bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel Process Approach for Additive Manufacturing Using Inductive Wire Melting by Forced Droplet Detachment
Authors: Kimme Jonas , Fröhlich Alexander , Kroll Martin , Kräusel Verena 
Published: April 2023

AbstractTo date, no AM technology for large-volume metallic components has been established on an industrial scale like Laser Powder Bed Fusion (LPBF). This contribution presents a new process approach to fabricate larger metallic structures from steel by inductive melting of a continuously fed wire. The presented method is characterized by the comparatively low energy input in contrast to comparable processes for AM, such as arc, laser, or electron beam. Previously published work is based on the principle of a melt reservoir of low-melting alloys and droplet delivery using gas pressure or vibration. In contrast, the approach described here is to transfer the material directly from the end of the wire to the substrate by continuous drop deposition. However, to avoid a stochastic material transition, a suitable process strategy has to be chosen. This challenge is met by a pulsed coil current and the resulting periodically varying Lorentz forces in order to achieve regular and forced droplet detachment. Tests confirm the principle of controlled droplet detachment and reveal the great potential of this technological approach.
Clinical and patient-reported outcome after patient-specific 3D printer-assisted cranioplasty
Authors: Ebel Florian , Schön Stephan , Sharma Neha , Guzman Raphael , Mariani Luigi , Thieringer Florian M. , Soleman Jehuda 
Published: April 2023

AbstractVarious cranioplasty techniques exist for the reconstruction of cranial bone defects. Patient-specific implants can be produced in-house using a recently developed 3D printer-assisted cranioplasty technique. However, the resulting cosmetic outcomes from the patient’s perspective are underreported. With our case series, we aim to present the clinical outcome, morbidity rate, patient-reported cosmetic results, and cost-effectiveness of patient-specific3D printer-assisted cranioplasty technique. This is a consecutive retrospective case series of adult patients undergoing cranioplasty using the patient-specific 3D printer-assisted technique. As primary endpoint, the functional outcome based on modified Rankin scale (mRS) at discharge and follow-up was assessed. A prospective telephone survey was conducted to collect and provide patient-reported outcomes. Thirty-one patients underwent patient-specific 3D printer-assisted cranioplasty, mostly to reconstruct frontotemporoparietal (61.3%) and frontotemporal defects with orbital involvement (19.4%). Good functional outcome (mRS ≤ 2) at discharge and during the last follow-up was achieved in 54.8% (n = 17) and 58.1% (n = 18) patients. Overall, the rate of clinically relevant surgery-related complications was 35.5% (n = 11). Postoperative epidural hematoma/collection (16.1%) and infections (12.9%) were the most frequent complications. Permanent morbidity occurred in one patient (3.2%) with postoperative acute ipsilateral vision loss after frontotemporal cranioplasty with orbital involvement. No surgery-related mortality occurred. The mean patient-reported cosmetic satisfaction score was 7.8 ± 1.5, with 80% of patients reporting satisfying or very satisfying cosmetic results. No significant differences were seen between the different defect localization regarding the cosmetic outcome. The mean manufacturing costs of a patient-specific 3D printer-assisted implant ranged from 748 to 1129 USD. Based on our case series, patient-specific 3D printer-assisted cranioplasty is cost-effective and leads to satisfying cosmetic results, especially in large defects and/or defects with complex geometry.
AiCEF: an AI-assisted cyber exercise content generation framework using named entity recognition
Authors: Zacharis Alexandros , Patsakis Constantinos 
Published: April 2023

AbstractContent generation that is both relevant and up to date with the current threats of the target audience is a critical element in the success of any cyber security exercise (CSE). Through this work, we explore the results of applying machine learning techniques to unstructured information sources to generate structured CSE content. The corpus of our work is a large dataset of publicly available cyber security articles that have been used to predict future threats and to form the skeleton for new exercise scenarios. Machine learning techniques, like named entity recognition and topic extraction, have been utilised to structure the information based on a novel ontology we developed, named Cyber Exercise Scenario Ontology (CESO). Moreover, we used clustering with outliers to classify the generated extracted data into objects of our ontology. Graph comparison methodologies were used to match generated scenario fragments to known threat actors’ tactics and help enrich the proposed scenario accordingly with the help of synthetic text generators. CESO has also been chosen as the prominent way to express both fragments and the final proposed scenario content by our AI-assisted Cyber Exercise Framework. Our methodology was assessed by providing a set of generated scenarios for evaluation to a group of experts to be used as part of a real-world awareness tabletop exercise.
Analysing the benefits of trajectory deviations for planar trajectory optimisation
Authors: Arif Salman , Atkin Jason , De Maere Geert 
Published: April 2023

