bluuebunny/crossref_metadata_2025_split huggingface dataset:
At the frontlines of implementing the right to a healthy environment: Understanding human rights and environmental due diligence in relation to armed conflicts
Authors: Kron Amanda 
Published: August 2023

AbstractPotential harm to human rights and the environment, including by corporate actors, is amplified in situations of conflict. This article focuses on applying the right to a healthy environment in relation to armed conflicts and corporate responsibility. In particular, it analyzes and compares due diligence requirements in the European Union Conflict Minerals Regulation and the International Law Commission's Draft Principles on Protection of the Environment in Relation to Armed Conflicts and examines how these align with the right to a healthy environment.
The Great Climate Mitigation Potential of Cropland Ecosystem Management in China
Authors: Zheng Huan , Guo Lanlan , He Bin , Shen Yanjun , Yuan Wenping , Yang Wentao , Li Tiewei , Zheng Hao 
Published: August 2023

AbstractLimiting climate warming to below 2°C requires more intense mitigation efforts. Alongside the steep reductions in fossil fuel emissions needed, natural climate solutions (NCS) act as an additional first step toward achieving China's emission reduction goals. We first quantified the historical contribution of NCS as 0.34 PgCO2equivalent (PgCO2e) yr−1through the implemented national ecological restoration projects as well as positive management measures. Based on successful practices, we then designed 21 pathways to quantify the potential of NCS in increasing terrestrial carbon sinks or reducing greenhouse gas (GHG) emissions in forest, grassland, cropland, and wetland ecosystems. We show that the maximum mitigation potential of NCS between 2020 and 2060 under guaranteed food and fiber security is 1.95 (1.54–2.38) PgCO2e yr−1(95% CI), which can offset nearly 20% of the annual net emissions. Historically, forest ecosystems have contributed the most to carbon sequestration; however, future projections show cropland ecosystems will account for the largest proportion (47.6%), followed by forest ecosystems. Approximately 47% (0.91 PgCO2e yr−1) of the maximum represents cost‐effective mitigation potential that can be realized at ≤100 USD/MgCO2e. Conservation tillage is the most cost‐effective option in China, achieving a maximum contribution of 181.60 TgCO2e yr−1. In addition, a series of cropland management measures have contributed 1.14 PgCO2e in the past two decades. Our study highlights the high effectiveness of cropland pathways in reducing carbon emissions and emphasizes the key role of cropland ecosystems in mitigating climate change.
The Largest Ever Recorded Heatwave—Characteristics and Attribution of the Antarctic Heatwave of March 2022
Authors: Blanchard‐Wrigglesworth Edward , Cox Tyler , Espinosa Zachary I. , Donohoe Aaron 
Published: August 2023

AbstractAn unprecedented heatwave impacted East Antarctica in March 2022, peaking at 39°C above climatology, the largest temperature anomaly ever recorded globally. We investigate the causes of the heatwave, the impact of climate change, and a climate model's ability in simulating such an event. The heatwave, which was skillfully forecast, resulted from a highly anomalous large‐scale circulation pattern that advected an Australian airmass to East Antarctica in 4 days and produced record atmospheric heat fluxes. Southern Ocean sea surface temperatures anomalies had a minimal impact on the heatwave's amplitude. Simulations from a climate model fail to simulate such a large temperature anomaly mostly due to biases in its large‐scale circulation variability, showcasing a pathway for future model improvement in simulating extreme heatwaves. The heatwave was made 2°C warmer by climate change, and end of 21st century heatwaves may be an additional 5–6°C warmer, raising the prospect of near‐melting temperatures over the interior of East Antarctica.
The 6 February 2023 Türkiye Earthquake Sequence as Detected in the Ionosphere
Authors: Maletckii B. , Astafyeva E. , Sanchez S. A. , Kherani E. A. , de Paula E. R. 
Published: August 2023

