risks in Western Kazakhstan up to 2030, focusing on the LS factor defined by the Universal Soil Loss Equation (USLE). High-resolution digital elevation models (DEMs) from ASTER GDEM and historical data on climate and land use were utilized to train a convolutional neural network (CNN), enabling projections of future LS-factor changes and the corresponding erosion risks. To further improve the accuracy of LS-factor calculations, the System for Automated Geoscientific Analyses (SAGA) was applied using a multiple-flow algorithm. The results forecast a significant rise in erosion risk by 2030, with areas having LS values between 8 and 24 expected to increase by 10%, and those with LS values above 24 by 0.05%, potentially affecting an additional 24,000 km2. The model achieved a 92% accuracy rate, underscoring the effectiveness of deep learning in environmental risk analysis. The integration of SAGA results provides a more detailed understanding of the erosion processes, enhancing the precision of the predictions.
Twin Nucleation Mechanism from a Screw Dislocation in BCC-Fe
Authors: Veerababu J. , Sainath G. , Nagesha A. 
Published: December 2024

Abstract
Twinning is a predominant deformation mechanism in nanocrystalline materials. The present study uses molecular dynamics simulations to address the feasibility of forming a twin in BCC-Fe via the three-fold dissociation of a screw dislocation, as proposed by Sleeswyk. Gliding of the screw dislocation at lower shear strain rates and formation of the twin at higher shear strain rate via two-fold dissociation was observed. The gliding of the screw dislocation occurred through the kink-pair-assisted mechanism. Three-fold dissociation on three co-zonal {110} planes with the trailing stacking faults was noticed only at temperatures below or equal to 50 K. However, this dissociation failed to support Sleeswyk’s reaction explicitly. Sleeswyk’s reaction may occur through a spontaneous collapsing of the three-fold dissociation at the time of dissociation and proceeds with twinning. Interatomic potentials, which can predict the three-fold dissociation, were presented.
Skin-Friendly Large Matrix Iontronic Sensing Meta-Fabric for Spasticity Visualization and Rehabilitation Training via Piezo-Ionic Dynamics
Authors: Xu Ruidong , Xu Tong , She Minghua , Ji Xinran , Li Ganghua , Zhang Shijin , Zhang Xinwei , Liu Hong , Sun Bin , Shen Guozhen , Tian Mingwei 
Published: December 2024

AbstractRehabilitation training is believed to be an effectual strategy that can reduce the risk of dysfunction caused by spasticity. However, achieving visualization rehabilitation training for patients remains clinically challenging. Herein, we propose visual rehabilitation training system including iontronic meta-fabrics with skin-friendly and large matrix features, as well as high-resolution image modules for distribution of human muscle tension. Attributed to the dynamic connection and dissociation of the meta-fabric, the fabric exhibits outstanding tactile sensing properties, such as wide tactile sensing range (0 ~ 300 kPa) and high-resolution tactile perception (50 Pa or 0.058%). Meanwhile, thanks to the differential capillary effect, the meta-fabric exhibits a “hitting three birds with one stone” property (dryness wearing experience, long working time and cooling sensing). Based on this, the fabrics can be integrated with garments and advanced data analysis systems to manufacture a series of large matrix structure (40 × 40, 1600 sensing units) training devices. Significantly, the tunability of piezo-ionic dynamics of the meta-fabric and the programmability of high-resolution imaging modules allow this visualization training strategy extendable to various common disease monitoring. Therefore, we believe that our study overcomes the constraint of standard spasticity rehabilitation training devices in terms of visual display and paves the way for future smart healthcare.
Analysis of emerging trends in artificial intelligence for education in Nigeria
Authors: Bali Bulus , Garba Etemi Joshua , Ahmadu Asabe Sandra , Takwate Kwaji Tizhe , Malgwi Yusuf Musa 
Published: December 2024

