bluuebunny/crossref_metadata_2025_split huggingface dataset:
Knowledge distillation and student–teacher learning for weed detection in turf
Authors: Zhai Danlan , Liu Teng , He Feiyu , Wang Jinxu , Jin Xiaojun , Yu Jialin 
Published: October 2024

AbstractMachine vision–based herbicide applications relying on object detection or image classification deep convolutional neural networks (DCNNs) demand high memory and computational resources, resulting in lengthy inference times. To tackle these challenges, this study assessed the effectiveness of three teacher models, each trained on datasets of varying sizes, including D-20k (comprising 10,000 true-positive and true-negative images) and D-10k (comprising 5,000 true-positive and true-negative images). Additionally, knowledge distillation was performed on their corresponding student models across a range of temperature settings. After the process of student–teacher learning, the parameters of all student models were reduced. ResNet18 not only achieved higher accuracy (ACC ≥ 0.989) but also maintained higher frames per second (FPS ≥ 742.9) under its optimal temperature condition (T = 1). Overall, the results suggest that employing knowledge distillation in the machine vision models enabled accurate and reliable weed detection in turf while reducing the need for extensive computational resources, thereby facilitating real-time weed detection and contributing to the development of smart, machine vision–based sprayers.
Is a Picture Worth 280 Characters?: Contextually Realistic Graphics vs. Plain Text in Survey Experiments
Authors: Harris Benjamin Norwood , Lin-Greenberg Erik 
Published: October 2024

Abstract
As survey experiments have become increasingly common in political science, some scholars have questioned whether inferences about the real world can be drawn from experiments involving hypothetical, text-based scenarios. In response to this criticism, some researchers recommended using realistic, context-heavy vignettes while others argue that abstract vignettes do not generate substantially different results. We contribute to this debate by evaluating whether incorporating contextually realistic graphics into survey experiment vignettes affects experimental outcomes. We field three original experiments that vary whether respondents are shown a realistic graphic or a plain text description during an international crisis. In our experiments, varying whether respondents are shown realistic graphics or plain text descriptions generally yields little difference in outcomes. Our findings have implications for survey methodology and experiments in political science – researchers may not need to invest the time to develop contextually realistic graphics when designing experiments.
Detection of Extensive Equatorial Plasma Depletions After the 2022 Tongan Volcanic Eruption From Multiple Geodetic Satellite Ranging Systems
Authors: Han Shin‐Chan , Kil Hyosub , Ray Richard , Lemoine Frank , Waters Colin 
Published: October 2024

AbstractWe present a number of unique observations of ionospheric anomalies following the Hunga‐Tonga Hunga‐Ha'apai (HTHH) volcanic eruption on 15 January 2022. All are based on non‐dedicated geodetic satellite systems: Global Positioning System tracking of Low Earth Orbit (LEO) CubeSats, intersatellite tracking between two GRACE Follow‐On satellites, satellite radar altimeters to the ocean surface, and Doppler radio beacons from ground stations to LEO geodetic satellites. Their observations revealed the development of anomalously large trough‐like plasma depletions, along with plasma bubbles, in the equatorial regions of the Pacific and East Asian sectors. Trough‐like plasma depletions appeared to be confined within approximately ±20° magnetic latitude, accompanied by density enhancements just outside this latitude range. These plasma depletions and enhancements were aligned with the magnetic equator and occurred across broad longitudes. They were detected in regions where atmospheric waves from the HTHH eruption passed through around the time of the sunset terminator. We interpret these phenomena in terms of the E dynamo electric fields driven by atmospheric waves from the eruption. The uplift of the ionosphere beyond satellite altitudes, followed by subsequent plasma diffusion to higher latitudes along magnetic field lines, results in the formation of trough‐like plasma depletions around the magnetic equator and density enhancement at higher latitudes. The detection of plasma bubbles in the Asian sector during the non‐bubble season (January) is likely associated with the uplift of the ionosphere at the sunset terminator.
Deriving the Ionospheric Electric Field From the Bulk Motion of Radar Aurora in the E‐Region
Authors: Ivarsen Magnus F. , St‐Maurice Jean‐Pierre , Huyghebaert Devin R. , Gillies Megan D. , Lind Frank , Pitzel Brian , Hussey Glenn C. 
Published: October 2024

