bluuebunny/crossref_metadata_2025_split huggingface dataset:
Theoretical modeling and experimental investigation of carbon fiber reinforced plastic-based piezoelectric actuator
Authors: Cao Teng , Wen Zhiyi , Wang Boquan , Yang Yaqing , Li Xiaoniu , Wu Dawei 
Published: March 2024

Abstract
Piezoelectric actuators based on non-metallic materials have drawn much attention in recent years. Carbon fiber reinforced plastic (CFRP) is one of the ideal materials for the development of lightweight, high power density piezoelectric actuators because of its low density, high stiffness. However, its anisotropic characteristics pose a challenge in actuator development. In this study, we designed a CFRP-based piezoelectric actuator, which utilizes hybrid modes of first-order longitudinal mode and second-order bending mode. The electromechanical coupling dynamic model for CFRP-based piezoelectric actuator was established a, based on the modal superposition method and energy method, and while taking into account the stress-strain relationships in anisotropic materials. The size of the actuator was calculated through the model and a prototype was processed for experimental research. The experimentally obtained results of frequencies and transient- as well as steady-state vibration characteristics demonstrated excellent agreement with the predictions of our mathematical modeling. Actuator performance evaluation results show that under a single-phase excitation voltage of 200 Vp-p, the CFRP-based actuator can reach maximum speed, thrust force, output power, thrust–weight ratio, power density, and efficiency of 617 mm s−1, 65 N, 1.14 W, 980.3 N kg−1, 223.5 W kg−1, and 10.4%, respectively. These results are satisfactory compared with actuators in other reports, especially the power density, which is nearly tripled. These results demonstrate the superior performance of the CFRP-based actuator and illustrate a new approach for developing lightweight and powerful actuators.
Local electronic structures of annealing induced phases in cobalt doped TiO2 nanoparticles: a combined study of transmission electron microscopy and x-ray absorption fine structure spectroscopy
Authors: Dawn Riya , Urkude Rajashri , Tripathi Shilpa , Bhunia Satyaban , Tjiu Weng Weei , Aabdin Zainul , Kandasami Asokan , Singh Vijay Raj 
Published: March 2024

Abstract
The evolution of the nanostructures and electronic properties of 5% cobalt-doped TiO2 nanoparticles (NPs) annealed at 400 °C, 600 °C, and 800 °C have been investigated to understand the structural phase transformations through chemical co-precipitation synthesis. A detailed analysis of the X-ray Diffractogram confirms that the sample annealed at 400 °C is anatase, at 600 °C, the mixed phase of anatase and rutile evolves, and at 800 °C, the sample is of rutile structure. A detailed morphological study by scanning transmission electron microscope provides the particle size, lattice spacing, and variation in polycrystalline grain growth at different phases. Electron Energy Loss Spectroscopy analysis indicates from the O K, Co, and Ti L
2,3-edges that Ti4+ ions are primarily in an octahedral symmetry with the oxygen ligands changing their structural phases from anatase to mixed phase and then stable rutile phase with increasing temperature of annealing. X-ray Absorption Near Edge Spectroscopy (XANES) extracts information about the varying oxidation states and 3-dimensional geometry of Ti-ions. The unresolved issues of the structural details at the atomic-scale picture with the local environment of the cation with a few nearest neighbour shells are derived from Extended X-ray Absorption Fine Structure (EXAFS) and pre-edge parts of the absorption spectra. The limits of EXAFS in this situation of asymmetric bond length disorder, which is typical for mixed-valence oxides, are generated to reconcile the two data and highlight the value of pre-edge XANES analysis for identifying local heterogeneities in structural and compositional motifs. TiO2 possesses unique properties depending upon its structural phase. The Ti L
2,3-edge spectrum indicates that there is an octahedron connectivity of the Oxygen atoms at the anatase state which transforms to a higher energetic tetrahedral correspondence as it proceeds towards the rutile phase. The driving force behind such interest is to modulate the properties of TiO2 NPs to better photocatalytic material and to integrate its application as a versatile energy storage device.
Oxysulfide perovskites: reduction of the electronic band gap of RbTaO3 by sulfur substitution
Authors: Akter H , Ali M A , Hossain M M , Uddin M M , Naqib S H 
Published: March 2024

