bluuebunny/crossref_metadata_2025_split huggingface dataset:
CNL2ASP: Converting Controlled Natural Language Sentences into ASP
Authors: CARUSO SIMONE , DODARO CARMINE , MARATEA MARCO , MOCHI MARCO , RICCIO FRANCESCO 
Published: December 2023

AbstractAnswer set programming (ASP) is a popular declarative programming language for solving hard combinatorial problems. Although ASP has gained widespread acceptance in academic and industrial contexts, there are certain user groups who may find it more advantageous to employ a higher-level language that closely resembles natural language when specifying ASP programs. In this paper, we propose a novel tool, called CNL2ASP, for translating English sentences expressed in a controlled natural language (CNL) form into ASP. In particular, we first provide a definition of the type of sentences allowed by our CNL and their translation as ASP rules and then exemplify the usage of the CNL for the specification of both synthetic and real-world combinatorial problems. Finally, we report the results of an experimental analysis conducted on the real-world problems to compare the performance of automatically generated encodings with the ones written by ASP practitioners, showing that our tool can obtain satisfactory performance on these benchmarks.
Participatory approaches for water monitoring and harvesting: Case study from India
Authors: Chinnasamy Pennan , Gupta Meeta 
Published: December 2023

Abstract
North Gujarat in India currently extracts three billion cubic meters of groundwater per year, which is up to 95% of the groundwater resources available in the region. This unsustainable abstraction has led to changes in groundwater levels and created water scarcity in many parts of the region. To address these issues, integrated groundwater resource management is required, which should be driven by good quality and quantity of groundwater data. However, current groundwater data are scarce; thus, new, affordable monitoring approaches are necessary. Participatory and community-based monitoring involving citizen scientists provides an approach to complement existing government-run monitoring. This study demonstrates the feasibility of developing a large-scale groundwater level monitoring wells network by directly involving farmers in two agriculturally-dominated blocks in North Gujarat, India. First, long-term groundwater level data for government-monitored wells were analyzed, and the regions lacking monitoring were identified. Then a network of 43 farmers was established through the field survey, who were trained to provide groundwater level observations for their wells every month. The data collected through the field survey were then integrated with the data from the existing government monitoring programs to understand the groundwater dynamics in the region. Results for the post-monsoon season 2022 show that the groundwater levels in Unjha block (Mehsana district) have declined to more than 100 meters below ground level due to unsustainable pumping for irrigation. The evaluation of the participatory approach showed that concern for existing groundwater challenges, social inclusion and contribution to scientific knowledge were the top three reasons that motivated farmers to participate in this research. Of the total volunteering farmers, 71% have shown interest in providing long-term observations for up to 3 years, and 57% agreed to provide observations weekly. Additionally, 70% of the farmers agreed to engage fellow farmers in groundwater monitoring, and 50% agreed to train new farmers. Thus, this study shows that farmers can play an important role in improving the existing challenges of groundwater monitoring through participatory training, and the integration of primary and secondary data can lead to better decision-making regarding need for well construction, crop selection, recharge methods and pathways for sustainable groundwater management.
Personal Exposure to Source‐Specific Particulate Polycyclic Aromatic Hydrocarbons and Systemic Inflammation: A Cross‐Sectional Study of Urban‐Dwelling Older Adults in China
Authors: Xu Jia , Zhang Nan , Zhang Yujuan , Li Penghui , Han Jinbao , Gao Shuang , Wang Xinhua , Geng Chunmei , Yang Wen , Zhang Liwen , Han Bin , Bai Zhipeng 
Published: December 2023

