Model Of Formation Research Articles

New rabbit model for benign biliary stricture formation with repeatable administration

BACKGROUND The treatment of benign biliary strictures (BBS) is a challenging clinical problem. At present, there is a lack of ideal models for the study of BBS treatment. AIM To develop a novel animal model of BBS to simulate studies on the processes and mechanisms in the human condition. METHODS A rabbit model of benign bile duct stricture was established by surgical injury of the bile duct. After removal of the gallbladder, a drainage tube was placed through the cystic duct at the stump, and a BBS model was induced by surgical injury at the lower end of the common bile duct. RESULTS Compared with the control group, the model rabbits showed gross jaundice, increased serum bilirubin, and decreased liver function. Cholangiography showed segmental bile duct stenosis in the model rabbits. Pathological staining showed inflammatory cell infiltration and fibrosis in the biliary tract of rabbits in the model group. This was consistent with the clinical manifestations of BBS. This model provided serology, imaging, pathology, and other aspects of BBS. CONCLUSION We have successfully established an animal model of benign stricture of the lower bile duct with repeatable administration, which is consistent with the clinical manifestations of BBS.

N6-methyladenosine modification of circular RNA circASH2L suppresses growth and metastasis in hepatocellular carcinoma through regulating hsa-miR-525-3p/MTUS2 axis.

CircRNAs have been demonstrated to play a crucial role in regulating the growth and progression of various cancers, including hepatocellular carcinoma (HCC). Nevertheless, the circRNA's expression pattern and function in HCC need more investigation. Bioinformatics techniques were used to identify differentially expressed circRNAs in HCC. CircASH2L expression in HCC tissues was assessed through qRT-PCR and ISH analysis. To assess circASH2L's impact on HCC progression, a variety of experiments were carried out both in vitro and in vivo, such as CCK8, colony formation, EdU assay, flow cytometry, transwell assay, and xenograft mouse model. Various experimental techniques including qRT-PCR, dual luciferase reporter assay, FISH, RNA pull-down, and RIP experiments were utilized to evaluate the relationship between circASH2L, miR-525-3p, and MTUS2. Additionally, experiments were conducted to explore the impact of m6A modification on circASH2L expression, including RNA stability assay, m6A RNA immunoprecipitation assay (MeRIP), and Co-IP experiments. We found that circASH2L was downregulated in HCC tissues and the downregulation of circASH2L was significantly correlated with malignant characteristics as well as poor overall survival of patients with HCC. CircASH2L was found to inhibit cells growth, migration and invasion as well as tumorigenesis and metastasis in vivo. Mechanistically, we established that circASH2L directly interacted with miR-525-3p to enhance MTUS2 expression, subsequently leading to tumor suppression. Moreover, the influence of circASH2L on tumor suppression was attenuated by increasing miR-525-3p levels, and MTUS2 was recognized as an essential intermediary in circASH2L-induced tumor suppression. Additionally, N6-methyladenosine (m6A) modification was identified in circASH2L. Our data suggested that METTL3 was responsible for mediating m6A methylation of circASH2L, ultimately regulating circASH2L expression through the promotion of its degradation. These findings collectively highlight the role of circASH2L as a tumor suppressor through a unique circASH2L/miR-525-3p/MTUS2 axis, shedding light on the significance of m6A modification in regulating circASH2L function. The work emphasizes circASH2L as a promising therapeutic target for treating HCC, offering new insights into the role of circRNAs in HCC development.

