bluuebunny/crossref_metadata_2025_split huggingface dataset:
Central similarity consistency hashing for asymmetric image retrieval
Authors: Xuan Zhaofeng , Wu Dayan , Zhang Wanqian , Su Qinghang , Li Bo , Wang Weiping 
Published: August 2024

AbstractAsymmetric image retrieval methods have drawn much attention due to their effectiveness in resource-constrained scenarios. They try to learn two models in an asymmetric paradigm, i.e., a small model for the query side and a large model for the gallery. However, we empirically find that the mutual training scheme (learning with each other) will inevitably degrade the performance of the large gallery model, due to the negative effects exerted by the small query one. In this paper, we propose Central Similarity Consistency Hashing (CSCH), which simultaneously learns a small query model and a large gallery model in a mutually promoted manner, ensuring both high retrieval accuracy and efficiency on the query side. To achieve this, we first introduce heuristically generated hash centers as the common learning target for both two models. Instead of randomly assigning each hash center to its corresponding category, we introduce the Hungarian algorithm to optimally match each of them by aligning the Hamming similarity of hash centers to the semantic similarity of their classes. Furthermore, we introduce the instance-level consistency loss, which enables the explicit knowledge transfer from the gallery model to the query one, without the sacrifice of gallery performance. Guided by the unified learning of hash centers and the distilled knowledge from gallery model, the query model can be gradually aligned to the Hamming space of the gallery model in a decoupled manner. Extensive experiments demonstrate the superiority of our CSCH method compared with current state-of-the-art deep hashing methods. The open-source code is available at https://github.com/dubanx/CSCH.
Fast and affordable detection of PKU disease using iron (III) chloride-based solutions and porous PCL biosensors at higher prediction rates
Authors: Gattu Dileep Kumar Reddy , Kaybal Halil Burak , Asmatulu Ramazan 
Published: August 2024

AbstractPhenylketonuria (PKU), a prevalent genetic metabolic disorder, poses substantial diagnostic and treatment challenges globally. Current treatments primarily revolve around strict dietary management, necessitating lifelong commitment and frequent monitoring of phenylalanine (Phe) levels in the body. This study introduces an innovative diagnostic approach utilizing iron (III) chloride solution and highly porous polycaprolactone (PCL)-based solid biosensors for cost-effective, user-friendly detection of L-phenylalanine (L-Phe) in urine, which reflects systemic Phe levels. These biosensors operate through colorimetric changes, quantified using red, green, and blue (RGB), hue, saturation, and lightness (HSL), and cyan, magenta, yellow and black (CMYK) color models, to determine the concentrations of Phe in urine when incorporated with iron (III) chloride. Laboratory tests confirmed that the proposed iron chloride-based liquid and solid sensors are fast, sensitive, specific, and reliable depending on the Phe concentrations. This method promises to simplify home-based monitoring, providing a real-time, low-cost alternative to traditional blood tests, thereby potentially improving patient compliance and outcomes in managing PKU disease. The findings emphasize the potential use of the liquid and PCL-based biosensors in bridging gaps in access to essential diagnostic services for PKU patients.
Thermal influence on performance characteristics of double gate MOSFET biosensors with gate stack configuration
Authors: Das Satish K. , Biswal Sudhansu M. , Giri Lalat Indu , Swain Dibyanshu 
Published: August 2024

AbstractThis study observes the MOSFET's performance concerning several biomolecules for use as a biosensor device. The double gate MOSFET with gate stack configuration has been chosen as the suggested device to surpass the limitations of short-channel effects (SCEs). The cavity was created to restrict the passage of charged and uncharged biological molecules so that they could be detected. These molecules fill the cavity, changing the device's electrical properties. The Double Gate MOSFET (DG-MOSFET) biosensor is subject to limitations such as Short Channel Effects (SCEs) and issues with the power supply. The suggested device decreased SCEs and it also demonstrates the potential benefits of having DG-MOSFETs with gate stacking for biosensor applications. Comparison of transconductance, the generating factor for transconductance, and sensitivity parameters such as Id and Vth sensitivity and Ion/Ioff sensitivity has been carried out in this study.
Applications of artificial intelligence for adolescent idiopathic scoliosis: mapping the evidence
Authors: Goldman Samuel N. , Hui Aaron T. , Choi Sharlene , Mbamalu Emmanuel K. , Tirabady Parsa , Eleswarapu Ananth S. , Gomez Jaime A. , Alvandi Leila M. , Fornari Eric D. 
Published: August 2024

Abstract
Purpose
Adolescent idiopathic scoliosis (AIS) is a common spinal deformity with varying progression, complicating treatment decisions. Artificial intelligence (AI) and machine learning (ML) are increasingly prominent in orthopedic care, aiding in diagnosis, risk-stratification, and treatment guidance. This scoping review outlines AI applications in AIS.

