bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving some of the physical properties of building blocks by adding porcelain in different proportions
Authors: Mohammed J. S. , Nsaif F. K. , Abbas Mustafa , Jasim Kareem A. , Shaban Auday H. 
Published: May 2024

Abstract
One innovative method that has been widely used over the past few decades is the production of heat-treated compressed earth bricks, which are low-cost and environmentally friendly. The aim of the current manuscript is to study the geotechnical properties of rammed earth bricks collected from four areas in Diyala Governorate, namely Baqubah, Al-Muradiyah, Khan Bani Saad, and Al-Rashidiyah, after placing the collected samples in special bags afterwards. The locations of each sample were determined using a GPS device. A mixture of soil samples taken from the study area was prepared to form a good soil mixture after grinding it well and sifting it with a sieve (2 mm). Then water was added in gradual proportions and it became a good mixture. It was dried and ground again after adding porcelain in different proportions (0, 5, 10.15%).). The soil mixture was mixed wet and then the samples were compressed under pressure (8 tons). Samples are placed in the oven at a temperature of 900°C for two hours to produce all models. All brick models produced are then dried naturally at room temperature for 28 days to undergo thermal insulation testing.
Impacts of wildfires on boreal forest ecosystem carbon dynamics from 1986 to 2020
Authors: Xu Yiming , Zhuang Qianlai , Zhao Bailu , Billmire Michael , Cook Christopher , Graham Jeremy , French Nancy HF , Prinn Ronald 
Published: May 2024

Abstract
Wildfires significantly change boreal forest ecosystem carbon balance through both direct combustion and post-fire carbon dynamics. Affected vegetation influences soil thermal regime and carbon cycling by impacting the surface energy balance of boreal forests. This study uses a process-based biogeochemistry model to quantify carbon budget of North American boreal forests during 1986–2020 based on satellite-derived burn severity data. During the study period, burn severity generally increases. Fires remove ecosystem carbon of 2.4 Pg C and reduce net ecosystem production (NEP) from 32.6 to 0.8 Tg C yr−1, making the forest ecosystems lose 3.5 Pg C, shifting a carbon sink to a source. The canopy’s cooling effect leads to lower soil temperature and lower net primary production due to lower nitrogen mineralization and uptake. Post-fire NEP decreases from 1.6 to 0.8 Tg C yr−1. This reduction accounts for 50% of the simulated NEP when the effects of fire-affected canopy are not considered. Our study highlights the importance of wildfires and their induced-canopy changes in soil thermal and ecosystem carbon dynamics of boreal forests.
A comprehensive review on flow field properties in polymer mixing processes: a focus on applications in energetic materials
Authors: Wang Jingcheng , Xie Zhongyuan , Liu Jing 
Published: May 2024

Abstract
The mixing process is a critical step in the production of energetic materials and has a profound impact on product performance. As modern formulations for energetic materials continue to advance, the needs placed on the mixing process have become increasingly complex. Understanding and mastering the properties of the mixing flow field are essential for achieving optimal mixing function, ensuring process safety, and optimizing the parameters of both the mixing process and equipment specifically for energetic materials. In this comprehensive review, we analyze the influence of flow field properties on the mixing process of energetic materials by examining the mixing mechanism of two types of flow within the flow field. Additionally, we provide evidence to support the advantages of elongational flow in achieving effective mixing. We also discuss the application of mixing flow field properties in the processing of energetic materials, including advancements in mixing equipment and methods designed to optimize flow fields. Finally, we address the current shortcomings in energetic material mixing and offer an outlook for future developments in this field.
Temperature dependence of phase stabilities of hexagonal hemicarbides from first principles
Authors: Deng Chao , Zhong Lisheng , Wang Xianhui , Yu Yutong , Peng Jianhong 
Published: May 2024