Predictions for the abundance and clustering of Hα emitting galaxies

Abstract We predict the surface density and clustering bias of Hα emitting galaxies for the Euclid and Nancy Grace Roman Space Telescope redshift surveys using a new calibration of the GALFORM galaxy formation model. We generate 3000 GALFORM models to train an ensemble of deep learning algorithms to create an emulator. We then use this emulator in a Markov Chain Monte Carlo (MCMC) parameter search of an eleven-dimensional parameter space, to find a best-fitting model to a calibration dataset that includes local luminosity function data, and, for the first time, higher redshift data, namely the number counts of Hα emitters. We discover tensions when exploring fits for the observational data when applying a heuristic weighting scheme in the MCMC framework. We find improved fits to the Hα number counts while maintaining appropriate predictions for the local universe luminosity function. For a flux limited Euclid-like survey to a depth of 2 × 10−16 erg−1 s−1 cm−2 for sources in the redshift range 0.9 < z < 1.8, we estimate 2962-4331 Hα emission-line sources deg−2. For a Nancy Grace Roman survey, with a flux limit of 1 × 10−16 erg−1 s−1 cm−2 and a redshift range 1.0 < z < 2.0, we predict 6786-10322 Hα emission-line sources deg−2.

Supporting diversity in clinical trials: the equitable breakthroughs in medicine site maturity model.

Among the most powerful barriers to broader inclusion of diverse participants in clinical trials are social determinants of health, trustworthiness of health care providers and research institutions, and competing pressures on potential participants. Nevertheless, current tools to assess organizational capabilities for clinical trial diversity focus primarily on trial infrastructure, rely solely on quantitative self-reported data, and lack meaningful assessment of capabilities related to community engagement. The Equitable Breakthroughs in Medicine (EQBMED) initiative developed a holistic, collaborative, site-driven formative model and accompanyingassessment to catalog sites' current capabilities and identify opportunities for growth in both conducting industry-sponsored clinical trials and enriching diversity of those trials. The model builds upon prior work and reflects unification of two historically distinct components-research operations and community engagement-since sustainable clinical trial diversity efforts must overcome these silos. Here we present the methodology we used to develop the model and accompanyingassessment, describe how findings can support clinical trial diversity efforts, and report findings from early field testing at three U.S. sites. The first three sites were diverse in size (e.g., < 250-1K beds), with varying levels of clinical trial capabilities and community engagement. The maturity assessment laid the foundation for sites to identify and prioritize key areas to advance clinical trial diversity capabilities, and each has made tangible progress. In parallel to completing the assessment with these early sites to understand their maturity and set actionable goals, we also collected their feedback on content validity (e.g., clarity, comprehensiveness, terminology) and feasibility (e.g., ability to collect needed information and data, time required). We describe refinements made to improve the assessment and streamline the process. The EQBMED program will deploy the assessment across various site types (e.g., FQHCs, safety net hospitals) and make further refinements as warranted. Strategic investment in clinical trial diversity requires structured assessment of site maturity as a starting point for collaborative action. We propose the EQBMED maturity model as a first step toward informing efforts to increase representation of diverse populations in clinical research.

Functional characteristics and computational model of abundant hyperactive loci in the human genome.

Enhancers and promoters are classically considered to be bound by a small set of transcription factors (TFs) in a sequence-specific manner. This assumption has come under increasing skepticism as the datasets of ChIP-seq assays of TFs have expanded. In particular, high-occupancy target (HOT) loci attract hundreds of TFs with often no detectable correlation between ChIP-seq peaks and DNA-binding motif presence. Here, we used a set of 1003 TF ChIP-seq datasets (HepG2, K562, H1) to analyze the patterns of ChIP-seq peak co-occurrence in combination with functional genomics datasets. We identified 43,891 HOT loci forming at the promoter (53%) and enhancer (47%) regions. HOT promoters regulate housekeeping genes, whereas HOT enhancers are involved in tissue-specific process regulation. HOT loci form the foundation of human super-enhancers and evolve under strong negative selection, with some of these loci being located in ultraconserved regions. Sequence-based classification analysis of HOT loci suggested that their formation is driven by the sequence features, and the density of mapped ChIP-seq peaks across TF-bound loci correlates with sequence features and the expression level of flanking genes. Based on the affinities to bind to promoters and enhancers we detected five distinct clusters of TFs that form the core of the HOT loci. We report an abundance of HOT loci in the human genome and a commitment of 51% of all TF ChIP-seq binding events to HOT locus formation thus challenging the classical model of enhancer activity and propose a model of HOT locus formation based on the existence of large transcriptional condensates.