Methods
This study followed PRISMA-ScR guidelines and included articles that reported the development, use, or validation of AI models for treating, diagnosing, or predicting clinical outcomes in AIS.

Results
40 full-text articles were included, with most studies published in the last 5 years (77.5%). Common ML techniques were convolutional neural networks (55%), decision trees and random forests (15%), and artificial neural networks (15%). Most AI applications in AIS were for imaging analysis (25/40; 62.5%), focusing on automatic measurement of Cobb angle, and axial vertebral rotation (13/25; 52%) and curve classification/severity (13/25; 52%). Prediction was the second most common application (15/40; 37.5%), with studies predicting curve progression (9/15; 60%), and Cobb angles (9/15; 60%). Only 15 studies (37.5%) reported clinical implementation guidelines for AI in AIS management. 52.5% of studies reported model accuracy, with an average of 85.4%.

Conclusion
This review highlights the applications of AI in AIS care, notably including automatic radiographic analysis, curve type classification, prediction of curve progression, and AIS diagnosis. However, the current lack of clear clinical implementation guidelines, model transparency, and external validation of studied models limits clinician trust and the generalizability and applicability of AI in AIS management.
Inversion of Gravity Data Constrained by a Magnetotelluric Resistivity Model: Application to the Asal Rift, Djibouti
Authors: Ragueh Rachid Robleh , Tarits Pascal , Hautot Sophie , Jalludin Mohamed 
Published: August 2024

AbstractBefore exploiting a geothermal resource in a volcanic setting such as the Asal rift, it is necessary to acquire a better knowledge of the subsoil, with the objective of locating the geothermal reservoir and evaluating the resource characteristic (permeability, temperature, etc.). For this type of resource, geophysical exploration methods are essential (such as gravimetry, magnetotellurics, etc.). However, a particular data type does not necessarily have the resolution and sensitivity. Furthermore, individual inversions of these geophysical data face the ambiguity of the non‐uniqueness of the inverse solution. In this paper, we present a new linear approach of gravity data using the constraint of a MT resistivity model. We coupled the resistivity and density using inversion cross‐gradients and the linear correlations. The approach was tested and validated on synthetic data and applied to gravity and MT data in the Asal Rift. Multiple inversions with different levels of coupling provided a series of density models. We applied the principal component analysis (PCA) technique to assess these models. We were able to define two dominant processes acting differently on the density and resistivity distribution at depth, namely the geothermal activity of the rift and the structural control of active tectonics.
Estimating Post‐Fire Flood Infrastructure Clogging and Overtopping Hazards
Authors: Jong‐Levinger Ariane , Houston Douglas , Sanders Brett F. 
Published: August 2024

AbstractCycles of wildfire and rainfall produce sediment‐laden floods that pose a hazard to development and may clog or overtop protective infrastructure, including debris basins and flood channels. The compound, post‐fire flood hazards associated with infrastructure overtopping and clogging are challenging to estimate due to the need to account for interactions between sequences of wildfire and storm events and their impact on flood control infrastructure over time. Here we present data sources and calibration methods to estimate infrastructure clogging and channel overtopping hazards on a catchment‐by‐catchment basis using the Post‐Fire Flood Hazard Model (PF2HazMo), a stochastic modeling approach that utilizes continuous simulation to resolve the effects of antecedent conditions and system memory. Publicly available data sources provide parameter ranges needed for stochastic modeling, and several performance measures are considered for model calibration. With application to three catchments in southern California, we show that PF2HazMo predicts the median of the simulated distribution of peak bulked flows within the 95% confidence interval of observed flows, with an order of magnitude range in bulked flow estimates depending on the performance measure used for calibration. Using infrastructure overtopping data from a post‐fire wet season, we show that PF2HazMo accurately predicts the number of flood channel exceedances. Model applications to individual watersheds reveal where infrastructure is undersized to contain present‐day and future overtopping hazards based on current design standards. Model limitations and sources of uncertainty are also discussed.
Zircon Constraints on the Eruptive Sequence and Magma Evolution of Rhyolites at South Sister Volcano, Oregon
Authors: Dechert Annika E. , Andersen Nathan L. , Dufek Josef , Jilly Christine E. 
Published: August 2024

