bluuebunny/crossref_metadata_2025_split huggingface dataset:
Excitation and Propagation of Magnetosonic Waves in the Earth's Dipole Magnetic Field: 3D PIC Simulation
Authors: Sun Jicheng , Wang Xueyi , Lu Quanming , Zhang Beichen , Hu Zejun , Liu Jianjun , Hu Hongqiao , Yang Huigen 
Published: August 2023

AbstractMagnetosonic (MS) waves are common plasma waves in the Earth's magnetosphere. The self‐consistent excitation of MS waves has been studied by 2D particle‐in‐cell simulations in the meridian and equatorial planes of a dipole magnetic field. However, the direction of wave propagation is artificially limited in the previous 2D simulations. Therefore, the 3D simulation of MS waves needs to be investigated. In this paper, we investigate the excitation and evolution of MS waves in the Earth's dipole magnetic field based on a 3D general curvilinear particle‐in‐cell simulation. We find that the MS waves are excited primarily within 3° of the equator when the thermal velocity of the ring distribution is much less than the ring velocity of the ring distribution. These waves propagate along both the radial and azimuthal directions nearly perpendicular to the background magnetic field. In the linear stage, the growth rates of MS waves are almost equal in the radial and azimuthal directions. Compared with the waves propagating along the radial direction, the waves propagating along the azimuthal direction can grow for a longer time, resulting in a larger wave amplification in this direction after saturation. The simulation results provide a valuable insight to understand the self‐consistent evolution of MS waves in the Earth's dipole magnetic field, and the findings are useful for understanding the plasma wave‐particle interaction in the Earth's radiation belts.
Elucidating Hidden and Enduring Weaknesses in Dust Emission Modeling
Authors: Chappell Adrian , Webb Nicholas P. , Hennen Mark , Zender Charles S. , Ciais Philippe , Schepanski Kerstin , Edwards Brandon L. , Ziegler Nancy P. , Balkanski Yves , Tong Daniel , Leys John F. , Heidenreich Stephan , Hynes Robert , Fuchs David , Zeng Zhenzhong , Baddock Matthew C. , Lee Jeffrey A. , Kandakji Tarek 
Published: August 2023

AbstractLarge‐scale classical dust cycle models, developed more than two decades ago, assume for simplicity that the Earth's land surface is devoid of vegetation, reduce dust emission estimates using a vegetation cover complement, and calibrate estimates to observed atmospheric dust optical depth (DOD). Consequently, these models are expected to be valid for use with dust‐climate projections in Earth System Models. We reveal little spatial relation between DOD frequency and satellite observed dust emission from point sources (DPS) and a difference of up to 2 orders of magnitude. We compared DPS data to an exemplar traditional dust emission model (TEM) and the albedo‐based dust emission model (AEM) which represents aerodynamic roughness over space and time. Both models overestimated dust emission probability but showed strong spatial relations to DPS, suitable for calibration. Relative to the AEM calibrated to the DPS, the TEM overestimated large dust emission over vast vegetated areas and produced considerable false change in dust emission. It is difficult to avoid the conclusion that calibrating dust cycle models to DOD has hidden for more than two decades, these TEM modeling weaknesses. The AEM overcomes these weaknesses without using masks or vegetation cover data. Considerable potential therefore exists for ESMs driven by prognostic albedo, to reveal new insights of aerosol effects on, and responses to, contemporary and environmental change projections.
Improving Global Subseasonal to Seasonal Precipitation Forecasts Using a Support Vector Machine‐Based Method
Authors: Yin Gaohong , Yoshikane Takao , Kaneko Ryo , Yoshimura Kei 
Published: August 2023

