bluuebunny/crossref_metadata_2025_split huggingface dataset:
Active Deformation Across the Western Anatolian Extensional Province (Türkiye) From Sentinel‐1 InSAR
Authors: Diercks Manuel , Hussain Ekbal , Mildon Zoë K. , Boulton Sarah J. , Lazecký Milan 
Published: November 2024

AbstractQuantifying interseismic deformation of fault networks which are predominantly deforming in a north‐south direction is challenging, because GNSS networks are usually not dense enough to resolve deformation at the level of individual faults. The alternative, interferometric synthetic aperture radar (InSAR), provides high spatial resolution but is limited by a low sensitivity to N‐S motion. We study the active normal fault network of Western Türkiye, which is undergoing rapid N‐S extension, using InSAR. Since most faults in the study region are normal faults, we overcome the low N‐S sensitivity by focusing on the vertical deformation component, which presents its own challenges. Sediment‐filled grabens show rapid anthropogenically induced subsidence, whereas urban areas tend toward erroneous uplift signals. Additionally, the morphological relief results in topographic and atmospheric disturbances of the InSAR signal. Our solution to these challenges is a systematic analysis of the high‐resolution vertical velocity field to deduce insights into regional deformation patterns, combined with detailed investigations of deformation along individual faults in the Western Anatolian Extensional Province. We show that tectonic deformation in the large graben systems is not restricted to the main faults. Smaller and seemingly less active faults are accommodating strain, favoring a continuum model of deformation over block models. We also observe a potential correlation between recent seismicity and active interseismic surface deformation. Observed deformation rates provide an estimate of current activity for many faults in the region. We discuss the potential and limitations of InSAR time series analysis for extensional regimes.
Trends and Projections in Climate‐Related Stressors Impacting Arctic Marine Ecosystems—A CMIP6 Model Analysis
Authors: Steiner Nadja S. , Reader Cathy M. 
Published: November 2024

AbstractEleven Earth System Models (ESMs) contributing to the Coupled Model Intercomparison Project (CMIP6) were evaluated with respect to climate‐related stressors impacting Arctic marine ecosystems (temperature, sea ice concentration, oxygen, ocean acidification). Stressors show regional differences and varying differences over time and space among models. Trends calculated over three consecutive 40‐year time periods are highest for 2061–2100 for temperature and O2. Differences between scenarios SSP2‐4.5 and SSP5‐8.5 vary among models and regions, mainly driven by sea‐ice retreat and dilution effects. Differences in biogeochemical parameterizations contribute to acidification differences. Projections indicate consistent ocean acidification until 2040 and faster progression for the high‐end emission scenario thereafter. For SSP5‐8.5 all Arctic regions show aragonite undersaturation by 2080, and calcite undersaturation for all but two regions by 2100 for all models. Most regions can avoid calcite undersaturation in a medium emission scenario (SSP2‐4.5). All variables show increases in seasonal amplitude, most prominently for temperature and oxygen. Calcium carbonate saturation state shows little change to the seasonal range but temporal shifts in extrema. Seasonal changes in may be underestimated due to lacking carbon cycle processes within sea ice in CMIP6 models. The analysis emphasizes regionally varying threats from multiple stressors on Arctic marine ecosystems and highlights the propagation of uncertainties from physical to biogeochemical variables. Large model differences in seasonal cycles emphasize the need for improved model constraints regarding the representation of sea‐ice decline, river inflow and Atlantic and Pacific water circulation to enhance the applicability of CMIP models in multi‐stressor impacts assessments.
A Multi‐Probe Automated Classification of Ice Crystal Habits During the IMPACTS Campaign
Authors: Schima Julian , McFarquhar Greg M. , Delene David , Heymsfield Andrew , Bansemer Aaron , Schnaiter Martin , Finlon Joseph A. , Järvinen Emma , Nehlert Franziska 
Published: November 2024

