bluuebunny/crossref_metadata_2025_split huggingface dataset:
Heritable responses to stress in plants
Authors: Kovalchuk Igor 
Published: December 2023

Abstract
Most plants are adapted to their environments through generations of exposure to all elements. The adaptation process involves the best possible response to fluctuations in the environment based on the genetic and epigenetic make-up of the organism. Many plant species have the capacity to acclimate or adapt to certain stresses, allowing them to respond more efficiently, with fewer resources diverted from growth and development. However, plants can also acquire protection against stress across generations. Such a response is known as an intergenerational response to stress; typically, plants lose most of the tolerance in the subsequent generation when propagated without stress. Occasionally, the protection lasts for more than one generation after stress exposure and such a response is called transgenerational. In this review, we will summarize what is known about inter- and transgenerational responses to stress, focus on phenotypic and epigenetic events, their mechanisms and ecological and evolutionary meaning.
Low-Skilled Liberalizers: Support for Free Trade in Africa
Authors: Dolan Lindsay R. , Milner Helen V. 
Published: December 2023

AbstractDespite populist backlash against globalization in advanced industrialized countries, developing countries have recently sought to liberalize trade. To shed light on this phenomenon, we investigate mass attitudes toward free trade in thirty-six African countries. Using two rounds of Afrobarometer data and original survey data from Ghana and Uganda, we find that individuals hold views that are consistent with their economic self-interest. As factor endowment models predict for a sample of skill-scarce countries, low-skilled individuals are more likely than high-skilled individuals to support free trade. Moreover, the strongest negative effects of skill occur for the most skill-scarce countries in the sample and are driven by individuals in the labor force. Our results are robust to measuring variables more precisely in original surveys and controlling for other factors thought to shape attitudes. The findings indicate that previous evidence against factor endowment models may have partially resulted from inadequate data from the developing world.
Do Exchange Rates Influence Voting? Evidence from Elections and Survey Experiments in Democracies
Authors: Quinn Dennis P. , Sattler Thomas , Weymouth Stephen 
Published: December 2023

AbstractIntense debate surrounds the effects of trade on voting, yet less attention has been paid to how fluctuations in the real exchange rate may influence elections. A moderately overvalued currency enhances consumers’ purchasing power, yet extreme overvaluation threatens exports and economic growth. We therefore expect exchange rates to have a conditional effect on elections: when a currency is undervalued, voters will punish incumbents for further depreciations; yet when it is highly overvalued, they may reward incumbents for depreciation. We empirically explore our argument in three steps. First, we examine up to 412 elections in up to 59 democratic countries and show that voters generally punish depreciation in the real exchange rate when the currency is undervalued. We also find that at extremely high levels of currency overvaluation, voters sometimes reward incumbents for depreciation. A currency peg, especially in the eurozone, appears to insulate incumbents from these effects. In a second step, we explore the microfoundations of the election results through survey experiments in three advanced industrialized and two emerging market nations with different monetary and exchange rate policies and institutions. Respondents in countries with undervalued to mildly overvalued currencies disapprove of currency depreciations, whereas those facing a very highly overvalued currency favor depreciation. Third, we examine the mechanism of political competition in exchange rate policymaking and demonstrate that sustained undervaluation is rare in countries with strong political competition. Democratic governments have electoral incentives to avoid using undervalued currencies as a means of shielding workers from import competition.
Millet research status and prospects for alleviating food insecurity through a text-mining approach
Authors: Sahu Jagajjit , Chandra Tilak , Jaiswal Sarika , Iquebal Mir Asif , Kumar Dinesh 
Published: December 2023

AbstractIn view of the celebration of the ‘International Year of Millets,’ millets are popularizing sustainable agricultural output amid challenging climates and nourishing adequately as food and feed. The extent of scientific intervention is the foundation for designing, promoting and popularizing neglected crops on social platforms. Planning future directions and adaptive strategies largely require regular evaluation of research efforts to identify hotspots and research gaps, as identified in the present study by creating a robust text-mining approach that integrates scientometrics using PubMed citation data. Keyword mining reveals that India and China are the leading publication centres on millets, possibly due to their large proportion of cultivation and indigenous nature. It further reveals that the pearl millet is the predominant one, followed by foxtail and finger millet, suggesting that most research is confined to them only; however, other millets, still have a research gap in comparison. The word abiotic stress is associated with high frequency in millet research due to its adaptive nature amid climate change. Thematic representation explored the novel concept of millet's utility as a probiotic and millet bran to ensure nutrient–cereal properties based on the persistency of keywords throughput research progression; however, incurious consumption is associated with harmful ochratoxin. Bio-concept mining and knowledge graph generation divided the millet research output into four large domains, which provides a largely covered bio-concepts for millet research and co-concurrence of emerging bio-concepts to intense progress and finds an adequate literature gap to improve millet research for sustained growth and equilibrate biodiversity.
Canadian Health Care Providers’ Perspectives on Working with Older Homeless Adults in Outreach Settings
Authors: Sacco Veronica , Stolee Paul , MacEachen Ellen , Boscart Veronique 
Published: December 2023