Stochastic Super-resolution of Cosmological Simulations with Denoising Diffusion Models

In recent years, deep learning models have been successfully employed for augmenting low-resolution cosmological simulations with small-scale information, a task known as “super-resolution”. So far, these cosmological super-resolution models have relied on generative adversarial networks (GANs), which can achieve highly realistic results, but suffer from various shortcomings (e.g. low sample diversity). We introduce denoising diffusion models as a powerful generative model for super-resolving cosmic large-scale structure predictions (as a first proof-of-concept in two dimensions). To obtain accurate results down to small scales, we develop a new “filter-boosted” training approach that redistributes the importance of different scales in the pixel-wise training objective. We demonstrate that our model not only produces convincing super-resolution images and power spectra consistent at the percent level, but is also able to reproduce the diversity of small-scale features consistent with a given low-resolution simulation. This enables uncertainty quantification for the generated small-scale features, which is critical for the usefulness of such super-resolution models as a viable surrogate model for cosmic structure formation.

Machine learning-based modeling of ground level ozone formation in Bangalore and New Delhi cities in India

Machine learning-based modeling of ground level ozone formation in Bangalore and New Delhi cities in India

Functional characteristics and computational model of abundant hyperactive loci in the human genome

Enhancers and promoters are classically considered to be bound by a small set of transcription factors (TFs) in a sequence-specific manner. This assumption has come under increasing skepticism as the datasets of ChIP-seq assays of TFs have expanded. In particular, high-occupancy target (HOT) loci attract hundreds of TFs with often no detectable correlation between ChIP-seq peaks and DNA-binding motif presence. Here, we used a set of 1003 TF ChIP-seq datasets (HepG2, K562, H1) to analyze the patterns of ChIP-seq peak co-occurrence in combination with functional genomics datasets. We identified 43,891 HOT loci forming at the promoter (53%) and enhancer (47%) regions. HOT promoters regulate housekeeping genes, whereas HOT enhancers are involved in tissue-specific process regulation. HOT loci form the foundation of human super-enhancers and evolve under strong negative selection, with some of these loci being located in ultraconserved regions. Sequence-based classification analysis of HOT loci suggested that their formation is driven by the sequence features, and the density of mapped ChIP-seq peaks across TF-bound loci correlates with sequence features and the expression level of flanking genes. Based on the affinities to bind to promoters and enhancers we detected five distinct clusters of TFs that form the core of the HOT loci. We report an abundance of HOT loci in the human genome and a commitment of 51% of all TF ChIP-seq binding events to HOT locus formation thus challenging the classical model of enhancer activity and propose a model of HOT locus formation based on the existence of large transcriptional condensates.

Planetesimal gravitational collapse in a gaseous environment: Thermal and dynamic evolution

Planetesimal formation models often invoke the gravitational collapse of pebble clouds to overcome various barriers to grain growth and propose processes to concentrate particles sufficiently to trigger this collapse. On the other hand, the geochemical approach for planet formation constrains the conditions for planetesimal formation and evolution by providing temperatures that should be reached to explain the final composition of planetesimals, the building blocks of planets. To elucidate the thermal evolution during gravitational collapse, we used numerical simulations of a self-gravitating cloud of particles and gas coupled with gas drag. Our goal is to determine how the gravitational energy relaxed during the contraction is distributed among the different energy components of the system, and how this constrains a thermal and dynamical planetesimal's history. We identify the conditions necessary to achieve a temperature increase of several hundred kelvins, and as much as 1600 K. Our results emphasise the key role of the gas during the collapse.

