Nested Sampling Research Articles

Structure Deterioration Identification and Model Updating for Prestressed Concrete Bridges Based on Massive Point Cloud Data

As a critical component of the transportation system, the safety of bridges is directly related to public safety and the smooth flow of traffic. This study addresses the aforementioned issues by focusing on the identification of bridge structure deterioration and the updating of finite element models, proposing a systematic research framework. First, this study presents a preprocessing method for bridge point cloud data and determines the parameter ranges for key algorithms through parameter tuning. Subsequently, based on the massive point cloud data, this research explores and optimizes the methods for identifying bridge cracks and spatial deformations, significantly enhancing the accuracy and efficiency of identification. On this basis, the particle swarm optimization algorithm is employed to optimize the key parameters in crack detection, ensuring the reliability and precision of the algorithm. Additionally, the study summarizes the methods for detecting bridge structural deformations based on point cloud data and establishes a framework for updating the bridge model. Finally, by integrating the results of bridge crack and deformation detection and combining Bayesian model correction and adaptive nested sampling methods, this research sets up the process for updating finite element model parameters and applies it to the analysis of actual bridge point cloud data.

Microbiology Test Results for White Edible Birds Nest with Fecal Contamination

Background: Southeast Asia's edible bird nest industry, particularly in Indonesia, has experienced rapid growth in recent years. Indonesia stands as the world's leading exporter of edible bird nests. However, concerns persist regarding the quality of edible bird nests produced in the country, specifically to do with meeting quality standards by ensuring freedom from microbial contaminants that can lead to foodborne illnesses. Purpose: To evaluate the microbiological contamination of cleaned edible bird nests sourced from Java Island, Indonesia. Cases(s): Yellow-brown discoloration of edible bird nests collected from bird houses of Javan origin. Case Management: Fifty samples of raw white edible bird’s nest samples (cup-shaped) with yellow-brown discoloration (n=25) originating from Java Island and raw white edible bird’s nest samples (cup-shaped) (n=25) were collected aseptically from the edible bird’s nest warehouses in Surabaya. These samples of edible nests from Java Island were subjected to microbiological analysis. The findings revealed a disconcerting trend, with 25 samples from Java Island exhibiting contamination by Escherichia coli (40%) and coliform bacteria (100%), surpassing established contamination thresholds. Conclusion: This raises critical concerns about the safety and quality of edible bird nests from the region, highlighting the need for enhanced production and processing practices, as well as rigorous quality control measures to ensure consumer safety and to maintain the industry's reputation on a global scale. Addressing these issues is imperative not only to safeguard public health but also to sustain and further develop the lucrative edible bird nest industry in Indonesia.

Enhanced Crashworthiness Parameters of Nested Thin-Walled Carbon Fiber-Reinforced Polymer and Al Structures: Effect of Using Expanded Polypropylene Foam

The in-plane loading conditions of carbon fiber/epoxy composite (CFRP) and aluminum nested-tube-reinforced expanded polypropylene (EPP) blocks were empirically examined. This study used crashworthiness metrics to estimate the best design configuration under quasi-static loading rates. The experimental phase began with lateral loading testing of single and nested aluminum and CFRP specimen. In-plane crushing experiments were performed on EPP foam blocks reinforced with nested tubes. Both single and nested aluminum tubes had comparable force–response curves and maintained their load-bearing capacity throughout testing. Despite a load-carrying capacity drop above a particular displacement threshold, the CFRP specimens had superior specific energy absorption (SEA) values due to their lightweight nature. The triple-tube nested specimens with two smaller tubes exhibited the best SEA results (1.72 and 1.88 J/g, respectively, for the aluminum and CFRP nested samples). During concurrent tube deformation, the nested samples showed a synergistic connection that increased energy absorption, especially in the EPP foam blocks with reinforced tubes. The study also examined the effects of building nested specimens with aluminum exterior tubes and CFRP inner tubes, and vice versa. This method showed that CFRP tubes within aluminum outer tubes lowered specimen weight (from 93.1 g to 67.7 g) and energy absorption (from 160.2 J to 153.3 J). However, the weight reduction outweighed the energy absorption, increasing SEA values for certain composite material configurations (from 1.72 J/g to 2.26 J/g).

