bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimization of Bio-Inspired Composite Structures for Enhanced Energy Absorption: An Experimental and Theoretical Approach
Authors: Fath Iman Karami , Niknejad Abbas , Zare-Zardini Hadi 
Published: July 2024

Abstract

The quest for lightweight materials with exceptional energy absorption capabilities has intensified in recent years, driven by the need to engineer robust structures for critical applications such as aerospace, transportation, and nuclear reactor containment. This paper presents a comprehensive study on the design and evaluation of bio-inspired composite quasi-scale specimens under quasi-static loading, with the aim of maximizing energy absorption efficiency. Drawing inspiration from the unique dermal armor of the pangolin, a distinctive mammalian species, we explore the use of sustainable plant fibers, including luffa and linen, as alternatives to traditional glass fibers. The Taguchi method, a robust statistical approach, is employed to systematically investigate the influence of various parameters on the Total Absorbed Energy (TAE) and Specific Absorbed Energy (SAE). A total of five parameters—fiber type, radius of curvature, number of composite plies, and the dimensions of the trapezoidal scales (Y1 and Y2)—are assessed for their impact on energy absorption. The experimental setup involves fabricating composite specimens using unsaturated isophthalic polyester resin as the matrix, and subjecting them to quasi-static lateral compressive loading. The energy absorption characteristics are analyzed by examining the force-displacement data, with the TAE inferred from the area beneath the curve and the SAE calculated by dividing TAE by the specimen's mass. The results indicate that luffa fibers exhibit superior TAE compared to linen and glass fibers, while linen fibers demonstrate higher SAE. The Taguchi method facilitates the identification of optimal parameter levels for maximizing energy absorption, with the predicted optimal specimen exhibiting a TAE of 11.2431 J and an SAE of 2.3677 J/g, closely matching experimental verification with errors of 5.76% and 3.94%, respectively. Theoretical analysis, incorporating the Rigid Perfectly Plastic (RPP) and Hollomon material models, elucidates the mechanisms underlying energy dissipation, including curvature flattening and plastic hinge formation. This framework provides a robust basis for predicting the energy absorption behavior of bio-inspired composite structures, offering insights into the design of advanced materials with enhanced performance characteristics. The study underscores the potential of bio-inspired designs in addressing contemporary engineering challenges, highlighting the synergy between natural forms and advanced materials science in the pursuit of sustainable and high-performance structural solutions.
Dominant role of NO2 oxidation in SO2 conversion to sulfate revealed by synchronous measurements of gas and particle sulfur isotopes in haze episodes
Authors: Chen Yingjun , Feng Xinxin , Liu Zeyu , Jiang Hongxing , Feng Yanli , Chen Tian 
Published: July 2024

Abstract

The oxidation pathways of SO2 conversion to sulfate remain controversial. Sulfur isotope (δ34S) has been used to trace SO42− formation pathways based on sulfur isotope fractionation. Accurately assessing the isotope fractionation is crucial for quantifying the oxidation pathways of SO42− formation. However, previous studies have used particle δ34S (δ34SO42−) to estimate the isotope fractionation (α34Sg→p-estimated), leading to significant uncertainties in SO42− formation. This study synchronously measured δ34S values of gas-phase SO2 and particle-phase SO42− to uncover isotope fractionation (α34Sg→p) in SO42− formation during haze episodes. Results found that the α34Sg→p values (-3.7 ~ + 9.9‰) obtained by gas-to-particle δ34S showed a significant difference with α34Sg→p-estimated values(-6.4 ~ + 1.4‰) obtained by δ34SO42−, implying different results for SO42− formation using the two methods. Among them, α34Sg→p results indicated the prominent contribution of NO2 oxidation(48–56%), followed by TMI-catalyzed O2 (transition-metal ions, 26–40%). While α34Sg→p-estimated (-6.4 ~ + 1.4‰) suggested the dominant role of TMI-catalyzed O2 (54–80%). Compared to α34Sg→p-estimated, α34Sg→p results show more reasonable response to SO42− formation and consistent trends with oxidant concentrations. α34Sg→p-estimated analysis overestimated the TMI-catalyzed O2 pathway contribution (38–47%) to SO42− formation. This is the first study to employ gas-to-particle δ34S to demonstrate the dominant role of NO2 oxidation in SO42− formation, implying the importance of synchronous measurements gas-to-particle δ34S. Furthermore, a functional relationship between D-values (difference values of α34Sg→p and α34Sg→p-estimated) and impact factors was established, simulating actual α34Sg→p in the absence of gas-phase δ34S. This approach offers a possible correction for α34Sg→p-estimated values, providing new insight into using single δ34SO42− for the analysis of SO42− formation.
An ultrafast algorithm for ultrafast spectroscopy
Authors: Bekerom Dirk van den , Mazza Francesco 
Published: July 2024