AbstractWe present 230Th‐238U crystallization ages and trace element compositions for zircons spanning the late Pleistocene to Holocene rhyolite eruptive record at South Sister volcano in the central Oregon Cascade Range. Most zircon ages are between 100 and 20 ka, with very few in secular equilibrium (>350 ka). The weighted mean of zircon ages for the two oldest South Sister rhyolites, 31.5 ± 2.1 and 39.1 ± 2.4 ka, are significantly younger than the associated 40Ar/39Ar ages, 47.4 ± 9.7 and 51.4 ± 9.7 ka. We propose that these 40Ar/39Ar dates, performed on plagioclase separates, are compromised by a subtle amount of excess Ar and therefore the younger weighted mean zircon ages yield more reliable eruption ages. These results imply that the interval of rhyolite eruption at South Sister during the late Pleistocene was both shorter and more productive than previously thought and that eruption at South Sister initiated after Middle Sister. Compositionally, zircons from the Pleistocene rhyolites are broadly similar and show down‐temperature zircon and plagioclase crystallization trends. However, we argue that destabilized amphibole and titanite in a common mush also exert leverage on the Pleistocene zircon trace element compositions. Divergence in the Eu/Eu* ratio between the Pleistocene and Holocene lavas implies chemically distinct magma reservoirs originating from the Pleistocene rhyolite eruptive sequence and the Holocene eruptive sequence. This work suggests a higher flux of rhyolite volcanism than previously thought and characterizes magmatic storage distinctions between the Pleistocene and Holocene rhyolites, aiding in the assessment of future eruptive hazards at South Sister volcano.
Pairwise‐Interaction Model Unifies Different Asymptotic Shapes of UHI Intensity
Authors: Li Yunfei , Ribeiro Fabiano L. , Zhou Bin , Rybski Diego 
Published: August 2024

AbstractCity size is a primary determinant of the urban heat island (UHI) intensity, with its effects further nuanced by the urban form. But how to factor in the urban form into the UHI assessment remains unresolved. We propose an every‐pair‐interaction model that meaningfully incorporates urban size and fractal dimension to characterize the UHI intensity. Regression on the summertime surface UHI intensity of 5,000 European cities shows that the model outperforms the simple linear combination of logarithmic size and fractal dimension. Subject to the interplay between the range of the every‐pair interaction and the urban fractal shape, the model also represents a generalization as it includes power‐law, logarithmic, and saturating size dependence of UHI—all three possibilities have been reported empirically in the literature. Our theoretical framework indicates that the surface UHI intensity saturates with urban size, opening up new research perspectives around UHI intensity.
Excitation of Low‐ and High‐Frequency Magnetosonic Whistler Waves Associated With SLAMS in the Terrestrial Foreshock
Authors: Yao Yuhang , Zhao Jinsong , Fu Huishan , Lin Yu , Zhang Wenzhe , Wang Tieyan , Dong Xiangcheng , Dunlop Malcolm W. , Wu Dejin , Guo Xudong 
Published: August 2024

AbstractBased on observations from the Magnetospheric Multiscale mission, this study presents an analysis of a short large‐amplitude magnetic structures (SLAMS) event with simultaneous occurrence of low‐ and high‐frequency magnetosonic whistler waves. It was found that low‐frequency magnetosonic whistler waves around the lower‐hybrid frequency emerge in the presence of solar wind ions and local low‐energy ions in the trailing region of SLAMS. Additionally, counter‐propagating whistler waves (the high‐frequency branch of the magnetosonic whistler wave) are observed within SLAMS, coinciding with a perpendicular temperature anisotropy in the electron population. Instability analyses demonstrate that these low‐frequency waves are induced by the two‐stream instability associated with the cross‐field relative velocity between low‐energy ions and electrons, while whistler waves are locally generated by the whistler anisotropy instability. Our results shed light on the impact of SLAMS on particle and wave dynamics in the terrestrial foreshock.
A Detailed Understanding of Slow Self‐Arresting Rupture
Authors: Wei Xueting , Liu Yuxiang , Xu Jiankuan , Liu Wei , Chen Xiaofei 
Published: August 2024