AbstractIn the auroral E‐region strong electric fields can create an environment characterized by fast plasma drifts. These fields lead to strong Hall currents which trigger small‐scale plasma instabilities that evolve into turbulence. Radio waves transmitted by radars are scattered off of this turbulence, giving rise to the ‘radar aurora’. However, the Doppler shift from the scattered signal does not describe the F‐region plasma flow, the drift imposed by the magnetosphere. Instead, the radar aurora Doppler shift is typically limited by nonlinear processes to not exceed the local ion‐acoustic speed of the E‐region. This being stated, recent advances in radar interferometry enable the tracking of the bulk motion of the radar aurora, which can be quite different and is typically larger than the motion inferred from the Doppler shift retrieved from turbulence scatter. We argue that the bulk motion inferred from the radar aurora tracks the motion of turbulent source regions (provided by auroras). This allows us to retrieve the electric field responsible for the motion of field tubes involved in auroral particle precipitation, since the precipitating electrons must drift. Through a number of case studies, as well as a statistical analysis, we demonstrate that, as a result, the radar aurora bulk motion is closely associated with the high‐latitude convection electric field. We conclude that, while still in need of further refinement, the method of tracking structures in the radar aurora has the potential to provide reliable estimates of the ionospheric electric field that are consistent with nature.
A Synoptic Scale Perspective of Solar Forcing on Extreme Precipitation and Floods Over Europe During Summer
Authors: Rimbu N. , Spiegl T. , Ionita M. , Doshi S. , Lohmann G. 
Published: October 2024

AbstractThe relationship between total solar irradiance (TSI) forcing and summer extreme precipitation and flood frequency over western Europe is investigated from a synoptic‐scale perspective, with a focus on the role of Rossby wave packets (RWPs). Utilizing observational, model, and proxy data, we reveal a significant increase in RWP frequency along a zonal band centered around 50°N, extending from North America to western Europe, during periods of low TSI. This anomaly in RWP frequency is consistent with a significant increase in the frequency of extreme precipitation events recorded over western Europe. Sensitivity experiments conducted with a state‐of‐the‐art chemistry‐climate model corroborate our findings based on observational data. Additionally, a flood record from western Europe demonstrates a significant increase in flood frequency during low TSI years, a relationship that persists across timescales. We argue that the frequency patterns associated with TSI forcing presented in this study are robust and, therefore, valuable for estimating the frequency of extreme precipitation events over western Europe under various solar irradiance scenarios. Moreover, our findings indicate that the North Atlantic sector is more responsive to changes in solar forcing during the boreal summer than previously thought, with this effect manifesting primarily on synoptic timescales rather than the long‐term climatological mean.
Modeling Groundwater Levels in California's Central Valley by Hierarchical Gaussian Process and Neural Network Regression
Authors: Pradhan Anshuman , Adams Kyra H. , Chandrasekaran Venkat , Liu Zhen , Reager John T. , Stuart Andrew M. , Turmon Michael J. 
Published: October 2024

AbstractModeling groundwater levels continuously across California's Central Valley (CV) hydrological system is challenging due to low‐quality well data which is sparsely and noisily sampled across time and space. The lack of consistent well data makes it difficult to evaluate the impact of 2017 and 2019 wet years on CV groundwater following a severe drought during 2012–2015. A novel machine learning method is formulated for modeling groundwater levels by learning from a 3D lithological texture model of the CV aquifer. The proposed formulation performs multivariate regression by combining Gaussian processes (GP) and deep neural networks (DNN). The hierarchical modeling approach constitutes training the DNN to learn a lithologically informed latent space where non‐parametric regression with GP is performed. We demonstrate the efficacy of GP‐DNN regression for modeling non‐stationary features in the well data with fast and reliable uncertainty quantification, as validated to be statistically consistent with the empirical data distribution from 90 blind wells across CV. We show how the model predictions may be used to supplement hydrological understanding of aquifer responses in basins with irregular well data. Our results indicate that on average the 2017 and 2019 wet years in California were largely ineffective in replenishing the groundwater loss caused during previous drought years.
Integrative spatial and genomic analysis of tumor heterogeneity with Tumoroscope
Authors: Shafighi Shadi , Geras Agnieszka , Jurzysta Barbara , Sahaf Naeini Alireza , Filipiuk Igor , Ra̧czkowska Alicja , Toosi Hosein , Koperski Łukasz , Thrane Kim , Engblom Camilla , Mold Jeff E. , Chen Xinsong , Hartman Johan , Nowis Dominika , Carbone Alessandra , Lagergren Jens , Szczurek Ewa 
Published: October 2024

