bluuebunny/crossref_metadata_2025_split huggingface dataset:
Variable Performance of D-dimer Testing by Hemostasis Laboratories: The Australasian/Asia-Pacific Experience
Authors: Favaloro Emmanuel J. , Arunachalam Sandya , Dean Elysse 
Published: March 2024

AbstractD-dimers represent the breakdown products of fibrin. Thus, elevated plasma D-dimers will arise following a thrombotic event, such as a deep vein thrombosis or a pulmonary embolism, and therefore, a nonelevated D-dimer is used to effectively exclude such events. D-dimers are also elevated in a range of other conditions, for example, during disseminated intravascular coagulation. D-dimer levels may also be associated with prognostic value. For example, highly raised D-dimer levels can be associated with worsening clinical features in coronavirus disease 2019. Thus, D-dimer testing represents a commonly requested hemostasis test, often performed in 24/7 laboratories. Unfortunately, D-dimer testing is neither standardized nor harmonized across manufacturers or laboratories. Indeed, considering reporting units and the magnitude of units, up to 28 different combinations may be reported by laboratories. We provide updated findings for D-dimer testing in our geographic region, using recent data from the Royal College of Pathologists of Australasia Quality Assurance Programs, an international external quality assessment program, currently with over 450 participants in the D-dimer module. Data show a wide variety of assays in use and variable outcomes in reported numerical values when assessing proficiency samples. D-dimer testing mostly comprised reagents from three main manufacturing suppliers, with a small number of users of reagents from other manufacturers. Reported results showed important differences in numerical values for the same homogeneous tested samples when normalized to a single reporting unit (e.g., mg/L). Nevertheless, despite using different test reagents and reporting, most participants uniformly identified D-dimer values as below or above a “detection” cut-off for samples that were constructed to be below or above most cut-off values. As expected, mixed findings were reported for samples containing levels around expected cut-off values. We hope that our findings, reflecting on the heterogeneity of test reagents and test data, help improve diagnostic testing for D-dimer testing and facilitate harmonization and standardization, in the future.
Artificial intelligence and religious freedom: divergent paths converging on economic expansion
Authors: He Yugang 
Published: March 2024

AbstractIn the current era, the symbiotic relationship between artificial intelligence, religious freedom, and economic growth remains a topic of paramount importance. This study embarks on an in-depth exploration of these dynamics across 26 countries from 2000 to 2021. Utilizing the panel vector auto-regression model, the findings underscore a significant positive correlation between artificial intelligence, religious freedom, and economic growth. The forecast-error variance decomposition highlights the growing importance of both variables. It projects their increasing relevance in future economic landscapes. Furthermore, the study reaffirms the indomitable role of traditional growth drivers, specifically labor and capital inputs. The Toda-Yamamoto Granger causality analysis bolsters the validity and reliability of these findings. In summary, this research strengthens established economic paradigms and reveals new interactions, offering important implications for academics, policymakers, and stakeholders.
Consequential insights for advancing informal STEM learning and outcomes for students from historically marginalized communities
Authors: Ludwig Claudia McLaughlin , Howsmon Rebecca A. , Stromholt Shelley , Valenzuela Jacob J. , Calder Rachel , Baliga Nitin S. 
Published: March 2024

AbstractConsequential STEM experiences in informal settings can address issues of equity by fully engaging historically marginalized high school students in complex socio-scientific issues. However, inclusive and effective programs are in high demand, and there is little research on what specific aspects, context, and timeframes are most important when scaling these experiences. Using a mixed method approach, this study demonstrates that students make significant gains, in the short and long term, through in-person and remote informal programs ranging between 22-h and 320-h. Progress across STEM learning constructs is attributed to authentic research experiences, students’ connections to STEM professionals, direct hands-on participation in projects, and group work. Relative to formal education settings, research-based informal STEM programs can be implemented with minimal resources, can maintain effectiveness while scaling, and work towards addressing the societal challenge of improving STEM learning and outcomes for high school students from historically marginalized communities.
Impacting life expectancies of incarcerated people through dialogic scientific gatherings and dialogic scientific workshops in prisons
Authors: Novo-Molinero Maria-Teresa , Morla-Folch Teresa , Jimenez Esteller Laureano , Molina Roldan Silvia , Gomez Gonzalez Aitor 
Published: March 2024