AbstractAlthough all ice crystals are unique, many can be grouped together by shape or habit, with members of a habit class sharing similar representations of properties such as fall velocity and growth rate. A decision tree algorithm designed to be adaptable to any particle imaging probe, thus enabling the creation of habit size distributions over a size range larger than that of any probe on its own, is used to classify ice crystals imaged by three airborne cloud probes in mid‐latitude winter cyclones during the Investigation of Microphysics and Precipitation for Atlantic Coast‐Threatening Snowstorms (IMPACTS) field campaign. Crystals are sorted into seven habit classes based on their morphological properties: sphere, column/needle, plate, graupel, dendrite, aggregate, and irregular. Although adaptability was its primary goal, the algorithm was found to be moderately skillful for identifying idealized habit images. Quantitative tests of the algorithm's adaptability displayed mixed results, as Two‐Dimensional Stereo Probe (2DS) classifications showed moderate correlation with Particle Habit Imaging and Polar Scattering Probe (PHIPS) classifications, but only weak correlation with High Volume Precipitation Spectrometer (HVPS) classifications. The algorithm was applied to random sets of images from each probe in a case study of a mesoscale snow band sampled on 7 February 2020. In the case study, qualitative analysis of particle images revealed general agreement on classifications among the probes, supporting the algorithm's applicability to multiple cloud probes. Most classifications appeared correct upon manual inspection, suggesting that in practical use, the algorithm is reasonably able to classify non‐idealized images.
Electromagnetic Energy Propagation Through Rock of Low Loss Tangent
Authors: Austin B. A. 
Published: November 2024

AbstractRadio equipment capable of communicating through hundreds of meters of quartzite rock was first designed and developed in South Africa over 50 years ago. The technology used was based on the analysis of the electromagnetic issues (as they were then understood) affecting propagation directly through such a lossy dielectric medium. That work has recently been considerably extended and is published here for the first time.
Reply to Comment on “Improving Bayesian Model Averaging for Ensemble Flood Modeling Using Multiple Markov Chains Monte Carlo Sampling” by Jasper Vrugt
Authors: Huang Tao , Merwade Venkatesh 
Published: November 2024

AbstractThis discussion is a reply to the comments made by Dr. Jasper Vrugt on the Metropolis‐Hastings (M‐H) algorithm with multiple independent Markov chains proposed by Huang and Merwade (2023a), https://doi.org/10.1029/2023wr034947 concerning the validity of the methodology in estimating Bayesian model averaging (BMA) parameters (weights and variances) of the framework proposed by Raftery et al. (2005), https://doi.org/10.1175/mwr2906.1. In this reply, we address his concerns by emphasizing the motivation of applying the proposed M‐H algorithm to BMA analysis and the applicability of the effective sample size that accounts for the autocorrelation across samples in evaluating the efficiency of Markov chain Monte Carlo sampling. Moreover, the details of sampling procedure for BMA prediction distribution are clarified. On the other hand, we present a fair comparison of the default Expectation‐Maximization, M‐H, and differential evolution adaptive Metropolis (DREAM) algorithms in estimating BMA parameters based on a numerical experiment. Results reinforce the findings obtained from Huang and Merwade (2023a) https://doi.org/10.1029/2023wr034947 and further indicate that the proposed M‐H algorithm is better than the DREAM algorithm in terms of sampling efficiency and prediction accuracy. Accordingly, we raise concerns on the use of DREAM algorithm in BMA analysis and suggest conducting peer reviews on the MODELAVG toolbox.
Molecularly imprinted fluorescence sensor chip for lactate measurement
Authors: Wusiman Muersha , Taghipour Fariborz 
Published: November 2024

AbstractLactate measurements provide an opportunity to conveniently evaluate bodily functions and sports performance. A molecularly imprinted fluorescence biochip provides an innovative way to achieve lactate measurement and overcomes the limitations of enzyme-based sensors. To realize this goal, ZnO quantum dots (QDs), a biocompatible sensing material, were combined with selective receptors comprised of molecularly imprinted polymers (MIPs). The lactate-selective imprinted polymers were formed using 3-aminopropyltriethoxysilane (APTES) and 5-indolyl boronic acid monomers. Furthermore, a new solid-phase sensing platform that overcomes the limitations of liquid-based sensors was developed to detect lactate in real-time. The platform consists of the biosensor chip with a thin-film sensing layer, an ultraviolet (UV) excitation source, and a portable light detector. The final sensor has a sensitivity of 0.0217 mmol L-1 for 0–30 mmol L-1 of lactate in phosphate-buffered saline (PBS) with a correlation coefficient of 0.97. The high sensor sensitivity and selectivity demonstrates the applicability of the ZnO QDs and synthetic receptors for sweat analysis.
5.5 GHz film bulk acoustic wave filters using thin film transfer process for WLAN applications
Authors: Yang Tingting , Gao Chao , Wang Yaxin , Lin Binghui , Zheng Yupeng , Liu Yan , Lei Cheng , Sun Chengliang , Cai Yao 
Published: November 2024