Abstract

Time-resolved coherent Raman spectroscopy (CRS) is a powerful non-linear optical technique for quantitative, in-situ analysis of chemically reacting flows, offering unparalleled accuracy and exceptional spatiotemporal resolution. Its application to large polyatomic molecules, crucial for understanding reaction dynamics, has thus far been limited by the complexity of their rotational-vibrational Raman spectra. Progress in developing comprehensive spectral codes for these molecules, a longstanding goal, has been hindered by prohibitively long computation times required for their spectral synthesis. Here, we present a novel ultrafast algorithm that achieves a million-fold improvement in computation time compared to existing methods. The algorithm demonstrates remarkable accuracy, with an approximation error below 0.1% across all tested probe delays, at both room temperature (296 K) and elevated temperatures (1500 K). This result could greatly expand the application of time-resolved CRS, particularly in plasma research, as well as in broader atmospheric and astrophysical sciences.
Estimation of the Shear Strength of Sand-Clay Mixtures Based on the ANN and Low-Field NMR
Authors: LIU Xiajun , LU Zhen , Zhu Yifei , Le Qiaoli , Wei Jiagang 
Published: July 2024

Abstract

As a key engineering parameter, the shear strength of sand-clay mixtures needs to be determined before the design and construction of impervious liners for waste landfill sites are performed. The traditional method for determining the shear strength requires considerable time and substantial professional skills. This study focused on the estimation of the shear strength of sand-clay mixtures using the artificial neural network (ANN) and low-field nuclear magnetic resonance (NMR) spectroscopy. In this study, NMR tests and triaxial compression tests were carried out on 160 artificial sand-clay mixtures with different mineralogical compositions, water contents, and dry densities in the laboratory to obtain the T2 spectra and shear strength indices, respectively. Twelve characteristic variables that could reflect the pore structure and water classification in the mixtures were calculated for each T2 spectrum. A novel predictive model for the shear strength of the mixtures was established using the ANN based on 12 characteristic variables, the Atterberg limits, and the tested shear strengths of mixtures. The Atterberg limits of the mixtures, 12 characteristic variables and shear strengths of the mixtures were defined as the input factors, input covariates and response variables, respectively. The model was proven to have a sufficiently high prediction capability by using the Pearson correlation coefficient (R), coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE).
Fuzzy circularity: A new fuzzy shape-based descriptor of the object
Authors: Ilić Vladimir , Ralević Nebojša M. 
Published: July 2024

Abstract

This paper introduces a new family of fuzzy shape measures, called fuzzy circularity, to evaluate the degree to which a considered fuzzy shape matches a fuzzy circle. A new family of fuzzy shape-based measures ranges the interval (0,1] where a maximum value equal to 1 is reached if and only if the shape under consideration is a fuzzy circle. This family is theoretically well grounded having the behavior that corresponds to human perception and can be predicted in advance. Additionally, a new family of fuzzy shape-based measures is invariant to rotation, translation, and scaling of the considered fuzzy shape. Various experiments on both synthetically generated and real images are included to provide a better understanding of the behavior of the new measures and to confirm the theoretically proven results. The performance of the new family of fuzzy circularity is extensively tested on several standard, well-known image datrasets such as MPEG-7 CE-1, Animal, Swedish Leaf, and Galaxy Zoo datasets. Experimental evaluations also illustrate the effectiveness and advantages of the new shape descriptors in various object classification and recognition tasks by comparing them with other known analysis approaches.
Automated crack detection and digital modeling of hydraulic fracture propagation in muddy shale using deep learning based on multi-scale feature and residual convolution improved U-net model
Authors: QU Wenhang , JIA Pengfei , CHEN Zihao , WANG Yong , REN Xiaohui , ZHANG Guochao 
Published: July 2024