AbstractIn the domain of education, the integration of Artificial Intelligence (AI) has ushered in a paradigm shift towards a more technologically-driven landscape, demonstrating its efficacy as an emergent strategy. The pervasive influence of computer technology has catalyzed a surge in online learning within the country, yielding positive educational outcomes. Despite these advancements, a considerable number of educational institutions in Nigeria have yet to leverage AI technologies. Recognizing the expanding significance of AI in education, this study seeks to align with this trajectory by aggregating instances of AI implementation in education from developed countries. The methodology employed involves a comprehensive review of current advancements in AI applications within the Nigerian educational context. The review process, spanning papers retrieved from four digital libraries published between 2008 and 2022, culminated in the inclusion of 74 papers. These selected papers demonstrated the utilization of AI software tools and technologies, adhering to predefined exclusion and inclusion criteria. The findings of the study reveal a prevalent use of AI technologies in education in Nigeria, encompassing evolutionary software modelling, student performance prediction, multimedia e-learning platforms and frameworks, and the incorporation of Moodle learning. This discernible trend indicates a growing demand for the application of AI technology in the educational landscape of Nigeria. However, the study highlights a discrepancy: sophisticated AI techniques like intelligent tutoring systems, learnable robots, web-based educational systems, and advanced learning management systems are infrequently applied in Nigeria. The study suggests that Nigerian educational institutions should adopt AI practices from advanced nations to enhance student learning and bridge the gap in AI integration.
Medication errors and their related aspects in antibiotic drugs used in pediatric inpatients with chest infections in the pediatric ward of a government hospital in a developing country: a prospective, cross-sectional study
Authors: Alsaqqaf Baraah , Alakhali Khaled 
Published: December 2024

Abstract
Background and aim
Children are particularly vulnerable to medication errors, with a greater risk of harm in young children and infants. These errors can lead to severe morbidity and mortality. Therefore, this research aimed to evaluate medication errors, specifically antibiotic medications, and their related aspects among pediatric patients hospitalized with chest infections at Alsabeen Hospital in Sanaa, Yemen.

Method
A prospective, cross-sectional study was conducted in a public hospital’s pediatric ward between 29 January and 29 July 2024. The study population consisted of pediatric inpatients aged 0–16 years. 119 pediatric inpatients were admitted to the hospital during the study period.

Key findings
From 119 study participants, 993 medication errors were identified. Medication errors (MEs) frequently occurred at the prescribing stage 459 (46.22%). The most common types of MEs were wrong rate 250 (25.2%), monitoring error (clinical) 177 (17.83%), and wrong strength/concentration 143 (14.4%). The presence of disease comorbidity indicates that 93 (78%) don’t have comorbidities, being male 68 (57.1%), and have a length of stay of 2–7 days 84 (70.5%). These factors were found to be independent predictors of the occurrence of medication errors.

Conclusion
Medication errors were prevalent among pediatric inpatients diagnosed with chest infections. Factors such as comorbidities, and length of hospitalization were found to be linked to the occurrence of medication errors. To minimize these errors, we suggest the utilization of e-prescribing, medication reconciliation, creating local antibiograms, and activating the clinical pharmacist's role in the hospital setting, which is crucial.
Threats to new product manufacturability and the effects of development team integration processes
Authors: Swink Morgan 
Published: July 2002

AbstractThe thesis of this article is that new product manufacturability (NPM) is influenced by certain challenges inherent in new product development (NPD), and by efforts to integrate manufacturing and other functional concerns into the product design process. This research tests the direct and interacting effects of these influences via a survey of 91 completed NPD projects representing a variety of manufacturing industries. While most hypotheses were supported, the analysis also provides some surprising findings. Project complexity and increased levels of design outsourcing are associated with poorer NPM. Product newness and project acceleration are associated with better NPM. All the measured aspects of development team integration are associated with better NPM, including intense manufacturing involvement, a collaborative work environment, supplier influence on the product design, and strong management support in the project. Furthermore, certain integration variables exert moderating effects on relationships between technological uncertainty, product newness, design outsourcing, project acceleration and NPM. By exposing these relationships this research extends the theory of product development influences on manufacturability beyond a focus on engineering‐oriented approaches (e.g., design‐for‐manufacture). The results suggest that larger managerial issues must be addressed and that more contingency‐oriented research is needed to explore the benefits and limitations of development team integration processes.