AbstractThe scientific literature has presented evidence that participants in dialogic scientific gatherings (DSGs) transform their scientific interest in science. DSGs are based on a dialogical perspective, where egalitarian dialogue and the co-creation of knowledge are the two corner pieces that allow the development of new meanings for participants, improving their scientific literacy. There is a clear gap in scientific studies regarding DSGs in prison. This is the first research to address the impact of DSG and dialogic scientific workshops in prisons. The study presents the positive impact of the DSGs and scientific activities in promoting scientific interest in incarcerated people. A communicative case study was conducted in a Catalonian (Spain) prison between February and April 2022. Nineteen males who were incarcerated aged between 29 and 44 participated in twenty-one DSGs and twelve scientific workshops following a communicative approach. Data were collected through fifteen communicative observations during the application of the DSG and eight interviews with incarcerated people and two interviews with prison workers involved in implementing the DSG. The activities conducted and analysed in this study demonstrate that bringing science closer to all people, including the traditionally excluded population, is possible. The results show that the persons who experience incarceration’s motivation to participate in these scientific activities, which fostered their awareness of and interest in science, gave meaning to their learning and transformed their interactions in and out of prison.
Evidence of grade inflation in bachelor of business administration degrees in Turkey for the period from 2002 to 2022
Authors: Karadag Engin , Dortyol Ibrahim Taylan 
Published: March 2024

AbstractThe study analysed the change in the proportion of business management undergraduate programme graduates in Turkey who received honours (>2.99) over the past two decades. It also investigated the factors that contribute to grade inflation and the distribution of course grades. The research employed various statistical methods, including the random effects estimator, ANOVA, t-test, and ANCOVA, to examine the GPAs and 515,739 student grades from 12,579 courses taken by 46,416 graduates of business management undergraduate programmes at 40 universities between 2002 and 2022. According to our findings, the percentage of undergraduate business management students graduating with honours (>2.99) has increased from 11% in 2002 to 56% in 2022. The most significant increases occurred in 2021 and 2022, which coincided with the COVID-19 pandemic. Our research also revealed grade inflation, with a significant increase of 28% after controlling for variables that may affect graduation grades in Turkish undergraduate business management programmes. The factors that affect course grades include the student’s gender, grade level, language of instruction, instructor title, and course content. According to our findings, it can be concluded that the rapid expansion of undergraduate business management programmes in Turkey has resulted in a decline in qualifications. This, in turn, has led to a rise in grades.
Quantifying predictive uncertainty in damage classification for nondestructive evaluation using Bayesian approximation and deep learning
Authors: Li Zi , Deng Yiming 
Published: March 2024

Abstract
Magnetic flux leakage (MFL), a widely used nondestructive evaluation (NDE) method, for inspecting pipelines to prevent potential long-term failures. However, during field testing, uncertainties can affect the accuracy of the inspection and the decision-making process regarding damage conditions. Therefore, it is essential to identify and quantify these uncertainties to ensure the reliability of the inspection. This study focuses on the uncertainties that arise during the inverse NDE process due to the dynamic magnetization process, which is affected by the relative motion of the MFL sensor and the material being tested. Specifically, the study investigates the uncertainties caused by sensing liftoff, which can affect the output signal of the sensing system. Due to the complexity of describing the forward uncertainty propagation process, this study compared two typical machine learning (ML)-based approximate Bayesian inference methods, convolutional neural network and deep ensemble, to address the input uncertainty from the MFL response data. Besides, an autoencoder method is applied to tackle the lack of experimental data for the training model by augmenting the dataset, which is constructed with the pre-trained model based on transfer learning. Prior knowledge learned from large simulated MFL signals can fine-tune the autoencoder model which enhances the subsequent learning process on experimental MFL data with faster generalization. The augmented data from the fine-tuned autoencoder is further applied for ML-based defect size classification. This study conducted prediction accuracy and uncertainty analysis with calibration, which can evaluate the prediction performance and reveal the relation between the liftoff uncertainty and prediction accuracy. Further, to strengthen the trustworthiness of the prediction results, the decision-making process guided by uncertainty is applied to provide valuable insights into the reliability of the final prediction results. Overall, the proposed framework for uncertainty quantification offers valuable insights into the assessment of reliability in MFL-based decision-making and inverse problems.
Manufacturing and characterization of CMOS-MEMS magnetic field microsensors with isolated cavities
Authors: Dai Ching-Liang , Zhu Zhang-Li , Chang Chun-Yi , Hsu Cheng-Chih 
Published: March 2024

