Ia Models Research Articles

Clinical value of aortic arch morphology in transfemoral TAVR: artificial intelligence evaluation.

The impact of aortic arch (AA) morphology on the management of the procedural details and the clinical outcomes of the transfemoral artery (TF)-transcatheter aortic valve replacement (TAVR) has not been evaluated. The goal of this study was to evaluate the AA morphology of patients who had TF-TAVR using an artificial intelligence algorithm and then to evaluate its predictive value for clinical outcomes. A total of 1480 consecutive patients undergoing TF-TAVR using a new-generation transcatheter heart valve at 12 institutes were included in this retrospective study. The AA measurements were evaluated by deep learning, and then the approach index (IA) was determined. The machine learning algorithm was used to construct the predictive model and was validated externally. The area under the curve of the IA model using random forest and logistic regression was 0.675 [95% confidence interval (CI): 0.586-0.764] and 0.757 (95% CI: 0.665-0.849), respectively. The IA model was validated externally, and consistent distinctions were obtained. After we used a generalized propensity score matching method for continuous exposure, the IA was the strongest correlation factor for major procedural events (odds ratio: 3.87; 95% CI: 2.13-7.59, P < 0.001). When leaflet morphology or transcatheter heart valve type was an interactive item with IA, neither of them was statistically significant in terms of clinical outcomes. IA may be used to identify the impact of AA morphology on procedural and clinical outcomes in patients having TF-TAVR and to help to predict the procedural complications.

P4HA2 knockdown prevents the progression of intracranial aneurysm by inducing prolyl hydroxylation of YAP1.

Prolyl 4-hydroxylase subunit alpha 2 (P4HA2), a key enzyme modulating the post-transcription of proteins, was reported to be a causative gene in IA. Nevertheless, the exact function and mechanism of P4HA2 in the formation and rupture of IA is elusive. The current study first explored the expression of P4HA2 and its association with the clinicopathological demonstrations in patients with IA. In addition, an in vitro model of IA was established using H2O2 to stimulate vascular smooth muscle cells (VSMCs). The behaviors of treated VSMCs were evaluated using CCK-8, Wound healing, and Transwell assays. The expression of genes was detected by RT-qPCR and Western blot. Interaction between genes was confirmed using Luciferase Reporter assay and Co-immunoprecipitation (Co-IP) assay. Our results revealed that P4HA2 expression was upregulated in IA, especially ruptured IA; high P4HA2 expression correlates with unfavorable clinicopathological parameters. Through the in vitro experiments, it was discovered that P4HA2 knockdown rescued VSMCs from H2O2-induced viability impairment, enhancement in migration and apoptosis, switch from contractile phenotype, and augmentation of oxidative stress and inflammation. Mechanistically, P4HA2 was found to trigger the prolyl hydroxylation of YAP1 to negatively regulate the transcriptional activity of YAP1 in H2O2-challenged VSMCs. The effect of P4HA2 on H2O2-challenged VSMCs could be annulled by the mutation of YAP1 hydroxylation sites. In summary, P4HA2 served as a contributing factor during IA progression through its suppression on YAP1 activity by prolyl hydroxylation.

Hawai‘i Supernova Flows: a peculiar velocity survey using over a Thousand Supernovae in the near-infrared

ABSTRACT We introduce the Hawai‘i Supernova Flows project and present summary statistics of the first 1217 astronomical transients observed, 668 of which are spectroscopically classified Type Ia Supernovae (SNe Ia). Our project is designed to obtain systematics-limited distances to SNe Ia while consuming minimal dedicated observational resources. To date, we have performed almost 5000 near-infrared (NIR) observations of astronomical transients and have obtained spectra for over 200 host galaxies lacking published spectroscopic redshifts. In this survey paper, we describe the methodology used to select targets, collect/reduce data, calculate distances, and perform quality cuts. We compare our methods to those used in similar studies, finding general agreement or mild improvement. Our summary statistics include various parametrizations of dispersion in the Hubble diagrams produced using fits to several commonly used SN Ia models. We find the lowest dispersions using the SNooPy package’s EBV_model2, with a root mean square deviation of 0.165 mag and a normalized median absolute deviation of 0.123 mag. The full utility of the Hawai‘i Supernova Flows data set far exceeds the analyses presented in this paper. Our photometry will provide a valuable test bed for models of SN Ia incorporating NIR data. Differential cosmological studies comparing optical samples and combined optical and NIR samples will have increased leverage for constraining chromatic effects like dust extinction. We invite the community to explore our data by making the light curves, fits, and host galaxy redshifts publicly accessible.