AbstractSpatial and genomic heterogeneity of tumors are crucial factors influencing cancer progression, treatment, and survival. However, a technology for direct mapping the clones in the tumor tissue based on somatic point mutations is lacking. Here, we propose Tumoroscope, the first probabilistic model that accurately infers cancer clones and their localization in close to single-cell resolution by integrating pathological images, whole exome sequencing, and spatial transcriptomics data. In contrast to previous methods, Tumoroscope explicitly addresses the problem of deconvoluting the proportions of clones in spatial transcriptomics spots. Applied to a reference prostate cancer dataset and a newly generated breast cancer dataset, Tumoroscope reveals spatial patterns of clone colocalization and mutual exclusion in sub-areas of the tumor tissue. We further infer clone-specific gene expression levels and the most highly expressed genes for each clone. In summary, Tumoroscope enables an integrated study of the spatial, genomic, and phenotypic organization of tumors.
Quantized current steps due to the synchronization of microwaves with Bloch oscillations in small Josephson junctions
Authors: Shaikhaidarov Rais S. , Kim Kyung Ho , Dunstan Jacob , Antonov Ilya , Golubev Dmitry , Antonov Vladimir N. , Astafiev Oleg V. 
Published: October 2024

AbstractSynchronization of Bloch oscillations in small Josephson junctions (JJs) under microwave radiation, which leads to current quantization, has been proposed as an effect that is dual to the appearance of Shapiro steps. This current quantization was recently demonstrated in superconducting nanowires in a compact high-impedance environment. Direct observation of current quantization in JJs would confirm the synchronization of Bloch oscillations with microwaves and help with the realisation of the metrological current standard. Here, we place JJs in a high-impedance environment and demonstrate dual Shapiro steps for frequencies up to 24 GHz (I = 7.7 nA). Current quantization exists, however, only in a narrow range of JJ parameters. We carry out a systematic study to explain this by invoking the model of a JJ in the presence of thermal noise. The findings are important for fundamental physics and application in quantum metrology.
Transcriptome analysis of rheumatoid arthritis uncovers genes linked to inflammation-induced pain
Authors: Hall Bradford E. , Mazhar Khadijah , Macdonald Emma , Cassidy Margaret , Doty Megan , Judkins Christian , Terse Anita , Shiers Stephanie , Tadros Saber , Yun Sijung , Burton Michael D. , Price Theodore J. , Kulkarni Ashok B. 
Published: October 2024

AbstractAutoimmune diseases such as rheumatoid arthritis (RA) can promote states of chronic inflammation with accompanying tissue destruction and pain. RA can cause inflammatory synovitis in peripheral joints, particularly within the hands and feet, but can also sometimes trigger temporomandibular joint (TMJ) arthralgia. To better understand the effects of ongoing inflammation-induced pain signaling, dorsal root ganglia (DRGs) were acquired from individuals with RA for transcriptomic study. We conducted RNA sequencing from the L5 DRGs because it contains the soma of the sensory neurons that innervate the affected joints in the foot. DRGs from 5 RA patients were compared with 9 non-arthritic controls. RNA-seq of L5 DRGs identified 128 differentially expressed genes (DEGs) that were dysregulated in the RA subjects as compared to the non-arthritic controls. The DRG resides outside the blood brain barrier and, as such, our initial transcriptome analysis detected signs of an autoimmune disorder including the upregulated expression of immunoglobulins and other immunologically related genes within the DRGs of the RA donors. Additionally, we saw the upregulation in genes implicated in neurogenesis that could promote pain hypersensitivity. Overall, our DRG analysis suggests that there are upregulated inflammatory and pain signaling pathways that can contribute to chronic pain in RA.
Effectiveness of ultra-/very-high-frequency oscillations combined with helium–oxygen gas mixture in a rabbit model
Authors: Akiyama Louis , Tatsunami Shinobu , Akita Mieko , Shimizu Naoki 
Published: October 2024