AbstractRecent numerical simulation studies suggest the existence of a seismic type that is distinct from regular earthquakes—the slow self‐arresting rupture (SSAR). Unlike regular earthquakes that propagate dynamically following the initiation, The SSARs automatically arrest within the nucleation zone without interference. Additionally, numerical simulations indicate that SSARs exhibit a significantly lower energy release compared to regular earthquakes, while also exhibiting a relatively long source duration. Given these distinctive properties, comprehending the source processes of SSARs assumes great strategic importance. However, our current understanding of SSARs, particularly regarding their response to different frictional conditions and their correlation with natural phenomena, remains limited in scope. To further explore the intricacies of SSARs, we employ a three‐dimensional fully dynamic source model to simulate SSARs under various slip‐weakening frictional conditions. The findings indicate that SSARs occur in frictional environments characterized by large normalized critical slip distances, with the seismic source process being primarily influenced by this parameter. Apart from displaying significantly smaller average slip and stress drop, which are two to three orders of magnitude lower than those of regular earthquakes of comparable magnitude, SSARs also showcase a decrease in duration, seismic moment, slip rate, and stress drop as the normalized critical slip distance increases. The moment‐duration scaling law of SSARs exhibits a linear pattern. Moreover, the observation of slow earthquakes offers further implications for the presence of SSARs, indicating their potential association with a wider range of intricate seismic phenomena.
Elaborating the Atmospheric Transformation of Combined and Free Amino Acids From the Perspective of Observational Studies
Authors: Xu Yu , Lin Xi , Sun Qi‐Bin , Xiao Hong‐Wei , Xiao Hao , Xiao Hua‐Yun 
Published: August 2024

AbstractProteinaceous matter (PrM) is a substantial component of bioaerosols. Although numerous studies have examined the characteristics and sources of PrM in the atmosphere, its interactions with atmospheric oxidants remain uncertain. A 1‐year observation of PrM characteristics in PM2.5 was performed in both urban Nanchang (eastern China) and suburban Guiyang (southwestern China), respectively. Glycine was the dominant free amino acid (FAA) species in urban Nanchang. In contrast, proline dominated both total free amino acids (FAAs) and total combined amino acids (CAAs) in suburban Guiyang. We found that oxidative degradation can significantly promote the release of FAAs, especially glycine, from CAAs in Nanchang. The controlled experiment on protein oxidation by hydroxyl radical suggested that the contribution of free glycine to the total FAA fraction tended to increase during the oxidative degradation of CAAs, supporting the predominance of glycine in FAAs in Nanchang and most previous observations. The composition of FAAs was mainly influenced by primary sources in suburban Guiyang with weak atmospheric degradation of PrM. These results suggest that the degradation of aerosol PrM by atmospheric oxidants can be responsible for the difference in FAA composition between the biosphere and the atmosphere, and also imply that the oxidative degradation of aerosol PrM may be a potential source of secondary organic nitrogen compounds in aerosols. Thus, this study can improve the current understanding of the composition characteristics of PrM in the biosphere and the atmosphere, as well as the liquid phase reactions of proteinaceous compounds with atmospheric oxidants.
Accounting for Black Carbon Mixing State, Nonsphericity, and Heterogeneity Effects in Its Optical Property Parameterization in a Climate Model
Authors: Chen Ganzhen , Liu Chao , Wang Jiandong , Yin Yan , Wang Yuan 
Published: August 2024

