bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comprehensive bibliometric and content analysis of artificial intelligence in language learning: tracing between the years 2017 and 2023
Authors: Rahman Abdur , Raj Antony , Tomy Prajeesh , Hameed Mohamed Sahul 
Published: April 2024

AbstractThe rising pervasiveness of Artificial Intelligence (AI) has led applied linguists to combine it with language teaching and learning processes. In many cases, such implementation has significantly contributed to the field. The retrospective amount of literature dedicated on the use of AI in language learning (LL) is overwhelming. Thus, the objective of this paper is to map the existing literature on Artificial Intelligence in language learning through bibliometric and content analysis. From the Scopus database, we systematically explored, after keyword refinement, the prevailing literature of AI in LL. After excluding irrelevant articles, we conducted our study with 606 documents published between 2017 and 2023 for further investigation. This review reinforces our understanding by identifying and distilling the relationships between the content, the contributions, and the contributors. The findings of the study show a rising pattern of AI in LL. Along with the metrics of performance analysis, through VOSviewer and R studio (Biblioshiny), our findings uncovered the influential authors, institutions, countries, and the most influential documents in the field. Moreover, we identified 7 clusters and potential areas of related research through keyword analysis. In addition to the bibliographic details, this review aims to elucidate the content of the field. NVivo 14 and Atlas AI were used to perform content analysis to categorize and present the type of AI used in language learning, Language learning factors, and its participants.
Determination, expression and characterization of an UDP-N-acetylglucosamine:α-1,3-D-mannoside β-1,2-N-acetylglucosaminyltransferase I (GnT-I) from the Pacific oyster, Crassostrea gigas
Authors: Thoma Julia , Grabherr Reingard , Staudacher Erika 
Published: April 2024

AbstractMolluscs are intermediate hosts for several parasites. The recognition processes, required to evade the host’s immune response, depend on carbohydrates. Therefore, the investigation of mollusc glycosylation capacities is of high relevance to understand the interaction of parasites with their host. UDP-N-acetylglucosamine:α-1,3-D-mannoside β-1,2-N-acetylglucosaminyltransferase I (GnT-I) is the key enzyme for the biosynthesis of hybrid and complex type N-glycans catalysing the transfer of N-acetylglucosamine from UDP-N-acetylglucosamine to the α-1,3 Man antenna of Man5GlcNAc2. Thereby, the enzyme produces a suitable substrate for further enzymes, such as α-mannosidase II, GlcNAc-transferase II, galactosyltransferases or fucosyltransferases. The sequence of GnT- I from the Pacific oyster, Crassostrea gigas, was obtained by homology search using the corresponding human enzyme as the template. The obtained gene codes for a 445 amino acids long type II transmembrane glycoprotein and shared typical structural elements with enzymes from other species. The enzyme was expressed in insect cells and purified by immunoprecipitation using protein A/G-plus agarose beads linked to monoclonal His-tag antibodies. GnT-I activity was determined towards the substrates Man5-PA, MM-PA and GnM-PA. The enzyme displayed highest activity at pH 7.0 and 30 °C, using Man5-PA as the substrate. Divalent cations were indispensable for the enzyme, with highest activity at 40 mM Mn2+, while the addition of EDTA or Cu2+ abolished the activity completely. The activity was also reduced by the addition of UDP, UTP or galactose. In this study we present the identification, expression and biochemical characterization of the first molluscan UDP-N-acetylglucosamine:α-1,3-D-mannoside β-1,2-N-acetylglucosaminyltransferase I, GnT-I, from the Pacific oyster Crassostrea gigas.
Graphical abstract
Illustration of GnT-I activity. (a) Transfer of GlcNAc to Man5-PA, creating Man5GlcNAc3-PA. (b) Transfer of GlcNAc to MM-PA, creating MGn-PA. (c) Transfer of GlcNAc to GnM-PA, creating GnGn-PA. Blue squares represent N-acetylglucosamine, green cycles depict mannose. Graphic illustration of N-glycans were created using bioRENDER.
Relationship between preinduction electroencephalogram patterns and propofol sensitivity in adult patients
Authors: Nam Seungpyo , Yoo Seokha , Park Sun-Kyung , Kim Youngwon , Kim Jin-Tae 
Published: April 2024

Abstract
Purpose
To determine the precise induction dose, an objective assessment of individual propofol sensitivity is necessary. This study aimed to investigate whether preinduction electroencephalogram (EEG) data are useful in determining the optimal propofol dose for the induction of general anesthesia in healthy adult patients.

Methods
Seventy healthy adult patients underwent total intravenous anesthesia (TIVA), and the effect-site target concentration of propofol was observed to measure each individual’s propofol requirements for loss of responsiveness. We analyzed preinduction EEG data to assess its relationship with propofol requirements and conducted multiple regression analyses considering various patient-related factors.