AbstractHigh-frequency oscillatory ventilation (HFOV) at frequencies of approximately 15 Hz is associated with optimal CO2 excretion. Higher frequencies using a nitrogen–oxygen gas mixture worsen CO2 excretion. An in vitro experiment using HFOV and a helium–oxygen gas mixture showed a significant increase in CO2 transport, which increased with increases in ventilation frequency. We hypothesised that in HFOV, the change in the arterial partial pressure of CO2 (PaCO2) would be greater at frequencies above 15 Hz when combined with helium–oxygen gas mixture administration. We tested this hypothesis in a hypoventilated healthy rabbit model by administering a helium–oxygen gas mixture at 15, 25, 35, and 45 Hz frequencies. One-way repeated measures ANOVA showed a significant decrease in PaCO2 among the four ventilation frequency groups. Post-hoc analysis showed significant differences between 15 and 35 Hz frequencies and between 15 and 45 Hz frequencies. The mean (standard error) decrease of PaCO2 was 10.8 (2.2), 14.1 (2.3), 21.3 (3.3), and 23.1 (2.5) mmHg at 15, 25, 35, and 45 Hz, respectively. Combination therapy of helium–oxygen gas mixture and high-frequency oscillation using ultra/very high frequencies (35–45 Hz) was associated with a greater PaCO2 decrease than that using the standard frequency (15 Hz).
Untangling the role of tau in sex hormone responsive cancers: lessons learnt from Alzheimer's disease
Authors: Barker Rachel M. , Chambers Alfie , Kehoe Patrick G. , Rowe Edward , Perks Claire M. 
Published: October 2024

Abstract
Tubulin associated unit has been extensively studied in neurodegenerative diseases including Alzheimer's disease (AD), whereby its hyperphosphorylation and accumulation contributes to disease pathogenesis. Tau is abundantly expressed in the central nervous system but is also present in non-neuronal tissues and in tumours including sex hormone responsive cancers such as breast and prostate. Curiously, hormonal effects on tau also exist in an AD context from numerous studies on menopause, hormone replacement therapy, and androgen deprivation therapy. Despite sharing some risk factors, most importantly advancing age, there are numerous reports from population studies of, currently poorly explained inverse associations between cancer and Alzheimer's disease. We previously reviewed important components of the phosphoinositide-3-kinase/protein kinase B (PI3K/Akt) signalling pathway and their differential modulation in relation to the two diseases. Similarly, receptor tyrosine kinases, estrogen receptor and androgen receptor have all been implicated in the pathogenesis of both cancer and AD. In this review, we focus on tau and its effects in hormone responsive cancer in terms of development, progression, and treatment and in relation to sex hormones and PI3K/Akt signalling molecules including IRS-1, PTEN, Pin1, and p53.
Aircraft human‐machine interaction assistant design: A novel multimodal data processing and application framework
Authors: Wu Ao , Jin Yang , Lv Maolong , Li Huanyu , Li Leyan , Yang Rennong 
Published: October 2024

AbstractDuring aircraft operations, pilots rely on human‐machine interaction platforms to access essential information services. However, the development of a highly usable aerial assistant necessitates the incorporation of two interaction modes: active‐command and passive‐response modes, along with three input modes: voice inputs, situation inputs, and plan inputs. This research focuses on the design of an aircraft human‐machine interaction assistant (AHMIA), which serves as a multimodal data processing and application framework for human‐to‐machine interaction in a fully voice‐controlled manner. For the voice mode, a finetuned FunASR model is employed, leveraging private aeronautical datasets to enable specific aeronautical speech recognition. For the situation mode, a hierarchical situation events extraction model is proposed, facilitating the utilization of high‐level situational features. For the plan mode, a multi‐formations double‐code network plan diagram with a timeline is utilized to effectively represent plan information. Notably, to bridge the gap between human language and machine language, a hierarchical knowledge engine named process‐event‐condition‐order‐skill (PECOS) is introduced. PECOS provides three distinct products: the PECOS model, the PECOS state chart, and the PECOS knowledge description. Simulation results within the air confrontation scenario demonstrate that AHMIA enables active‐command and passive‐response interactions with pilots, thereby enhancing the overall interaction modality.
New insights on thermal ageing of electrical insulating oils as revealed from photoluminescence and absorption spectroscopy
Authors: Karaman Hesham S. , Atiya Eman G. , Mansour Diaa‐Eldin A. , Ghali Mohsen , Elbarbary Z. M. S. , Emara Manal M. 
Published: October 2024