Under the magnifying glass: A combined 3D model applied to cloudy warm Saturn-type exoplanets around M dwarfs

Warm Saturn-type exoplanets orbiting M dwarfs are particularly suitable for an in-depth cloud characterisation through transmission spectroscopy because the contrast of their stellar to planetary radius is favourable. The global temperatures of warm Saturns suggest efficient cloud formation in their atmospheres which in return affects the temperature, velocity, and chemical structure. However, a consistent modelling of the formation processes of cloud particles within the 3D atmosphere remains computationally challenging. We explore the combined atmospheric and micro-physical cloud structure and the kinetic gas-phase chemistry of warm Saturn-like exoplanets in the irradiation field of an M dwarf. The combined modelling approach supports the interpretation of observational data from current (e.g. JWST and CHEOPS) and future missions (PLATO, Ariel, and HWO). A combined 3D cloudy atmosphere model for HATS-6b was constructed by iteratively executing the 3D general circulation model (GCM) expeRT/MITgcm and a detailed kinetic cloud formation model, each in its full complexity. The resulting cloud particle number densities, particle sizes, and material compositions were used to derive the local cloud opacity which was then used in the next GCM iteration. The disequilibrium H/C/O/N gas-phase chemistry was calculated for each iteration to assess the resulting transmission spectrum in post-processing. We present the first model atmosphere that iteratively combines cloud formation and 3D GCM simulation and applied it to the warm Saturn HATS-6b. The cloud opacity feedback causes a temperature inversion at the sub-stellar point and at the evening terminator at gas pressures higher than 10$^ $ bar. Furthermore, clouds cool the atmosphere between $10^ $ bar and 10 bar, and they narrow the equatorial wind jet. The transmission spectrum shows muted gas-phase absorption and a cloud particle silicate feature at $ The combined atmosphere-cloud model retains the full physical complexity of each component and therefore enables a detailed physical interpretation with JWST NIRSpec and MIRI LRS observational accuracy. The model shows that warm Saturn-type exoplanets around M dwarfs are ideal candidates for a search for limb asymmetries in clouds and chemistry, for identifying the cloud particle composition by observing their spectral features, and for identifying in particular the cloud-induced strong thermal inversion that arises on these planets.

THE EVOLUTION OF A CLAY CRUST IN A BOREHOLE

Based on the previously proposed quasi-stationary model of clay crust formation when drilling wells in depth intervals with permeable rocks, software was created and computational experiments were performed, which made it possible to clarify the contribution of various physical parameters to the process of its growth.Based on the analysis of the results of computational experiments, the contribution of the physical parameters of the formation and clay crust to the dependence of its size on time has been clarified. The model assumes that the filtration pressure fields are described by stationary piezo conductivity equations. This made it possible to construct explicit dependences of pressure, thickness of the clay crust, radius of the zone of pressure disturbances in the reservoir during drilling and other parameters on time. Simple approximate formulas have been found for the dependence of the thickness of the clay crust, the filtration rate and the radius of the pressure disturbance zone in the reservoir on time, which describe their evolution with high accuracy.Based on the analysis of the calculation results, it was found that the thickness of the clay crust significantly depends on the permeability of the reservoir and repression, and these parameters determine the process of its formation. The porosity of the collector makes a smaller contribution, and the filtration and capacitance parameters of the clay crust have little effect on its thickness.New possibilities for estimating the physical parameters of reservoirs based on cavernometry have been identified. The solution of this problem is especially important for horizontal wells, in which the clay crust intervals have a significant length, and its formation occurs under conditions of a wide range of reservoir properties of the formation. The considered problem is of practical importance, since the zone of penetration of drilling mud filtrate into the formation has a screening effect on the use of geophysical methods to determine reservoir saturation. The results obtained can be used both to improve the interpretation of geophysical methods and to develop those.When conducting computational experiments using an exact formula, the stochastic behavior of the calculated curves was found. It was found that the noted effect is associated with rounding error, and in this sense is a manifestation of the features of the processor. An approach is proposed to eliminate the detected stochastic errors.

Chemically reactive and aging macromolecular mixtures. II. Phase separation and coarsening.