AbstractAircraft traverse airspace sectors under the supervision of Air Traffic Controllers by following navigation points. The trajectories can deviate from these points under the supervision of controllers. However, the controllers have to consider various factors for managing air traffic which increases their workload. We aim to offline analyse the potential benefits of trajectory deviations, by tactically shifting navigation points for planar trajectory optimisation of multiple aircraft at an enroute sector level. Historic deviations of trajectories are considered for this analysis to implement them at practical level. Within nominal speed and turning rate of aircraft trajectories, 5.47% reduction in time cost and an annual fuel saving worth US$ 29.32 million has been estimated using shifts for an airspace sector.
Use of delivery drones for humanitarian operations: analysis of adoption barriers among logistics service providers from the technology acceptance model perspective
Authors: Edwards David , Subramanian Nachiappan , Chaudhuri Atanu , Morlacchi Piera , Zeng Wen 
Published: April 2023

AbstractDelivery drones are yet to be adopted as a systematic delivery system for humanitarian operations but have the potential to substantially increase the efficiency and effectiveness of future delivery options. Thus, we analyse the impact of factors affecting the adoption of delivery drones by logistics service providers for humanitarian operations. A conceptual model of potential barriers to adoption and development is created using the Technology Acceptance Model theory involving security, perceived usefulness, perceived ease of use and attitude as factors that affect the intention to use. We validate the model using empirical data collected from 103 respondents by the 10 leading logistics firms located in China between May and August 2016. through a survey to examine factors currently affecting the intention/non-intention to adopt delivery drones. The results show that ease of use and addressing key security considerations about the drone, the delivery package and the recipient are crucial for adopting the technology as a specialized delivery option for logistics service providers. This is the first study of its kind and contributes to understanding the operational, supply chain and behavioural factors in the adoption of drones by logistics services providers for humanitarian operations.
Use of giant reed (Arundo donax L.) for polymer composites obtaining: a mapping review
Authors: Suárez Luis , Ortega Zaida , Barczewski Mateusz , Cunningham Eoin 
Published: April 2023

AbstractThe massive biomass availability generated by the common giant reed (Arundo donaxL.) motivates the research for its possible industrial use for high-added-value products through a biorefinery approach. The literature demonstrates the potential of common cane to obtain different high-value compounds, such as levulinic acid, oligosaccharides, fermentable sugars, highly digestible fiber for animal feed, polyphenols, and natural fibers for composite materials, among others.Arundocan also provide valuable lignocellulosic fibers with an application as composite reinforcement, which is the aim of this review. The work is split into different sections: fiber obtaining, mainly done by mechanical procedures, fiber characterization (composition, thermal degradation, "mechanical properties", and crystallinity), and properties of composites with reed fiber. Most authors refer to producing board panels with insulating properties, followed by introducing reed fibers or ground materials in thermoset resins. Few papers focus on the production of thermoplastic composites withArundo, which shows the opportunity for deepening research in this area. PRISMA flowchart has been followed to perform the literature review. Different sources have been used, and retrieved results have been combined to obtain the core studies assessed in this review, evaluating the options of usingArundofibers to obtain polymer composites.
Error estimates for Runge–Kutta schemes of optimal control problems with index 1 DAEs
Authors: Martens Björn 
Published: April 2023