AbstractRecently, significant efforts have been exerted to replace mineral oil with environmentally friendly oils due to safety and environmental issues. However, there is a need to clarify the physical mechanisms behind the ageing impact of these oils. The authors use advanced optical spectroscopy techniques in correlation with dielectric measurements to understand the ageing processes in environmentally friendly oils as well as mineral oil. Firstly, different samples of environmentally friendly oils and mineral oil were utilised to investigate the ageing mechanism. The samples were subjected to different ageing periods using a thermal accelerated ageing process. Secondly, the severity of the produced byproducts due to the oil degradation is examined based on several measured properties representing macroscopic and microscopic categories. The macroscopic category was evaluated through dielectric properties, including breakdown voltage, dielectric permittivity, and dissipation factor. The microscopic category, on the other hand, was assessed using techniques such as ultraviolet–visible absorption spectroscopy and photoluminescence spectroscopy. These techniques enabled a deep understanding of the molecular‐level changes occurring in the oil under ageing conditions, thereby getting new insights into oil ageing mechanisms. It is worth mentioning that natural ester oil demonstrated the most favourable performance across various properties under ageing conditions.
Photometry and kinematics of dwarf galaxies from the Apertif H I survey
Authors: Šiljeg B. , Adams E. A. K. , Fraternali F. , Hess K. M. , Oosterloo T. A. , Marasco A. , Adebahr B. , Dénes H. , Garrido J. , Lucero D. M. , Mancera Piña P. E. , Moss V. A. , Parra-Royón M. , Ponomareva A. A. , Sánchez-Expósito S. , van der Hulst J. M. 
Published: October 2024

Context. Understanding the dwarf galaxy population in low density environments (in the field) is crucial for testing the current Λ Cold Dark Matter cosmological model. The increase in diversity toward low-mass galaxies is seen as an increase in the scatter of scaling relations, such as the stellar mass–size and the baryonic Tully-Fisher relation (BTFR), and is also demonstrated by recent in-depth studies of an extreme sub-class of dwarf galaxies with low surface brightnesses but large physical sizes called ultra-diffuse galaxies (UDGs).
Aims. We aim to select dwarf galaxies independent of their stellar content and to make a detailed study of their gas and stellar properties. We selected galaxies from the APERture Tile In Focus (Apertif) H I survey and applied a constraint on their i-band absolute magnitude in order to exclude high-mass systems. The sample consists of 24 galaxies, 22 of which are resolved in H I by at least three beams, and they span H I mass ranges of 8.6 ≲ log(MH I/M⊙) ≲ 9.7 and a stellar mass range of 8.0 ≲ log(M⋆/M⊙)≲9.7 (with only three galaxies having log (M⋆/M⊙) > 9).
Methods. We determined the geometrical parameters of the H I and stellar disks, built kinematic models from the H I data using 3DBarolo, and extracted surface brightness profiles in the g-, r-, and i-bands from the Pan-STARRS 1 photometric survey. We used these measurements to place our galaxies on the stellar mass–size relation and the BTFR, and we compared them with other samples from the literature.
Results. We find that at a fixed stellar mass, our H I-selected dwarfs have larger optical effective radii than isolated optically selected dwarfs from the literature, and we found misalignments between the optical and H I morphologies for some of our sample. For most of our galaxies, we used the H I morphology to determine their kinematics, and we stress that deep optical observations are needed to trace the underlying stellar disks. Standard dwarfs in our sample follow the same BTFR of high-mass galaxies, whereas UDGs are slightly offset toward lower rotational velocities, in qualitative agreement with results from previous studies. Finally, our sample features a fraction (25%) of dwarf galaxies in pairs that is significantly larger with respect to previous estimates based on optical spectroscopic data.