Abstract
In this study, the effects of sulfur substitution on the structural, mechanical, electronic, optical, and thermodynamic properties of RbTaO3−x
S
x
have been investigated using the WIEN2k code in the framework of density functional theory (DFT). The cubic phase of RbTaO3 transforms to tetragonal for RbTaO2S and RbTaOS2; the latter transforms again to a cubic phase with added sulfur for RbTaS3. The results show that substituting S for O anions in RbTaO3 effectively decreased the band gap [calculated using TB-mBJ functional] from 2.717 eV to 1.438 eV, 0.286 eV, and 0.103 eV for the RbTaO3, RbTaO2S, RbTaOS2, and RbTaS3 compounds, respectively. The optical constants such as dielectric constant, refractive index, absorption coefficient, photoconductivity, reflectivity, and loss function have been calculated and analyzed. The elastic constants and moduli and their anisotropic nature were also investigated. Finally, the Debye temperature, thermal conductivity, melting temperature, specific capacities, and thermal expansion coefficients were computed and analyzed using established formalisms. The reduced band gap (1.438 eV) and high absorption coefficient (∼106 cm−1) of RbTaO2S, make it suitable for solar cell applications and for other visible light devices. Both ordered structure and super-cell have been used to cross-check results for RbTaO2S and RbTaOS2 compositions.
Combining a climate-permafrost model with fine resolution remote sensor products to quantify active-layer thickness at local scales
Authors: Zhang Caiyun , Douglas Thomas A , Brodylo David , Bosche Lauren V , Jorgenson M Torre 
Published: March 2024

Abstract
Quantification of active-layer thickness (ALT) over seasonally frozen terrains is critical to understand the impacts of climate warming on permafrost ecosystems in cold regions. Current large-scale process-based models cannot characterize the heterogeneous response of local landscapes to homogeneous climatic forcing. Here we linked a climate-permafrost model with a machine learning solution to indirectly quantify soil conditions reflected in the edaphic factor using high resolution remote sensor products, and then effectively estimated ALT across space and time down to local scales. Our nine-year field measurements during 2014–2022 and coincident high resolution airborne hyperspectral, lidar, and spaceborne sensor products provided a unique opportunity to test the developed protocol across two permafrost experiment stations in lowland terrains of Interior Alaska. Our developed model could explain over 60% of the variance of the field measured ALT for estimating the shallowest and deepest ALT in 2015 and 2019, suggesting the potential of the designed procedure for projecting local varying terrain response to long-term climate warming scenarios. This work will enhance the National Aeronautics and Space Administration’s Arctic-Boreal Vulnerability Experiment’s mission of combining field, airborne, and spaceborne sensor products to understand the coupling of permafrost ecosystems and climate change.
Phase compensation of a continuous-variable quantum key distribution via temporal convolutional neural network
Authors: Jiang Wenqi , Zuo Zhiyue , Luo Gaofeng , Zhang Hang , Guo Ying 
Published: March 2024

Abstract
Although the continuous-variable quantum key distribution (CV-QKD) protocol based on a local local oscillator (LLO) can close all the security loopholes from the transmitted local oscillator (TLO), the phase noise caused by the inaccurate phase reference information limits the performance of the protocol. To reduce the residual phase noise, in this work, we propose a phase estimation and compensation method based on the temporal convolutional neural (TCN) model, where a part of phase information obtained by measuring pilot pulses is employed as the training data and input into the TCN module. With a trained TCN module, the subsequent phase drifts can be more accurately estimated, allowing for better phase compensation and lower phase noise. Numerical analysis shows that the proposed scheme can improve the transmission distance and the secret key rate of the LLO protocol.
Alternative community-led intervention to improve uptake of cataract surgery services in rural Tanzania—The Dodoma Community Cataract Acceptance Trial (DoCCAT): a protocol for intervention co-designing and implementation in a cluster-randomized controlled trial
Authors: Sandi Frank , Mercer Gareth , Geneau Robert , Bassett Kenneth , Bintabara Deogratius , Kalolo Albino 
Published: March 2024