The effect of rotationality on nonlinear shear flow of polymer melts and solutions

By considering the rotationality of shear flow, we distinguish between tube segments created by reptation before the inception of shear flow and those created during flow. Tube segments created before inception of shear flow experience both stretch and orientation, while tube segments created after inception of flow are not stretched, but are only aligned in the flow direction. Based on this idea, the Rotation Zero Stretch (RZS) model allows for a quantitative description of the start-up of shear flow and stress relaxation after step-shear strain experiments, in agreement with data of polystyrene long/short blends and corresponding polystyrene 3-arm star polymers investigated by Liu et al. (Polymer 2023, 281:126125), as well as the shear viscosity data of poly(propylene carbonate) melts reported by Yang et al. (Nihon Reoroji Gakkaishi 2022, 50:127–135). In the limit of steady-state shear flow, the RZS model converges to the Doi-Edwards IA model, which quantitatively describes the steady-state shear viscosity of linear polymer melts and long/short blends. The assumption of “non-stretching” of tube segments created during rotational flow is therefore in agreement with the available experimental evidence. Three-arm star polymers behave in a similar way as corresponding blends of long and short polymers confirming the solution effect of the short arm in asymmetric stars. The analysis of step-shear strain experiments reveals that stress relaxation is at first dominated by stretch relaxation, followed at times larger than the Rouse stretch relaxation time by relaxation of orientation as described by the damping function of the Doi-Edwards IA model. The RZS model does not require any nonlinear-viscoelastic parameter, but relies solely on the linear-viscoelastic relaxation modulus and the Rouse stretch relaxation time.Graphical

Combined interaction of fungicides binary mixtures: experimental study and machine learning-driven QSAR modeling

Fungicide mixtures are an effective strategy in delaying the development of fungicide resistance. In this research, a fixed ratio ray design method was used to generate fifty binary mixtures of five fungicides with diverse modes of action. The interaction of these mixtures was then analyzed using CA and IA models. QSAR modeling was conducted to assess their fungicidal activity through multiple linear regression (MLR), support vector machine (SVM), and artificial neural network (ANN). Most mixtures exhibited additive interaction, with the CA model proving more accurate than the IA model in predicting fungicidal activity. The MLR model showed a good linear correlation between selected theoretical descriptors by the genetic algorithm and fungicidal activity. However, both ML-based models demonstrated better predictive performance than the MLR model. The ANN model showed slightly better predictability than the SVM model, with R2 and R2cv at 0.91 and 0.81, respectively. For external validation, the R2test value was 0.845. In contrast, the SVM model had values of 0.91, 0.78, and 0.77 for the same metrics. In conclusion, the proposed ML-based model can be a valuable tool for developing potent fungicidal mixtures to delay fungicidal resistance emergence.

Ground-based and JWST Observations of SN 2022pul. II. Evidence from Nebular Spectroscopy for a Violent Merger in a Peculiar Type Ia Supernova