AbstractEnvironmental exposure to ambient polycyclic aromatic hydrocarbons (PAHs) can disturb the immune response. However, the evidence on adverse health effects caused by exposure to PAHs emitted from specific sources among different vulnerable subpopulations is limited. In this cross‐sectional study, we aimed to evaluate whether exposure to source‐specific PAHs could increase systemic inflammation in older adults. The present study included community‐dwelling older adults and collected ﬁlter samples of personal exposure to PM2.5 during the winter of 2011. Blood samples were collected after the PM2.5 sample collection. We analyzed PM2.5 bound PAHs and serum inflammatory cytokines (interleukin (IL)1β, IL6, and tumor necrosis factor alpha levels. The Positive Matrix Factorization model was used to identify PAH sources. We used a linear regression model to assess the relative eﬀects of source‐specific PM2.5 bound PAHs on the levels of measured inflammatory cytokines. After controlling for confounders, exposure to PAHs emitted from biomass burning or diesel vehicle emission was significantly associated with increased serum inflammatory cytokines and systemic inflammation. These findings highlight the importance of considering exposure sources in epidemiological studies and controlling exposures to organic materials from specific sources.
Extremely Distant Magnetopause Locations Caused by Magnetosheath Jets
Authors: Němeček Z. , Šafránková J. , Grygorov K. , Mokrý A. , Pi G. , Aghabozorgi Nafchi M. , Němec F. , Xirogiannopoulou N. , Šimůnek J. 
Published: December 2023

AbstractMagnetopause position is controlled mainly by the solar wind dynamic pressure and north‐south interplanetary magnetic field component and these quantities are included in different empirical magnetopause models. We have collected about 50,000 of dayside magnetopause crossings observed by THEMIS in course of 2007–2019 and compared the observed magnetopause position with model prediction. The difference between observed and predicted magnetopause radial distance, Robs − Rmod is used for quantifying the model‐observation agreement. Its median values are well predicted for cases up to Robs ≈ 12 RE for all models but higher positive deviations are found for larger magnetopause distances, mainly under a nearly radial field and low dynamic pressure. The analysis reveals their connection with transient magnetopause displacements caused by strong sunward flows in the magnetosheath. We discuss the possible origin of the observed magnetosheath flow switching in terms of the interaction of magnetosheath jets with the magnetopause.
Identifying Perturbations That Tipped the Stratosphere Into a Sudden Warming During January 2013
Authors: Kent Chris , Scaife Adam A. , Seviour William J. M. , Dunstone Nick , Smith Doug , Smout‐Day Kerry 
Published: December 2023

AbstractWe present a new methodology demonstrating that specific small‐magnitude regional perturbations can cause large systematic responses in subseasonal predictions. We show this with ensemble forecasts of the January 2013 Sudden Stratospheric Warming (SSW) from an operational long‐range global prediction system. In forecast members which predict the SSW, tropospheric ridging over the North Atlantic is strengthened 10 days prior to the event. This subsequently enhances planetary wave forcing and weakens the stratospheric polar vortex. Transplanting tropospheric conditions in this region from “correct” to “incorrect” forecasts (and vice versa) significantly alters the SSW forecast probability. The occurrence of this SSW is therefore strongly controlled by the troposphere several days prior. Tipping more members into a sudden warming also significantly affects surface predictions the following month. Despite chaotic behavior of the climate system, small‐magnitude synoptic‐scale perturbations can drive different dynamical states and systematically impact medium and long‐range predictions.
Connection Between Chorus Wave Amplitude and Background Magnetic Field Inhomogeneity: A Parametric Study
Authors: Wu Zeyin , Huang Hua , Wu Yifan , Tao Xin , Katoh Yuto , Wang Xiaogang 
Published: December 2023

AbstractWhistler mode chorus waves frequently appear as discrete, repetitive, and quasi‐monochromatic emissions with frequency chirping. With different wave amplitude and frequency chirping rate, chorus waves have been observed not only in the magnetosphere of the Earth but also in the magnetospheres of other planets, such as Saturn and Jupiter. Motivated by understanding different properties of chorus waves at these planets using the recently proposed “Trap‐Release‐Amplify” (TaRA) model, we perform a parametric study using Particle‐In‐Cell simulations by varying background magnetic field inhomogeneity and the corresponding threshold hot electron number density. We show the consistency between simulation results and theoretical predictions for threshold hot electron number density, chorus chirping rate, and wave amplitude. Our results suggest the significant role of the background magnetic field inhomogeneity in affecting chorus wave properties, including its amplitude at different planets as predicted by the TaRA model.
Bayesian Inversion of Lithology and Liquid Phase Parameters From Seismic Velocity and Electrical Conductivity in the Crust and Uppermost Mantle
Authors: Kuwatani Tatsu , Nagata Kenji , Sakai Toshimoto , Iwamori Hikaru 
Published: December 2023