In a companion paper, we put forth a thermodynamic model for complex formation via a chemical reaction involving multiple macromolecular species, which may subsequently undergo liquid-liquid phase separation and a further transition into a gel-like state. In the present work, we formulate a thermodynamically consistent kinetic framework to study the interplay between phase separation, chemical reaction, and aging in spatially inhomogeneous macromolecular mixtures. A numerical algorithm is also proposed to simulate domain growth from collisions of liquid and gel domains via passive Brownian motion in both two and three spatial dimensions. Our results show that the coarsening behavior is significantly influenced by the degree of gelation and Brownian motion. The presence of a gel phase inside condensates strongly limits the diffusive transport processes, and Brownian motion coalescence controls the coarsening process in systems with high area/volume fractions of gel-like condensates, leading to the formation of interconnected domains with atypical domain growth rates controlled by size-dependent translational and rotational diffusivities.

Establishment of a Predictive Model for Seroma Formation After TAPP Repair for Unilateral Indirect Inguinal Hernia in Males.

Inguinal hernia repair, particularly using TAPP, is common in males, and acclaimed for minimal invasiveness but often complicated by seromas, significantly affecting recovery and health care costs. This retrospective study analyzed data from 266 male patients with unilateral indirect inguinal hernia who underwent transabdominal preperitoneal (TAPP) repair. We divided the patients into a training set (n = 188) and a validation set (n = 78). We employed logistic regression to identify independent risk factors for post-TAPP seroma and developed a nomogram to predict the occurrence of seromas. The model's accuracy was evaluated using receiver operating characteristic (ROC) curves, Hosmer-Lemeshow goodness-of-fit test, calibration curves, and decision curve analysis (DCA). Postoperatively, 20.3% of patients developed a seroma. Multivariate logistic regression analysis highlighted several independent risk factors for seroma formation: the use of anticoagulants, an internal ring defect ≥5cm, scrotal hernia, incarcerated hernia, and transected hernia sac (P < 0.05). The ROC curves for the training and validation sets demonstrated areas under the curve of 0.893 (95% CI: 0.845-0.942) and 0.864 (95% CI: 0.765-0.963), respectively, indicating good model fits (P > 0.05). DCA confirmed significant clinical applicability of the model. The findings suggest that the use of anticoagulants, an internal ring defect ≥5cm, scrotal hernia, incarcerated hernia, and transected hernia sac are significant independent risk factors for seroma formation after TAPP repair. Clinical consideration of these factors and proactive preventive measures are essential. Although many of these factors are non-modifiable, understanding them is crucial for preoperative risk assessment and patient management.

Glow-to-arc transition in graphite cathode with high-current magnetron discharge

The glow-to-arc transition is a critical phenomenon in plasma discharges, commonly leading to detrimental effects. The physical mechanisms triggering this transition remain poorly understood. The advent of a discharge called Hyper-Power Impulse Magnetron has opened possibilities. Hyper-Power Impulse Magnetron allows the glow mode to be maintained over long periods (1 ms) and at high-current densities (&amp;gt;5 A .cm−2), which has unveiled certain features in the glow-to-arc transition. This work focuses on a graphite target that transits easily in the arc regime. The high-speed video-camera analysis revealed specific properties of graphite in ExB discharges, and the statistical study of the arc transition revealed differences from other refractory target materials. The early stage of cathodic spot formation, observed as bright dots, will be presented and analyzed within the known “ecton” and “vaporization” models for spot formation. This experimental study highlights the role of luminous spot formation prior to arc transition, with possible optimization on the stability of magnetron discharges.

Are all models wrong? Falsifying binary formation models in gravitational-wave astronomy using exceptional events

Abstract As the catalogue of gravitational-wave transients grows, several entries appear ‘exceptional’ within the population. Tipping the scales with a total mass of ∼150M⊙, GW190521 likely contained black holes in the pair-instability mass gap. The event GW190814, meanwhile, is unusual for its extreme mass ratio and the mass of its secondary component. A growing model-building industry has emerged to provide explanations for such exceptional events, and Bayesian model selection is frequently used to determine the most informative model. However, Bayesian methods can only take us so far. They provide no answer to the question: does our model provide an adequate explanation for exceptional events in the data? If none of the models we are testing provide an adequate explanation, then it is not enough to simply rank our existing models—we need new ones. In this paper, we introduce a method to answer this question with a frequentist p-value. We apply the method to different models that have been suggested to explain the unusually massive event GW190521: hierarchical mergers in active galactic nuclei and globular clusters. We show that some (but not all) of these models provide adequate explanations for exceptionally massive events like GW190521.