We present an analysis of ground-based and JWST observations of SN 2022pul, a peculiar “03fg-like” (or “super-Chandrasekhar”) Type Ia supernova (SN Ia), in the nebular phase at 338 days postexplosion. Our combined spectrum continuously covers 0.4–14 μm and includes the first mid-infrared spectrum of a 03fg-like SN Ia. Compared to normal SN Ia 2021aefx, SN 2022pul exhibits a lower mean ionization state, asymmetric emission-line profiles, stronger emission from the intermediate-mass elements (IMEs) argon and calcium, weaker emission from iron-group elements (IGEs), and the first unambiguous detection of neon in a SN Ia. A strong, broad, centrally peaked [Ne ii] line at 12.81 μm was previously predicted as a hallmark of “violent merger” SN Ia models, where dynamical interaction between two sub-M Ch white dwarfs (WDs) causes disruption of the lower-mass WD and detonation of the other. The violent merger scenario was already a leading hypothesis for 03fg-like SNe Ia; in SN 2022pul it can explain the large-scale ejecta asymmetries seen between the IMEs and IGEs and the central location of narrow oxygen and broad neon. We modify extant models to add clumping of the ejecta to reproduce the optical iron emission better, and add mass in the innermost region (<2000 km s−1) to account for the observed narrow [O i] λ λ6300, 6364 emission. A violent WD–WD merger explains many of the observations of SN 2022pul, and our results favor this model interpretation for the subclass of 03fg-like SNe Ia.

IA model for the creation of automatic and personalized health literacy plans for home care services and protocol for its validation

Background: Health Literacy (HL) is considered a social determinant of health with a direct and significant impact on health-related quality of life, especially in groups of elderly, polymedicated or chronically ill persons. According to the WHO, HL implies achieving a level of knowledge, personal skills and confidence that allows the adoption of measures to improve health through a change in lifestyle. It is a concept that combines elements of health and education. HL is the result of health education. In fact, a poor understanding of health recommendations or instructions is related to poor disease self-management and limited use of preventive resources. Furthermore, a low level of HL translates into an increase in (a) avoidable hospitalizations, (b) healthcare costs and (c) mortality rates. Artificial intelligence (AI) can help create personalized HL plans for each patient automatically. Moreover, thanks to digital education platforms these plans can be delivered and monitored remotely and digitally, reducing the resource of professional hours. The application of AI in health literacy is especially interesting in home health services, where the resources of professionals are scarce and care falls mainly on the family and the patient him/herself.&#x0D; Aim: The aim of this study is to develop an IA model for the creation of automatic and personalized HL plans for home care settings that can be consumed by families through a digital tool. The protocol for validation of the HL plans created by the model is also presented.&#x0D; Method: At the beginning, (1) a comprehensive geriatric assessment is performed that identifies the needs and capabilities of the care ecosystem (patient-caregiver) in a model of comprehensive person-centered care in the home care setting. (2) After analysis of the data collected in the assessment using validated diagnostic algorithms the IA model automatically generates an individualized training itinerary HL plan adapted to each user profile. (3) Using nursing indicators defined in the NNN taxonomy (NANDA, NOC, NIC) we measure at the beginning and at the end of the HL plan: (a) the knowledge acquired; (b) the change in behavior/behavior and (c) objective results of the health status.&#x0D; Main Results: We present an AI model for automated and scalable HL plan creation for home care settings. This model has the potential to improve the HL of the 65+ population (chronicity, complexity, multi-pathology, dependency, frailty, pre-frailty or autonomy) and their informal caregiving ecosystem (non-professional caregivers) in the home setting, especially if long-term care is present. The learning programs created for the HL plan were carried out under a rigorous protocol based on criteria of accessibility and scientific evidence.&#x0D; Conclusions: Thanks to the protocol, it will be possible to validate the impact of the HL plans created by the IA model on both the patient and the caregiver. The IA model is currently in the process of validation but shows promising results in reducing the time spent on direct intervention by professionals and improving the population's accessibility to HL plans thanks to the IA model.