Results
Patients with higher relative delta power (ρ = 0.47, p < 0.01) and higher absolute delta power (ρ = 0.34, p = 0.01) required a greater amount of propofol for anesthesia induction. In contrast, patients with higher relative beta power (ρ = -0.33, p < 0.01) required less propofol to achieve unresponsiveness. Multiple regression analysis revealed an independent association between relative delta power and propofol requirements.

Conclusion
Preinduction EEG, particularly relative delta power, is associated with propofol requirements during the induction of general anesthesia. The utilization of preinduction EEG data may improve the precision of induction dose selection for individuals.
An Edge Cloud Based Coordination Platform for Multi-user AR Applications
Authors: Sonkoly Balázs , Nagy Bálint György , Dóka János , Kecskés-Solymosi Zsófia , Czentye János , Formanek Bence , Jocha Dávid , Gerő Balázs Péter 
Published: April 2024

AbstractAugmented Reality (AR) applications can reshape our society enabling novel ways of interactions and immersive experiences in many fields. However, multi-user and collaborative AR applications pose several challenges. The expected user experience requires accurate position and orientation information for each device and precise synchronization of the respective coordinate systems in real-time. Unlike mobile phones or AR glasses running on battery with constrained resource capacity, cloud and edge platforms can provide the computing power for the core functions under the hood. In this paper, we propose a novel edge cloud based platform for multi-user AR applications realizing an essential coordination service among the users. The latency critical, computation intensive Simultaneous Localization And Mapping (SLAM) function is offloaded from the device to the edge cloud infrastructure. Our solution is built on open-source SLAM libraries and the Robot Operating System (ROS). Our contribution is threefold. First, we propose an extensible, edge cloud based AR architecture. Second, we develop a proof-of-concept prototype supporting multiple devices and building on an AI-based SLAM selection component. Third, a dedicated measurement methodology is described, including energy consumption aspects as well, and the overall performance of the system is evaluated via real experiments.
Deep Self-Supervised Attributed Graph Clustering for Social Network Analysis
Authors: Lu Hu , Hong Haotian , Geng Xia 
Published: April 2024

AbstractDeep graph clustering is an unsupervised learning task that divides nodes in a graph into disjoint regions with the help of graph auto-encoders. Currently, such methods have several problems, as follows. (1) The deep graph clustering method does not effectively utilize the generated pseudo-labels, resulting in sub-optimal model training results. (2) Each cluster has a different confidence level, which affects the reliability of the pseudo-label. To address these problems, we propose a Deep Self-supervised Attribute Graph Clustering model (DSAGC) to fully leverage the information of the data itself. We divide the proposed model into two parts: an upstream model and a downstream model. In the upstream model, we use the pseudo-label information generated by spectral clustering to form a new high-confidence distribution with which to optimize the model for a higher performance. We also propose a new reliable sample selection mechanism to obtain more reliable samples for downstream tasks. In the downstream model, we only use the reliable samples and the pseudo-label for the semi-supervised classification task without the true label. We compare the proposed method with 17 related methods on four publicly available citation network datasets, and the proposed method generally outperforms most existing methods in three performance metrics. By conducting a large number of ablative experiments, we validate the effectiveness of the proposed method.
The contributions of executive functions, transcription skills and text-specific skills to text quality in narratives
Authors: Philippek Julie , Kreutz Rebecca Maria , Hennes Ann-Kathrin , Schmidt Barbara Maria , Schabmann Alfred 
Published: April 2024

AbstractTo ensure adequate writing support for children, a profound understanding of the subskills of text quality is essential. Writing theories have already helped to better understand the contribution of different subskills to text quality, but empirical work is often limited to more general low-level transcription skills like handwriting fluency and spelling. Skills that are particularly important for composing a functional text, while theoretically seen as important, are only studied in isolation. This study combines subskills at different hierarchical levels of composition. Executive functions, handwriting fluency and spelling were modeled together with text-specific skills (lexically diverse and appropriate word usage and cohesion), text length and text quality in secondary school students’ narratives. The results showed that executive functions, spelling and handwriting fluency had indirect effects on text quality, mediated by text-specific skills. Furthermore, the text-specific skills accounted for most of the explained variance in text quality over and above text length. Thus, it is clear from this study that, in addition to the frequently reported influence of transcription skills, it is text-specific skills that are most relevant for text quality.
Parsimonious ultrametric Gaussian mixture models
Authors: Cavicchia Carlo , Vichi Maurizio , Zaccaria Giorgia 
Published: April 2024