Further evidence that peritraumatic 17β-estradiol levels influence chronic posttraumatic pain outcomes in women, data from both humans and animals.

Chronic posttraumatic pain (CPTP) is common after traumatic stress exposure (TSE) and disproportionately burdens women. We previously showed across 3 independent longitudinal cohort studies that, in women, increased peritraumatic 17β-estradiol (E2) levels were associated with substantially lower CPTP over 1 year. Here, we assessed this relationship in a fourth longitudinal cohort and also assessed the relationship between E2 and CPTP at additional time points post-TSE. Furthermore, we used a well-validated animal model of TSE to determine whether exogenous E2 administration protects against mechanical hypersensitivity. Using nested samples and data from the Advancing Understanding of RecOvery afteR traumA study (n = 543 samples, 389 participants), an emergency department-based prospective study of TSE survivors, we assessed the relationship between circulating E2 levels and CPTP in women and men using multivariate repeated-measures mixed modeling. Male and ovariectomized female Sprague Dawley rats were exposed to TSE and administered E2 either immediately after or 3 days post-TSE. Consistent with previous results, we observed an inverse relationship between peritraumatic E2 and longitudinal CPTP in women only (β = -0.137, P = 0.033). In animals, E2 protected against mechanical hypersensitivity in female ovariectomized rats only if administered immediately post-TSE. In conclusion, peritraumatic E2 levels, but not those at post-TSE time points, predict CPTP in women TSE survivors. Administration of E2 immediately post TSE protects against mechanical hypersensitivity in female rats. Together with previous findings, these data indicate that increased peritraumatic E2 levels in women have protective effects against CPTP development and suggest that immediate post-TSE E2 administration in women could be a promising therapeutic strategy for reducing risk of CPTP.

Using a Nested Sampling Design Across Spatial Scales to Gain Insights Into Distribution Patterns of Fishes, Mussels and Macroinvertebrates in a Riverine System

ABSTRACTAimThe goal of our study was to use a nested sampling design to compare the distribution of different groups of organisms with different dispersal modes and examine their responses in community composition to environmental heterogeneity at different spatial scales (local pool vs. riffle habitat, sections within a river and between rivers).LocationUpper Colorado River basin, Texas, USA.TaxonFishes, mussels and macroinvertebrates.MethodsWe sampled 100 sites using a nested sampling design across five rivers (four tributaries and the mainstem), with four river sections and five sampling sites per section, each consisting of a pool and riffle habitat. Collected data on species abundances, local and landscape environmental variables and spatial variables were analysed using a combination of dissimilarity, redundancy and variation partitioning analysis.ResultsAt the river scale, environmental heterogeneity explained 28% and 34% of the variation in mussel and fish communities, respectively, and 15% for macroinvertebrates. Community changes between sections in the tributaries were highest for fishes, but similarly high for fishes and macroinvertebrates in the mainstem. Significant patterns for mussels were only detected in rivers with higher abundances. No significant differences in dissimilarity were found between mesohabitats, but a small significant effect of mesohabitat was detected for mussels with RDA after removing the river effect.Main ConclusionsAlthough the depauperate mussel communities made it more difficult to draw any conclusions, there were some indications that their distribution was driven by environmental heterogeneity across scales. Section and river scales were relevant for fish, whereas macroinvertebrates showed a weaker response to environmental heterogeneity at these scales. The combination of approaches detected more ecologically meaningful patterns than one analysis alone would have. This study highlights the complexity of riverine community dynamics and underscores the need for a multiscale approach to identify their distribution patterns.