AbstractOn 6 February 2023, a series of large earthquakes struck Turkey and Northern Syria. The main earthquake of Mw 7.8 occurred at 01:17:34 UTC and was followed by the three notable (Mw > 5.5) aftershocks within the next 18 min. Then, ∼9 hr later, the biggest aftershock with magnitude Mw 7.5 and a Mw 6.0 earthquake occurred to the north‐east from the first main earthquake. In this work, we use data of ground‐based Global Navigation Satellite Systems (GNSS) receivers in Turkey, Israel and Cyprus to analyze the ionospheric response to this series of earthquakes. We separate these events in two groups: the first sequence of earthquakes (at 01–02 UTC) and the second sequence (at 10–11 UTC). For the first sequence, we observe a clear N‐shaped total electron content (TEC) response after the Mw 7.8 mainshock earthquake and Mw 6.7 aftershock, and a smaller TEC disturbance that is, most likely, caused by the Mw 5.6 earthquake. The latter is now the smallest earthquake detected by using ionospheric GNSS data. The co‐seismic ionospheric disturbances (CSID) propagated from the epicentral area in the south‐west direction with velocities of about 750–830 m/s. For the second sequence, we observed the response to the Mw 7.5 aftershock earthquake and the Mw 6.0 aftershock. The CSID propagated both to the south‐west and the north‐west to the epicentral area, with velocities of about 950–1,100 m/s.
Quantifying Site Effects and Their Influence on Earthquake Source Parameter Estimations Using a Dense Array in Oklahoma
Authors: Chang Hilary , Abercrombie Rachel E. , Nakata Nori , Pennington Colin N. , Kemna Kilian B. , Cochran Elizabeth S. , Harrington Rebecca M. 
Published: August 2023

AbstractWe investigate the effects of site response on source parameter estimates using earthquakes recorded by the LArge‐n Seismic Survey in Oklahoma (LASSO). While it is well known that near‐surface unconsolidated sediments can cause an apparent breakdown of earthquake self‐similarity, the influence of laterally varying site conditions remains unclear. We analyze site conditions across the 1825‐station array on a river plain within an area of 40 km by 23 km using vertical ground motions from 14 regional earthquakes. While the source radiation pattern controls P‐wave ground motions below 8 Hz, the surface geology correlates with P‐wave ground motions above 8 Hz and S‐wave ground motions at 2–21 Hz. Stations installed in alluvial sediments have vertical ground motions that can exceed three times the array median. We use the variation of ground motion of regional earthquakes across the array as a proxy for site effects. The corner frequencies and stress drops of local earthquakes (ML = 0.01–3) estimated using a standard single‐spectra approach show negative correlations with the site‐effect proxy, while the seismic moments show positive correlations. In contrast, the spectral‐ratio approach effectively shows no correlation. The overall bias is small as expected for this relatively homogeneous structure; accurate estimation of site‐related biases requires at least 30 stations. Correcting for site‐related biases reduces the standard deviations of the source parameters by less than 13% of the total variations. Remaining variations are partially associated with source directivity and model misfits— as small earthquakes can have complex ruptures.
Rethinking Variability in Bedrock Rivers: Sensitivity of Hillslope Sediment Supply to Precipitation Events Modulates Bedrock Incision During Floods
Authors: DeLisle Clarke , Yanites Brian J. 
Published: August 2023

AbstractBedrock rivers are the pacesetters of landscape evolution in uplifting fluvial landscapes. Water discharge variability and sediment transport are important factors influencing bedrock river processes. However, little work has focused on the sensitivity of hillslope sediment supply to precipitation events and its implications on river evolution in tectonically active landscapes. We model the temporal variability of water discharge and the sensitivity of sediment supply to precipitation events as rivers evolve to equilibrium over 106 model years. We explore how coupling sediment supply sensitivity with discharge variability influences rates and timing of river incision across climate regimes. We find that sediment supply sensitivity strongly impacts which water discharge events are the most important in driving river incision and modulates channel morphology. High sediment supply sensitivity focuses sediment delivery into the largest river discharge events, decreasing rates of bedrock incision during floods by orders of magnitude as rivers are inundated with new sediment that buries bedrock. The results show that the use of river incision models in which incision rates increase monotonically with increasing river discharge may not accurately capture bedrock river dynamics in all landscapes, particularly in steep landslide prone landscapes. From our modeling results, we hypothesize the presence of an upper discharge threshold for river incision at which storms transition from being incisional to depositional. Our work illustrates that sediment supply sensitivity must be accounted for to predict river evolution in dynamic landscapes. Our results have important implications for interpreting and predicting climatic and tectonic controls on landscape morphology and evolution.
Advancing optothermal manipulation: decoupling temperature and flow fields in quasi-isothermal microscale streaming
Authors: Kim Youngsun , Zheng Yuebing 
Published: August 2023