AbstractIn this paper we derive error estimates for Runge–Kutta schemes of optimal control problems subject to index one differential–algebraic equations (DAEs). Usually, Runge–Kutta methods applied to DAEs approximate the differential and algebraic state in an analogous manner. These schemes can be considered as discretizations of the index reduced system where the algebraic equation is solved for the algebraic variable to get an explicit ordinary differential equation. However, in optimal control this approach yields discrete necessary conditions that are not consistent with the continuous necessary conditions which are essential for deriving error estimates. Therefore, we suggest to treat the algebraic variable like a control, obtaining a new type of Runge–Kutta scheme. For this method we derive consistent necessary conditions and compare the discrete and continuous systems to get error estimates up to order three for the states and control as well as the multipliers.
A case study of improving a non-technical losses detection system through explainability
Authors: Coma-Puig Bernat , Calvo Albert , Carmona Josep , Gavaldà Ricard 
Published: April 2023

AbstractDetecting and reacting to non-technical losses (NTL) is a fundamental activity that energy providers need to face in their daily routines. This is known to be challenging since the phenomenon of NTL is multi-factored, dynamic and extremely contextual, which makes artificial intelligence (AI) and, in particular, machine learning, natural areas to bring effective and tailored solutions. If the human factor is disregarded in the process of detecting NTL, there is a high risk of performance degradation since typical problems like dataset shift and biases cannot be easily identified by an algorithm. This paper presents a case study on incorporating explainable AI (XAI) in a mature NTL detection system that has been in production in the last years both in electricity and gas. The experience shows that incorporating this capability brings interesting improvements to the initial system and especially serves as a common ground where domain experts, data scientists, and business analysts can meet.
Too Much of a Good Thing Might Be Bad: the Double-Edged Sword of Parental Aspirations and the Adverse Effects of Aspiration-Expectation Gaps
Authors: Marsh Herbert W. , Pekrun Reinhard , Guo Jiesi , Hattie John , Karin Eyal 
Published: April 2023

AbstractConventional wisdom suggests that parents’ educational expectations (how far they expect their children to go) and aspirations (how far they want their children to go) positively impact academic outcomes and benefits from attending high-ability schools. However, here we juxtapose the following: largely positive effects of educational expectations (of parents, teachers, and students); small, mixed effects of parent aspirations; largely adverse effects of parental aspiration-expectation gaps; and negative effects of school-average achievement on expectations, aspirations, and subsequent outcomes. We used a large, nationally representative longitudinal sample (16,197 Year-10 students from 751 US high schools).Controlling background (achievement, SES, gender, age, ethnicity, academic track, and a composite risk factor), Year 10 educational expectations of teachers and parents had consistently positive effects on the following: student expectations in Years 10 and 12, Year 10 academic self-concept, final high-school grade-point-averages, and long-term outcomes at age 26 (educational attainment, educational and occupational expectations). Effects of parent aspirations on these outcomes were predominantly small and mixed in direction. However, the aspiration-expectation gap negatively predicted all these outcomes. Contrary to our proposed Goldilocks Effect (not too much, not too little, but just right), non-linear effects of expectations and aspirations were small and largely non-significant.Parent, teacher, student expectations, and parent aspirations were all negatively predicted by school-average achievement (a big-fish-little-pond effect). However, these adverse effects of school-average achievement were larger for parents and particularly teachers than students. Furthermore, these expectations and aspirations partly mediated the adverse impacts of school-average achievement on subsequent grade-point-average and age-26 outcomes.
Preparation and characterization of nanomuscovite by intercalation method for adsorption of heavy metals from polluted water
Authors: Rashed M. Nageeb , Arifien A. E , El-Dowy F. A. 
Published: April 2023