Implications for the explosion mechanism of Type Ia supernovae from their late-time spectra

ABSTRACT Late-time spectra of Type Ia supernovae (SNe Ia) are important in clarifying the physics of their explosions, as they provide key clues to the inner structure of the exploding white dwarfs. We examined late-time optical spectra of 36 SNe Ia, including five from our own project (SNe 2019np, 2019ein, 2021hpr, 2021wuf, and 2022hrs), with phase coverage of ∼200 to ∼400 d after maximum light. At this late phase, the outer ejecta have become transparent and the features of inner iron-group elements emerge in the spectra. Based on multicomponent Gaussian fits and reasonable choices for the pseudo-continuum around Ni and Fe emission features, we get reliable estimates of the Ni to Fe ratio, which is sensitive to the explosion models of SNe Ia. Our results show that the majority (about 67 per cent) of our SNe Ia are more consistent with the sub-Chandrasekhar-mass (i.e. double-detonation) model, although they could be affected by evolutionary or ionization effects. Moreover, we find that the Si ii λ6355 velocity measured around the time of maximum light tends to increase with the Ni to Fe ratio for the subsample with either redshifted or blueshifted nebular velocities, suggesting that progenitor metallicity might play an important role in accounting for the observed velocity diversity of SNe Ia.

Systematic Investigation of Very-early-phase Spectra of Type Ia Supernovae

It has been widely accepted that Type Ia supernovae (SNe Ia) are thermonuclear explosions of a CO white dwarf. However, the natures of the progenitor system(s) and explosion mechanism(s) are still unclarified. Thanks to the recent development of transient observations, they are now frequently discovered shortly after the explosion, followed by rapid spectroscopic observations. In this study, by modeling very-early-phase spectra of SNe Ia, we try to constrain the explosion models of SNe Ia. By using the Monte Carlo radiation transfer code, TARDIS, we estimate the properties of their outermost ejecta. We find that the photospheric velocity of normal-velocity supernovae (NV SNe) in the first week is ∼15,000 km s−1. The outer velocity, to which the carbon burning extends, spans the range between ∼20,000 and 25,000 km s−1. The ejecta density of NV SNe also shows a large diversity. For high-velocity supernovae (HV SNe) and 1999aa-like SNe, the photospheric velocity is higher, ∼20,000 km s−1. They have different photospheric densities, with HV SNe having higher densities than 1999aa-like SNe. For all these types, we show that the outermost composition is closely related to the outermost ejecta density; the carbon-burning layer and the unburnt carbon layer are found in the higher-density and lower-density objects, respectively. This finding suggests that there might be two sequences, the high-density and carbon-poor group (HV SNe and some NV SNe) and the low-density and carbon-rich group (1999aa-like and other NV SNe), which may be associated with different progenitor channels.

Peculiar Spectral Evolution of the Type I Supernova 2019eix: A Possible Double Detonation from a Helium Shell on a Sub-Chandrasekhar-mass White Dwarf

We present photometric and spectroscopic data for the nearby Type I supernova (SN Ia) 2019eix (originally classified as an SN Ic), from the day of its discovery up to 100 days after maximum brightness. Before maximum light, SN 2019eix resembles a typical SN Ic, albeit lacking the usual O i feature. Its light curve is similar to the typical SN Ic with decline rates (ΔM 15,V = 0.84) and absolute magnitude M V = −18.35. However, after maximum light, this SN has unusual spectroscopic features, a large degree of line blending, significant line blanketing in the blue (λ < 5000 Å), and strong Ca ii absorption features during and after peak brightness. These unusual spectral features are similar to models of subluminous thermonuclear explosions, specifically double-detonation models of SNe Ia. Photometrically, SN 2019eix appears to be somewhat brighter with slower decline rates than other double-detonation candidates. We modeled the spectra using the radiative-transfer code TARDIS using SN 1994I (an SN Ic) as a base model to see whether we could reproduce the unusual features of SN 2019eix and found them to be consistent with the exception of the O i feature. We also compared SN 2019eix with double-detonation models and found them to best match the observations of SN 2019eix, but failed to reproduce its full photometric and spectroscopic evolution.