AbstractService providers have a unique understanding of older homeless adults’ challenges and service needs. However, research on the experiences of health care providers (HCPs) who work with this population is limited. We aimed to gain a better understanding of the experiences (roles, challenges, and rewards) of HCPs who work with older homeless adults (age 50 and over) in outreach settings. We conducted individual semi-structured interviews with 10 HCPs who worked in these roles. Four themes emerged: (a) the client–provider relationship as an essential building block to HCPs’ work; (b) progression of care that acknowledges the “whole person”; (c) collaboration as integral to providers’ work; and (d) the importance of system navigation. Providers found their work personally and professionally fulfilling but were frustrated by system-level challenges. Findings can be used to identify strategies on how to further support providers in their roles and enhance service provision for older homeless individuals.
Product structure of graph classes with bounded treewidth
Authors: Campbell Rutger , Clinch Katie , Distel Marc , Gollin J. Pascal , Hendrey Kevin , Hickingbotham Robert , Huynh Tony , Illingworth Freddie , Tamitegama Youri , Tan Jane , Wood David R. 
Published: December 2023

AbstractWe show that many graphs with bounded treewidth can be described as subgraphs of the strong product of a graph with smaller treewidth and a bounded-size complete graph. To this end, define the underlying treewidth of a graph class
$\mathcal{G}$
to be the minimum non-negative integer
$c$
such that, for some function
$f$
, for every graph
$G \in \mathcal{G}$
there is a graph
$H$
with
$\textrm{tw}(H) \leqslant c$
such that
$G$
is isomorphic to a subgraph of
$H \boxtimes K_{f(\textrm{tw}(G))}$
. We introduce disjointed coverings of graphs and show they determine the underlying treewidth of any graph class. Using this result, we prove that the class of planar graphs has underlying treewidth
$3$
; the class of
$K_{s,t}$
-minor-free graphs has underlying treewidth
$s$
(for
$t \geqslant \max \{s,3\}$
); and the class of
$K_t$
-minor-free graphs has underlying treewidth
$t-2$
. In general, we prove that a monotone class has bounded underlying treewidth if and only if it excludes some fixed topological minor. We also study the underlying treewidth of graph classes defined by an excluded subgraph or excluded induced subgraph. We show that the class of graphs with no
$H$
subgraph has bounded underlying treewidth if and only if every component of
$H$
is a subdivided star, and that the class of graphs with no induced
$H$
subgraph has bounded underlying treewidth if and only if every component of
$H$
is a star.
A low-profile wideband circularly polarized metasurface antenna based on characteristic mode analysis
Authors: Chai Kun , Li Zhi , Zhao Yajuan , Han Liping , Han Guorui , Liu Yufeng 
Published: December 2023

AbstractA low-profile wideband circularly polarized (CP) metasurface antenna is demonstrated for C-band applications. The metasurface consists of 4 × 4 square patches with Z-shaped slots. Characteristic mode analysis is used to investigate the modal behavior of the metasurface, and a pair of degenerate modes is chosen as the operating modes. The CP radiation is realized by exciting a pair of degenerate modes of the metasurface through a slot antenna, which is used as a feed structure with a 90° phase difference. The CP bandwidth is further widened by combining the resonance modes of the metasurface and slot antenna. The measured results show that the −10 dB impedance bandwidth of the antenna is 3.47–4.76 GHz, and the 3 dB axial ratio bandwidth is 3.5–4.9 GHz with a peak gain of 6.9 dBic. Moreover, the antenna exhibits well left-hand CP radiation performances with a low profile of 0.046λ0.
Heterogeneous Processes in the Atmosphere of Mars and Impact on H2O2 and O3 Abundances
Authors: Daerden Frank , Crowley John N. , Neary Lori , Smith Michael D. , Loeffler Mark J. , Clancy R. Todd , Wolff Michael J. , Aoki Shohei , Sagawa Hideo 
Published: December 2023

