bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effectiveness of social media-assisted course on learning self-efficacy
Authors: Hu Jiaying , Lai Yicheng , Yi Xiuhua 
Published: May 2024

AbstractThe social media platform and the information dissemination revolution have changed the thinking, needs, and methods of students, bringing development opportunities and challenges to higher education. This paper introduces social media into the classroom and uses quantitative analysis to investigate the relation between design college students’ learning self-efficacy and social media for design students, aiming to determine the effectiveness of social media platforms on self-efficacy. This study is conducted on university students in design media courses and is quasi-experimental, using a randomized pre-test and post-test control group design. The study participants are 73 second-year design undergraduates. Independent samples t-tests showed that the network interaction factors of social media had a significant impact on college students learning self-efficacy. The use of social media has a significant positive predictive effect on all dimensions of learning self-efficacy. Our analysis suggests that using the advantages and value of online social platforms, weakening the disadvantages of the network, scientifically using online learning resources, and combining traditional classrooms with the Internet can improve students' learning self-efficacy.
Elevated serum homocysteine levels associated with poor recurrence-free and overall survival in patients with colorectal cancer
Authors: Xie Hailun , Wei Lishuang , Wang Qiwen , Tang Shuangyi , Gan Jialiang 
Published: May 2024

AbstractThis study aimed to evaluate the significance of homocysteine (HCY) levels in predicting recurrence-free survival (RFS) and overall survival (OS) in colorectal cancer (CRC) patients. This retrospective study involved 1272 CRC patients. The risk of mortality increased with increasing HCY levels in CRC patients. The optimal HCY cutoff value in CRC patients was 15.2 μmol/L. The RFS (45.8% vs. 60.5%, p < 0.001) and OS (48.2% vs. 63.2%, p < 0.001) of patients with high HCY levels were significantly lower than those of patients with low HCY levels. Patients with high HCY levels were older, male, had large tumours, high carcinoembryonic antigen (CEA) levels, and long hospital stays, and incurred high hospitalisation costs. Multivariate analysis showed that when HCY levels exceeded 15.2 μmol/L, the risk of adverse RFS and OS increased by 55.7% and 61.4%, respectively. Subgroup analysis showed that HCY levels could supplement CEA levels and pathological staging. We constructed HCY-based prognostic nomograms, which demonstrated feasible discrimination and calibration values better than the traditional tumour, node, metastasis staging system for predicting RFS and OS. Elevated serum HCY levels were strongly associated with poor RFS and OS in CRC patients. HCY-based prognostic models are effective tools for a comprehensive evaluation of prognosis.
Bi-layer cBN-based composites reinforced with oxide and non-oxide microfibers of refractory compounds
Authors: Klymenko Serhiy , Zhang Hao , Savchenko Denys , Chumak Anatoliy , Klymenko Sergiy , Melniychuk Yuriy , Manokhin Andriy , Kremenytskyi Valerii V. , Novichenko Victor M. 
Published: May 2024

AbstractResearch into new composites utilizing cubic boron nitride (PcBN) shows promise for enhancing cutting tool performance. The unique properties of these materials stem from the addition of microfibers made of refractory compounds to their structure. This study looks at developing two-layer composites based on cBN group BL, reinforced with SiCw and Al2O3w microfibers. The goal is to improve tool stability when cutting hardened steels with impact loads. PcBN composite samples were made by sintering a mixture of cBN powder with bundles and microfibers under 7.7 GPa pressure. Bond material selection was based on analyzing the relationship between Poisson's ratio (η) and plasticity parameter (G/B). The density, Young's modulus, Poisson's ratio, and hardness of the composites were determined, and the microstructure of samples with TiCN bond was studied. Tool-life tests were conducted on two-layer cutting inserts made of PcBN reinforced with SiCw and Al2O3w microfibers during the machining of hardened KhVG steel (HRC 55) under impact loads at cutting speeds of 100 and 200 m/min.
Identification and validation of N-acetylputrescine in combination with non-canonical clinical features as a Parkinson’s disease biomarker panel
Authors: Peng Kuan-Wei , Klotz Allison , Guven Arcan , Kapadnis Unnati , Ravipaty Shobha , Tolstikov Vladimir , Vemulapalli Vijetha , Rodrigues Leonardo O. , Li Hongyan , Kellogg Mark D. , Kausar Farah , Rees Linda , Sarangarajan Rangaprasad , Schüle Birgitt , Langston William , Narain Paula , Narain Niven R. , Kiebish Michael A. 
Published: May 2024