New solar radiation transmittance models of transparent envelope based on spectral splitting and their influence on building heat gain

Climate change and the energy crisis have led to increasing attention to building energy efficiency worldwide, and transparent envelopes are more critical as a weak link in building energy efficiency. However, there is a lack of quantitative research on the spectral transmittance properties of transparent envelopes. In this paper, the spectral transmittance of transparent envelopes is quantitatively studied using the controlled variable method. The transmittance calculation formula in the existing standard is modified. Firstly, five types of transparent envelopes commonly used are selected, and their transmittance to the full solar spectrum is studied to establish a transmittance model for different wavelengths. The study also focuses on the 300 nm–1100nm waveband and establishes a solar radiation transmittance benchmark model (SRTB model) based on single-pane clear glass. Secondly, the solar radiation transmittance at different wavelengths is tested by considering both the glass material and the inclination angle, and a solar radiation transmittance modified model (SRTM model) that can be modified to the SRTB model is established. Thirdly, the variation between the incident angle and transmittance is investigated, and the solar radiation transmittance-incident angle model (SRT - IA model) is developed. The results show that deviations between the fixed transmittance and SRT - IA model can reach a maximum of more than 10% for incident angles of less than 60°. Finally, the variation in radiation heat gain due to the SRT - IA model and fixed transmittance is compared in China based on typical meteorological year data. The research conclusion can provide a more precise assessment of the building heat gain from transparent envelopes and then evaluate the building energy consumption reasonably, and provide a theoretical basis for the full-spectrum utilization efficiency of solar radiation.

From Puppies to adults: In vivo editing of hepatocytes in a canine model of glycogen storage disease type Ia

From Puppies to adults: In vivo editing of hepatocytes in a canine model of glycogen storage disease type Ia

Improving Access to Diagnostic Evaluations for Developmental Disabilities Through an Initial Assessment Model.

This study aimed to evaluate a novel model of care to improve access to diagnostic evaluations for autism spectrum disorder and/or developmental delays for school-age children. An "initial assessment" (IA) model for children aged 7 to 9 years was implemented at a large regional pediatric hospital. Referral patterns and the number of patients evaluated with the IA model were obtained through the electronic health record (EHR). Referral patterns from the EHR were checked against clinician surveys. Total IA volume had a strong negative association with school-age WL volume ( r (22) = -0.92, p < 0.001), indicating that as IA volume increased, the WL volume declined. Evaluation of referral patterns after IAs revealed that approximately 1 in 3 children seen for IA did not require further evaluation and could be immediately removed from the WL. Results indicate that implementation of a novel IA model was strongly associated with a decrease in WL volume for neurodevelopmental evaluations of school-age children. These findings support a "right-fit" approach to optimize clinical resources and improve access to neurodevelopmental evaluations.

Toxicity of fipronil and 2,4-D pesticides in Daphnia similis: a multiple endpoint approach

In Brazil, among the pesticides widely applied simultaneously in sugarcane monocultures are the Regent® 800 WG insecticide (active ingredient (a.i.) fipronil) and the DMA® 806 BR herbicide (a.i. 2,4-D). Thus, this study aimed to investigate, through different endpoints, the effects of the fipronil and 2,4-D pesticides, isolated and as mixtures, on the cladoceran Daphnia similis. To do this, acute toxicity tests were carried out with the compounds acting in isolation and in mixture, where the survival of the organisms was evaluated, and chronic toxicity tests with the isolated compounds, where reproduction and maternal and neonatal body length were evaluated. In this study, the physiological endpoints of D. similis were also analyzed, through the analysis of feeding rates (filtration and ingestion) in exposure and post-exposure scenarios, in order to verify the cladoceran food recovery capacity. In addition, D. similis data were compared with other species when exposed to the studied pesticides, using species sensitivity distribution curves. Acute toxicity tests of the fipronil and 2,4-D showed an average EC50-48h of 66.68μg a.i./L and 327.07mg a.i./L, respectively. In both cases, D. similis showed lower sensitivity compared to other species. For the mixture test, the evaluation by the IA model (independent action) and deviation DR (dose ratio dependent) indicated the occurrence of mostly antagonistic effects. The chronic test with fipronil showed a decrease in the fecundity of the organism at a concentration of 16μg a.i./L, a concentration already found in aquatic environments. For 2,4-D, no significant differences were observed for reproduction at the concentrations tested. Regarding the maternal body length, there were no significant changes when D. similis were exposed to both fipronil and 2,4-D, but these differences were observed in the body length of the neonates only for 2,4-D. There were no significant changes in the feeding rates of the organisms when exposed to both pesticides.