Abstract
Age-related lens opacification (cataract) remains the leading cause of visual impairment and blindness worldwide. In low- and middle-income countries, utilization of cataract surgical services is often limited despite community-based outreach programmes. Community-led research, whereby researchers and community members collaboratively co-design intervention is an approach that ensures the interventions are locally relevant and that their implementation is feasible and socially accepted in the targeted contexts. Community-led interventions have the potential to increase cataract surgery uptake if done appropriately.
In this study, once the intervention is co-designed it will be implemented through a cluster-randomized controlled trial (cRCT) with ward as a unit of randomization.
This study will utilise both the qualitative methods for co-designing the intervention and the quantitative methods for effective assessment of the developed community-led intervention through a cRCT in 80 rural wards of Dodoma region, Tanzania (40 Intervention). The ‘intervention package’ will be developed through participatory community meetings and ongoing evaluation and modification of the intervention based on its impact on service utilization. Leask’s four stages of intervention co-creation will guide the development within Rifkin’s CHOICE framework. The primary outcomes are two: the number of patients attending eye disease screening camps, and the number of patients accepting cataract surgery. NVivo version 12 will be used for qualitative data analysis and Stata version 12 for quantitative data. Independent and paired t-tests will be performed to make comparisons between and within groups. P-values less than 0.05 will be considered statistically significant.
The central role of the identifying assumption in population size estimation
Authors: Aleshin-Guendel Serge , Sadinle Mauricio , Wakefield Jon 
Published: March 2024

ABSTRACT
The problem of estimating the size of a population based on a subset of individuals observed across multiple data sources is often referred to as capture-recapture or multiple-systems estimation. This is fundamentally a missing data problem, where the number of unobserved individuals represents the missing data. As with any missing data problem, multiple-systems estimation requires users to make an untestable identifying assumption in order to estimate the population size from the observed data. If an appropriate identifying assumption cannot be found for a data set, no estimate of the population size should be produced based on that data set, as models with different identifying assumptions can produce arbitrarily different population size estimates—even with identical observed data fits. Approaches to multiple-systems estimation often do not explicitly specify identifying assumptions. This makes it difficult to decouple the specification of the model for the observed data from the identifying assumption and to provide justification for the identifying assumption. We present a re-framing of the multiple-systems estimation problem that leads to an approach that decouples the specification of the observed-data model from the identifying assumption, and discuss how common models fit into this framing. This approach takes advantage of existing software and facilitates various sensitivity analyses. We demonstrate our approach in a case study estimating the number of civilian casualties in the Kosovo war.
Comparisons of Hounsfield units and volumetric bone density in discriminating vertebral fractures on lumbar CT scans
Authors: Zhou Fengyun , Zhang Wenshuang , Geng Jian , Liu Yandong , Yuan Yi , Ma Kangkang , Cheng Zitong , Huang Pengju , Cheng Xiaoguang , Wang Ling , Liu Yajun 
Published: March 2024

Abstract

Objectives
To compare the performance of areal Hounsfield units (aHUs), volumetric Hounsfield units (vHUs), and volumetric bone mineral density (vBMD) by quantitative CT (QCT) in discriminating vertebral fractures (VFs) risk.

Methods
We retrospectively included CT scans of the lumbar spine 101 VFs cases (60 women, mean age: 64 ± 4 years; 41 men, mean age: 73 ± 10 years) and sex- and age-matched 101 control subjects (60 women, mean age: 64 ± 4 years; 41 men, mean age: 72 ± 7 years). In order to assess the discriminatory capability of aHU, vHU, and vBMD measurements at the L1 and L2 levels in identifying VFs, we conducted binary logistic regression and receiver operating characteristic (ROC) curve analyses in men and women. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated.