AbstractIn this study, nanomuscovite adsorbents were prepared by intercalation with various organic intercalates (DTAB-TTAB-DTPA-PA-PN) and used to remove Cd2+ and Pb2+ from polluted water. The best nanomuscovite was prepared using DTPA and muscovite (Muc/DTPA) and characterized by XRD, TEM, EDX, FTIR, and BET surface area. The developed nanoadsorbent was used to remove Cd2+ and Pb2+ from polluted water. The effect of various factors, including contact time, adsorbent dosage, solution pH, and temperature, was investigated. The results reveal that the maximum adsorption of Cd2+ and Pb2+ was 91.5% and 97%, respectively, at the initial metal concentration 50 ppm, adsorbent dosage 0.2 g, contact time 60 min, solution temperature 25 °C, and pH 6 for Pb2+ and pH 7 for Cd2+. Adsorption isotherm models (Freundlich, Langmuir, Dubunin–Radushkevich, and Temkin isotherm models) as well as kinetic models (pseudo-first-order, pseudo-second-order, Elovich, and intra-particle diffusion models) were employed to evaluate the experimental results. The adsorption of Cd2+ and Pb2+ on Muc/DTPA fitted well within the Langmuir isotherm model and followed pseudo-second-order kinetics. Thermodynamics parameters of metal adsorption indicated exothermic and spontaneous processes. Results were applied to the real wastewater that showed high Cd2+ and Pb2+ removal.
Explaining Residential Clustering of Large Families
Authors: Bergsvik Janna , Cools Sara , Hart Rannveig K. 
Published: April 2023

AbstractNumerous studies have shown that fertility behavior is spatially clustered. In addition to pure contextual effects, two causal mechanisms could drive this pattern. First, neighbors may influence each other's fertility and second, family size may influence decisions about where to live. In this study we examine these two potential causal mechanisms empirically, using the sex composition of the two eldest children and twin births as instrumental variables (IVs) for having a third child. We estimate how having a third child affects three separate outcomes: the fertility of neighbors; the propensity to move houses; and the likelihood of living in a family-friendly neighborhood with many children. We draw residential and childbearing histories (2000–2018) from Norwegian administrative registers (N ~ 167,000 women). Individuals' neighborhoods are defined using time-varying geocoordinates for place of residence. We identify selective moves as one plausible causal driver of residential clustering of large families. This study contributes to the understanding of fertility and relocation, and to the literature on the social interaction effects of fertility, by testing the relevance of yet another network: that of neighbors.
ST3GalIV drives SLeX biosynthesis in gastrointestinal cancer cells and associates with cancer cell motility
Authors: Costa Ana F. , Senra Emanuel , Faria-Ramos Isabel , Teixeira Andreia , Morais João , Pacheco Mariana , Reis Celso A. , Gomes Catarina 
Published: April 2023

AbstractExpression of sialyl Lewis X (SLeX) is a well-documented event during malignant transformation of cancer cells, and largely associates with their invasive and metastatic properties. Glycoproteins and glycolipids are the main carriers of SLeX, whose biosynthesis is known to be performed by different glycosyltransferases, namely by the family of β-galactoside-α2,3-sialyltransferases (ST3Gals). In this study, we sought to elucidate the role of ST3GalIV in the biosynthesis of SLeX and in malignant properties of gastrointestinal (GI) cancer cells. By immunofluorescent screening, we selected SLeX-positive GI cancer cell lines and silenced ST3GalIV expression via CRISPR/Cas9. Flow cytometry, immunofluorescence and western blot analysis showed that ST3GalIV KO efficiently impaired SLeX expression in most cancer cell lines, with the exception of the colon cancer cell line LS174T. The impact of ST3GalIV KO in the biosynthesis of SLeX isomer SLeA and non sialylated Lewis X and A were also evaluated and overall, ST3GalIV KO led to a decreased expression of SLeA and an increased expression in both LeX and LeA. In addition, the abrogation of SLeX on GI cancer cells led to a reduction in cell motility. Furthermore, ST3GalVI KO was performed in LS174T ST3GalIV KO cells, resulting in the complete abolishment of SLeX expression and consequent reduced motility capacity of those cells. Overall, these findings portray ST3GalIV as the main, but not the only, enzyme driving the biosynthesis of SLeX in GI cancer cells, with a functional impact on cancer cell motility.
The Novelty Effect on Assessment Interventions: a Qualitative Replication Study of Oral Performance Assessment in Undergraduate Mathematics
Authors: Iannone Paola , Vondrová Naďa 
Published: April 2023