AbstractSubseasonal to seasonal (S2s) precipitation forecasts provide great potential for hydrological forecasting at an extended range. The study proposed a support vector machine (SVM) regression‐based method to improve S2s precipitation forecasts from the European Center for Medium‐Range Weather Forecasts (ECMWF) across the globe (60°N to 60°S). Results suggested that the SVM‐based method significantly improved ECMWF daily precipitation forecasts in representing the spatiotemporal variation of precipitation with higher consistency and reduced errors when compared against observations. Furthermore, the SVM‐based method enhanced the probabilistic skill of ECMWF forecasts, providing improved ranked probability skill score (RPSS) for real‐time forecasts in 2020 (e.g., RPSSECMWF = −0.03 and RPSSrg3 = 0.08 for lead week 1). The most substantial improvement from the SVM‐based method is witnessed in regions with complex terrains where ECMWF yielded the worst skill, such as the Andes mountain range, Congo River Basin, and the Tibet Plateau. However, the SVM‐based post‐processing method did not alter the characteristics of precipitation forecasts regarding climate zone and lead time. Both ECMWF and post‐processed forecasts showed higher skill in the temperate and continental climate zones when the lead time is shorter than 2 weeks. In comparison, low‐latitude regions exhibited higher predictability when the lead time is longer than 5 weeks, which is attributed to the slow variation of boundary conditions such as the El Niño‐Southern Oscillation (ENSO).
The Linkage Between Methane Fluxes and Gross Primary Productivity at Diurnal and Seasonal Scales on a Rice Paddy Field in Eastern China
Authors: Zhu Tingting , Zhou Yanlian , Ju Weimin , Li Jing , Hu Lu , Yuan Shu , Xing Xiuli 
Published: August 2023

AbstractCarbon dioxide (CO2) and methane (CH4) are the most important two greenhouse gases in the atmosphere which were closely coupled between terrestrial ecosystems and the atmosphere. However, the relationship between CO2 and CH4 fluxes of rice paddy at different temporal scales is still unclear. Based on 6 years of eddy covariance measurements on a flooded rice paddy field in Eastern China, the relationship between gross primary productivity (GPP) and CH4 fluxes and the effects of biophysical and environmental factors on daily CH4/GPP were investigated. CH4 fluxes and GPP were tightly linked at diurnal and seasonal scales. On average, half‐hourly CH4 fluxes lagged GPP by 1.5 hr while daily GPP lagged CH4 fluxes by 19 days over the growing season. Leaf area index, water table depth (WTD), air temperature, vapor pressure deficit, and canopy conductance significantly affect daily CH4/GPP. A semi‐empirical multiplicative model was able to capture 77% and 84% seasonal variability of daily CH4/GPP for the training data set and testing data set, respectively. WTD is a crucial input affecting the performance of the model. Without WTD included, the agreement between estimated and observed daily CH4/GPP was weakened. Under the condition without WTD data available, separate calibration of the semi‐empirical multiplicative model before and after panicle initiation could improve the estimation of daily CH4/GPP to some extent. The findings in this study enhance our understanding regarding the complex interactions between CH4 fluxes and GPP in the rice paddy and are helpful for better estimation of CH4 fluxes from GPP.
High-speed electro-optic modulation in topological interface states of a one-dimensional lattice
Authors: Zhang Yong , Shen Jian , Li Jingchi , Wang Hongwei , Feng Chenglong , Zhang Lei , Sun Lu , Xu Jian , Liu Ming , Wang Ying , Tian Yonghui , Dong Jianwen , Su Yikai 
Published: August 2023

AbstractElectro-optic modulators are key components in data communication, microwave photonics, and quantum photonics. Modulation bandwidth, energy efficiency, and device dimension are crucial metrics of modulators. Here, we provide an important direction for the miniaturization of electro-optic modulators by reporting on ultracompact topological modulators. A topological interface state in a one-dimensional lattice is implemented on a thin-film lithium-niobate integrated platform. Due to the strong optical confinement of the interface state and the peaking enhancement of the electro-optic response, a topological cavity with a size of 1.6 × 140 μm2 enables a large modulation bandwidth of 104 GHz. The first topological modulator exhibits the most compact device size compared to reported LN modulators with bandwidths above 28 GHz, to the best of our knowledge. 100 Gb/s non-return-to-zero and 100 Gb/s four-level pulse amplitude modulation signals are generated. The switching energy is 5.4 fJ/bit, owing to the small electro-optic mode volume and low capacitance. The topological modulator accelerates the response time of topological photonic devices from the microsecond order to the picosecond order and provides an essential foundation for the implementation of large-scale lithium-niobate photonic integrated circuits.
Harnessing metabolism of hepatic macrophages to aid liver regeneration
Authors: Liu Rui , Scimeca Manuel , Sun Qiang , Melino Gerry , Mauriello Alessandro , Shao Changshun ,   TOR Centre, Francesca Bernassola , Pierluigi Bove , Eleonora Candi , Valentina Rovella , Giuseppe Sica , Ying Wang , Shi Yufang , Piacentini Mauro , Tisone Giuseppe , Agostini Massimiliano 
Published: August 2023