Abstract
The study investigates a magnetic field (MF) microsensor with isolated cavities manufactured utilizing complementary metal oxide semiconductor (CMOS)-microelectromechanical system technology. This microsensor, which is a type of magnetic transistor, comprises four identical magnetic sensing elements, each featuring an emitter, a base, two collectors, and an additional collector. The magnetic transistor operates on the principles of the Lorentz force. This force is employed to modulate the electrical properties of the transistor, responding to changes in the surrounding MF. The MF microsensor chip is fabricated using the commercial CMOS process. Upon completing the CMOS process, post-processing is employed to etch the silicon substrate of the microsensor chip, generating isolated cavities on the silicon substrate. These isolated cavities effectively mitigate substrate leakage current, enhancing the sensitivity of the MF microsensor. The experimental results reveal that the sensitivity of the microsensor without isolated cavities is 60 mV T−1. In contrast, the microsensor with isolated cavities exhibits a sensitivity of 121 mV T−1. A comparison between microsensors with and without isolated cavities depicts that the sensitivity of the MF microsensor with isolated cavities doubled.
Shape-interaction dualism: unraveling complex phase behavior in triangular particle monolayers
Authors: Akimenko S S , Gorbunov V A , Myshlyavtsev A V , Myshlyavtseva M D , Podgornyi S O 
Published: March 2024

Abstract
This paper examines the effect of finite attractive and repulsive interactions on the self-assembly of triangular-shaped particles on a triangular lattice. The ground state analysis of the lattice model has revealed an infinite sequence of ordered structures, a phenomenon referred to as the ‘devil’s staircase’ of phase transitions. The model has been studied at finite temperatures using both the transfer-matrix and tensor renormalization group methods. The concurrent use of these two methods lends credibility to the obtained results. It has been demonstrated that the initial ordered structures of the ‘devil’s staircase’ persist at non-zero temperatures. Further increase of the attraction between particles or a decrease of the temperature induces the appearance of subsequent ordered structures of the ‘devil’s staircase’. The corresponding phase diagram of the model has been calculated. The phase behavior of our model agrees qualitatively with the phase behavior of trimesic acid adsorption layer on single crystal surfaces.
Permutation fuzzy entropy based ICEEMDAN de-noising for inertial sensors
Authors: Tian Su , Wang Chenglong , Gong Xiaoying , Huang Dingfa 
Published: March 2024

Abstract
As one of the critical factors affecting the accuracy of inertial navigation system (INS) positioning, random noise will lead to the accumulation of INS positioning errors, even the failure of the system. Previous studies mainly focus on achieving noise reduction by adopting either the wavelet decomposition method or some relevant methods of the empirical mode decomposition (EMD). However, the former is limited by Heisenberg’s uncertainty principle when processing non-stationary signals, and the latter exhibits numerous mode-mixing phenomena during the decomposition process. In this paper, a permutation fuzzy entropy (PFE) based improved complete ensemble EMD with adaptive noise (ICEEMDAN) de-noising method is proposed to utilize the ICEEMDAN method for signal decomposition, and the PFE as an index to distinguish the effective intrinsic mode functions (IMFs) and the noisy IMFs during the decomposition process. In addition, simulated signals with different noise levels and field data with different durations are utilized to design a group of experiments to test the de-noising performance of the PFE-based ICEEMDAN de-noising method. The experimental results demonstrate that the advantages of our proposed method consists of three main parts: (1) The ICEEMDAN method more effectively alleviates the mode-mixing problem compared to the complete ensemble EMD with adaptive noise (CEEMDAN), thereby enhancing the accuracy of inertial measurement unit (IMU) signal reconstruction; (2) the PFE is more preferable than the permutation entropy for classify IMFs decomposed by the ICEEMDAN method; (3) our proposed method can effectively reduce IMU signal noise and improve the positioning accuracy of inertial sensor.
Research on sensing characteristics of microfluidic sensor based on photonic crystal fiber
Authors: Wang Zhan , Wang Shuai , Luo Yanhua , Xue Qi , Wang PengFei , Sun XiaoHong 
Published: March 2024