AbstractCurrent models underestimate the highest observed ozone (O3) column densities on Mars. These estimates could be improved by including the uptake of odd hydrogen species (HOx) on water ice clouds, but the reported uptake coefficient of HO2 is likely overestimated for atmospheric conditions. This leaves a fundamental problem in Mars' atmospheric chemistry unsolved. Here, using the GEM‐Mars general circulation model, we explore a range of processes involving multiple phases (gas, adsorbed and solid) that may contribute to an alternative solution. First, we focus on hydrogen peroxide (H2O2) and discuss its physical states on Mars and its chemical impact. We also conjecture its photolytic destruction in ices with model simulations and Compact Reconnaissance Imaging Spectrometer for Mars observations. Then, we include in the model all relevant (for Mars) heterogeneous reactions, both on dust and water ice, recommended by the International Union of Pure and Applied Chemistry for terrestrial atmospheric studies. We find that only the uptake of HO2 and H2O2 on dust are efficient on Mars. Finally, we find that attenuation of sunlight by water ice clouds in the calculation of photolysis rates leads to increased O3 and H2O2 abundances below the ice clouds. The combination of the proposed processes leads to O3 increases without the need for strong uptake of HO2 on ice, but it remains difficult to find a good agreement with O3 and H2O2 observations on the global scale. We provide specific recommendations for future work in observations, laboratory experiments and modeling to advance our understanding of fundamental chemistry on Mars.
Influence of Vertical Hydrologic Exchange Flow, Channel Flow, and Biogeochemical Kinetics on CH4 Emissions From Rivers
Authors: Chen Kewei , Yang Shuai , Roden Eric E. , Chen Xingyuan , Chang Kuang‐Yu , Guo Zhilin , Liang Xiuyu , Ma Enze , Fan Linfeng , Zheng Chunmiao 
Published: December 2023

AbstractCH4 emissions from inland water are highly uncertain in the current global CH4 budget, especially for rivers and streams due to sparse measurements and the uncertainty of measurements caused by turbulent water flow. A previous study has revealed that vertical hydrologic exchange flow (VHEF) is the main regulator of CH4 emissions from riverbed sediments. However, to what extent the understanding obtained from the plot‐scale can be extended to the reach scale and basin scale remains unknown. To address this challenge, we developed a process‐based model to estimate CH4 flux at the air‐water interface using the attributes available in the national hydrography data set. It calculates the annual mean flux of VHEF, CH4 production in sediments, and CH4 transport in the river channel in a sequential manner. Model performance is evaluated by CH4 efflux observed at the Hanford reach of the Columbia River. We show that reach‐wise sediment hydrologic and biogeochemical conditions estimated from the national hydrography data set could serve as a good indicator of CH4 emissions from rivers. Aerobic methane oxidation and export to the downstream are the dominant ways of total CH4 loss for the large lowland river. The hotspots of CH4 emissions are likely to be at the reaches with fine sediments and slow channel velocity. This study demonstrates the possibility of quantifying CH4 emissions at the reach scale and the modeling framework has the potential to be extended to the basin scale to improve estimates of CH4 emissions from lotic inland water.
Predictors of early morbidity and mortality in newly diagnosed multiple myeloma: data from five randomized, controlled, phase III trials in 3700 patients
Authors: Mai Elias K. , Hielscher Thomas , Bertsch Uta , Salwender Hans J. , Zweegman Sonja , Raab Marc S. , Munder Markus , Pantani Lucia , Mancuso Katia , Brossart Peter , Beksac Meral , Blau Igor W. , Dürig Jan , Besemer Britta , Fenk Roland , Reimer Peter , van der Holt Bronno , Hänel Mathias , von Metzler Ivana , Graeven Ullrich , Müller-Tidow Carsten , Boccadoro Mario , Scheid Christof , Dimopoulos Meletios A. , Hillengass Jens , Weisel Katja C. , Cavo Michele , Sonneveld Pieter , Goldschmidt Hartmut 
Published: December 2023