AbstractLiver regeneration is a dynamic and regulated process that involves inflammation, granulation, and tissue remodeling. Hepatic macrophages, abundantly distributed in the liver, are essential components that actively participate in each step to orchestrate liver regeneration. In the homeostatic liver, resident macrophages (Kupffer cells) acquire a tolerogenic phenotype and contribute to immunological tolerance. Following toxicity-induced damage or physical resection, Kupffer cells as well as monocyte-derived macrophages can be activated and promote an inflammatory process that supports the survival and activation of hepatic myofibroblasts and thus promotes scar tissue formation. Subsequently, these macrophages, in turn, exhibit the anti-inflammatory effects critical to extracellular matrix remodeling during the resolution stage. However, continuous damage-induced chronic inflammation generally leads to hepatic macrophage dysfunction, which exacerbates hepatocellular injury and triggers further liver fibrosis and even cirrhosis. Emerging macrophage-targeting strategies have shown efficacy in both preclinical and clinical studies. Increasing evidence indicates that metabolic rewiring provides substrates for epigenetic modification, which endows monocytes/macrophages with prolonged “innate immune memory”. Therefore, it is reasonable to conceive novel therapeutic strategies for metabolically reprogramming macrophages and thus mediate a homeostatic or reparative process for hepatic inflammation management and liver regeneration.
Neonatal and maternal outcomes following SARS-CoV-2 infection and COVID-19 vaccination: a population-based matched cohort study
Authors: Lindsay Laura , Calvert Clara , Shi Ting , Carruthers Jade , Denny Cheryl , Donaghy Jack , Hopcroft Lisa E. M. , Hopkins Leanne , Goulding Anna , McLaughlin Terry , Moore Emily , Taylor Bob , Bhaskaran Krishnan , Katikireddi Srinivasa Vittal , McCabe Ronan , McCowan Colin , Simpson Colin R. , Robertson Chris , Sheikh Aziz , Wood Rachael , Stock Sarah J. 
Published: August 2023

AbstractUnderstanding the impact of SARS-CoV-2 infection and COVID-19 vaccination in pregnancy on neonatal and maternal outcomes informs clinical decision-making. Here we report a national, population-based, matched cohort study to investigate associations between SARS-CoV-2 infection and, separately, COVID-19 vaccination just before or during pregnancy and the risk of adverse neonatal and maternal outcomes among women in Scotland with a singleton pregnancy ending at ≥20 weeks gestation. Neonatal outcomes are stillbirth, neonatal death, extended perinatal mortality, preterm birth (overall, spontaneous, and provider-initiated), small-for-gestational age, and low Apgar score. Maternal outcomes are admission to critical care or death, venous thromboembolism, hypertensive disorders of pregnancy, and pregnancy-related bleeding. We use conditional logistic regression to derive odds ratios adjusted for socio-demographic and clinical characteristics (aORs). We find that infection is associated with an increased risk of preterm (aOR=1.36, 95% Confidence Interval [CI] = 1.16–1.59) and very preterm birth (aOR = 1.90, 95% CI 1.20–3.02), maternal admission to critical care or death (aOR=1.72, 95% CI = 1.39–2.12), and venous thromboembolism (aOR = 2.53, 95% CI = 1.47–4.35). We find no evidence of increased risk for any of our outcomes following vaccination. These data suggest SARS-CoV-2 infection during pregnancy is associated with adverse neonatal and maternal outcomes, and COVID-19 vaccination remains a safe way for pregnant women to protect themselves and their babies against infection.
Investigation with able-bodied subjects suggests Myosuit may potentially serve as a stair ascent training robot
Authors: Kim Jaewook , Kim Yekwang , Kang Seonghyun , Kim Seung-Jong 
Published: August 2023