Abstract

The extension of fine microscopic cracks in muddy shale during water saturation-deydration circulation has an important role in the propagation of hydraulic fractures and the formation of fracture network. However, traditional image processing methods for segmenting CT scan images of muddy shale are prone to low efficiency and poor accuracy, as well as lack automation and intelligence. This study proposes a muddy shale crack segmentation network (MSCS-Net) based on the U-Net model that fuses the residual network and multi-scale features of Convolutional Neural Networks (CNNs). The proposed MSCS-ett efficiently segmented muddy shale cracks in CT scanned images after a degradation cycle, allowing for both qualitative and quantitative analysis. The results showed that the values of precision (P), recall (R), F1 score (F1_score), Intersection and Union Ratio (IoU) and Pixel Accuracy (PA) of the proposed MSCS-Net were 91.27%, 93.89%, 92.56%, 85.32% and 98.34%, respectively. Besides, the detection performance of the MSCS-Net was also compared with that of the other three different deep learning models (U-Net, U-Net3 + and Attention U-Net). The test results have demonstrated the superiority of the MSCS-Net over the other three network models in crack detection, localization and segmentation.
Different Trajectories of Adolescent Mental Health Problems Before and Over the Course of COVID-19: Evidence of Increase, Decrease, and Stability
Authors: de Heer Coriena , Finkenauer Catrin , Stevens Gonneke 
Published: July 2024

Abstract

Background.
The COVID-19 pandemic and related measures to control the spread of the virus have negatively impacted adolescent mental health. However, the pandemic may have been more consequential for the mental health of some adolescents than others. Little is known about the heterogeneity in mental health responses to the pandemic among adolescents. This study aims to identify and characterize different trajectories of adolescent mental health problems before and over the course of the COVID-19 pandemic.
Methods.
We used data from 1,522 adolescents (Mage = 17.82) collected at four measurement points: autumn 2019 (pre-COVID-19), spring 2020, autumn 2020, and autumn 2021. Mental health problems were assessed using four indicators: emotional symptoms, conduct problems, hyperactivity-inattention problems, and peer relationship problems.
Results.
Latent class growth analyses identified stable low, stable high, increasing and decreasing trajectories for emotional symptoms, conduct problems, and hyperactivity-inattention problems, and a stable low and stable high trajectory for peer relationship problems. Adolescents with high mental health problems before and during the pandemic reported relatively low levels of family and friend support. Gender, migration background, and family socioeconomic status were not consistently associated with the trajectories across mental health problems.
Conclusions.
Our findings highlight the diverse impact of the COVID-19 pandemic on mental health problems among adolescents. This suggests that interventions and support strategies for adolescents to cope with stressful circumstances should be tailored to the specific needs of different groups of adolescents.
Fuzzy Logic and HOMER: Innovations in Distributed Generation for System Stability and Performance
Authors: Tiwari Nimisha , Dwivedi Kaustubh 
Published: July 2024