AbstractParkinson’s disease is a progressive neurodegenerative disorder in which loss of dopaminergic neurons in the substantia nigra results in a clinically heterogeneous group with variable motor and non-motor symptoms with a degree of misdiagnosis. Only 3–25% of sporadic Parkinson’s patients present with genetic abnormalities that could represent a risk factor, thus environmental, metabolic, and other unknown causes contribute to the pathogenesis of Parkinson’s disease, which highlights the critical need for biomarkers. In the present study, we prospectively collected and analyzed plasma samples from 194 Parkinson’s disease patients and 197 age-matched non-diseased controls. N-acetyl putrescine (NAP) in combination with sense of smell (B-SIT), depression/anxiety (HADS), and acting out dreams (RBD1Q) clinical measurements demonstrated combined diagnostic utility. NAP was increased by 28% in Parkinsons disease patients and exhibited an AUC of 0.72 as well as an OR of 4.79. The clinical and NAP panel demonstrated an area under the curve, AUC = 0.9 and an OR of 20.4. The assessed diagnostic panel demonstrates combinatorial utility in diagnosing Parkinson’s disease, allowing for an integrated interpretation of disease pathophysiology and highlighting the use of multi-tiered panels in neurological disease diagnosis.
Siberian vegetation growth intensifies monsoon precipitation in southern East Asia in late spring and early summer
Authors: Yeh Sang-Wook , Sohn Byung-Ju , Oh Sae-Yoon , Song Se-Yong , Jeong Jee-Hoon , Wang Bin , Wu Renguang , Yang Young-Min 
Published: May 2024

AbstractRegional hydrological cycle responding to rising temperatures can have significant influences on society and human activities. We suggest a new perspective on East Asia’s enhanced precipitation amount that emphasizes the role of Siberian surface warming. Increased vegetation greenness in late spring and early summer in eastern Siberia, which may be a response to global warming, acts to warm the surface by reducing the surface albedo with an increase in net absorbed shortwave radiation. Subsequently, eastern Siberia warming leads to the strengthening of anti-cyclonic atmospheric circulation over inner East Asia as well as the subtropical western North Pacific high via thermal forcing and the enhanced land-sea thermal contrast, respectively. Consequently, the anticyclonic circulation over inner East Asia transports much drier and cooler air to southern East Asia. This leads to favorable conditions for increased precipitation in combination with an increased tropical moisture flux from the subtropical western North Pacific high. Therefore, continuous Siberian vegetation growth has a potential influence on the future precipitation amount in the subtropics through vegetation–atmosphere coupled processes.
Constructing personalized characterizations of structural brain aberrations in patients with dementia using explainable artificial intelligence
Authors: Leonardsen Esten H. , Persson Karin , Grødem Edvard , Dinsdale Nicola , Schellhorn Till , Roe James M. , Vidal-Piñeiro Didac , Sørensen Øystein , Kaufmann Tobias , Westman Eric , Marquand Andre , Selbæk Geir , Andreassen Ole A. , Wolfers Thomas , Westlye Lars T. , Wang Yunpeng 
Published: May 2024

AbstractDeep learning approaches for clinical predictions based on magnetic resonance imaging data have shown great promise as a translational technology for diagnosis and prognosis in neurological disorders, but its clinical impact has been limited. This is partially attributed to the opaqueness of deep learning models, causing insufficient understanding of what underlies their decisions. To overcome this, we trained convolutional neural networks on structural brain scans to differentiate dementia patients from healthy controls, and applied layerwise relevance propagation to procure individual-level explanations of the model predictions. Through extensive validations we demonstrate that deviations recognized by the model corroborate existing knowledge of structural brain aberrations in dementia. By employing the explainable dementia classifier in a longitudinal dataset of patients with mild cognitive impairment, we show that the spatially rich explanations complement the model prediction when forecasting transition to dementia and help characterize the biological manifestation of disease in the individual brain. Overall, our work exemplifies the clinical potential of explainable artificial intelligence in precision medicine.
Human intraparietal sulcal morphology relates to individual differences in language and memory performance
Authors: Santacroce Federica , Cachia Arnaud , Fragueiro Agustina , Grande Eleonora , Roell Margot , Baldassarre Antonello , Sestieri Carlo , Committeri Giorgia 
Published: May 2024