Abstract
Transition metal hemicarbides, specifically M2C (where M = V, Nb, Ta, Mo and W), have received considerable attention in the fields of catalysis and metallurgy. However, the determination of the exact phase of each compound can still be challenging due to the close energetic proximity of its various polymorphs. This study uses first-principles calculations to carefully consider the subtle differences between different polymorphs, with temperature as a key factor. It is found that the energies of each polymorph of M2C are close, but can be distinguished when temperature effects are considered. This means that temperature plays an important role in the polymorph transformations. In addition, these phases exhibit dynamic stability at both zero and finite temperatures, in part due to the particular ordering of C atom occupancy in the metal lattice interstices. The study can provide calculations of a range of properties that help to identify stable structures and deepen the understanding of these materials in terms of chemical bonding, structural changes, lattice thermal vibrations and molecular dynamics.
Prediction of flow stress in Mg-3Dy alloy based on constitutive equation and PSO-SVR model
Authors: Liu Yafei , Feng Yunduo , Liu Qiangbing , Luan Shiyu , Li Xiaowei , Liu Xiaoyu , Zhang Lei , Wang Jinhui 
Published: May 2024

Abstract
This study conducted hot compression experiments on as-cast Mg-3Dy alloy under deformation parameters of 380 °C–470 °C and 0.001–1 s−1. The microstructure of the alloy was observed using EBSD, and the flow stress of the Mg-3Dy alloy was predicted using the Arrhenius model and the particle swarm optimization-support vector regression (PSO-SVR) model. The organizational analysis results showed that the main recrystallization mechanism in the alloy is the discontinuous dynamic recrystallization (DDRX) mechanism. The generation of twins in the alloy was mostly the result of local stress action. The optimal processing window for this alloy was determined to be 380 °C–470 °C and 0.001–0.01 s−1 through the thermal processing map. The prediction accuracies of the Arrhenius model and PSO-SVR model were evaluated using the correlation coefficient R2 and mean squared error MSE. The results showed that the PSO-SVR model significantly outperforms the Arrhenius model in prediction accuracy, with R2 value of 0.99982 and MSE of 0.074.
Systematic analysis of the gallium ions and structure-directing agents in the preparation of NiW HDS catalysts over mixed oxides of Al2O3-TiO2
Authors: Guzmán-Cruz M A , Pacheco-Sosa J G , Morales de la Garza L , Gochi Bautista A I , Medina-Cervantes J A , Gutiérrez-López E D , Fuentes-Moyado S , Díaz de León J N 
Published: May 2024

Abstract
In this study, we prepared Al2O3-TiO2 (AT) mixed oxides to synthesize NiW catalysts for sulfur removal reactions. The AT support samples were prepared with various surfactants. Additionally, gallium atoms (2.4 wt%) were introduced as an additive to coat the outer surface layers of AT support that lacked Al3+ or Ti2+ cations. Characterization results showed substantial differences in textural properties, chemical composition, and surface acidity. The x-ray Photoelectron Spectroscopy (XPS) and High-Resolution Transmission Electron Microscopy (HR-TEM) results demonstrated that the NiW/AT-L-Ga sample has a better combination of dispersion, sulfidation, and promotion among materials. The sulfided NiW/AT-L-Ga catalyst had the highest catalytic activity. After incorporating Ga, XPS observed that the activity could be associated with an increase in the NiWS active phase; however, including a surfactant in the synthesis of the support allowed an increase in the amount of NiWS phase. The active phase was modeled considering the HR-TEM results for the slab length, revealing the atoms at the border susceptible to promotion.
Thermal damage to the skin from 8.2 and 95 GHz microwave exposures in swine
Authors: Parker J E , Butterworth J W , Rodriguez R A , Kowalczewski C J , Christy R J , Voorhees W B , Payne J A , Whitmore J N 
Published: May 2024

Abstract
A study of burn thresholds from superficially penetrating radio-frequency (RF) energy at 8.2 and 95 GHz for swine skin was conducted. The study determined the thresholds for superficial, partial-thickness, and full-thickness burn severities after 5 seconds of exposure at power densities of 4–30 W/cm2 and 2–15 W/cm2 at 8.2 and 95 GHz, respectively. There were significant differences in the burn thresholds at the different severities between the two frequencies due to the large difference in energy penetration depths. Biopsies were collected from each burn site at 1, 24, 72, and 168 hr post exposure. Each sample was assessed by a burn pathologist against 20 histological factors to characterize the damage resulting from these RF overexposures. A one-dimensional, layered digital phantom that utilized realistic values for dielectric and thermal properties was used to explain some observed thresholds. The results of the heating and cooling response of the animal model and histology scores of each exposure are provided to enhance future efforts at simulation of RF overexposures and to establish damage thresholds.
Benchmarking Bayesian quantum estimation
Authors: Cimini Valeria , Polino Emanuele , Valeri Mauro , Spagnolo Nicolò , Sciarrino Fabio 
Published: May 2024