Results
In both men and women with and without VFs, aHU, vHU, and vBMD were highly correlated with each other (r2 from 0.832 to 0.957, all P &lt; .001). There was a statistically significant difference in aHU, vHU, and vBMD between subjects with and without VFs (P &lt; .001). When age, gender, and BMI were taken into account as covariances and adjusted simultaneously, odds ratios (ORs) for aHU, vHU, and vBMD values, which represent the risk of VFs, were significant (P &lt; .001). Compared with aHU and vHU, vBMD was more strongly associated with VF risk (vBMD: OR, 6.29; 95% CI, 3.83-10.35 vs vHU: OR, 3.64; 95% CI, 2.43-5.46 vs aHU: OR, 2.56; 95% CI, 1.79-3.67). In both men and women, further, vBMD had higher values for AUC, sensitivity, specificity, PPV, and NPV compared to vHU, with vHU in turn surpassing aHU. The area under the receiver operating characteristic curve (AUC) for discriminating VFs using the average aHU, vHU, and vBMD of 2 vertebrae was 0.72, 0.77, and 0.87 in men and 0.76, 0.79, and 0.86 in women. In both men and women, there exist statistically significant differences in the AUC when employing the 3 measurements—namely, aHU, vHU, and vBMD—to discriminate fractures (P &lt; .05).

Conclusions
The QCT-measured vBMD is more associated with acute VFs than vHU and aHU values of the lumbar spine. Although the use of vHU and aHU values for the diagnosis of osteoporosis and discriminating fracture risk is limited to scanner- and imaging protocol-specific, they have great potential for opportunistic osteoporosis screening, particularly vHU.

Advances in knowledge
The novelty of this study presents a comparison of the VF discriminative capabilities among aHU, vHU, and vBMD. The vHU values introduced in this study demonstrate a greater capacity to discriminate fractures compared to aHU, presenting an improved clinical choice. Although its discriminatory capability is slightly lower than that of vBMD, it is more convenient to measure and does not require specialized software.
Sex differences in the pleiotropy of hearing difficulty with imaging-derived phenotypes: a brain-wide investigation
Authors: He Jun , Cabrera-Mendoza Brenda , De Angelis Flavio , Pathak Gita A , Koller Dora , Curhan Sharon G , Curhan Gary C , Mecca Adam P , van Dyck Christopher H , Polimanti Renato 
Published: March 2024

Abstract
Hearing difficulty (HD) is a major health burden in older adults. While ageing-related changes in the peripheral auditory system play an important role, genetic variation associated with brain structure and function could also be involved in HD predisposition.
We analysed a large-scale HD genome-wide association study (GWAS; ntotal = 501 825, 56% females) and GWAS data related to 3935 brain imaging-derived phenotypes (IDPs) assessed in up to 33 224 individuals (52% females) using multiple MRI modalities. To investigate HD pleiotropy with brain structure and function, we conducted genetic correlation, latent causal variable, Mendelian randomization and multivariable generalized linear regression analyses. Additionally, we performed local genetic correlation and multi-trait co-localization analyses to identify genomic regions and loci implicated in the pleiotropic mechanisms shared between HD and brain IDPs.
We observed a widespread genetic correlation of HD with 120 IDPs in females, 89 in males and 171 in the sex-combined analysis. The latent causal variable analysis showed that some of these genetic correlations could be due to cause-effect relationships. For seven of them, the causal effects were also confirmed by the Mendelian randomization approach: vessel volume→HD in the sex-combined analysis; hippocampus volume→HD, cerebellum grey matter volume→HD, primary visual cortex volume→HD and HD→fluctuation amplitudes of node 46 in resting-state functional MRI dimensionality 100 in females; global mean thickness→HD and HD→mean orientation dispersion index in superior corona radiata in males. The local genetic correlation analysis identified 13 pleiotropic regions between HD and these seven IDPs. We also observed a co-localization signal for the rs13026575 variant between HD, primary visual cortex volume and SPTBN1 transcriptomic regulation in females.
Brain structure and function may have a role in the sex differences in HD predisposition via possible cause-effect relationships and shared regulatory mechanisms.
Green hydrogen production from photovoltaic power station as a road map to climate change mitigation
Authors: Kamil Kehinde Ridwan , Samuel Bassey Okon , Khan Umar 
Published: March 2024