The future of cosmological likelihood-based inference: accelerated high-dimensional parameter estimation and model comparison

We advocate for a new paradigm of cosmological likelihood-based inference, leveraging recent developments in machine learning and its underlying technology, to accelerate Bayesian inference in high-dimensional settings. Specifically, we combine (i) emulation, where a machine learning model is trained to mimic cosmological observables, e.g. CosmoPower-JAX; (ii) differentiable and probabilistic programming, e.g. JAX and NumPyro, respectively; (iii) scalable Markov chain Monte Carlo (MCMC) sampling techniques that exploit gradients, e.g. Hamiltonian Monte Carlo; and (iv) decoupled and scalable Bayesian model selection techniques that compute the Bayesian evidence purely from posterior samples, e.g. the learned harmonic mean implemented in harmonic. This paradigm allows us to carry out a complete Bayesian analysis, including both parameter estimation and model selection, in a fraction of the time of traditional approaches. First, we demonstrate the application of this paradigm on a simulated cosmic shear analysis for a Stage IV survey in 37- and 39-dimensional parameter spaces, comparing ΛCDM and a dynamical dark energy model ( w0waCDM). We recover posterior contours and evidence estimates that are in excellent agreement with those computed by the traditional nested sampling approach while reducing the computational cost from 8 months on 48 CPU cores to 2 days on 12 GPUs. Second, we consider a joint analysis between three simulated next-generation surveys, each performing a 3x2pt analysis, resulting in 157- and 159-dimensional parameter spaces. Standard nested sampling techniques are simply unlikely to be feasible in this high-dimensional setting, requiring a projected 12 years of compute time on 48 CPU cores; on the other hand, the proposed approach only requires 8 days of compute time on 24 GPUs. All packages used in our analyses are publicly available.

The phase diagram of Mercedes Benz model of water using nested sampling algorithm and molecular dynamics simulations

The Mercedes Benz (MB) model of water is quite popular for explaining the properties of water, but the complete phase diagram has not yet been published. In the MB model, water molecules are modelled as two-dimensional Lennard-Jones discs, with three orientation-dependent hydrogen-bonding arms arranged as in the MB logo. Nested Sampling (NS) is a powerful sampling algorithm for the parameter space that directly calculates the partition function. NS can be used for sampling the equilibrium thermodynamics of atomistic systems and allows access to all thermodynamic quantities in absolute terms, including absolute free energies and absolute entropies. Here, NS is used to calculate the phase diagram of the simple two-dimensional Mercedes-Benz (MB) model of water. 32 water particles were used in NS. While this number of particles provides sufficient agreement with the simulations, the results from fewer particles slowly begin to diverge from the result from NS with 32 particles as some of the equilibrium lines begin to shift. By combining the results from NS and molecular dynamics (MD) simulations, different phases were located and identified. In total, 5 different solid phases, 3 liquid phases and one gaseous phase were observed.

Constraining the Selection-corrected Luminosity Function and Total Pulse Count for Radio Transients

Studying transient phenomena, such as individual pulses from pulsars, has garnered considerable attention in the era of astronomical big data. Of specific interest to this study are rotating radio transients (RRATs), nulling, and intermittent pulsars. This study introduces a new algorithm named LuNfit, tailored to correct the selection biases originating from the telescope and detection pipelines. Ultimately LuNfit estimates the intrinsic luminosity distribution and nulling fraction of the single pulses emitted by pulsars. LuNfit relies on Bayesian nested sampling so that the parameter space can be fully explored. Bayesian nested sampling also provides the additional benefit of simplifying model comparisons through the Bayes ratio. The robustness of LuNfit is shown through simulations and applying LuNfit onto pulsars with known nulling fractions. LuNfit is then applied to three RRATs, J0012+5431, J1538+1523, and J2355+1523, extracting their intrinsic luminosity distribution and burst rates. We find that their nulling fractions are 0.4(2), 0.749(5), and 0.995(2), respectively. We further find that a log-normal distribution likely describes the single pulse luminosity distribution of J0012+5431 and J1538+1523, while the Bayes ratio for J2355+1523 slightly favors an exponential distribution. We show the conventional method of correcting selection effects by “scaling up” the missed fraction of radio transients can be unreliable when the mean luminosity of the source is faint relative to the telescope sensitivity. Finally, we discuss the limitations of the current implementation of LuNfit while also delving into potential enhancements that would enable LuNfit to be applied to sources with complex pulse morphologies.