Photometric study of the late-time near-infrared plateau in Type Ia supernovae

ABSTRACTWe present an in-depth study of the late-time near-infrared plateau in Type Ia supernovae (SNe Ia), which occurs between 70 and 500 d. We double the existing sample of SNe Ia observed during the late-time near-infrared plateau with new observations taken with the Hubble Space Telescope, Gemini, New Technology Telescope, the 3.5-m Calar Alto Telescope, and the Nordic Optical Telescope. Our sample consists of 24 nearby SNe Ia at redshift &amp;lt; 0.025. We are able to confirm that no plateau exists in the Ks band for most normal SNe Ia. SNe Ia with broader optical light curves at peak tend to have a higher average brightness on the plateau in J and H, most likely due to a shallower decline in the preceding 100 d. SNe Ia that are more luminous at peak also show a steeper decline during the plateau phase in H. We compare our data to state-of-the-art radiative transfer models of nebular SNe Ia in the near-infrared. We find good agreement with the sub-Mch model that has reduced non-thermal ionization rates, but no physical justification for reducing these rates has yet been proposed. An analysis of the spectral evolution during the plateau demonstrates that the ratio of [Fe ii] to [Fe iii] contribution in a near-infrared filter determines the light curve evolution in said filter. We find that overluminous SNe decline slower during the plateau than expected from the trend seen for normal SNe Ia.

Ecotoxicological and biochemical effects of a binary mixture of pesticides on the marine diatom Thalassiosira weissflogii in a scenario of global warming

Under the current scenario of global warming, it is ecologically relevant to understand how increased temperature influences the combined toxicity of pesticides to aquatic species. Hence, this work aims to: a) determine the temperature effect (15 °C, 20 °C and 25 °C) on the toxicity of two pesticides (oxyfluorfen and Copper (Cu)), on the growth of Thalassiosira weissflogii; b) assess whether temperature affects the type of toxicity interaction between these chemicals; and c) assess the temperature effect on biochemical responses (fatty acids (FA) and sugar profiles) of the pesticides on T. weissflogii. Temperature increased the tolerance of the diatoms to the pesticides with EC50 values between 3.176 and 9.929 μg L−1 for oxyfluorfen and 42.50–230.75 μg L−1 for Cu, respectively, at 15 °C and 25 °C. The mixtures toxicity was better described by the IA model, but temperature altered the type of deviation from dose ratio (15 °C and 20 °C) to antagonism (25 °C). Temperature, as well as the pesticide concentrations, affected the FA and sugar profiles. Increased temperature increased saturated FA and decreased unsaturated FA; it also affected the sugar profiles with a pronounced minimum at 20 °C. Results highlight effects on the nutritional value of these diatoms, with potential repercussion on food webs.

What makes products trendy: Introducing an innovation adoption model

Here we propose and study a new model of innovation adoption, IA. Our hypothesis is that individuals’ decisions regarding the purchase of a new product, are driven by the perceived type of adoption trend. Our assumptions split adopters into four groups, Innovators, Early Adopters, Majority, and Laggards, based on their innovativeness, and assign particular preferences for various adoption trends based on their psychological profile. We have built several mathematical models to test our hypothesis and generated forecasts for retail sales of products sold in a supermarket chain in Poland. The performance in sales forecasting of our IA model, points to evidence of customers’ behavior as described by our hypotheses, and the usefulness in quantifying psychological behavior in a general social context of innovation.