Abstract
The quest for precision in parameter estimation is a fundamental task in different scientific areas. The relevance of this problem thus provided the motivation to develop methods for the application of quantum resources to estimation protocols. Within this context, Bayesian estimation offers a complete framework for optimal quantum metrology techniques, such as adaptive protocols. However, the use of the Bayesian approach requires extensive computational resources, especially in the multiparameter estimations that represent the typical operational scenario for quantum sensors. Hence, the requirement to characterize protocols implementing Bayesian estimations can become a significant challenge. This work focuses on the crucial task of robustly benchmarking the performances of these protocols in both single and multiple-parameter scenarios. By comparing different figures of merits, evidence is provided in favor of using the median of the quadratic error in the estimations in order to mitigate spurious effects due to the numerical discretization of the parameter space, the presence of limited data, and numerical instabilities. These results, providing a robust and reliable characterization of Bayesian protocols, find natural applications to practical problems within the quantum estimation framework.
‘Quantum technology will change my life.’ Citizens’ attitudes and knowledge of quantum science and technology
Authors: van de Merbel Anka , Peer Jasper , Willems Sanne J W , Cramer Julia 
Published: May 2024

Abstract
Technology experts, industry leaders, and policy makers expect that a revolution in quantum technology is imminent. From earlier emerging technologies such as nanotechnology, it has become clear that an early connection with the public is beneficial for the societal impact of the technology. However, little research has yet been done on public attitudes and knowledge of quantum science and technology. In this work, we quantitatively measure the attitude of N = 145 citizens of Leiden (NL) towards quantum science and technology and probe their knowledge on quantum concepts. Results indicate that these citizens have heard about ‘quantum’ through a wide variety of sources. They see quantum as globally important and admirable and most would like to learn more about quantum, but they do feel disconnected from developments in the field. Recommendations for the future include emphasizing any personal connections between citizens and quantum, adapting explanations to fit any level of education, and providing either reliable sources or a framework for critically evaluating quantum-related information.
Comparison of optical trapping wavelengths for nanoscopic diamonds containing nitrogen-vacancy centers
Authors: Roy Srestha , Ghosh Atanu , Lokesh Muruga , Nalupurackal Gokul , Chakraborty Snigdhadev , Goswami Jayesh , Bhallamudi Vidya P , Dhomkar Siddharth , Roy Basudev 
Published: May 2024

Abstract
In this article, we explore the effect of two different infrared (IR) laser wavelengths on the optical properties of trapped nano-diamonds containing high-density ensembles of nitrogen vacancy (NV) centers. We investigate 975 nm and 1064nm wavelengths for trapping lasers and find that NV photoluminescence quenching is more prominent for 1064nm illumination than for 975 nm illumination when simultaneously excited with a 532 nm laser. In order to understand the underlying mechanism, we develop a rate-equation-based model that takes into account various transition probabilities. The model suggests that the findings cannot be explained only by imposing modification of the NV charge-state ratio under varied illumination wavelengths, and, thus, we speculate that the effective ionization and recombination rates associated with NV charge states for the studied samples are highly wavelength-dependent in the probed regime. Importantly, the results demonstrate that 975 nm laser is desirable for optical trapping of NV-diamonds, especially for NV-based sensing applications.
Detection method for structural defects of U-shaped hanging ring for power fittings based on magnetic leakage principle
Authors: Bai Xin , Ji Hongling , Wang Leyu , Zhou Yang , Wu Jinnan , Jiang Yuan , Zhang Zhanlong 
Published: May 2024