AbstractReal world settings are seldomly just composed of level surfaces and stairs are frequently encountered in daily life. Unfortunately, ~ 90% of the elderly population use some sort of compensation pattern in order to negotiate stairs. Because the biomechanics required to successfully ascend stairs is significantly different from level walking, an independent training protocol is warranted. Here, we present as a preliminary investigation with 11 able-bodied subjects, prior to clinical trials, whether Myosuit could potentially serve as a stair ascent training robot. Myosuit is a soft wearable exosuit that was designed to assist the user via hip and knee extension during the early stance phase. We hypothesized that clinical studies could be carried out if the lower limb kinematics, sensory feedback via plantar force, and electromyography (EMG) patterns do not deviate from the user’s physiological stair ascent patterns while reducing hip and knee extensor demand. Our results suggest that Myosuit conserves the user’s physiological kinematic and plantar force patterns. Moreover, we observe approximately 20% and 30% decrease in gluteus maximus and vastus medialis EMG levels in the pull up phase, respectively. Collectively, Myosuit reduces the hip and knee extensor demand during stair ascent without any introduction of significant compensation patterns.
MnEdgeNet for accurate decomposition of mixed oxidation states for Mn XAS and EELS L2,3 edges without reference and calibration
Authors: Ji Zhengran , Hu Mike , Xin Huolin L. 
Published: August 2023

AbstractAccurate decomposition of the mixed Mn oxidation states is highly important for characterizing the electronic structures, charge transfer and redox centers for electronic, and electrocatalytic and energy storage materials that contain Mn. Electron energy loss spectroscopy (EELS) and soft X-ray absorption spectroscopy (XAS) measurements of the Mn L2,3 edges are widely used for this purpose. To date, although the measurements of the Mn L2,3 edges are straightforward given the sample is prepared properly, an accurate decomposition of the mix valence states of Mn remains non-trivial. For both EELS and XAS, 2+, 3+, and 4+ reference spectra need to be taken on the same instrument/beamline and preferably in the same experimental session because the instrumental resolution and the energy axis offset could vary from one session to another. To circumvent this hurdle, in this study, we adopted a deep learning approach and developed a calibration-free and reference-free method to decompose the oxidation state of Mn L2,3 edges for both EELS and XAS. A deep learning regression model is trained to accurately predict the composition of the mix valence state of Mn. To synthesize physics-informed and ground-truth labeled training datasets, we created a forward model that takes into account plural scattering, instrumentation broadening, noise, and energy axis offset. With that, we created a 1.2 million-spectrum database with 1-by-3 oxidation state composition ground truth vectors. The library includes a sufficient variety of data including both EELS and XAS spectra. By training on this large database, our convolutional neural network achieves 85% accuracy on the validation dataset. We tested the model and found it is robust against noise (down to PSNR of 10) and plural scattering (up to t/λ = 1). We further validated the model against spectral data that were not used in training. In particular, the model shows high accuracy and high sensitivity for the decomposition of Mn3O4, MnO, Mn2O3, and MnO2. The accurate decomposition of Mn3O4 experimental data shows the model is quantitatively correct and can be deployed for real experimental data. Our model will not only be a valuable tool to researchers and material scientists but also can assist experienced electron microscopists and synchrotron scientists in the automated analysis of Mn L edge data.
Trimming flow, plasticity, and mechanical properties by cubic silsesquioxane chemistry
Authors: Sztorch Bogna , Brząkalski Dariusz , Głowacka Julia , Pakuła Daria , Frydrych Miłosz , Przekop Robert E. 
Published: August 2023

AbstractIn this work, the possibility of managing the rheological and mechanical parameters of composites based on PLA with the use of cubic structures of organofunctional spherosilicates was verified. To accurately observe the effect of various organosilicon modifier substitutions on changes in composites’ properties, we synthesized and used monofunctional octasubstituted derivatives as reference systems. The OSS/PLA systems were tested with concentrations of 0.1–2.5% (w/w) using extrusion to obtain a filament with a diameter of 1.75 mm. The printed samples underwent comprehensive tests including microscopic (SEM–EDS, optical microscope), rheological, thermal (TG, DSC, HDT), mechanical (impact and strength) as well as water contact angle tests. The work is interdisciplinary in nature and combines elements of organosilicon synthesis, materials engineering, and materials processing and characterization technology.
Identification of the novel potential pathogen Trueperella pecoris with interspecies significance by LAMP diagnostics
Authors: Kreitlow Antonia , Ningrum Siti Gusti , Lämmler Christoph , Erhard Marcel , Hoffmann Christiane , Plötz Madeleine , Abdulmawjood Amir 
Published: August 2023