Abstract

The HOMER software is described in this article to provide the efficient distributed generation configurations. This is based on nature of the area and its renewable energy availability. This software is used to develop and assess alternatives for stand-alone and grid-connected power distributed generation applications, both technically and financially. It enables the consideration of a huge range of technological alternatives. It’s a powerful tool for simulating both the traditional and sustainable energy techniques. Furthermore, in distributed generation electric networks, a fuzzy-based strategy is suggested to choose the suitable power source and ascribe it to the appropriate load. Fuzzy Logic Control is an effective approach to resolve complex problems using algebraic calculations Moreover, sustainable energy distributed generation has grown rapidly as large central power plants have become financially unviable because of substantial decreases in fossil fuels, rising fuel costs, global energy crunch and the emergence of environment degradation problems. Nevertheless, the integration of distributed power generation into conventional electric power networks has influence on their consistency, safeness, and power feature. As a result, inoculation of distributed power generation necessitates the use of adequate controllers to preserve system stability and performance.
Effects of 2.4 GHz radiofrequency electromagnetic field exposure on hippocampal proteins in APP/PS1 mice
Authors: Zhang Shengqingyu , Wu Xi-Nan , Li Zhi-qiang , Mu Yun-Zhen , Shu Xiao , Zhou Qiong , Du Kun-Yu , Jiang Yu-Rong , Zhang Yuan , Wu Hui-Xin 
Published: July 2024

Abstract

Radiofrequency electromagnetic fields (RF-EMF) can have several biological and genetic effects, particularly in the nervous system. Recent studies have reported that exposure to RF-EMF showed beneficial effects in Alzheimer 's disease (AD). In this study, we determined whether exposure to 2.4 GHz RF-EMF affected protein expression in the hippocampus of APP/PS1 mice. APP/PS1 mice were exposed to 2.4 GHz RF-EMF for 8 hours per day for a total of 90 days. Learning and memory function tests were performed, and protein expression of APP, NR1, NR2A, NR2B, PGC1α, p62 and LC3B in the hippocampus was measured.There was no difference in the learning and memory function between 1-month-old APP/PS1 mice and 1-month-old C57 mice, while 4-month-old APP/PS1 mice showed weaker functions when compared to 1-month-old C57 mice. After 3 months of RF-EMF exposure, the learning and memory function of APP/PS1 and C57 mice improved. The protein expression of APP, NR2A, and NR1 in the hippocampus of 1-month-old APP/PS1 mice increased, while PGC1α expression decreased, and NR2B, p62 and LC3B expression was unaltered. The protein expression of APP, NR2A, NR2B, NR1, PGC1α, and LC3B in the hippocampus of 4-month old APP/PS1 mice increased, while the expression of p62 protein decreased. After 3 months of RF-EMF exposure, the protein expression of NR2A, NR2B, and NR1 protein in the hippocampus of mice decreased, while the expression of PGC1α and p62 increased, and the expression of APP and LC3B was unaltered.
Testing free alternatives to proprietary software in architectural education
Authors: Christenson Mike , Green Abigail , Liu Xiaotong , Self Kallie 
Published: July 2024

Abstract

Certain software applications are broadly considered essential for use in architectural design education. Proprietary software applications can be expensive for students. Given this context, we are interested in identifying core functions of software for architectural education, and on this basis, in identifying possible free software applications as alternatives to proprietary ones. We define and implement several simple tests to evaluate alternative applications such as Blender, GIMP, Canva, and Inkscape. We conclude that certain freely available software applications can effectively fulfill core functions, acknowledging challenges in adoption and interoperability but underscoring cost benefits for students.
Global occurrence of large volcanic collapses in a changing climate.
Authors: bernard karine 
Published: July 2024

Abstract

From Google Earth imagery and published data on Quaternary volcanoes worldwide, this paper presents a semi-quantitative analysis of large volcanic events inventory in worldwide examples during Quaternary periods. Volume, area, the run-out distance on the surface avalanche units, the ratio of the vertical drop with run out distance are calculated to characterize the avalanche mobility. Morphological parameters of volcanic destabilization imply critical stability of volcanic edifices and cyclic evolution of volcanoes. Alignment of collapsed volcanic complex along fault zones are related to slab depth of oblique subduction zones.
From the statistical dataset, a few equations have been developed, indicating a co-genetic evolution of avalanche deposits. Positive correlations are established between times, latitudes, the ratios of the vertical drop with run-out distancearound 0.05 -0.18, the run-out distance, and the volume or flow area of avalanche deposits.The morphological variations of the debris-avalanche deposits are associated with the avalanche dam-break-out and reworked deposits with matrix transformation and dilution during quarternary climatic variations. The oldest Pleistocene avalanche deposits show successive transformations into lahar deposits within a continental extensional context. Flow transformations are identified during the transitional context of the Maunder Minimum during the Little Ice Age. Climatic conditions durin the Greenlandien and the Spörer minimum contribute to reduce the large volcanic destabilization. These results highlight the importance of semi-quantitative studies along avalanche fault zones to better constrain subsequent hazardous flows related to the effects of climate change.
Unlocking the Secrets of Regeneration: Histology of Regenerating Arm in Ophiocoma scolopendrina from the Persian Gulf
Authors: Nowruzi Nasim , Biuki Narges Amrollahi , Ferrario Cinzia , Sugni Michela 
Published: July 2024