Mathematical model of liver cirrhosis formation during morphological and molecular-genetic preclinical studies

BACKGROUND: Currently, researchers describe challenges in developing new treatments for fibrosis and cirrhosis: poor quality of preclinical models, insufficient trial duration, and lack of markers of therapeutic response. A separate task is to standardize the process of liver cirrhosis formation in preclinical trials, which is necessary to obtain accurate quantitative estimates in a short timeframe. AIM: This study aimed to develop a mathematical model for the formation of liver cirrhosis during preclinical trials. MATERIALS AND METHODS: Liver fibrosis and cirrhosis were induced in male Wistar rats using freshly prepared thioacetamide solution for 17 weeks. The area of connective tissue was determined as a percentage of the image area. The area of interlobular veins was measured in µm2. The numbers of cells expressing the FAP marker and the α-SMA marker were counted. The level of mRNA expression of the Vegfa and Yap1 genes was assessed by real-time polymerase chain reaction. A mathematical model for classifying observations into stages was constructed using multiple logistic regression with stepwise selection of predictors, followed by calculation of sensitivity, specificity, and area under the curve with a 95% confidence interval based on ROC analysis. RESULTS: As a result of the analysis, a mathematical model of liver cirrhosis formation was developed. The model is based on the values of two indicators: FAP+ cells and Yap1 mRNA and demonstrated good quality. The resulting value of the area under the ROC curve of 0.883 suggests good results for classifying cases. CONCLUSIONS: The mathematical model makes it possible to differentiate the stage of liver cirrhosis from the stage of fibrosis during preclinical studies. It provides a foundation for studying the pathogenesis of liver fibrosis and cirrhosis, identifying new potential molecular targets for antifibrotic therapy, and reducing the number of expensive, labor-intensive laboratory tests.

From particles to pixels: How many particles do I really need to construct stellar kinematic mock observational measurements?

Abstract This work considers the impact of resolution in the construction of mock observations of simulated galaxies. In particular, when building mock integral field spectroscopic observations from galaxy formation models in cosmological simulations, we investigate the possible systematics that may arise given the assumption that all galaxies above some stellar mass limit will provide unbiased and meaningful observable stellar kinematics. We build a catalogue of N-body simulations to sample the range of stellar particle resolutions within the Eagle Ref0050N0752 simulation box and examine how their observable kinematics vary relative to a higher-resolution N-body control. We use these models to compile a table of the minimum number of particles-per-pixel to reach a given uncertainty in the fitted line-of-sight velocity distribution parameters. Further, we introduce a Voronoi-binning module to the mock observation code, SimSpin, in order to meet these minimum numbers. Using Eagle, we show the impact of this shot noise on the observed spin-ellipticity plane and the recovery of this space when observations are binned with increasing numbers of particles. In conclusion, we advise binning mock images to meet at least 200 particles-per-pixel to avoid systematically under-estimating the velocity dispersion along a given line-of-sight. We demonstrate that this is important for comparing galaxies extracted from the same simulation, as well as between simulations of varying mass resolution and observations of real galaxies.

In vitro plaque formation model to unravel biofilm formation dynamics on implant abutment surfaces