AbstractTo deeply understand various geodynamic processes, including volcanic activities and earthquakes, it is essential to extract detailed information about Earth materials, such as lithology and geofluid, from geophysical, petrological, and geochemical observations of Earth's interior. We developed a Bayesian probabilistic framework that can estimate the lithology and geofluid type (aqueous fluid or melt), geofluid amount (porosity), and parameters related to the fluid geometry (aspect ratio and critical fluid fraction related to connectivity) from P‐wave and S‐wave seismic velocities and electrical conductivity data obtained from geophysical tomography. By conducting synthetic inversion tests, we showed that methods based on a joint probability distribution, which simultaneously determines all parameters, sometimes fail to narrow the number of possible answers from 78 lithologies (e.g., basalt, granite, and eclogite) × two geofluid type (melt or aqueous fluid) candidate sets. This failure is derived directly from the difficult nature of inversion problems with relatively large data uncertainties. The proposed method uses a marginalization technique that first estimates lithology and geofluid type and then quantifies geofluid parameter values, which can narrow the probable lithology, geofluid type, and geofluid parameter sets in many cases. In addition, the computational cost of the proposed marginalization method is comparative to a former joint‐estimation method, which is theoretically identical to a previous heuristic method based on the least squares method. Therefore, the marginalization method is useful for geophysical data analyses that involve large amounts of observational data with relatively large uncertainties.
A Diffuse Interface Method for Earthquake Rupture Dynamics Based on a Phase‐Field Model
Authors: Hayek Jorge N. , May Dave A. , Pranger Casper , Gabriel Alice‐Agnes 
Published: December 2023

AbstractIn traditional modeling approaches, earthquakes are often depicted as displacement discontinuities across zero‐thickness surfaces embedded within a linear elastodynamic continuum. This simplification, however, overlooks the intricate nature of natural fault zones and may fail to capture key physical phenomena integral to fault processes. Here, we propose a diffuse interface description for dynamic earthquake rupture modeling to address these limitations and gain deeper insight into fault zones' multifaceted volumetric failure patterns, mechanics, and seismicity. Our model leverages a steady‐state phase‐field, implying time‐independent fault zone geometry, which is defined by the contours of a signed distance function relative to a virtual fault plane. Our approach extends the classical stress glut method, adept at approximating fault‐jump conditions through inelastic alterations to stress components. We remove the sharp discontinuities typically introduced by the stress glut approach via our spatially smooth, mesh‐independent fault representation while maintaining the method's inherent logical simplicity within the well‐established spectral element method framework. We verify our approach using 2D numerical experiments in an open‐source spectral element implementation, examining both a kinematically driven Kostrov‐like crack and spontaneous dynamic rupture in diffuse fault zones. The capabilities of our methodology are showcased through mesh‐independent planar and curved fault zone geometries. Moreover, we highlight that our phase‐field‐based diffuse rupture dynamics models contain fundamental variations within the fault zone. Dynamic stresses intertwined with a volumetrically applied friction law give rise to oblique plastic shear and fault reactivation, markedly impacting rupture front dynamics and seismic wave radiation. Our results encourage future applications of phase‐field‐based earthquake modeling.
Updating Biogenic Volatile Organic Compound (BVOC) Emissions With Locally Measured Emission Factors in South China and the Effect on Modeled Ozone and Secondary Organic Aerosol Production
Authors: Wang Peng , Zhang Yanli , Gong Haixing , Zhang Hongliang , Guenther Alex , Zeng Jianqiang , Wang Tao , Wang Xinming 
Published: December 2023

AbstractBiogenic volatile organic compounds (BVOCs) emitted from terrestrial plants contribute substantially to ozone (O3) and secondary organic aerosol (SOA) formation in the troposphere. Accurate estimation of BVOC emissions is highly challengeable with a variety of uncertainties, one of which is the use of default emission factors (EFs) particularly for underrepresented regions without local data. In this study, locally measured BVOC‐EFs in south China, a subtropical region with abundant vegetation, were used to update regional BVOC emissions as estimated by the Model of Emissions of Gases and Aerosols from Nature (MEGAN). These EFs were recently determined in situ with characterized dynamic chambers for the emissions of isoprene, monoterpenes, and sesquiterpenes from tree species. The Community Multiscale Air Quality (CMAQ) model was then employed to see how much the regional O3 and SOA production is altered with the updated BVOC emissions. Results revealed lower BVOC emission estimates in south China when using the localized EFs than the MEGAN default ones, particularly for sesquiterpenes with a notable average reduction rate of approximately 40%. Using the updated BVOC emissions improved model O3 predictions in all seasons when compared to surface O3 monitoring, yet the lower BVOC emissions resulted in modeled O3 and SOA concentrations decreased by up to −6 ppb and −1.5 μg m−3, respectively, throughout south China. This study highlights the significance of localized EFs in refining emission estimates and air quality predictions in regions with a wealth of vegetation.
Implementation of the Novel Duo‐Grid in GFDL's FV3 Dynamical Core
Authors: Mouallem Joseph , Harris Lucas , Chen Xi 
Published: December 2023