Clinical Significance and Patterns of Potential Drug-Drug Interactions in Cardiovascular Patients: Focus on Low-Dose Aspirin and Angiotensin-Converting Enzyme Inhibitors.

Objective: This study assessed the patterns and clinical significance of potential drug-drug interactions (pDDIs) in patients with diseases of the cardiovascular system. Methods: Electronic health records (EHRs), established in 2018-2023, were selected using the probability serial nested sampling method (n = 1030). Patients were aged 27 to 95 years (65.0% men). Primary diagnosis of COVID-19 was present in 17 EHRs (1.7%). Medscape Drug Interaction Checker was used to characterize pDDIs. The Mann-Whitney U test and chi-square test were used for statistical analysis. Results: Drug numbers per record ranged from 1 to 23 in T-List and from 1 to 20 in P-List. In T-List, 567 drug combinations resulted in 3781 pDDIs. In P-List, 584 drug combinations resulted in 5185 pDDIs. Polypharmacy was detected in 39.0% of records in T-List versus 65.9% in P-List (p-value < 0.05). The rates of serious and monitor-closely pDDIs due to 'aspirin + captopril' combinations were significantly higher in P-List than in T-List (p-value < 0.05). The rates of serious pDDIs due to 'aspirin + enalapril' and 'aspirin + lisinopril' combinations were significantly lower in P-List compared with the corresponding rates in T-List (p-value < 0.05). Serious pDDIs due to administration of aspirin with fosinopril, perindopril, and ramipril were detected less frequently in T-List (p-value < 0.05). Conclusions: Obtained data may suggest better patient adherence to 'aspirin + enalapril' and 'aspirin + lisinopril' combinations, which are potentially superior to the combinations of aspirin with fosinopril, perindopril, and ramipril. An abundance of high-order pDDIs in real-world clinical practice warrants the development of a decision support system aimed at reducing pharmacotherapy-associated risks while integrating patient pharmacokinetic, pharmacodynamic, and pharmacogenetic information.

Aeons: approximating the end of nested sampling

ABSTRACT This paper presents analytical results on the anatomy of nested sampling, from which a technique is developed to estimate the run-time of the algorithm that works for any nested sampling implementation. We test these methods on both toy models and true cosmological nested sampling runs. The method gives an order-of-magnitude prediction of the endpoint at all times, forecasting the true endpoint within standard error around the halfway point.

The ManhattAnt: identification, distribution, and colony structure of a new pest in New York City, Lasius emarginatus

An unidentified ant species was discovered in the heart of New York City in 2011, which garnered national headlines and created the memorable nickname “ManhattAnt.” New York City is one of the oldest and largest cities in North America and has been the site of introduction for some of North America’s most damaging invasive pests. Nevertheless, there has been little follow up research on the ManhattAnt since its discovery, and it has yet to be formally identified. Here we use genetic and morphological approaches to confirm the identity of the ManhattAnt and characterize its introduced range and colony structure. Results from genetic analyses placed the ManhattAnt within the Lasius emarginatus species complex, and morphological comparisons ruled out closely related species to identify the ManhattAnt as the European ant L. emarginatus with 93–99% certainty depending on the nest sample. Since its initial discovery in the region, the ManhattAnt has become one of the most common ants in New York City and has spread at a rate of 2 km/yr into New Jersey and onto Long Island. Based on the climate it inhabits within its native range, L. emarginatus could expand to cover much of the eastern United states from Massachusetts to Georgia. Although many successful invasive ants display supercoloniality with little aggression between neighboring nests, we found no evidence that L. emarginatus colonies in New York City are supercolonial. Continued monitoring of L. emarginatus is warranted, as it has been increasingly reported as an indoor pest and is known to form mutualisms with honeydew producing pests of street trees.