Abstract
To address the challenges associated with sample injection into the air hole of photonic crystal fiber (PCF) and collimation, in this paper, we assemble a single-mode photonic crystal single-mode fiber structure sensor chip based on the Mach–Zehnder interference principle using microfluidic chip processing technology. The sensing principle is analyzed mathematically and the sensing characteristics are verified theoretically and experimentally. The temperature sensitivity of the sensor is −1.3325 nm °C−1, and the refractive index sensitivity is 1666.2 nm RIU−1. This structure solves the difficulty of filling and coupling PCFs. Furthermore, it introduces a novel research methodology for the design and assembly of high-performance biosensors based on PCFs.
An improvement on the electrocatalytic performance of ZIF-67 by in situ self-growing CNTs on surface
Authors: Tang Miao , Sun Jintao , Naibao Huang , Wang Bin , Ge Xiaowen , Dong Wenjing , Li Wanting , Sun Xiannian 
Published: March 2024

Abstract
Efficient and robust oxygen reduction reaction (ORR) catalysts are essential for the development of high-performance anion-exchange membrane fuel cells (AEMFC). To enhance the electrochemical performance of metal–organic frameworks of cobalt-based zeolite imidazolium skeleton (ZIF-67), this study reported a novel ZIF-67-4@CNT by in situ growing carbon nanotubes (CNTs) on the surface of ZIF-67 via a mild two-step pyrolysis/oxidation treatment. The electrochemical results showed that the as-prepared ZIF-67-4@CNT after CTAB modification exhibited excellent catalytic activity with good stability, with Eonset, E1/2, and Ilimit, respectively were 0.98 V (versus RHE), 0.87 V (versus RHE) and 6.04 mA cm−2@1600 rpm, and a current retention rate of about 94.21% after polarized at 0.80 V for 10 000 s, which were all superior to that of the commercial 20 wt% Pt/C. The excellent ORR catalytic performance was mainly attributed to the large amount of the in situ growing CNTs on the surface, encapsulated with a wide range of valence states of metallic cobalt.
The Kresling origami spring: a review and assessment
Authors: Masana Ravindra , Dalaq Ahmed S , Khazaaleh Shadi , Daqaq Mohammed F 
Published: March 2024

Abstract
Structures inspired by the Kresling origami pattern have recently emerged as a foundation for building functional engineering systems with versatile characteristics that target niche applications spanning different technological fields. Their light weight, deployability, modularity, and customizability are a few of the key characteristics that continue to drive their implementation in robotics, aerospace structures, metamaterial and sensor design, switching, actuation, energy harvesting and absorption, and wireless communications, among many other examples. This work aims to perform a systematic review of the literature to assess the potential of the Kresling origami springs as a structural component for engineering design keeping three objectives in mind: (i) facilitating future research by summarizing and categorizing the current literature, (ii) identifying the current shortcomings and voids, and (iii) proposing directions for future research to fill those voids.
Classical and quantum cost of measurement strategies for quantum-enhanced auxiliary field quantum Monte Carlo
Authors: Kiser Matthew , Schroeder Anna , Anselmetti Gian-Luca R , Kumar Chandan , Moll Nikolaj , Streif Michael , Vodola Davide 
Published: March 2024