Abstract
The U-shaped hanging ring of electric power fittings is usually installed outdoors and operates in harsh environments. Under the combined effect of the weight of the conductor and wind load, the bending part at the bottom of the U-shaped hanging ring often experiences wear and cracks due to friction contact, which can easily lead to accidents such as the detachment of transmission lines. Traditional methods for detecting structural defects in ferromagnetic materials, such as ultrasonic testing, eddy current testing, and manual testing, are affected by environmental factors, have a shallow measurement depth, and are difficult to quantify. In order to solve the above problems, this paper proposes a measurement method for detecting structural defects in the U-shaped hanging ring of electric power fittings based on the principle of magnetic leakage. The magnetic leakage signal characteristics of U-shaped hanging ring defects under different excitation structural parameters and different defect types are analyzed. The method of arranging magnetic leakage signal measurement points is studied. The detection of defect parameters is achieved based on the characteristic quantity of the magnetic leakage signal under different defect conditions. Finally, the method is analyzed and verified through examples. The results show that this method can achieve quantitative detection of defect parameters in the U-shaped hanging ring under uniform structural defect and crack structural defect, and has the advantages of high measurement accuracy and small error. The research results of this paper can provide a scientific theoretical basis for the inspection and replacement of transmission line fittings in engineering, which is of great engineering significance for ensuring the safe and stable operation of the power grid.
‘Kinning’ Education
Authors: Hebbar N. Nandini 
Published: May 2024

Abstract
This chapter uses the metaphorical and conceptual frames of genealogy to establish the local histories of engineering colleges. Historical shifts such as the mechanization of agriculture and the region’s participation in the global knitwear industry contributed to the prosperity and the necessary resources for investment in higher education. The chapter takes forward the argument that neoliberalism and privatization do not take place as a sweeping change, but move forward through the circulation of an ‘economy of affect’. In the case of Kongunadu, successful privatization has been achieved through the secularization of traditional patronage as philanthropy as well as efforts by various backward class groups to enter education in general, and engineering education in particular. This has also sealed a new form of industry in the form of ‘edupreneurship’.
Using Eye tracking to Examine Young Adults’ Visual Attention to E-cigarette Advertising Features and Associated Positive E-cigarette Perceptions
Authors: Chen-Sankey Julia , Weiger Caitlin , La Capria Kathryn 
Published: May 2024

AbstractBackgroundLittle is known about the influence of e-cigarette marketing features on the antecedents of e-cigarette use.PurposeUsing an eye-tracking experiment, we examined visual attention to common features in e-cigarette ads and its associations with positive e-cigarette perceptions among young adults.MethodsYoung adults (ages 18–29) who smoke cigarettes (n = 40) or do not use tobacco (n = 71) viewed 30 e-cigarette ads on a computer screen. Eye-tracking technology measured dwell time (fixation duration) and entry time (time to first fixation) for 14 pre-defined ad features. Participants then completed a survey about perceptions of e-cigarettes shown in the ads. We used regression models to examine the associations between ad features and standardized attention metrics among all participants and by tobacco-use status and person-aggregated standardized attention for each ad feature and positive e-cigarette perceptions.ResultsDwell time was the longest for smoker-targeted claims, positive experience claims, and price promotions. Entry time was the shortest for multiple flavor descriptions, nicotine warnings, and people. Those who do not use tobacco had a longer dwell time for minor sales restrictions and longer entry time for purchasing information than those who smoke. Longer dwell time for multiple flavor descriptions was associated with e-cigarette appeal. A shorter entry time for fruit flavor description was associated with positive e-cigarette-use expectancies.ConclusionsYoung adults allocated attention differently to various e-cigarette ad features, and such viewing patterns were largely similar by tobacco-use statuses. Multiple or fruit flavors may be the features that contribute to the positive influence of e-cigarette marketing among young adults.
Artificial intelligence–aided steatosis assessment in donor livers according to the Banff consensus recommendations
Authors: Jiao Jingjing , Tang Haiming , Sun Nanfei , Zhang Xuchen 
Published: May 2024

Abstract

Objectives
Severe macrovesicular steatosis in donor livers is associated with primary graft dysfunction. The Banff Working Group on Liver Allograft Pathology has proposed recommendations for steatosis assessment of donor liver biopsy specimens with a consensus for defining “large droplet fat” (LDF) and a 3-step algorithmic approach.