AbstractGaussian mixture models represent a conceptually and mathematically elegant class of models for casting the density of a heterogeneous population where the observed data is collected from a population composed of a finite set of G homogeneous subpopulations with a Gaussian distribution. A limitation of these models is that they suffer from the curse of dimensionality, and the number of parameters becomes easily extremely large in the presence of high-dimensional data. In this paper, we propose a class of parsimonious Gaussian mixture models with constrained extended ultrametric covariance structures that are capable of exploring hierarchical relations among variables. The proposal shows to require a reduced number of parameters to be fit and includes constrained covariance structures across and within components that further reduce the number of parameters of the model.
Ordered Arrays of Ultrafine Au Nanoprisms by Means of Nanosphere Lithography and Ion Hammering Effect
Authors: Zárate-Reyes J. M. , Salinas-Fuentes C. , Kudriavtsev Y. , Cheang-Wong J. C. , Asomoza R. 
Published: April 2024

AbstractThe search for new nanomaterials with precisely customized optical and geometric characteristics is highly suitable for potential applications in nanophotonics and optoelectronics. In this work, ordered arrays of ultrafine Au nanoprisms on silicon substrates were prepared by combining nanosphere lithography with the ion hammering effect. Indeed, the silica particle lithographic masks were previously irradiated with 4 MeV Si+ ions to modify and tune the mask interstice size. An extensive analysis of the samples by SEM and AFM determined the geometrical properties and the narrow average size of the ultrafine Au nanoprisms, exhibiting an area base of 750 nm2, a lateral size as small as 26.2 nm, and a height of 6.3 nm. Moreover, the Surface-Enhanced Raman Scattering (SERS) efficiency of the fabricated ultrafine Au nanoprisms was probed using Rhodamine 6G dye as probe molecules, presenting excellent stability and reaching the sensitivity level of 10−5 M.
Mind the Echo Chamber: Mindfulness as a Contemplative Practice That can Contribute to Public Health
Authors: Galante Julieta , Van Dam Nicholas T. 
Published: April 2024

AbstractWe offer an invited commentary on the article entitled “Mindfulness for Global Public Health: Critical Analysis and Agenda” by Doug Oman. First, we question his proposal that it would be advantageous to include a more diverse set of contemplative practices under the mindfulness umbrella term, and instead we argue for the opposite. We propose that academics move the term mindfulness away from the spotlight, acknowledging the role of popular culture in its constant reshaping, while studying the mechanisms and outcomes of contemplative practices such as mindfulness using better delineated terms from relevant academic disciplines. Second, we argue that a head-to-head comparison between the fields of mindfulness and public health incurs a category error. While mindfulness is often defined by a limited set of specific processes and practices, public health is a field defined by its application, irrespective of the practices or interventions used. Instead, thinking of mindfulness as an aid to public health can bring more clarity and increase the scope and impact of the contributions that the mindfulness field can make to public health. We illustrate how this reframing helps see mindfulness training as a potential individual-level component of multi-level public health interventions to tackle social determinants of health, rather than expect mindfulness training to address this singlehandedly. For this potential to realize fully, we argue that the mindfulness field will need to work “with” rather than “as” public health, moving away from the practitioner-researcher model to a collaborative one, whereby mindfulness intervention developers partner with independent public health researchers for intervention evaluation and implementation purposes. In such a model, using participatory research methods, the public health team should first seek to understand the local community health needs, and assess whether and how mindfulness practitioners may be able to address some of those needs. We are delighted that the field is having these conversations, and hope to advance understanding of the potential of contemplative practices to contribute to public health research and implementation efforts.
Investigation of the cellular and molecular effects of dehydrozingerone formulation on various days of diabetic wound repair
Authors: Begum Farmiza , Nandakumar Krishnadas , Shenoy Rekha Raghuveer 
Published: April 2024

AbstractCases of diabetes are significantly increasing year by year, attracting the attention of medical professionals and researchers to focus on diabetes and its underlying complications. One among such are diabetic wounds which are difficult to heal, creating severe implications in the day-to-day chores of not only patients, but also family members. Dehydrozingerone (DHZ) is known to possess various effects like anti-inflammatory, anti-microbial, antioxidant, and wound-healing properties. The effect of DHZ on different phases of diabetic wound healing remains untested. Hence, this study was proposed to find out the effect of oral and topical formulation of DHZ on day 5, 10 and 15 of diabetic wound healing. Excisional wounds were created on the dorsal side of animals using punch biopsy to mimic human diabetic wounds. Topical DHZ gel (100 mg in 1 gm of gel) was prepared using 1% Carbopol 934 and was applied twice a day. The treated groups had increased percentage of wound closure; western blotting suggested that DHZ significantly increased ERK and JNK levels and decreased TNF and MMP 2 and 9 levels. From histopathological studies, it was observed that angiogenesis, collagen formation, granulation tissue formation, and fibroblast proliferation were improved on days 5, 10, and 15 of diabetic wound healing. These findings indicate that DHZ (both systemic and topical) are effective during the early phases of wound healing which gets impaired in diabetic wounds. Dehydrozingerone accelerated diabetic wound healing by regulating the various hallmarks of wound healing process.
Effect of Pilates exercises on balance and gross motor coordination in children with Down syndrome
Authors: AL-Nemr Alaa , Reffat Shimaa 
Published: April 2024

Abstract
Objective
To investigate the effect of Pilates exercises on balance and gross motor coordination in children with Down syndrome (DS).