AbstractThe sulco-gyral pattern is a qualitative feature of the cortical anatomy that is determined in utero, stable throughout lifespan and linked to brain function. The intraparietal sulcus (IPS) is a nodal associative brain area, but the relation between its morphology and cognition is largely unknown. By labelling the left and right IPS of 390 healthy participants into two patterns, according to the presence or absence of a sulcus interruption, here we demonstrate a strong association between the morphology of the right IPS and performance on memory and language tasks. We interpret the results as a morphological advantage of a sulcus interruption, probably due to the underlying white matter organization. The right-hemisphere specificity of this effect emphasizes the neurodevelopmental and plastic role of sulcus morphology in cognition prior to lateralisation processes. The results highlight a promising area of investigation on the relationship between cognitive performance, sulco-gyral pattern and white matter bundles.
Projected poleward migration of the Southern Ocean CO2 sink region under high emissions
Authors: Mongwe Precious , Gregor Luke , Tjiputra Jerry , Hauck Judith , Ito Takamitsu , Danek Christopher , Vichi Marcello , Thomalla Sandy , Monteiro Pedro M. S. 
Published: May 2024

AbstractThe Southern Ocean is a major region of ocean carbon uptake, but its future changes remain uncertain under climate change. Here we show the projected shift in the Southern Ocean CO2 sink using a suite of Earth System Models, revealing changes in the mechanism, position and seasonality of the carbon uptake. The region of dominant CO2 uptake shifts from the Subtropical to the Antarctic region under the high-emission scenario. The warming-driven sea-ice melt, increased ocean stratification, mixed layer shoaling, and a weaker vertical carbon gradient is projected to together reduce the winter de-gassing in the future, which will trigger the switch from mixing-driven outgassing to solubility-driven uptake in the Antarctic region during the winter season. The future Southern Ocean carbon sink will be poleward-shifted, operating in a hybrid mode between biologically-driven summertime and solubility-driven wintertime uptake with further amplification of biologically-driven uptake due to the increasing Revelle Factor.
Cyber‐physical‐based welding systems: Components and implementation strategies
Authors: Szőlősi József , Magyar Péter , Antal József , Szekeres Béla J. , Farkas Gábor , Andó Mátyás 
Published: May 2024

AbstractThe conditions for a feasible Cyber‐Physical System (CPS) in a welding environment are explored for the manufacturing technology components while also focusing on machine learning tools. Increasing manufacturing efficiency means making digitalisation feasible for all technologies, including welding, given today's challenges. Early versions of manufacturing management, such as Computer Integrated Manufacturing, are already leading the way, and one of the latest milestones in these developments is CPS. It can be shown that the digital migration of specific sub‐domains (e.g. visual inspection of the weld seam during quality assurance) is significantly more challenging and unimaginable without artificial intelligence applications. However, it is also true that the full integration needed to achieve autonomous manufacturing has yet to be fully achieved, although there is a strong demand in the industry for these CPS to work. In some areas, the digital switchover has already been prepared. However, the interconnection of these subsystems requires modern information systems or, in the case of existing ones, their upgrading to the appropriate level. This research area is set to be addressed comprehensively by initiating several projects. In the initial phase, the aim is to develop an architecture that integrates the various Information Technology applications. In this work, the digital manufacturing environment under CPS is studied, the relevant components are explored, the conditions for the transition from traditional to CPS‐based manufacturing are examined and examples of planned further specific studies on the components are listed.
ALMA-IMF
Authors: Bonfand M. , Csengeri T. , Bontemps S. , Brouillet N. , Motte F. , Louvet F. , Ginsburg A. , Cunningham N. , Galván-Madrid R. , Herpin F. , Wyrowski F. , Valeille-Manet M. , Stutz A. M. , Di Francesco J. , Gusdorf A. , Fernández-López M. , Lefloch B. , Liu H-L. , Sanhueza P. , Álvarez-Gutiérrez R. H. , Olguin F. , Nony T. , Lopez-Sepulcre A. , Dell’Ova P. , Pouteau Y. , Jeff D. , Chen H.-R. V. , Armante M. , Towner A. , Bronfman L. , Kessler N. 
Published: May 2024