A JWST Near- and Mid-infrared Nebular Spectrum of the Type Ia Supernova 2021aefx

We present JWST near-infrared (NIR) and mid-infrared (MIR) spectroscopic observations of the nearby normal Type Ia supernova (SN) SN 2021aefx in the nebular phase at +255 days past maximum light. Our Near Infrared Spectrograph (NIRSpec) and Mid Infrared Instrument observations, combined with ground-based optical data from the South African Large Telescope, constitute the first complete optical+NIR+MIR nebular SN Ia spectrum covering 0.3–14 μm. This spectrum unveils the previously unobserved 2.5−5 μm region, revealing strong nebular iron and stable nickel emission, indicative of high-density burning that can constrain the progenitor mass. The data show a significant improvement in sensitivity and resolution compared to previous Spitzer MIR data. We identify numerous NIR and MIR nebular emission lines from iron-group elements as well as lines from the intermediate-mass element argon. The argon lines extend to higher velocities than the iron-group elements, suggesting stratified ejecta that are a hallmark of delayed-detonation or double-detonation SN Ia models. We present fits to simple geometric line profiles to features beyond 1.2 μm and find that most lines are consistent with Gaussian or spherical emission distributions, while the [Ar iii] 8.99 μm line has a distinctively flat-topped profile indicating a thick spherical shell of emission. Using our line profile fits, we investigate the emissivity structure of SN 2021aefx and measure kinematic properties. Continued observations of SN 2021aefx and other SNe Ia with JWST will be transformative to the study of SN Ia composition, ionization structure, density, and temperature, and will provide important constraints on SN Ia progenitor and explosion models.

Adsorption and Diffusion Behaviors of CO2 and CH4 Mixtures in Different Types of Kerogens and Their Roles in Enhanced Energy Recovery

CO2 geological sequestration in subsurface shale formations is a promising strategy to store CO2 and to increase shale gas production. The understanding of gas adsorption and diffusion mechanisms in microporous media is critical for CO2 storage-enhanced gas recovery (CS-EGR). The type of kerogens is one of the important factors that influence the adsorption and diffusion behaviors of gases. In this work, the Grand Canonical Monte Carlo and Molecular Dynamics simulations were utilized to develop kerogen models and further investigate gas and water adsorption and diffusion behavior on the type IA, IIA, and IIIA kerogen models. The results indicated that the adsorption and diffusion capacities of CO2 are larger than those of CH4. The adsorption and diffusion capacity decreased with increasing water content. However, the CO2/CH4 adsorption selectivity increased with the increase in water content. Type IIIA demonstrated the best potential for adsorption and diffusion. This study provides insights into the role of the adsorption and diffusion behavior of CO2 and CH4 mixtures on kerogens of different types under different water contents at a microscopic scale, and can facilitate further understanding of the processes involved in CO2 storage coupled with enhanced energy recovery.

The Pantheon+ Analysis: The Full Data Set and Light-curve Release

Here we present 1701 light curves of 1550 unique, spectroscopically confirmed Type Ia supernovae (SNe Ia) that will be used to infer cosmological parameters as part of the Pantheon+ SN analysis and the Supernovae and H 0 for the Equation of State of dark energy distance-ladder analysis. This effort is one part of a series of works that perform an extensive review of redshifts, peculiar velocities, photometric calibration, and intrinsic-scatter models of SNe Ia. The total number of light curves, which are compiled across 18 different surveys, is a significant increase from the first Pantheon analysis (1048 SNe), particularly at low redshift (z). Furthermore, unlike in the Pantheon analysis, we include light curves for SNe with z < 0.01 such that SN systematic covariance can be included in a joint measurement of the Hubble constant (H 0) and the dark energy equation-of-state parameter (w). We use the large sample to compare properties of 151 SNe Ia observed by multiple surveys and 12 pairs/triplets of “SN siblings”—SNe found in the same host galaxy. Distance measurements, application of bias corrections, and inference of cosmological parameters are discussed in the companion paper by Brout et al., and the determination of H 0 is discussed by Riess et al. These analyses will measure w with ∼3% precision and H 0 with ∼1 km s−1 Mpc−1 precision.