AbstractThis paper reports on a qualitative replication study investigating the impact of the novelty effect on findings from interventions about the assessment of mathematics at university. The replication study used the same data collection tools of a previous study on oral assessment of mathematics, but data were collected in a context where oral assessment is the norm. We aimed to find whether the results of the two studies were comparable and whether there was plausible evidence of an impact of novelty effect on the findings of the original study. The findings of the current study appear to be comparable to those of the original study. Students associate oral assessment with the assessment of conceptual understanding and written assessment with the assessment of procedures; they report being more anxious about the oral assessment, but they perceive oral assessment as a better learning experience than closed book exams. However, in a culture where oral assessment is the norm, we found students engaging with learning also following considerations of the difficulties of other modules taken in the same period of their degree. Finally, in this culture, oral communication of mathematics is also much valued.
Micro- and nanostructure of additively manufactured, in-situ alloyed, magnetic spinodal Fe54Cr31Co15
Authors: Mairhofer T. , Arneitz S. , Hofer F. , Sommitsch C. , Kothleitner G. 
Published: April 2023

AbstractExploring the chemical micro- and nanostructure of metal alloys is essential to understand their physical properties, such as magnetism or hardness. Additively manufactured (AM) materials, e.g. via laser powder bed fusion (LPBF) followed by various heat treatments, can raise further questions concerning the printed material. For the in-situ alloyed, spinodal Fe54Cr31Co15 system, the macroscopic magnetic behaviour is greatly influenced by subsequent homogenisation and heat treatment steps. Here we show that the decomposition takes place on the nanometre scale, resulting in ferromagnetic FeCo-rich particles embedded in a Cr-rich matrix. By studying phenomena like chemical homogeneity, grain structure, and texture of the in-situ alloyed material at different scales, we reveal correlations between the heat treatment and the resulting nanostructure and its ferromagnetic properties. We found that the isothermal heating conditions determine the degree of phase segregation and that a homogenization step can be omitted for additively manufactured, in-situ alloyed FeCrCo alloys. The approach thereby offers insight and a path for also tailoring specific manufacturing parameters to provide the right quality printed materials with desired functionalities. For example, magnetic FeCrCo alloys are often used in electric motors or magnetic sensors, and the flexibility of the presented approach can lead to optimal use of the material.
Fully bio-based furan/maleic anhydride epoxy resin with enhanced adhesive properties
Authors: Faggio Noemi , Marotta Angela , Ambrogi Veronica , Cerruti Pierfrancesco , Gentile Gennaro 
Published: April 2023

AbstractEpoxy resins are widely used in a variety of application fields, thanks to their good mechanical strength, chemical resistance and adhesion to several substrates. Nowadays, the quite majority of epoxy resins are based on derivatives of bisphenol A (BPA), which poses serious health concerns. This issue is pushing the research towards suitable bio-based alternatives to this product, being furan-based epoxies very promising in this respect. In a previous work, 2,5-bis[(oxiran-2-ylmethoxy)methyl]furan (BOMF) was cured with methyl nadic anhydride (MNA), and successfully used as tinplate coating. Herein, in a view of increasing the sustainability of these epoxy resins, we have replaced MNA with maleic anhydride (MA), which can be derived from vegetable feedstocks, thus obtaining a fully bio-based epoxy resin. This latter has then been used as adhesive for carbon fiber-reinforced thermosetting plastics (CFRP). The curing process of the resin was monitored by differential scanning calorimetry (DSC) and chemo-rheological analysis. The results highlighted the significantly higher reactivity of BOMF towards MA compared to the diglycidyl ether of BPA (DGEBA). The crosslinked samples were characterized in their thermal, mechanical and adhesive properties. In comparison to DGEBA/MA and BOMF/MNA, BOMF/MA showed higher ultimate strain and slightly lower glass transition temperature, tensile modulus and ultimate strength. Interestingly, BOMF/MA displayed outstanding adhesive strength on CFRP joints, outperforming the DGEBA-based counterpart by three times. Indeed, by properly selecting the anhydride curing agent, a highly ductile fully bio-based material was developed for high performance adhesive applications. The overall results demonstrate that the properties of BOMF-based epoxy resins can be tailored to meet technical and safety requirements of downstream applications, representing a sustainable alternative to traditional systems containing DGEBA.