Context. The star formation process leads to an increased chemical complexity in the interstellar medium. Sites associated with high-mass star and cluster formation exhibit a so-called hot core phase, characterized by high temperatures and column densities of complex organic molecules.
Aims. We aim to systematically search for and identify a sample of hot cores toward the 15 Galactic protoclusters of the ALMA-IMF Large Program and investigate their statistical properties.
Methods. We built a comprehensive census of hot core candidates toward the ALMA-IMF protoclusters based on the detection of two CH3OCHO emission lines at 216.1 GHz. We used the source extraction algorithm GExt2D to identify peaks of methyl formate (CH3OCHO) emission, a complex species commonly observed toward sites of star formation. We performed a cross-matching with the catalog of thermal dust continuum sources from the ALMA-IMF 1.3 mm continuum data to infer their physical properties.
Results. We built a catalog of 76 hot core candidates with masses ranging from ~0.2 M⊙ to ~80 M⊙, of which 56 are new detections. A large majority of these objects, identified from methyl formate emission, are compact and rather circular, with deconvolved full width at half maximum (FWHM) sizes of ~2300 au on average. The central sources of two target fields show more extended, but still rather circular, methyl formate emission with deconvolved FWHM sizes of ~6700 au and 13 400 au. About 30% of our sample of methyl formate sources have core masses above 8 M⊙ and range in size from ~1000 au to 13 400 au, which is in line with measurements of archetypical hot cores. The origin of the CH3OCHO emission toward the lower-mass cores may be explained as a mixture of contributions from shocks or may correspond to objects in a more evolved state (i.e., beyond the hot core stage). We find that the fraction of hot core candidates increases with the core mass, suggesting that the brightest dust cores are all in the hot core phase.
Conclusions. Our results suggest that most of these compact methyl formate sources are readily explained by simple symmetric models, while collective effects from radiative heating and shocks from compact protoclusters are needed to explain the observed extended CH3OCHO emission. The large fraction of hot core candidates toward the most massive cores suggests that they rapidly enter the hot core phase and that feedback effects from the forming protostar(s) impact their environment on short timescales.
A Process for Institutional Adoption and Diffusion of Blended Learning in Higher Education
Authors: Ali Ramiz , Georgiou Helen 
Published: May 2024

AbstractBlended learning has emerged as a prominent feature in higher education over the past decade, aiming to enhance students’ learning experiences and improve outcomes. It has been adopted at various levels within universities, with an increasing trend of institutional adoption. Despite its prevalence, scholars have expressed concerns about our limited understanding of blended learning beyond small-scale and individual applications. Drawing on Rogers’ diffusion of innovations theory, this case study explores the intricate process of adoption and implementation of blended learning within a university. Semi-structured, one-on-one interviews were conducted with 24 lecturers and six university executives involved in a university-wide initiative for blended learning. The interviews were analysed using a thematic pattern matching technique. In addition, a variety of relevant university documents were gathered and analysed using a content analysis method. Results reveal that despite some hesitancies among lecturers, the process of adoption of blended learning was supported by a well-justified strategy, investment in infrastructure, and provision of continued lecturer support. Viewing these results through the lens of Roger’s stage model highlights a lack of a proper ‘matching’ stage, reflecting a failure to engage lecturers in adoption decision-making and incorporate their feedback into the blended learning strategy.
Improved filtering methods to suppress cardiovascular contamination in electrical impedance tomography recordings
Authors: Wisse Jantine J , Somhorst Peter , Behr Joris , van Nieuw Amerongen Arthur R , Gommers Diederik , Jonkman Annemijn H 
Published: May 2024