AbstractEarly morbidity and mortality affect patient outcomes in multiple myeloma. Thus, we dissected the incidence and causes of morbidity/mortality during induction therapy (IT) for newly diagnosed multiple myeloma (NDMM), and developed/validated a predictive risk score. We evaluated 3700 transplant-eligible NDMM patients treated in 2005–2020 with novel agent-based triplet/quadruplet IT. Primary endpoints were severe infections, death, or a combination of both. Patients were divided in a training (n = 1333) and three validation cohorts (n = 2367). During IT, 11.8%, 1.8%, and 12.5% of patients in the training cohort experienced severe infections, death, or both, respectively. Four major, baseline risk factors for severe infection/death were identified: low platelet count (<150/nL), ISS III, higher WHO performance status (>1), and age (>60 years). A risk score (1 risk factor=1 point) stratified patients in low (39.5%; 0 points), intermediate (41.9%; 1 point), and high (18.6%; ≥2 points) risk. The risk for severe infection/death increased from 7.7% vs. 11.5% vs. 23.3% in the low- vs. intermediate- vs. high-risk groups (p < 0.001). The risk score was independently validated in three trials incorporating quadruplet IT with an anti-CD38 antibody. Our analyses established a robust and easy-to-use score to identify NDMM patients at risk of severe infection/death, covering the latest quadruplet induction therapies. Trial registrations: HOVON-65/GMMG-HD4: EudraCT No. 2004-000944-26. GMMG-MM5: EudraCT No. 2010-019173-16. GMMG-HD6: NCT02495922. EMN02/HOVON-95: NCT01208766. GMMG-HD7: NCT03617731.
Periodontitis salivary microbiota exacerbates colitis-induced anxiety-like behavior via gut microbiota
Authors: Qian Jun , Lu Jiangyue , Cheng Shuyu , Zou Xihong , Tao Qing , Wang Min , Wang Nannan , Zheng Lichun , Liao Wenzheng , Li Yanfen , Yan Fuhua 
Published: December 2023

AbstractThe gut–brain axis is a bidirectional communication system between the gut and central nervous system. Many host-related factors can affect gut microbiota, including oral bacteria, making the brain a vulnerable target via the gut–brain axis. Saliva contains a large number of oral bacteria, and periodontitis, a common oral disease, can change the composition of salivary microbiota. However, the role and mechanism of periodontitis salivary microbiota (PSM) on the gut–brain axis remain unclear. Herein, we investigated the nature and mechanisms of this relationship using the mice with dextran sulfate sodium salt (DSS)-induced anxiety-like behavior. Compared with healthy salivary microbiota, PSM worsened anxiety-like behavior; it significantly reduced the number of normal neurons and activated microglia in DSS mice. Antibiotic treatment eliminated the effect of PSM on anxiety-like behavior, and transplantation of fecal microbiota from PSM-gavaged mice exacerbated anxiety-like behavior. These observations indicated that the anxiety-exacerbating effect of PSM was dependent on the gut microbiota. Moreover, the PSM effect on anxiety-like behavior was not present in non-DSS mice, indicating that DSS treatment was a prerequisite for PSM to exacerbate anxiety. Mechanistically, PSM altered the histidine metabolism in both gut and brain metabolomics. Supplementation of histidine-related metabolites had a similar anxiety-exacerbating effect as that of PSM, suggesting that histidine metabolism may be a critical pathway in this process. Our results demonstrate that PSM can exacerbate colitis-induced anxiety-like behavior by directly affecting the host gut microbiota, emphasizing the importance of oral diseases in the gut–brain axis.
Error-mitigated quantum simulation of interacting fermions with trapped ions
Authors: Chen Wentao , Zhang Shuaining , Zhang Jialiang , Su Xiaolu , Lu Yao , Zhang Kuan , Qiao Mu , Li Ying , Zhang Jing-Ning , Kim Kihwan 
Published: December 2023