AbstractModeling atmospheric black carbon (BC) aerosol optical properties remains largely uncertain due to their complex mixing states, nonsphericity, and heterogeneity of coating distribution. Although there exist numerical models with realistic BC morphologies, these models are mostly limited to particle‐scale studies and have not been coupled to large‐scale atmospheric or climate models. In this study, a multidimensional parameterization scheme is developed by an accurate numerical algorithm for BC optical property calculation in global climate models, by incorporating their mixing state and nonspherical structure as well as heterogeneous coating distribution. The scheme was coupled and tested with the Community Atmosphere Model version 6 (CAM6) by a weighted averaging algorithm for individual particles and integration for particle ensembles. The simulation results indicate that BC morphology has a limited influence on the aerosol absorption cross section (Cabs), and the differences in Cabs between irregularly coated fractal aggregates and ideal core‐shell spherical (CS) counterparts are ∼3% on average. However, the relative positions between the BC core and coating parts may introduce Cabs variations of up to 69% as compared with the CS results. The BC mixing state introduce ∼20% relative variations in the global average aerosol absorption optical depth, which is comparable to that of heterogeneity of coating distribution and three times greater than that of particle nonsphericity. Furthermore, the normalized mean biases of modeled single scattering coalbedo (1−SSA, i.e., the ratio of absorption to extinction) compared to those observed in BC‐rich regions are reduced by 20%∼80% when applying our new parameterization in CAM6.
Where Dust Comes From: Global Assessment of Dust Source Attributions With AeroCom Models
Authors: Kim Dongchul , Chin Mian , Schuster Greg , Yu Hongbin , Takemura Toshihiko , Tuccella Paolo , Ginoux Paul , Liu Xiaohong , Shi Yang , Matsui Hitoshi , Tsigaridis Kostas , Bauer Susanne E. , Kok Jasper F. , Schulz Michael 
Published: August 2024

AbstractThe source of dust in the global atmosphere is an important factor to better understand the role of dust aerosols in the climate system. However, it is a difficult task to attribute the airborne dust over the remote land and ocean regions to their origins since dust from various sources are mixed during long‐range transport. Recently, a multi‐model experiment, namely the AeroCom‐III Dust Source Attribution (DUSA), has been conducted to estimate the relative contribution of dust in various locations from different sources with tagged simulations from seven participating global models. The BASE run and a series of runs with nine tagged regions were made to estimate the contribution of dust emitted in East‐ and West‐Africa, Middle East, Central‐ and East‐Asia, North America, the Southern Hemisphere, and the prominent dust hot spots of the Bodélé and Taklimakan Deserts. The models generally agree in large scale mean dust distributions, however models show large diversity in dust source attribution. The inter‐model differences are significant with the global model dust diversity in 30%–50%, but the differences in regional and seasonal scales are even larger. The multi‐model analysis estimates that North Africa contributes 60% of global atmospheric dust loading, followed by Middle East and Central Asia sources (24%). Southern hemispheric sources account for 10% of global dust loading, however it contributes more than 70% of dust over the Southern Hemisphere. The study provides quantitative estimates of the impact of dust emitted from different source regions on the globe and various receptor regions including remote land, ocean, and the polar regions synthesized from the seven models.
Miniaturized, Broadband, Circular Polarized Horn Antenna With Groove Gap Waveguide Technology
Authors: Haghparast Amir Hossein , Rezaei Pejman 
Published: August 2024

AbstractIn this study, a wideband circularly polarized (CP) H‐plane horn antenna based on Gap Waveguide (GW) technology in K‐band is presented. The proposed antenna consists of two unconnected metal planes. To produce broadband CP radiation, two main methods are utilized. First, two antipodal tapered plates (ATPs) are added in front of the horn. The ATPs are carefully designed for dissimilar polarization orientations. By this technique, the orthogonal electric fields can be prepared. Then, by embedding three metal square pins near the center of the aperture in both inner plates, the impedance bandwidth (BW) and BW of CP radiation of the proposed horn is entirely improved. Its BW for target |S11| < −10 dB is 18–28 GHz. Also, the peak gain fluctuates between 11.5 and 13 dB. This antenna can provide a 3 dB polarization axial‐ratio BW of about 28.5% (20–26 GHz). Total radiation efficiency is higher than 94%. To verify the design, the proposed structure is manufactured and tested. The proposed horn antenna result has an appropriate agreement between measurement and simulation. Its miniaturized dimensions, easy and cheap fabrication, and broadband CP capability make it a proper volunteer for broadband communication systems.