AbstractWireless local area network (WLAN) has gained widespread application as a convenient network access method, demanding higher network efficiency, stability, and responsiveness. High-performance filters are crucial components to meet these needs. Film bulk acoustic resonators (FBARs) are ideal for constructing these filters due to their high-quality factor (Q) and low loss. In conventional air-gap type FBAR, aluminum nitride (AlN) is deposited on the sacrificial layer with poor crystallinity. Additionally, FBARs with single-crystal AlN have high internal stress and complicated fabrication process. These limit the development of FBARs to higher frequencies above 5 GHz. This paper presents the design and fabrication of FBARs and filters for WLAN applications, combining the high electromechanical coupling coefficient ($${K}_{{\rm{t}}}^{2}$$

K

t

2

) of Al0.8Sc0.2N film with the advantages of the thin film transfer process. An AlN seed layer and 280 nm-thick Al0.8Sc0.2N are deposited on a Si substrate via physical vapor deposition (PVD), achieving a full width at half maximum (FWHM) of 2.1°. The ultra-thin film is then transferred to another Si substrate by wafer bonding, flipping, and Si removal. Integrating conventional manufacturing processes, an FBAR with a resonant frequency reaching 5.5 GHz is fabricated, demonstrating a large effective electromechanical coupling coefficient ($${{k}}_{{\rm{eff}}}^{2}$$

k

eff

2

) of 13.8% and an excellent figure of merit (FOM) of 85. A lattice-type filter based on these FBARs is then developed for the Wi-Fi UNII-2 band, featuring a center frequency of 5.5 GHz and a −3 dB bandwidth of 306 MHz, supporting high data rates and large throughputs in WLAN applications.
The function of the ZFP189 transcription factor in the nucleus accumbens facilitates cocaine-specific transcriptional and behavioral adaptations
Authors: Picone Joseph A. , Hassan Annalise , Kim R. Kijoon , Lira Diego Piñeiro , Silva Gabriella M. , Truby Natalie L. , Johnson Hadessah Y. , Teague Collin D. , Neve Rachael L. , Banks Matthew L. , Cui Xiaohong , Hamilton Peter J. 
Published: November 2024

AbstractDistinguishing the brain mechanisms affected by distinct addictive drugs may inform targeted therapies against specific substance use disorders (SUDs). Here, we explore the function of a drug-associated, transcriptionally repressive transcription factor (TF), ZFP189, whose expression in the nucleus accumbens (NAc) facilitates cocaine-induced molecular and behavioral adaptations. To uncover the necessity of ZFP189-mediated transcriptional control in driving cocaine-induced behaviors, we created synthetic ZFP189 TFs of distinct transcriptional function, including ZFP189VPR, which activates the expression of target genes and exerts opposite transcriptional control to the endogenously repressive ZFP189. By virally delivering synthetic ZFP189 TFs to the NAc of mice, we discover that the transcriptional control exerted by synthetic or endogenous ZFP189 solely alters behavioral adaptations to cocaine but not morphine, saline, or sucrose. Further, these synthetic ZFP189 TFs are only capable of producing gene-expression changes in rodents exposed to cocaine, but not morphine or saline. In these cocaine exposed mice, the gene-expression profile produced by ZFP189VPR is inversely related to the cocaine-induced transcriptional response, as characterized by Upstream Regulator Analysis in Ingenuity Pathway Analysis. Lastly, we demonstrate that NAc ZFP189WT increases vulnerability to cocaine reinforcement through selective sensitization to the reinforcing effects of small cocaine doses. In contrast, ZFP189VPR treated mice do not experience changes in cocaine sensitivity and had lower rates of cocaine self-administration. Collectively, this research describes the brain mechanisms by which a TF specifically coordinates the molecular adaptations that produce increased cocaine addiction-like behaviors. The use of synthetic ZFP189VPR uncovers novel strategies for therapeutic interventions to potentially halt these cocaine-induced transcriptional processes.
Macrophages and nociceptor neurons form a sentinel unit around fenestrated capillaries to defend the synovium from circulating immune challenge
Authors: Hasegawa Tetsuo , Lee Colin Y. C. , Hotchen Andrew J. , Fleming Aaron , Singh Rahul , Suzuki Kunimichi , Yuzaki Michisuke , Watanabe Masahiko , Birch Mark A. , McCaskie Andrew W. , Lénárt Nikolett , Tóth Krisztina , Dénes Ádám , Liu Zhaoyuan , Ginhoux Florent , Richoz Nathan , Clatworthy Menna R. 
Published: November 2024