AbstractThe gnomonic cubed‐sphere grid has excellent accuracy and uniformity, but the “kink” in the coordinates at the cube edges in the halo region can leave an imprint of the cube in the solution, and requires special edge handling. To reduce grid imprinting, we implement the novel “Duo‐Grid” within the Geophysical Fluid Dynamics Laboratory's (GFDL) Finite‐Volume Cubed‐Sphere Dynamical Core (FV3). The Duo‐Grid remaps a cube face's data from neighboring face from kinked to natural locations along great circle lines using 1D piecewise linear interpolation. A 2D interpolation algorithm is used to fill correct data at the eight corners of the cubed‐sphere needed for FV3's 2D advection scheme. The Duo‐Grid was tested in idealized tests using the 2D shallow water solver and the 3D hydrostatic and non‐hydrostatic solvers. We found that error norms are greatly reduced and grid imprinting is practically eliminated when employing the Duo‐Grid. These results indicate that FV3's accuracy and robustness have improved.
A Systematic Role for Extreme Ocean‐Atmosphere Oscillations in the Development of Glacial Conditions Since the Mid Pleistocene Transition
Authors: Barker Stephen , Knorr Gregor 
Published: December 2023

AbstractWe introduce a new hypothesis concerning the role of internal climate dynamics in the non‐linear transitions from interglacial to glacial (IG‐G) state since the Mid Pleistocene Transition (MPT). These transitions encompass large and abrupt changes in atmospheric CO2, ice volume, and temperature that we suggest involve critical interactions between insolation and high amplitude oscillations in ocean/atmosphere circulation patterns. Specifically, we highlight the large amplitude of millennial‐scale climate oscillations across the transition from Marine Isotope Stage (MIS) 5 to 4, which we argue led to amplified cooling of the deep ocean and we demonstrate that analogous episodes of extreme cooling systematically preceded glacial periods of the last 800 kyr. We suggest that such cooling necessitates a reconfiguration of the deep ocean to avoid a density paradox between northern and southern‐sourced deep waters (SSW), which could be accomplished by increasing the relative volume and or salinity of SSW, thus providing the necessary storage capacity for the subsequent (delayed) and relatively abrupt drawdown of CO2. We therefore explain the transient decoupling of Antarctic temperature from CO2 across MIS 5/4 as a direct consequence of millennial activity at that time. We further show that similar climatic decoupling typically occurred during times of low obliquity and was a ubiquitous feature of IG‐G transitions over the past 800 kyr, producing the appearance of bimodality in records of CO2, benthic δ18O and others. Finally we argue that the apparent lack of bimodality in the pre‐MPT record of benthic δ18O implies that the dynamics associated with IG‐G transitions changed across the MPT.
De novo variants underlying monogenic syndromes with intellectual disability in a neurodevelopmental cohort from India
Authors: Pande Shruti , Majethia Purvi , Nair Karthik , Rao Lakshmi Priya , Mascarenhas Selinda , Kaur Namanpreet , do Rosario Michelle C. , Neethukrishna Kausthubham , Chaurasia Ankur , Hunakunti Bhagesh , Jadhav Nalesh , Xavier Sruthy , Kumar Jeevan , Bhat Vivekananda , Bhavani Gandham SriLakshmi , Narayanan Dhanya Lakshmi , Yatheesha B. L. , Patil Siddaramappa J. , Nampoothiri Sheela , Kamath Nutan , Aroor Shrikiran , Bhat Y Ramesh , Lewis Leslie E. , Sharma Suvasini , Bajaj Shruti , Sankhyan Naveen , Siddiqui Shahyan , Nayak Shalini S. , Bielas Stephanie , Girisha Katta Mohan , Shukla Anju 
Published: December 2023