Experimental investigation on energy absorption capability of 3D printed onyx nested rings under lateral loading

This study presents a focused experimental exploration into the energy absorption characteristics and failure mechanisms of nested circular rings under lateral loading. The rings were 3D printed using the fuse deposition modeling method with an onyx material containing chopped carbon fiber. The dimensions of the rings were determined to be the same in width and thickness, while the diameter had four different values. The samples of nested rings consist of at least two and up to five individual rings. These samples were obtained by using individual rings in various different sequences and orders. Two different configurations for each nested sample type were also studied to observe the effect of the ring sequences and orders on the energy absorption capability. It is concluded from the results that even though the single ring with the smallest diameter has the highest force values, the highest energy absorption and specific energy absorption values were obtained in another single ring. The alignment of the single rings has a superior effect on the energy absorption capacity of the nested samples. Also, a gain in absorbed energy was observed in nested samples due to the interaction between the single rings. This interaction showed that the algebraic summation of the energy values of single rings used in a nested sample was lower than the energy value of the same nested sample. In the nested samples, the absorbed energy increased proportionally to the number of single rings. However, the crashworthiness parameters were affected quite differently from the energy absorption capacity. While the highest energy absorption values are obtained in nested samples with five single rings, other nested samples reached the highest values in terms of some of the crashworthiness parameters. The NR5-A sample absorbed 52% and 88% higher energy compared to the same combination of nested samples, which contain four and three single rings, respectively. Additionally, the specific energy absorption value of this sample is 32% and 47% higher than the same nested samples mentioned above. Considering these results, it can be expressed that the NR5-A sample is the best design in terms of an ideal energy absorption structure.

Information content of JWST spectra of WASP-39b

The era of James Webb Space Telescope (JWST) transmission spectroscopy of exoplanetary atmospheres commenced with the study of the Saturn-mass gas giant WASP-39b as part of the Early Release Science (ERS) program. WASP-39b was observed using several different JWST instrument modes (NIRCam, NIRISS, NIRSpec G395H and NIRSpec PRISM) and the spectra were published in a series of papers by the ERS team. The current study examines the information content of these spectra measured using the different instrument modes, focusing on the complexity of the temperature-pressure profiles and number of chemical species warranted by the data. We examine if the molecules H2O CO CO2 K H2S CH4 and SO2 are detected in each of the instrument modes. Two Bayesian inference methods are used to perform atmospheric retrievals: the standard nested sampling method, as well as the supervised machine learning method of the random forest (trained on a model grid). For nested sampling, Bayesian model comparison is used as a guide to identify the set of models with the required complexity to explain the data. Generally, non-isothermal transit chords are needed to fit the transmission spectra of WASP-39b, although the complexity of the temperature-pressure profile required is mode-dependent. The minimal set of chemical species needed to fit a spectrum is mode-dependent as well, and also depends on whether grey or non-grey clouds are assumed. When a non-grey cloud model is used to fit the NIRSpec G395H spectrum, it generates a spectral continuum that compensates for the water opacity. The same compensation is absent when fitting the non-grey cloud model to the NIRSpec PRISM spectrum (which has broader wavelength coverage), suggesting that it is spurious. The interplay between the cloud spectral continuum and the water opacity determines if sulphur dioxide is needed to fit either spectrum. The inferred elemental abundances of carbon and oxygen and the carbon-to-oxygen (C/O) ratios are all mode- and model-dependent, and should be interpreted with caution. Bayesian model comparison does not always offer a clear path forward for favouring specific retrieval models (e.g. grey versus non-grey clouds) and thus for enabling unambiguous interpretations of exoplanet spectra.