Methods
We retrieved slides and initial pathology reports from potential liver donor biopsy specimens from 2010 to 2021. Following the Banff approach, we reevaluated LDF steatosis and employed a computer-assisted manual quantification protocol and artificial intelligence (AI) model for analysis.

Results
In a total of 113 slides from 88 donors, no to mild (&lt;33%) macrovesicular steatosis was reported in 88.5% (100/113) of slides; 8.8% (10/113) was reported as at least moderate steatosis (≥33%) initially. Subsequent pathology evaluation, following the Banff recommendation, revealed that all slides had LDF below 33%, a finding confirmed through computer-assisted manual quantification and an AI model. Correlation coefficients between pathologist and computer-assisted manual quantification, between computer-assisted manual quantification and the AI model, and between the AI model and pathologist were 0.94, 0.88, and 0.81, respectively (P &lt; .0001 for all).

Conclusions
The 3-step approach proposed by the Banff Working Group on Liver Allograft Pathology may be followed when evaluating steatosis in donor livers. The AI model can provide a rapid and objective assessment of liver steatosis.
AI-accelerated prostate MRI: a systematic review
Authors: Reinhardt Ciaran , Briody Hayley , MacMahon Peter J 
Published: May 2024

Abstract

Background
Prostate cancer ranks among the most prevalent cancers affecting men globally. While conventional MRI serves as a diagnostic tool, its extended acquisition time, associated costs, and strain on healthcare systems, underscore the necessity for more efficient methods. The emergence of AI-acceleration in prostate MRI offers promise to mitigate these challenges.

Methods
A systematic review of studies looking at AI-accelerated prostate MRI was conducted, with a focus on acquisition time along with various qualitative and quantitative measurements.

Results
Two primary findings were observed. Firstly, all studies indicated that AI-acceleration in MRI achieved notable reductions in acquisition times without compromising image quality. This efficiency offers potential clinical advantages, including reduced scan durations, improved scheduling, diminished patient discomfort, and economic benefits. Secondly, AI demonstrated a beneficial effect in reducing or maintaining artefact levels in T2-weighted images despite this accelerated acquisition time. Inconsistent results were found in all other domains, which were likely influenced by factors such as heterogeneity in methodologies, variability in AI models, and diverse radiologist profiles. These variances underscore the need for larger, more robust studies, standardization, and diverse training datasets for AI models.

Conclusion
The integration of AI-acceleration in prostate MRI thus far shows some promising results for efficient and enhanced scanning. These advancements may fill current gaps in early detection and prognosis. However, careful navigation and collaborative efforts are essential to overcome challenges and maximize the potential of this innovative and evolving field

Advances in knowledge
This article reveals overall significant reductions in acquisition time without compromised image quality in AI-accelerated prostate MRI, highlighting potential clinical and diagnostic advantages.
Neural processing of speech comprehension in noise predicts individual age using fNIRS-based brain-behavior models
Authors: Liu Yi , Wang Songjian , Lu Jing , Ding Junhua , Chen Younuo , Yang Liu , Wang Shuo 
Published: May 2024

Abstract
Speech comprehension in noise depends on complex interactions between peripheral sensory and central cognitive systems. Despite having normal peripheral hearing, older adults show difficulties in speech comprehension. It remains unclear whether the brain’s neural responses could indicate aging. The current study examined whether individual brain activation during speech perception in different listening environments could predict age. We applied functional near-infrared spectroscopy to 93 normal-hearing human adults (20 to 70 years old) during a sentence listening task, which contained a quiet condition and 4 different signal-to-noise ratios (SNR = 10, 5, 0, −5 dB) noisy conditions. A data-driven approach, the region-based brain-age predictive modeling was adopted. We observed a significant behavioral decrease with age under the 4 noisy conditions, but not under the quiet condition. Brain activations in SNR = 10 dB listening condition could successfully predict individual’s age. Moreover, we found that the bilateral visual sensory cortex, left dorsal speech pathway, left cerebellum, right temporal–parietal junction area, right homolog Wernicke’s area, and right middle temporal gyrus contributed most to prediction performance. These results demonstrate that the activations of regions about sensory-motor mapping of sound, especially in noisy conditions, could be sensitive measures for age prediction than external behavior measures.