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School journey as a third place By Zoe Moody, Ayuko Berchtold‐Sedooka, Sara Camponovo, Philip D. Jaffé and Frédéric Darbellay (Eds.), London: Anthem Press. 2023. pp. 263. £80. ISBN 9781839986314
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A Movement Classification of Polymyalgia Rheumatica Patients Using Myoelectric Sensors
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Data can be made available upon request to the relevant institution.Gait disorder is common among people with neurological disease and musculoskeletal disorders. The detection of gait disorders plays an integral role in designing appropriate rehabilitation protocols. This study presents a clinical gait analysis of patients with polymyalgia rheumatica to determine impaired gait patterns using machine learning models. A clinical gait assessment was conducted at KATH hospital between August and September 2022, and the 25 recruited participants comprised 18 patients and 7 control subjects. The demographics of the participants follow: age 56 years ± 7, height 175 cm ± 8, and weight 82 kg ± 10. Electromyography data were collected from four strained hip muscles of patients, which were the rectus femoris, vastus lateralis, biceps femoris, and semitendinosus. Four classification models were used—namely, support vector machine (SVM), rotation forest (RF), k-nearest neighbors (KNN), and decision tree (DT)—to distinguish the gait patterns for the two groups. SVM recorded the highest accuracy of 85% among the classifiers, while KNN had 75%, RF had 80%, and DT had the lowest accuracy of 70%. Furthermore, the SVM classifier had the highest sensitivity of 92%, while RF had 86%, DT had 90%, and KNN had the lowest sensitivity of 84%. The classifiers achieved significant results in discriminating between the impaired gait pattern of patients with polymyalgia rheumatica and control subjects. This information could be useful for clinicians designing therapeutic exercises and may be used for developing a decision support system for diagnostic purposes.This research received no external funding
Green, keen, and somewhere in between: An employee environmental segmentation study
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Data will be made available on request.Past research analyzes employee engagement in pro-environmental behavior by assuming all employees are similar in their values, beliefs, and norms (VBN). We argue that a segmented approach is more effective in understanding workplace pro-environmental behaviors (PEBs) and seek to develop a typology of employees. Analyzing data from 702 office employees in the UK, this study yields a more finely grained segmentation of employee differences regarding environmental dimensions, personality traits, behaviors, and perceptions. Based on a cluster analysis methodology, this paper identifies three distinct employee segments: ‘Acorns,’ ‘Saplings,’ and ‘Trees.’ Theoretically, our findings suggest that the VBN theory should be expanded by integrating personality traits, and that organizational environmental policy makers should pay attention to the green subcultures that may form within clusters. Practically, our typology helps organizations design interventions to target different groups of employees with customized motivational strategies, communication tactics, and engagement approaches.US-UK Fulbright Commission (Fulbright grant number: 8142001); Durham University, UK
Editorial: Rising stars in neuropsychology 2021
Get PDFIn the kaleidoscope of neuropsychological research, the Rising stars in neuropsychology 2021 Research Topic converges on pivotal studies exploring Adult Attention-Deficit/Hyperactivity Disorder (ADHD), the role of predictive processing in linguistics, and the variants of Primary Progressive Aphasia (PPA). In this editorial, we delve into these studies while weaving connections with executive functioning, neurodegenerative diseases, and the nuanced framework of neurocognitive models.No financial support was received for the research, authorship, and/or publication of this article
Frontiers Media
No full textMajor advancements in the fast-growing field of neurocognitive aging and behavior were highlighted in the inaugural Insights in neurocognitive aging and behavior: 2021 Research Topic. It included 15 articles that addressed novel approaches to identifying and predicting cognitive decline, neurocognitive markers for Alzheimer's disease (AD), lifestyle contributions to aging and AD, and commentary on neurocognitive aging theory.No financial support was received for the research, authorship, and/or publication of this article
Study of azimuthal anisotropy of (1S) mesons in pPb collisions at = 8.16 TeV