AbstractBy decoupling temperature and flow fields through symmetry-correlated laser scan sequences, ISO-FLUCS enables quasi-isothermal optofluidic microscale streaming. This technique offers precise control over fluid manipulation while minimizing thermal damage.
Infrared avalanche photodiodes from bulk to 2D materials
Authors: Martyniuk Piotr , Wang Peng , Rogalski Antoni , Gu Yue , Jiang Ruiqi , Wang Fang , Hu Weida 
Published: August 2023

AbstractAvalanche photodiodes (APDs) have drawn huge interest in recent years and have been extensively used in a range of fields including the most important one—optical communication systems due to their time responses and high sensitivities. This article shows the evolution and the recent development of AIIIBV, AIIBVI, and potential alternatives to formerly mentioned—“third wave” superlattices (SL) and two-dimensional (2D) materials infrared (IR) APDs. In the beginning, the APDs fundamental operating principle is demonstrated together with progress in architecture. It is shown that the APDs evolution has moved the device’s performance towards higher bandwidths, lower noise, and higher gain-bandwidth products. The material properties to reach both high gain and low excess noise for devices operating in different wavelength ranges were also considered showing the future progress and the research direction. More attention was paid to advances in AIIIBVAPDs, such as AlInAsSb, which may be used in future optical communications, type-II superlattice (T2SLs, “Ga-based” and “Ga-free”), and 2D materials-based IR APDs. The latter—atomically thin 2D materials exhibit huge potential in APDs and could be considered as an alternative material to the well-known, sophisticated, and developed AIIIBVAPD technologies to include single-photon detection mode. That is related to the fact that conventional bulk materials APDs’ performance is restricted by reasonably high dark currents. One approach to resolve that problem seems to be implementing low-dimensional materials and structures as the APDs’ active regions. The Schottky barrier and atomic level thicknesses lead to the 2D APD dark current significant suppression. What is more, APDs can operate within visible (VIS), near-infrared (NIR)/mid-wavelength infrared range (MWIR), with a responsivity ~80 A/W, external quantum efficiency ~24.8%, gain ~105for MWIR [wavelength,λ = 4 μm, temperature,T = 10–180 K, Black Phosphorous (BP)/InSe APD]. It is believed that the 2D APD could prove themselves to be an alternative providing a viable method for device fabrication with simultaneous high-performance—sensitivity and low excess noise.
Chaos Raman distributed optical fiber sensing
Authors: Wang Chenyi , Li Jian , Zhou Xinxin , Cheng Zijia , Qiao Lijun , Xue Xiaohui , Zhang Mingjiang 
Published: August 2023

AbstractThe physics principle of pulse flight positioning is the main theoretical bottleneck that restricts the spatial resolution of the existing Raman distributed optical fiber sensing scheme. Owing to the pulse width of tens of nanoseconds, the spatial resolution of the existing Raman distributed optical fiber sensing scheme with kilometer-level sensing distance is limited to the meter level, which seriously restricts the development of the optical time-domain reflection system. In this paper, a chaos laser is proposed in the context of the physical principle of the Raman scattering effect, and a novel theory of chaos Raman distributed optical fiber sensing scheme is presented. The scheme reveals the characteristics of chaos Raman scattering light excited by a chaotic signal on the sensing fiber. Further, the chaos time-domain compression demodulation mechanism between the temperature variation information and chaos correlation peak is demonstrated. Then, the position of the temperature variation signal is precisely located using the delay time of the chaos correlation peak combined with the chaos pulse flight time. Based on this novel optical sensing mechanism, an experiment with 10 cm spatial resolution and 1.4 km sensing distance was conducted, and the spatial resolution was found to be independent of the sensing distance. Within the limit of the existing spatial resolution theory, the spatial resolution of the proposed scheme is 50 times higher than that of the traditional scheme. The scheme also provides a new research direction for optical chaos and optical fiber sensing.
Emergence of putative energy parasites within Clostridia revealed by genome analysis of a novel endosymbiotic clade
Authors: Takahashi Kazuki , Kuwahara Hirokazu , Horikawa Yutaro , Izawa Kazuki , Kato Daiki , Inagaki Tatsuya , Yuki Masahiro , Ohkuma Moriya , Hongoh Yuichi 
Published: August 2023