AbstractTrueperella pecoris was described as a new species of the genus Trueperella in 2021 and might be pathogenic to various animal species. However, the lack of a suitable diagnostic test system stands in the way of epidemiological surveys to clarify possible causalities. In this study, a Loop-mediated Isothermal Amplification (LAMP) assay was developed and validated that was highly specific for T. pecoris. The assay provided an analytical sensitivity of 0.5 pg/25 µL and showed 100% inclusivity and exclusivity for 11 target and 33 non-target strains, respectively. Three different DNA extraction methods were evaluated to select the most LAMP-compatible method for cell disruption in pure and complex samples. Using an on-site applicable single-buffer DNA extraction with additional heating, the cell-based detection limit was 2.3 CFU/reaction. Finally, the LAMP assay was validated by means of artificially contaminated porcine lung tissue samples in which minimal microbial loads between 6.54 and 8.37 × 103 CFU per swab sample were detectable. The LAMP assay established in this study represents a suitable diagnostic procedure for identifying T. pecoris in clinical specimens and will help to collect epidemiological data on the pathogenicity of this species.
Low-light image enhancement via adaptive frequency decomposition network
Authors: Liang Xiwen , Chen Xiaoyan , Ren Keying , Miao Xia , Chen Zhihui , Jin Yutao 
Published: August 2023

AbstractImages captured in low light conditions suffer from low visibility, blurred details and strong noise, resulting in unpleasant visual appearance and poor performance of high level visual tasks. To address these problems, existing approaches have attempted to enhance the visibility of low-light images using convolutional neural networks (CNN). However, due to the insufficient consideration of the characteristics of the information of different frequency layers in the image, most of them yield blurry details and amplified noise. In this work, to fully extract and utilize these information, we proposed a novel Adaptive Frequency Decomposition Network (AFDNet) for low-light image enhancement. An Adaptive Frequency Decomposition (AFD) module is designed to adaptively extract low and high frequency information of different granularities. Specifically, the low-frequency information is employed for contrast enhancement and noise suppression in low-scale space and high-frequency information is for detail restoration in high-scale space. Meanwhile, a new frequency loss function are proposed to guarantee AFDNet’s recovery capability for different frequency information. Extensive experiments on various publicly available datasets show that AFDNet outperforms the existing state-of-the-art methods both quantitatively and visually. In addition, our results showed that the performance of the face detection can be effectively improved by using AFDNet as pre-processing.
Mycobacterial DNA-binding protein 1 is critical for BCG survival in stressful environments and simultaneously regulates gene expression
Authors: Shaban Amina K. , Gebretsadik Gebremichal , Hakamata Mariko , Takihara Hayato , Inouchi Erina , Nishiyama Akihito , Ozeki Yuriko , Tateishi Yoshitaka , Nishiuchi Yukiko , Yamaguchi Takehiro , Ohara Naoya , Okuda Shujiro , Matsumoto Sohkichi 
Published: August 2023

AbstractSurvival of the live attenuated Bacillus Calmette-Guérin (BCG) vaccine amidst harsh host environments is key for BCG effectiveness as it allows continuous immune response induction and protection against tuberculosis. Mycobacterial DNA binding protein 1 (MDP1), a nucleoid associated protein, is essential in BCG. However, there is limited knowledge on the extent of MDP1 gene regulation and how this influences BCG survival. Here, we demonstrate that MDP1 conditional knockdown (cKD) BCG grows slower than vector control in vitro, and dies faster upon exposure to antibiotics (bedaquiline) and oxidative stress (H2O2 and menadione). MDP1-cKD BCG also exhibited low infectivity and survival in THP-1 macrophages and mice indicating possible susceptibility to host mediated stress. Consequently, low in vivo survival resulted in reduced cytokine (IFN-gamma and TNF-alpha) production by splenocytes. Temporal transcriptome profiling showed more upregulated (81–240) than downregulated (5–175) genes in response to MDP1 suppression. Pathway analysis showed suppression of biosynthetic pathways that coincide with low in vitro growth. Notable was the deferential expression of genes involved in stress response (sigI), maintenance of DNA integrity (mutT1), REDOX balance (WhiB3), and host interactions (PE/PE_PGRS). Thus, this study shows MDP1’s importance in BCG survival and highlights MDP1-dependent gene regulation suggesting its role in growth and stress adaptation.