Abstract
The increasing recognition of hydrogen as a critical element in the global net-zero transition and its clear role in decarbonizing challenging sectors coincide with the growing urgency to address climate change. Africa's favourable renewable-energy capacity, ranging from 28% to 36% for solar, has been reported by the global solar irradiance index. However, the majority of hydrogen production today relies on fossil fuels (96%), with only a small fraction (4%) being produced through water electrolysis. Even though there have been many studies on climate change mitigation with a focus on Africa, a green hydrogen production from a photovoltaic power station approach has not been reported. Also, literature with a focus on Nigeria is lacking. This study focuses on the African green hydrogen production industry, utilizing Nigeria as a case study to explore the feasibility of generating clean hydrogen vectors from a percentage of photovoltaic power output in various regions of the country through stand-alone solar grid electrification projects. Analyses of the usage and effectiveness of the produced hydrogen fuel in each region are carried out, with the highest region having an annual output of 12 247 278 kg of green hydrogen and 8 573 094 kg of ammonia and the lowest region having an output of 511 245 kg of green hydrogen and 357 871 kg of ammonia, and the expected production from the proposed usage of 50% of the power generation output of the installed 1.6-MWp and 80-kWp solar power minigrids in the regions is calculated. The analyses were repeated for the other considered regions in the country. The results showcased the enormous advantages of the electrolytic production of hydrogen and how the greener economy project can play a major role in mitigating climate change effects and overreliance on fossil fuels as the driver of the economy in many African countries.
The gut metagenome harbors metabolic and antibiotic resistance signatures of moderate-to-severe asthma
Authors: Wilson Naomi G , Hernandez-Leyva Ariel , Schwartz Drew J , Bacharier Leonard B , Kau Andrew L 
Published: March 2024

Abstract
Asthma is a common allergic airway disease that has been associated with the development of the human microbiome early in life. Both the composition and function of the infant gut microbiota have been linked to asthma risk, but functional alterations in the gut microbiota of older patients with established asthma remain an important knowledge gap. Here, we performed whole metagenomic shotgun sequencing of 95 stool samples from a cross-sectional cohort of 59 healthy and 36 subjects with moderate-to-severe asthma to characterize the metagenomes of gut microbiota in adults and children 6 years and older. Mapping of functional orthologs revealed that asthma contributes to 2.9% of the variation in metagenomic content even when accounting for other important clinical demographics. Differential abundance analysis showed an enrichment of long-chain fatty acid (LCFA) metabolism pathways, which have been previously implicated in airway smooth muscle and immune responses in asthma. We also observed increased richness of antibiotic resistance genes (ARGs) in people with asthma. Several differentially abundant ARGs in the asthma cohort encode resistance to macrolide antibiotics, which are often prescribed to patients with asthma. Lastly, we found that ARG and virulence factor (VF) richness in the microbiome were correlated in both cohorts. ARG and VF pairs co-occurred in both cohorts suggesting that virulence and antibiotic resistance traits are coselected and maintained in the fecal microbiota of people with asthma. Overall, our results show functional alterations via LCFA biosynthetic genes and increases in antibiotic resistance genes in the gut microbiota of subjects with moderate-to-severe asthma and could have implications for asthma management and treatment.
Towards limited-domain full waveform ambient noise inversion
Authors: Tsai Victor C , Sager Korbinian , Bowden Daniel C 
Published: March 2024

SUMMARY
Ambient noise tomography is a well-established tomographic imaging technique but the effect that spatially variable noise sources have on the measurements remains challenging to account for. Full waveform ambient noise inversion has emerged recently as a promising solution but is computationally challenging since even distant noise sources can have an influence on the interstation correlation functions and therefore requires a prohibitively large numerical domain, beyond that of the tomographic region of interest. We investigate a new strategy that allows us to reduce the simulation domain while still being able to account for distant contributions. To allow nearby numerical sources to account for distant true sources, we introduce correlated sources and generate a time-dependent effective source distribution at the boundary of a small region of interest that excites the correlation wavefield of a larger domain. In a series of 2-D numerical simulations, we demonstrate that the proposed methodology with correlated sources is able to successfully represent a far-field source that is simultaneously present with nearby sources and the methodology also successfully results in a robustly estimated noise source distribution. Furthermore, we show how beamforming results can be used as prior information regarding the azimuthal variation of the ambient noise sources in helping determine the far-field noise distribution. These experiments provide insight into how to reduce the computational cost needed to perform full waveform ambient noise inversion, which is key to turning it into a viable tomographic technique. In addition, the presented experiments may help reduce source-induced bias in time-dependent monitoring applications.