AbstractQuantum error mitigation has been extensively explored to increase the accuracy of the quantum circuits in noisy-intermediate-scale-quantum (NISQ) computation, where quantum error correction requiring additional quantum resources is not adopted. Among various error-mitigation schemes, probabilistic error cancellation (PEC) has been proposed as a general and systematic protocol that can be applied to numerous hardware platforms and quantum algorithms. However, PEC has only been tested in two-qubit systems and a superconducting multi-qubit system by learning a sparse error model. Here, we benchmark PEC using up to four trapped-ion qubits. For the benchmark, we simulate the dynamics of interacting fermions with or without spins by applying multiple Trotter steps. By tomographically reconstructing the error model and incorporating other mitigation methods such as positive probability and symmetry constraints, we are able to increase the fidelity of simulation and faithfully observe the dynamics of the Fermi–Hubbard model, including the different behavior of charge and spin of fermions. Our demonstrations can be an essential step for further extending systematic error-mitigation schemes toward practical quantum advantages.
Georeferenced dataset of maritime piracy in the Gulf of Guinea from 2010 to 2021
Authors: Moura Ricardo , Pessanha Santos Nuno , Rocha André , Lobo Victor , de Castro Neto Miguel 
Published: December 2023

AbstractPiracy has been a global concern and a threat to the safety of people performing maritime trade around the globe. Since ancient times maritime piracy has been a common practice that, unfortunately, has not ended in the current days. A georeferenced dataset providing the position, meteorologic conditions, and a description of the occurrence can provide essential information for analyzing this global phenomenon. The dataset focuses on the Gulf of Guinea (GoG) as an area dominated by corruption and weak supervision capacity by the local authorities. The time interval considered in this paper is between 2010 and 2021. Using this simple dataset, it is possible to analyze attributes such as when the piracy occurred or if the illegal activity involved deaths or kidnapping. The accuracy of the data was guaranteed by cross-referencing data sources, so we have 595 pirate attacks accurately described. This dataset can easily be used for data mining, allowing further analysis of the patterns and trends of pirate attacks in the GoG over time.
A global land cover training dataset from 1984 to 2020
Authors: Stanimirova Radost , Tarrio Katelyn , Turlej Konrad , McAvoy Kristina , Stonebrook Sophia , Hu Kai-Ting , Arévalo Paulo , Bullock Eric L. , Zhang Yingtong , Woodcock Curtis E. , Olofsson Pontus , Zhu Zhe , Barber Christopher P. , Souza Carlos M. , Chen Shijuan , Wang Jonathan A. , Mensah Foster , Calderón-Loor Marco , Hadjikakou Michalis , Bryan Brett A. , Graesser Jordan , Beyene Dereje L. , Mutasha Brian , Siame Sylvester , Siampale Abel , Friedl Mark A. 
Published: December 2023

AbstractState-of-the-art cloud computing platforms such as Google Earth Engine (GEE) enable regional-to-global land cover and land cover change mapping with machine learning algorithms. However, collection of high-quality training data, which is necessary for accurate land cover mapping, remains costly and labor-intensive. To address this need, we created a global database of nearly 2 million training units spanning the period from 1984 to 2020 for seven primary and nine secondary land cover classes. Our training data collection approach leveraged GEE and machine learning algorithms to ensure data quality and biogeographic representation. We sampled the spectral-temporal feature space from Landsat imagery to efficiently allocate training data across global ecoregions and incorporated publicly available and collaborator-provided datasets to our database. To reflect the underlying regional class distribution and post-disturbance landscapes, we strategically augmented the database. We used a machine learning-based cross-validation procedure to remove potentially mis-labeled training units. Our training database is relevant for a wide array of studies such as land cover change, agriculture, forestry, hydrology, urban development, among many others.
A dataset of proteomic changes during human heat stress and heat acclimation
Authors: Gagnon Daniel , Barry Hadiatou , Barhdadi Amina , Oussaid Essaid , Mongrain Ian , Lemieux Perreault Louis-Philippe , Dubé Marie-Pierre 
Published: December 2023

AbstractHotter climates have important impacts on human health and performance. Yet, the cellular and molecular responses involved in human heat stress and acclimation remain understudied. This dataset includes physiological measurements and the plasma concentration of 2,938 proteins collected from 10 healthy adults, before and during passive heat stress that was performed both prior to and after a 7-day heat acclimation protocol. Physiological measurements included body temperatures, sweat rate, cutaneous vascular conductance, blood pressure, and skin sympathetic nerve activity. The proteomic dataset was generated using the Olink Explore 3072 assay, enabling a high-multiplex antibody-based assessment of protein changes based on proximity extension assay technology. The data need to be interpreted in the context of the moderate level of body hyperthermia attained and the specific demographic of young, healthy adults. We have made this dataset publicly available to facilitate research into the cellular and molecular mechanisms involved in human heat stress and acclimation, crucial for addressing the health and performance challenges posed by rising temperatures.