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Release and preservation of data used by the CMS Collaboration as the basis for publications is guided by the CMS policy as stated in “CMS data preservation, re-use and open access policy”.A preprint of this paper is available at arXiv:2310.03233v2 [hep-ex], https://doi.org/10.48550/arXiv.2310.03233. It has not been certified by peer review.The azimuthal anisotropy of Υ(1S) mesons in high-multiplicity proton-lead collisions is studied using data collected by the CMS experiment at a nucleon-nucleon center-of-mass energy of 8.16 TeV. The Υ(1S) mesons are reconstructed using their dimuon decay channel. The anisotropy is characterized by the second Fourier harmonic coefficients, found using a two-particle correlation technique, in which the Υ(1S) mesons are correlated with charged hadrons. A large pseudorapidity gap is used to suppress short-range correlations. Nonflow contamination from the dijet background is removed using a low-multiplicity subtraction method, and the results are presented as a function of Υ(1S) transverse momentum. The azimuthal anisotropies are smaller than those found for charmonia in proton-lead collisions at the same collision energy, but are consistent with values found for Υ(1S) mesons in lead-lead interactions at a nucleon-nucleon center-of-mass energy of 5.02 TeV.SCOAP3
Microstructure and Tensile Properties of HPDC Mg–RE Alloys with Varying Y Additions
Get PDFThis paper is an invited submission to IJMC selected from presentations at the Light Metals Technology Conference (LMT2023) held July 10 to 12, 2023, in Melbourne, Australia, based upon the original presentation.Supplementary Information is available online at: https://link.springer.com/article/10.1007/s40962-024-01266-z#Sec17 .High-pressure die-casting Mg–2.6RE–xY (EW) alloys with Y contents between 0 and 3% (in wt%) were investigated for their microstructure and tensile properties. In the Y-containing alloy, the intermetallic phases at the grain boundaries consisted of skeletal Mg12RE phase, bulk Mg24Y5 phase and irregular Mg3Y phase, while {011} twins were observed in the Mg12RE phase. The yield strength was improved by Y addition at both room temperature and high temperatures. Compared with Y-free alloy, the yield strength of 3% Y alloy increased from 143.1 to 174.8 MPa and improved by 22.2% at room temperature, while it was increased from 72.2 to 104.6 MPa and enhanced by 44.9% at 300 °C. The area fraction of intermetallic phase increased dramatically from 14.5 to 18.4% with 3% Y addition. Second phase strengthening was the major contributor to the yield strength increase at ambient temperature. The increment of the area fraction of the high-thermally stable Mg–RE intermetallic phases with Y addition contributed to the consequent improvement in yield strength at high temperatures. At ambient temperature, the mechanism for the fracture of EW alloys was a ductile and quasi-cleavage fracture blend.Innovate UK (Project reference: 10004694)
Microstructural evolution and strengthening mechanisms of a high-strength Al-Mg-Si alloy processed by laser powder bed fusion and ageing treatment
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Data will be made available on request.In this work, the processability, microstructural evolution and mechanical properties of a novel crack-free Al-5.3 wt% Mg-3.3 wt% Si alloy fabricated by laser powder bed fusion (LPBF) were investigated systematically. The Al-5.3 wt% Mg-3.3 wt% Si alloy with low solidification range exhibits good processability and reaches a high relative density of 99.6% at the VED of 103.3 J/mm3. The hierarchical microstructure was featured by the fine α-Al matrix that contains the interaction between the nanosized Mg2Si eutectic and high-density dislocations in the as-LPBFed alloy, which delivers high yield strength of 374 MPa and elongation of 5.8% under as-LPBFed condition. The yield strength is further enhanced to 433 MPa under as-aged condition of 180 °C for 6 h. The property enhancement is associated with the precipitation of β'′ and β phase. However, the broken and coarsened Mg2Si eutectics as well as the reduction of dislocation density result in strength degradation after ageing exceeds 300 °C.National Natural Science Foundation of China (Grant No. 52071343); Leading Innovation and Entrepreneurship Team of Zhejiang Province – Automotive Light Alloy Innovation Team (2022R01018)
Physiological Data for User Experience and Quality of Experience: A Systematic Review (2018–2022)
Get PDFThe evaluation of human responses in multimedia experiences using physiological data has a well-established presence in the academic literature. However, this field is currently undergoing transformative changes, driven by the accessibility of diverse and cost-effective devices, innovative software analysis methods, and the emergence of novel application domains such as Virtual and Augmented Reality and mulsemedia. To address the imperative of contextualizing these evolving trends in a contemporary context, this paper presents a systematic review with the objective of delineating the array of physiological data utilized in assessing Quality of Experience (QoE) and User Experience (UX) in multimedia studies. It also examines the devices employed for data collection and the analytical techniques applied to interpret the acquired data. While our review exposes both constraints and promising discoveries in these domains, it also emphasizes the escalating significance and practicality of leveraging physiological data in user assessments, especially as the boundaries between the physical and digital domains continue to blur.Coordination for the Improvement of Higher Education Personnel (CAPES, Brazil) – Finance Codes 88887.570688/2020-00 and 88881.689984/2022-01; National Council for Scientific and Technological Development (CNPQ, Brazil) – Finance Code 307718/2020-4; Fundação de Amparo à Pesquisa e Inovação do Espírito Santo (FAPES, Brazil) – Finance Code 2021-GL60J
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