Abstract
Quantum-enhanced auxiliary field quantum Monte Carlo (QC-AFQMC) uses output from a quantum computer to increase the accuracy of its classical counterpart. The algorithm requires the estimation of overlaps between walker states and a trial wavefunction prepared on the quantum computer. We study the applicability of this algorithm in terms of the number of measurements required from the quantum computer and the classical costs of post-processing those measurements. We compare the classical post-processing costs of state-of-the-art measurement schemes using classical shadows to determine the overlaps and argue that the overall post-processing cost stemming from overlap estimations scales like

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per walker throughout the algorithm. With further numerical simulations, we compare the variance behavior of the classical shadows when randomizing over different ensembles, e.g. Cliffords and (particle-number restricted) matchgates beyond their respective bounds, and uncover the existence of covariances between overlap estimations of the AFQMC walkers at different imaginary time steps. Moreover, we include analyses of how the error in the overlap estimation propagates into the AFQMC energy and discuss its scaling when increasing the system size.
Phonon heat removal from metal nanoparticles and dynamics of nanoparticle cooling at low temperatures
Authors: Bezuglyj A I , Davydov L N 
Published: March 2024

Abstract
The theoretical analysis of the energy relaxation of an electron–phonon system of metal nanoparticles embedded in a dielectric matrix is usually based on semiphenomenological dynamic equations for electron and phonon temperatures (two-temperature model), which does not take into account the nonthermal nature of the phonon distribution function. In this work, we use a microscopic model that describes the dynamics of the electron–phonon system of metal nanorods and metal spherical nanoparticles in terms of the kinetic equation for the phonon distribution function. We focus on the size effect in the transfer of heat from a nanoparticle to a dielectric matrix. If the dimensions of the nanoparticle are much larger than the phonon-electron mean free path, then the heat transfer is determined by the properties of the interface between the nanoparticle and the matrix. In the opposite case, heat removal is determined solely by the parameters of the electron–phonon interaction in a metal nanoparticle. The dynamics of cooling of nanoparticles is also considered and the dependence of the electron temperature on time is obtained.
Cooperative properties of multiple quantum scattering: I quantum nutation
Authors: Enaki Nicolae A 
Published: March 2024

Abstract
The cooperative models of the bimodal field in the multiple quantum scattering nutations are discussed and proposed for possible detections in open cavities. We proposed two types of cooperation between the converted photon processes in these multiple steps of scattering nutation in the cavity. One of them takes into consideration the cooperative process between the photons of each step of the multiple steps of Raman conversion. The second cooperative process takes place between the photons belonging to different steps of multiple scattering conversions. The proposed novel bimodal entangled sources take into consideration both the coherence and collective phenomena between the photons belonging to the system of the bimodal field obtained in multiple scattering emissions. The application of higher-order multiple Raman bimodal coherent field in quantum information is proposed.
Weibel- and non-resonant Whistler wave growth in an expanding plasma in a 1D simulation geometry
Authors: Dieckmann M E , Palodhi L , Fegan C , Borghesi M 
Published: March 2024

Abstract
Ablating a target with an ultraintense laser pulse can create a cloud of collisionless plasma. A density ramp forms, in which the plasma density decreases and the ion’s mean speed increases with distance from the plasma source. Its width increases with time. Electrons lose energy in the ion’s expansion direction, which gives them a temperature anisotropy. We study with one-dimensional particle-in-cell simulations the expansion of a dense plasma into a dilute one, yielding a density ramp similar to that in laser-plasma experiments and a thermal-anisotropy-driven instability. Non-propagating Weibel-type wave modes grow in the simulation with no initial magnetic field. Their magnetic field diffuses across the shock and expands upstream. Circularly polarized propagating Whistler waves grow in a second simulation, in which a magnetic field is aligned with the ion expansion direction. Both wave modes are driven by non-resonant instabilities, they have similar exponential growth rates, and they can leave the density ramp and expand into the dilute plasma. Their large magnetic amplitude should make them detectable in experimental settings.