Abstract
The Clostridia is a dominant bacterial class in the guts of various animals and are considered to nutritionally contribute to the animal host. Here, we discovered clostridial endosymbionts of cellulolytic protists in termite guts, which have never been reported with evidence. We obtained (near-)complete genome sequences of three endosymbiotic Clostridia, each associated with a different parabasalid protist species with various infection rates: Trichonympha agilis, Pseudotrichonympha grassii, and Devescovina sp. All these protists are previously known to harbor permanently-associated, mutualistic Endomicrobia or Bacteroidales that supplement nitrogenous compounds. The genomes of the endosymbiotic Clostridia were small in size (1.0–1.3 Mbp) and exhibited signatures of an obligately-intracellular parasite, such as an extremely limited capability to synthesize amino acids, cofactors, and nucleotides and a disrupted glycolytic pathway with no known net ATP-generating system. Instead, the genomes encoded ATP/ADP translocase and, interestingly, regulatory proteins that are unique to eukaryotes in general and are possibly used to interfere with host cellular processes. These three genomes formed a clade with metagenome-assembled genomes (MAGs) derived from the guts of other animals, including human and ruminants, and the MAGs shared the characteristics of parasites. Gene flux analysis suggested that the acquisition of the ATP/ADP translocase gene in a common ancestor was probably key to the emergence of this parasitic clade. Taken together, we provide novel insights into the multilayered symbiotic system in the termite gut by adding the presence of parasitism and present an example of the emergence of putative energy parasites from a dominant gut bacterial clade.
A route to metalloligands consolidated silver nanoclusters by grafting thiacalix[4]arene onto polyoxovanadates
Authors: Wang Zhi , Zhu Yan-Jie , Han Bao-Liang , Li Yi-Zhi , Tung Chen-Ho , Sun Di 
Published: August 2023

AbstractMetalloligands provide a potent strategy for manipulating the surface metal arrangements of metal nanoclusters, but their synthesis and subsequent installation onto metal nanoclusters remains a significant challenge. Herein, two atomically precise silver nanoclusters {Ag14[(TC4A)6(V9O16)](CyS)3} (Ag14) and {Ag43S[(TC4A)2(V4O9)]3(CyS)9(PhCOO)3Cl3(SO4)4(DMF)3·6DMF} (Ag43) are synthesized by controlling reaction temperature (H4TC4A = p-tert-butylthiacalix[4]arene). Interestingly, the 3D scaffold-like [(TC4A)6(V9O16)]11- metalloligand in Ag14 and 1D arcuate [(TC4A)2(V4O9)]6- metalloligand in Ag43 exhibit a dual role that is the internal polyoxovanadates as anion template and the surface TC4A4- as the passivating agent. Furthermore, the thermal-induced structure transformation between Ag14 and Ag43 is achieved based on the temperature-dependent assembly process. Ag14 shows superior photothermal conversion performance than Ag43 in solid state indicating its potential for remote laser ignition. Here, we show the potential of two thiacalix[4]arene modified polyoxovanadates metalloligands in the assembly of metal nanoclusters and provide a cornerstone for the remote laser ignition applications of silver nanoclusters.
Synthesize high-dimensional longitudinal electronic health records via hierarchical autoregressive language model
Authors: Theodorou Brandon , Xiao Cao , Sun Jimeng 
Published: August 2023

AbstractSynthetic electronic health records (EHRs) that are both realistic and privacy-preserving offer alternatives to real EHRs for machine learning (ML) and statistical analysis. However, generating high-fidelity EHR data in its original, high-dimensional form poses challenges for existing methods. We propose Hierarchical Autoregressive Language mOdel () for generating longitudinal, high-dimensional EHR, which preserve the statistical properties of real EHRs and can train accurate ML models without privacy concerns. generates a probability density function over medical codes, clinical visits, and patient records, allowing for generating realistic EHR data without requiring variable selection or aggregation. Extensive experiments demonstrated that can generate high-fidelity data with high-dimensional disease code probabilities closely mirroring (above 0.9 R2 correlation) real EHR data. also enhances the accuracy of predictive modeling and enables downstream ML models to attain similar accuracy as models trained on genuine data.
Antibody-mediated neutralization of galectin-3 as a strategy for the treatment of systemic sclerosis
Authors: Ortega-Ferreira Céline , Soret Perrine , Robin Gautier , Speca Silvia , Hubert Sandra , Le Gall Marianne , Desvaux Emiko , Jendoubi Manel , Saint-Paul Julie , Chadli Loubna , Chomel Agnès , Berger Sylvie , Nony Emmanuel , Neau Béatrice , Fould Benjamin , Licznar Anne , Levasseur Franck , Guerrier Thomas , Elouej Sahar , Courtade-Gaïani Sophie , Provost Nicolas , Nguyen The Quyen , Verdier Julien , Launay David , De Ceuninck Frédéric 
Published: August 2023