Abstract

Ophiocoma scolopendrina, a prevalent brittle star species in the southernmost intertidal zone of Qeshm Island, serves as an exemplary model for studying echinoderm arm regeneration processes within the Persian Gulf. To elucidate the regenerative mechanisms of these organisms, we conducted a comprehensive investigation of their regenerative structures from a histological perspective. The collected specimens were carefully acclimated to laboratory conditions in aerated seawater aquaria before being transferred to specially treated environments. Adhering to strict ethical protocols, we amputated the arms of the brittle stars and meticulously documented the subsequent regenerative changes at various intervals: 24 hours, 72 hours, and weekly up to six weeks post-amputation. Our findings reveal that Ophiocoma scolopendrina undergoes a triphasic regenerative pathway, encompassing a repair phase, an early regenerative phase, and an advanced regenerative phase. Notably, the temporal progression of these phases differs from that observed in other previously studied species. Initially, the brittle stars effectuate wound closure and healing of the autotomy plane through an epimorphic process, characterized by the migration of epidermal cells and re-epithelialization. Subsequently, the formation of a regenerative blastema within the bud initiates morphogenesis, followed by the differentiation and proliferation of blastemal cells, culminating in the development of the regenerated arm.
SARS-CoV-2 Spike Protein Exacerbates Thromboembolic Cerebrovascular Complications in Humanized ACE2 Mouse Model
Authors: Heath Stan P. , Hermanns Veronica C. , Coucha Maha , Abdelsaid Mohammed 
Published: July 2024

Abstract

COVID-19 increases the risk for acute ischemic stroke, yet the molecular mechanisms are unclear and remain unresolved medical challenges. We hypothesize that the SARS-CoV-2 spike protein exacerbates stroke and cerebrovascular complications by increasing coagulation and decreasing fibrinolysis by disrupting the renin-angiotensin-aldosterone system (RAAS). A thromboembolic model was induced in humanized ACE2 knock-in mice after one week of SARS-CoV-2 spike protein injection. hACE2 mice were treated with Losartan, an angiotensin receptor (AT1R) blocker, immediately after spike protein injection. Cerebral blood flow and infarct size were compared between groups. Vascular-contributes to cognitive impairments and dementia was assessed using a Novel object recognition test. Tissue factor-III and plasminogen activator inhibitor-1 were measured using immunoblotting to assess coagulation and fibrinolysis. Human brain microvascular endothelial cells (HBMEC) were exposed to hypoxia with/without SARS-CoV-2 spike protein to mimic ischemic conditions and assessed for inflammation, RAAS balance, coagulation, and fibrinolysis. Our results showed that the SARS-CoV-2 spike protein caused an imbalance in the RAAS that increased the inflammatory signal and decreased the RAAS protective arm. SARS-CoV-2 spike protein increased coagulation and decreased fibrinolysis when coincident with ischemic insult, which was accompanied by a decrease in cerebral blood flow, an increase in neuronal death, and a decline in cognitive function. Losartan treatment restored RAAS balance and reduced spike protein-induced effects. SARS-CoV-2 spike protein exacerbates inflammation and hypercoagulation, leading to increased neurovascular damage and cognitive dysfunction. However, the AT1R blocker, Losartan, restored the RAAS balance and reduced COVID-19-induced thromboembolic cerebrovascular complications.