ABSTRACT Background Biofilm formation on implant-abutment surfaces can cause inflammatory reactions. Ethical concerns often limit intraoral testing, necessitating preliminary in vitro or animal studies. Here, we propose an in vitro model using human saliva and hypothesize that this model has the potential to closely mimic the dynamics of biofilm formation on implant-abutment material surfaces in vivo. Methods A saliva stock was mixed with modified Brain-Heart-Infusion medium to form biofilms on Titanium-Aluminum-Vanadium (Ti6Al4V) and Yttria-partially Stabilized Zirconia (Y-TZP) discs in 24-well plates. Biofilm analyses included crystal violet staining, intact cell quantification with BactoBox, 16S rRNA gene analysis, and short-chain fatty acids measurement. As a control, discs were worn in maxillary splints by four subjects for four days to induce in vivo biofilm formation. Results After four days, biofilms fully covered Ti6Al4V and Y-TZP discs both in vivo and in vitro, with similar cell viability. There was a 60.31% overlap of genera between in vitro and in vivo biofilms in the early stages, and 41% in the late stages. Ten key oral bacteria, including Streptococcus, Haemophilus, Neisseria, Veillonella, and Porphyromonas, were still detectable in vitro, representing the common stages of oral biofilm formation. Conclusion This in vitro model effectively simulates oral conditions and provides valuable insights into biofilm dynamics.

Tracing the Integration Journey: A Qualitative Study of Conflict Between Gender/Sexuality Identity and Religiosity Among LGBTQ Individuals in Indonesia

The mainstream religious perspective that opposes homosexuality and cross-gender expression creates a dilemma for LGBTQ individuals, especially those who grew up with a specific religious affiliation. This can result in internal conflict between gender and religiosity. The present study aims to explore how individuals perceive and cope with the conflict between their religious status and gender and sexual identity over time. We used qualitative methods, specifically the grounded theory approach, which allowed for a focus on the process of theory formation and development. Six participants were selected using purposive and snowball sampling criteria: 1) they identified as part of the LGBTQ community; 2) they had practiced or were currently practicing a particular religion, and; 3) they were at least 18 years old. Data were collected through semi-structured interviews and analyzed using thematic analysis. We developed an “Integration Model of Conflict Between Gender/Sexuality Identity and Religiosity” derived from Cass’s Gender Identity Formation Model [6]. This model consists of the following stages: nonconform, questioning, conflict, exploration, self-identify, compromise, self-integration, and spiritual integration. Additionally, we observed how cognitive appraisal and attachment to religion as a community can play a role in preventing gender-religiosity conflict. This study provides insight into the experiences of LGBTQ individuals who also have a religious affiliation and may be struggling with conflicting identities. The model developed in this study can be used as a framework for understanding and supporting individuals going through this process. Keywords: LGBTQ+, gender, Indonesia

The impact of the cosmological constant on past and future star formation

ABSTRACT We present an extended analytical model for cosmic star formation, with the aim of investigating the impact of cosmological parameters on the star formation history within the $\Lambda$CDM paradigm. Constructing an ensemble of flat $\Lambda$CDM models where the cosmological constant varies between $\Lambda = 0$ and $10^5$ times the observed value, $\Lambda _{\rm obs}$, we find that the fraction of cosmic baryons that are converted into stars over the entire history of the universe peaks at $\sim$ 27 per cent for $0.01 \lesssim \Lambda /\Lambda _{\rm obs} \lesssim 1$. We explain, from first principles, that the decline of this asymptotic star formation efficiency for lower and higher values of $\Lambda$ is driven, respectively, by the astrophysics of star formation, and by the suppression of cosmic structure formation. However, the asymptotic efficiency declines slowly as $\Lambda$ increases, falling below 5 per cent only for $\Lambda \gt 100 \, \Lambda _{\rm obs}$. Making the minimal assumption that the probability of generating observers is proportional to this efficiency, and following Weinberg in adopting a flat prior on $\Lambda$, the median posterior value of $\Lambda$ is $539 \, \Lambda _{\rm obs}$. Furthermore, the probability of observing $\Lambda \le \Lambda _{\rm obs}$ is only 0.5 per cent. Although this work has not considered recollapsing models with $\Lambda \lt 0$, the indication is thus that $\Lambda _{\rm obs}$ appears to be unreasonably small compared to the predictions of the simplest multiverse ensemble. This poses a challenge for anthropic reasoning as a viable explanation for cosmic coincidences and the apparent fine-tuning of the Universe: either the approach is invalid or more parameters than $\Lambda$ alone must vary within the ensemble.