AbstractSystemic sclerosis (SSc) is an autoimmune, inflammatory and fibrotic disease with limited treatment options. Developing new therapies is therefore crucial to address patient needs. To this end, we focused on galectin-3 (Gal-3), a lectin known to be associated with several pathological processes seen in SSc. Using RNA sequencing of whole-blood samples in a cross-sectional cohort of 249 patients with SSc, Gal-3 and its interactants defined a strong transcriptomic fingerprint associated with disease severity, pulmonary and cardiac malfunctions, neutrophilia and lymphopenia. We developed new Gal-3 neutralizing monoclonal antibodies (mAb), which were then evaluated in a mouse model of hypochlorous acid (HOCl)-induced SSc. We show that two of these antibodies, D11 and E07, reduced pathological skin thickening, lung and skin collagen deposition, pulmonary macrophage content, and plasma interleukin-5 and -6 levels. Moreover, E07 changed the transcriptional profiles of HOCl-treated mice, resulting in a gene expression pattern that resembled that of control mice. Similarly, pathological pathways engaged in patients with SSc were counteracted by E07 in mice. Collectively, these findings demonstrate the translational potential of Gal-3 blockade as a therapeutic option for SSc.
Coronary heart disease prediction method fusing domain-adaptive transfer learning with graph convolutional networks (GCN)
Authors: Lin Huizhong , Chen Kaizhi , Xue Yutao , Zhong Shangping , Chen Lianglong , Ye Mingfang 
Published: August 2023

AbstractGraph convolutional networks (GCNs) have achieved impressive results in many medical scenarios involving graph node classification tasks. However, there are difficulties in transfer learning for graph representation learning and graph network models. Most GNNs work only in a single domain and cannot transfer the learned knowledge to other domains. Coronary Heart Disease (CHD) is a high-mortality disease, and there are non-public and significant differences in CHD datasets for current research, which makes it difficult to perform unified transfer learning. Therefore, in this paper, we propose a novel adversarial domain-adaptive multichannel graph convolutional network (DAMGCN) that can perform graph transfer learning on cross-domain tasks to achieve cross-domain medical knowledge transfer on different CHD datasets. First, we use a two-channel GCN model for feature aggregation using local consistency and global consistency. Then, a uniform node representation is generated for different graphs using an attention mechanism. Finally, we provide a domain adversarial module to decrease the discrepancies between the source and target domain classifiers and optimize the three loss functions in order to accomplish source and target domain knowledge transfer. The experimental findings demonstrate that our model performs best on three CHD datasets, and its performance is greatly enhanced by graph transfer learning.
Impact of vertical stratification on the 2020 spring bloom in the Yellow Sea
Authors: Kim Go-Un , Lee Jaeik , Kim Yong Sun , Noh Jae Hoon , Kwon Young Shin , Lee Howon , Lee Meehye , Jeong Jongmin , Hyun Myung Jin , Won Jongseok , Jeong Jin-Yong 
Published: August 2023

AbstractThe Yellow Sea is one of the world’s most abundant marine resources, providing food and economic benefits to the Korean and Chinese populations. In spring 2020, a decrease in the intensity of phytoplankton bloom was observed. While one study attributed this decline to a decrease in nutrient associated with the COVID-19 pandemic, our previous research proposed weakened thermal stratification accompanied by a surface cooling anomaly as the cause. However, the relationship between the marine environment and ecosystem has not been fully elucidated. Using observations and marine physical-biogeochemical model data, we identified the weakened stratification as a critical factor for suppressing the 2020 spring bloom. Intense vertical mixing hindered the accumulation of nutrient and chlorophyll-a concentrations within the euphotic zone, resulting in a diminished phytoplankton bloom. In contrast, reduced nitrate and phosphate concentrations in 2020 were insignificant compared to those in 2017–2019, despite the notable decline in PM2.5 in March 2020 due to COVID-19. In April 2020, nutrient levels fell within the range of interannual variability based on long-term observations, reflecting a negligible effect on the spring phytoplankton bloom. Our findings provide insight into the importance of marine physical factors on the phytoplankton biomass in the Yellow Sea.