AbstractA wide variety of systemic pathologies, including infectious and autoimmune diseases, are accompanied by joint pain or inflammation, often mediated by circulating immune complexes (ICs). How such stimuli access joints and trigger inflammation is unclear. Whole-mount synovial imaging revealed PV1+ fenestrated capillaries at the periphery of the synovium in the lining–sublining interface. Circulating ICs extravasated from these PV1+ capillaries, and nociceptor neurons and three distinct macrophage subsets formed a sentinel unit around them. Macrophages showed subset-specific responses to systemic IC challenge; LYVE1+CX3CR1+ macrophages orchestrated neutrophil recruitment and activated calcitonin gene-related peptide+ (CGRP+) nociceptor neurons via interleukin-1β. In contrast, major histocompatibility complex class II+CD11c+ (MHCII+CD11c+) and MHCII+CD11c– interstitial macrophages formed tight clusters around PV1+ capillaries in response to systemic immune stimuli, a feature enhanced by nociceptor-derived CGRP. Altogether, we identify the anatomical location of synovial PV1+ capillaries and subset-specific macrophage–nociceptor cross-talk that forms a blood–joint barrier protecting the synovium from circulating immune challenges.
Eco-friendly fabrication of copper oxide nanoparticles using peel extract of Citrus aurantium for the efficient degradation of methylene blue dye
Authors: Khedr Alaa I. , Ali Mohamed H. H. 
Published: November 2024

AbstractThis study presents a simple, sustainable, eco-friendly approach for synthesizing copper oxide (CuO) nanoparticles using Citrus aurantium peel extract as a natural reducing and stabilizing agent. The synthesized CuO and CuO-OP were characterized using various techniques, including surface area measurement (SBET), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), diffuse reflectance spectroscopy (DRS), scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectroscopy (EDX), and high resolution transmission electron microscope (HRTEM). DRS analysis determines band gap energy (Eg) of 1.7 eV for CuO and 1.6 eV for CuO-OP. FTIR confirmed the presence of Cu–O bond groups. The XRD and HRTEM results revealed monoclinic and spherical nanostructures, with average particle sizes ranging from 53.25 to 68.02 nm, as determined via Scherer’s equation. EDX analysis indicated incorporation of carbon (1.6%) and nitrogen (0.3%) from the peel extract. The synthesized CuO and CuO-OP NPs exhibited excellent photocatalytic efficiencies for methylene blue dye under UV irradiation, reaching 95.34 and 97.5%, respectively, under optimal conditions; the initial dye concentration was 100 mg/L, the pH was 10, the catalyst dosage was 1 g/L, and the contact time was 120 min. Isothermal studies showed that the adsorption of MB onto the nanoparticles followed the Freundlich isotherm model (R2 = 0.97 and 0.96). Kinetic studies indicated that the degradation followed pseudo-first-order kinetics, with rate constants (K1) of 0.0255 min−1 for CuO and 0.033 min−1 for CuO-OP. The sorption capacities were calculated as 98.19 mg/g for CuO and 123.1 mg/g for CuO-OP. The energy values obtained from the Dubinin–Radushkevich isotherm were 707.11 and 912.87 KJ mol−1, suggesting that chemisorption was the dominant mechanism.
Preliminary investigations of plasma lipidome and selenium levels in adults with treated hypothyroidism and in healthy individuals without selenium deficiency
Authors: Błażewicz Anna , Wojnicka Julia , Grabrucker Andreas M. , Sosnowski Piotr , Trzpil Alicja , Kozub-Pędrak Anna , Szałaj Klaudia , Szmagara Agnieszka , Grywalska Ewelina , Skórzyńska-Dziduszko Katarzyna 
Published: November 2024