Abstract

Objective. Electrical impedance tomography (EIT) produces clinical useful visualization of the distribution of ventilation inside the lungs. The accuracy of EIT-derived parameters can be compromised by the cardiovascular signal. Removal of these artefacts is challenging due to spectral overlapping of the ventilatory and cardiovascular signal components and their time-varying frequencies. We designed and evaluated advanced filtering techniques and hypothesized that these would outperform traditional low-pass filters. Approach. Three filter techniques were developed and compared against traditional low-pass filtering: multiple digital notch filtering (MDN), empirical mode decomposition (EMD) and the maximal overlap discrete wavelet transform (MODWT). The performance of the filtering techniques was evaluated (1) in the time domain (2) in the frequency domain (3) by visual inspection. We evaluated the performance using simulated contaminated EIT data and data from 15 adult and neonatal intensive care unit patients. Main result. Each filter technique exhibited varying degrees of effectiveness and limitations. Quality measures in the time domain showed the best performance for MDN filtering. The signal to noise ratio was best for DLP, but at the cost of a high relative and removal error. MDN outbalanced the performance resulting in a good SNR with a low relative and removal error. MDN, EMD and MODWT performed similar in the frequency domain and were successful in removing the high frequency components of the data. Significance. Advanced filtering techniques have benefits compared to traditional filters but are not always better. MDN filtering outperformed EMD and MODWT regarding quality measures in the time domain. This study emphasizes the need for careful consideration when choosing a filtering approach, depending on the dataset and the clinical/research question.
Additive effect of poly(N-methylaniline) coated Fe3O4 composite particles on carbonyl iron based magnetorheological fluid
Authors: Wang Shizhao , Park ChaeWon , Kwon Yong Ku , Jin Hyoung-Joon , Lee Jin-Kyun , Choi Hyoung Jin 
Published: May 2024

Abstract
Poly(N-methylaniline) (PNMA) coated magnetite (Fe3O4) (PNMA@Fe3O4) composite particles synthesized through both chemical oxidative polymerization and chemical co-precipitation processes were used as a magnetic additive for carbonyl iron (CI)-based magnetorheological (MR) fluid. The effect of the additive’s content on the rheological characteristics of the MR fluid in the presence of an externally applied magnetic field was studied along with its effect on the sedimentation ratio compared with that of CI-based MR fluid. Shear stress curves as a function of the shear rate of the CI-based MR fluids with the additive were found to be well-fitted by the Herschel–Bulkley equation and the slope of the dynamic yield stress was determined to be 2.0. The curves also showed yield stresses higher than those of the CI-based MR fluid for different magnetic field strengths. Specifically, the CI-based MR fluid with 1.0 wt% additive showed the highest yield stress and the best solid-like properties among the tested samples. Furthermore, the sedimentation issue for the CI-based MR fluid was found to improve significantly, especially for the lowest settling rate of the MR fluid with 1.0 wt% additive. The addition of 1.0 wt% PNMA@Fe3O4 additive resulted in the CI-based MR fluid exhibiting the best properties, owing to improved rheological features and a reduced sedimentation rate.
Representation of solutions to fuzzy linear fractional differential equations with a piecewise constant argument
Authors: Van Phut Lai 
Published: May 2024

Abstract
This study marks the first exploration of fuzzy linear fractional differential equations with a piecewise constant argument (FLFDEs-PCA), incorporating the concept of Caputo’s type gH-differentiability with the order α ∈ (0, 1]. Such problems are noteworthy as they represent hybrid systems, blending the characteristics of continuous and discrete dynamical systems and integrating aspects from both differential and difference equations. The primary objective of this research is to establish a standardized framework for deriving explicit solution formulas for FLFDEs-PCA under various scenarios. Additionally, illustrative examples are provided to demonstrate the practical implications of our theoretical findings.
The energy dissipation of a test-charge particle within a dense, degenerate electron- positron-ion plasma
Authors: Ali S , Hafeez S , Khan Majid 
Published: May 2024

Abstract
The energy loss of a moving test-charge particle is studied in a degenerate quantized plasma, whose constituents are the electrons, positrons, and ions. The electrons and positrons are assumed to be quantized and degenerate species, whereas positive ions are treated classically. Relying on the kinetic formalism, an expression for the test-charge potential is derived with a modified dielectric response function involving the ion-acoustic oscillations. The energy loss or stopping power is solvedas a function of a test-charge speed, which is significantly affected by the positron concentration, the electron and positron quantization factors and plasma parameters. It is examined that quantization and quantum parameters lead to the enhancement of energy loss in an electron-positron-ion (EPI) dense plasma. The present findings may prove useful to understand the test-charge response in degenerate dense plasmas, where electrons and positrons are quantized in the strong magnetic fields.