Methods
Forty children with DS, aged 8 up to 10 years, were randomly divided into two groups; experimental and control groups. A designed physical therapy program was applied for both groups, while the experimental group received an additional Pilates exercise program. Balance and gross motor coordination as primary outcomes and quality of life (QoL) as secondary outcome were assessed using Biodex balance system (BBS), Bruininks Oseretsky of Motor Proficiency (BOT-2), and Pediatric quality of life inventory (PedsQL™) sequentially.

Results
Both experimental (Pilates) and control groups demonstrated significant improvements in dynamic balance, gross motor coordination, and QoL after interventions. However, comparison between groups showed significant improvement in favor of the Pilates group in all measured outcomes (P < 0.0001).

Conclusion
Adding Pilates exercises to the designed physical therapy program could provide more significant improvements in balance, gross motor coordination, and QoL in children with DS.

Trial registration
Clinical Trial gov number Identifier: NCT05928949.
Learning to teach with simulation: historical insights
Authors: Ledger Susan , Mailizar Mailizar , Gregory Sue , Tanti Miriam , Gibson David , Kruse Stacy 
Published: April 2024

AbstractSimulation-based learning (SBL) has been trialed and embedded in many disciplines and professions over many years to practice complex skills before embarking on real-life applications. Much research has confirmed the benefits of SBL and found simulations are among the most effective means to facilitate the learning of complex skills across domains. Yet, despite this evidence-based support for SBL, teacher education continues to be slow to adopt and embed SBL within their programs. This paper compares literature on two of the longest and widest adopted simulated programs in teacher education,Second LifeandsimSchool—to gain insight into the research types, findings and reasons for limited implementation. The findings support previously confirmed pedagogical benefits of SBL increasing student self-efficacy and reveal commonalities and differences between the two simulated platforms and a lack of adoption of SBL that centres around costs, accessibility and technical issues. The findings are positioned in practice-theory literature and highlight SBL’s ability to provide preservice teachers with a ‘third space’ where theory can be practiced, rehearsed and reviewed virtually before real classroom transference occurs. We offer recommendations that will stimulate future research and support wider adoption of SBL in Initial Teacher Education (ITE).
Closed-form solutions of consistency ratio in best worst method minmax optimization model: max of edge error matrix and minmax edge error determinant methods
Authors: Yuen Kevin Kam Fung 
Published: April 2024

AbstractThe Best Worst Method (BWM), a reduced version of the AHP, is a recent multi-criteria decision-making tool based on pairwise comparisons with reference to the best and worst criteria. Consistency Ratio (CR) measurement for the rating quality and prioritizations is still a controversial topic. Firstly, the computation for the current CR of BWM must rely on a software optimization solver to find the optimal values, and the solver may not always guarantee the exact optimal solutions, especially if the computational cost settings are not large enough for higher number of criteria. Secondly, much effort to evaluate optimization algorithms is needed to find the best solutions with the least computational resources due to diverse solvers possibly leading to different results with different performances. Thirdly, optimization programming code is not trivial to be implemented for general BWM users. To address these issues, this paper presents the closed-form solutions, Max of Edge Error Matrix (MEEM) (Eq. (44) of Theorem 4) and Minmax Edge Error Determinant (MEED) (Algorithm 1), to replace the BWM optimization models to directly calculate the CR values. Two simulations have been performed with a basic laptop using a single process. One simulation of twenty thousand random pairs of vectors took 26.34 h to perform to verify that the approximate results are higher than or very close to the exact closed-form values of both methods when high computational cost is allocated for the solver to increase the precision. Another simulation of one million random pairs of vectors only took 1.27 h to perform to verify that the MEED and MEEM methods always produce the same results for the number of criteria up to nine. The computational time for the exact results is dramatically reduced when the solver is not needed. The advantages of the proposed solutions include the following: the software to solve the optimization model to obtain CR is unnecessary, and the proposed calculation is extremely efficient to obtain the exact accuracy. The two-step optimization model can preserve the fixed Minmax Edge Error to find the weights which add up to one, which is the condition to determine if the model reaches exact optimal solutions. As the CR optimization model produces multiple versions of weights, which are recommended not to be used, the new method does not need to compute the unnecessary weight values to get the Minmax Edge Error. With the provision of equations leading to closed forms, users can understand the properties of CR in much clearer perspectives. Due to the computational efficiency and explainability, the proposed closed forms can replace the CR optimization model to compute CR efficiently and accurately for all diverse applications using BWM.