AbstractThe present preliminary study aimed to provide a targeted lipidomic analysis of Hashimoto (HT) and non-HT patients with well-controlled hypothyroidism as well as in healthy adults, and is the first to demonstrate the association of several components of the human lipidome with hypothyroidism in relation to the total plasma selenium content. All the patients and age-, sex-, and BMI-matched healthy controls met the very strict qualification criteria. Se levels were analyzed by ICP-MS, and lipidome studies were conducted using TQ-LC/MS. The 40 acylcarnitines, 90 glycerophospholipids, and 15 sphingomyelins were identified and quantified. PCaaC26:0 and PCaaC40:1 were negatively correlated with Se concentrations. Other lipids that were negatively correlated with Se concentrations but did not present significant differences between the three groups in the Kruskal–Wallis ANOVA test were PCaaC32:0, PCaeC30:0, PCaeC36:5, SMC18:0, and SM C18:1. In the multiple linear regression analyses, Se levels showed negative relationship, whereas different phosphatidylcholines: PCaaC24:0, PCaaC26:0, PCaeC30:1, PCaeC34:0, PCaeC36:4, PCaeC42:0 were positively associated with the presence of (H). Different lipidome components were identified in healthy and hypothyroid patients regardless of the cause of that condition. Studies on larger populations are needed to determine cause-and-effect relations and the potential mechanisms underlying these associations.
Compressive sensing and DNA coding operation: Revolutionary approach to colour medical image compression‐encryption algorithm
Authors: Xue Xianglian , Jin Haiyan , Zhou Changjun 
Published: November 2024

AbstractWith advancements in medical imaging technology, colour medical images make lesion diagnosis more intuitive. However, when transmitting these high‐capacity images, doctors and researchers must not only address the challenges of storage and transmission efficiency but also guard against unauthorized access and data security risks. To address these issues, a revolutionary approach for colour medical image compression encryption based on compressive sensing and deoxyribonucleic acid (DNA) coding operation is introduced in this study. Randomness and sparse optimizations are performed on three floating‐point matrices obtained through discrete wavelet and sparse transforms of plain colour medical images by employing position scrambling and reduced‐stiffness operations. Subsequently, the floating‐point matrices are measured and quantized to generate three 8‐bit integer matrices. Further, pixel‐by‐pixel DNA encoding, DNA‐base scrambling, DNA XOR, and DNA decoding operations are performed to achieve DNA base‐position scrambling and value diffusion. Finally, the regrouped bit planes help yield the compressed encrypted images. A comprehensive analysis of the proposed algorithm's encryption and decryption effectiveness, compression performance, and security was conducted. The results show that, with a compression ratio of 0.5, average PSNR = 42.7153 dB and average MSSIM = 0.9779, key space is , average entropy = 7.9986 bits, average histogram variance = 509.53, and the correlation coefficients are close to 0. Moreover, the algorithm shows some immunity to common cryptographic attacks, such as differential, known‐plaintext, noise, and occlusion attacks. Thus, the proposed algorithm addresses the challenges posed by the sensitive nature of patient information and limited storage space.
Transient classifiers for Fink
Authors: Fraga B. M. O. , Bom C. R. , Santos A. , Russeil E. , Leoni M. , Peloton J. , Ishida E. E. O. , Möller A. , Blondin S. 
Published: November 2024

Context. The upcoming Legacy Survey of Space and Time (LSST) at the Vera C. Rubin Observatory is expected to detect a few million transients per night, which will generate a live alert stream during the entire ten years of the survey. This stream will be distributed via community brokers whose task is to select subsets of the stream and direct them to scientific communities. Given the volume and complexity of the anticipated data, machine learning (ML) algorithms will be paramount for this task.
Aims. We present the infrastructure tests and classification methods developed within the FINK broker in preparation for LSST. This work aims to provide detailed information regarding the underlying assumptions and methods behind each classifier and enable users to make informed follow-up decisions from FINK photometric classifications.
Methods. Using simulated data from the Extended LSST Astronomical Time-series Classification Challenge (ELAsTiCC), we showcase the performance of binary and multi-class ML classifiers available in FINK. These include tree-based classifiers coupled with tailored feature extraction strategies as well as deep learning algorithms. Moreover, we introduce the CBPF (Centro Brasileiro de Pesquisas Físicas) Alert Transient Search (CATS), a deep learning architecture specifically designed for this task.
Results. Our results show that FINK classifiers are able to handle the extra complexity that is expected from LSST data. CATS achieved ≥93% precision for all classes except ‘long’ (for which it achieved ∼83%), while our best performing binary classifier achieves ≥98% precision and ≥99% completeness when classifying the periodic class.
Conclusions. ELAsTiCC was an important milestone in preparing the FINK infrastructure to deal with LSST-like data. Our results demonstrate that FINK classifiers are well prepared for the arrival of the new stream, but this work also highlights that transitioning from the current infrastructures to Rubin will require significant adaptation of the currently available tools. This work was the first step in the right direction.