AbstractThe contribution of de novo variants as a cause of intellectual disability (ID) is well established in several cohorts reported from the developed world. However, the genetic landscape as well as the appropriate testing strategies for identification of de novo variants of these disorders remain largely unknown in low-and middle-income countries like India. In this study, we delineate the clinical and genotypic spectrum of 54 families (55 individuals) with syndromic ID harboring rare de novo variants. We also emphasize on the effectiveness of singleton exome sequencing as a valuable tool for diagnosing these disorders in resource limited settings. Overall, 46 distinct disorders were identified encompassing 46 genes with 51 single-nucleotide variants and/or indels and two copy-number variants. Pathogenic variants were identified in CREBBP, TSC2, KMT2D, MECP2, IDS, NIPBL, NSD1, RIT1, SOX10, BRWD3, FOXG1, BCL11A, KDM6B, KDM5C, SETD5, QRICH1, DCX, SMARCD1, ASXL1, ASXL3, AKT3, FBN2, TCF12, WASF1, BRAF, SMARCA4, SMARCA2, TUBG1, KMT2A, CTNNB1, DLG4, MEIS2, GATAD2B, FBXW7, ANKRD11, ARID1B, DYNC1H1, HIVEP2, NEXMIF, ZBTB18, SETD1B, DYRK1A, SRCAP, CASK, L1CAM, and KRAS. Twenty-four of these monogenic disorders have not been previously reported in the Indian population. Notably, 39 out of 53 (74%) disease-causing variants are novel. These variants were identified in the genes mainly encoding transcriptional and chromatin regulators, serine threonine kinases, lysosomal enzymes, molecular motors, synaptic proteins, neuronal migration machinery, adhesion molecules, structural proteins and signaling molecules.
Precise control over gas-transporting channels in zeolitic imidazolate framework glasses
Authors: Smirnova Oksana , Hwang Seungtaik , Sajzew Roman , Ge Lingcong , Reupert Aaron , Nozari Vahid , Savani Samira , Chmelik Christian , Reithofer Michael R. , Wondraczek Lothar , Kärger Jörg , Knebel Alexander 
Published: December 2023

AbstractPorous metal–organic frameworks have emerged to resolve important challenges of our modern society, such as CO2 sequestration. Zeolitic imidazolate frameworks (ZIFs) can undergo a glass transition to form ZIF glasses; they combine the liquid handling of classical glasses with the tremendous potential for gas separation applications of ZIFs. Using millimetre-sized ZIF-62 single crystals and centimetre-sized ZIF-62 glass, we demonstrate the scalability and processability of our materials. Further, following the evolution of gas penetration into ZIF crystals and ZIF glasses by infrared microimaging techniques, we determine the diffusion coefficients and changes to the pore architecture on the ångström scale. The evolution of the material on melting and processing is observed in situ on different length scales by using a microscope-coupled heating stage and analysed microstructurally by transmission electron microscopy. Pore collapse during glass processing is further tracked by changes in the volume and density of the glasses. Mass spectrometry was utilized to investigate the crystal-to-glass transition and thermal-processing ability. The controllable tuning of the pore diameter in ZIF glass may enable liquid-processable ZIF glass membranes for challenging gas separations.
Autonomous chemical research with large language models
Authors: Boiko Daniil A. , MacKnight Robert , Kline Ben , Gomes Gabe 
Published: December 2023

AbstractTransformer-based large language models are making significant strides in various fields, such as natural language processing1–5, biology6,7, chemistry8–10 and computer programming11,12. Here, we show the development and capabilities of Coscientist, an artificial intelligence system driven by GPT-4 that autonomously designs, plans and performs complex experiments by incorporating large language models empowered by tools such as internet and documentation search, code execution and experimental automation. Coscientist showcases its potential for accelerating research across six diverse tasks, including the successful reaction optimization of palladium-catalysed cross-couplings, while exhibiting advanced capabilities for (semi-)autonomous experimental design and execution. Our findings demonstrate the versatility, efficacy and explainability of artificial intelligence systems like Coscientist in advancing research.