Scalable inference with autoregressive neural ratio estimation

ABSTRACT In recent years, there has been a remarkable development of simulation-based inference (SBI) algorithms, and they have now been applied across a wide range of astrophysical and cosmological analyses. There are a number of key advantages to these methods, centred around the ability to perform scalable statistical inference without an explicit likelihood. In this work, we propose two technical building blocks to a specific sequential SBI algorithm, truncated marginal neural ratio estimation (TMNRE). In particular, first, we develop autoregressive ratio estimation with the aim to robustly estimate correlated high-dimensional posteriors. Secondly, we propose a slice-based nested sampling algorithm to efficiently draw both posterior samples and constrained prior samples from ratio estimators, the latter being instrumental for sequential inference. To validate our implementation, we carry out inference tasks on three concrete examples: a toy model of a multidimensional Gaussian, the analysis of a stellar stream mock observation, and finally, a proof-of-concept application to substructure searches in strong gravitational lensing. In addition, we publicly release the code for both the autoregressive ratio estimator and the slice sampler.

A taxonomic revision of the Palaearctic species of the ant genus Tapinoma Mayr 1861 (Hymenoptera: Formicidae)

A taxonomic revision of the Palaearctic species of the ant genus Tapinoma Emery 1861 is provided. Due to the extreme rarity of discernable characters, the female castes of 64% of the species are not separable by primary visual perception of an expert and are thus truly cryptic. The main working rationale of the revision is Numeric Morphology-Based Alpha-Taxonomy (NUMOBAT) with formation of species hypotheses largely based on exploratory data analyses and checking these hypotheses by discriminant analysis. NUMOBAT data of all considered species comprise 648 worker samples with 2014 individuals and 30,000 primary data. Species are depicted by z-stack imaging in three standard visual positions. Numeric data on 15 phenotypical characters are presented in comparative tables and supplementary verbal descriptions are given. Analysis of nuclear DNA was based on evaluation of 15 microsatellite loci in 274 nest samples. The NUMOBAT-based classification of eight species of the Tapinoma nigerrimum and T. simrothi group which are inseparable by subjective visual inspection was confirmed by nuclear DNA data in 98.3% of 169 samples where both morphological and nuDNA data were available. The three cases of disagreement between NUMOBAT and nuDNA classification were discussed. Excluding Nomina Nuda and unavailable names, the revision recognized 34 available names which divide into 21 valid species, 11 junior synonyms and two names placed under Incertae Sedis. Four species are described as new: Tapinoma hispanicum n. sp., T. insularis n. sp., T. dabashanica n. sp. and T. sichuense n. sp. The following synonymies were stated: T. collina Foerster 1850, T. erraticum platyops Emery 1925 and T. erraticum bononiensis Emery 1925 as synonyms of T. erraticum (Latreille 1798); T. tauridis Emery 1925 and T. breve Emery 1925 as synonyms of T. glabrella (Nylander 1849) that is erected to species level; T. minor Bernard 1945 as synonym of T. simrothi Krausse-Heldrungen 1911; T. simrothi azerbaidzhanica Karavajev 1932 as synonym of Tapinoma karavaievi Emery 1925 that is erected here to species level; T. erraticum ambiguum Emery 1925 as synonym of T. madeirense Forel 1895 and T. emeryanum Kuznetzov-Ugamsky 1927 as synonym of T. sinense Emery 1925. Despite an insufficient separation of the female castes of Tapinoma madeirense and T. subboreale Seifert 2011 by NUMOBAT characters and detection of a hybrid zone in southern France, the heterospecific status of the two taxa was maintained based on sufficient differences in male genitalia and of nuclear DNA over a larger geographic scale. Formica caerulescens Losana 1834 is removed from genus Tapinoma and recognized as member of the subfamily Formicinae.

XookSuut: A BAYESIAN TOOL FOR MODELING CIRCULAR AND NON–CIRCULAR FLOWS ON 2D VELOCITY MAPS

We present XookSuut, a Python implementation of the DiskFit algorithm, optimized to perform robust Bayesian inference on parameters describing models of circular and noncircular rotation in galaxies. XookSuut surges as a Bayesian alternative for kinematic modeling of 2D velocity maps; it implements effcient sampling methods, specifically Markov Chain Monte Carlo (MCMC) and Nested Sampling (NS), to obtain the posteriors and marginalized distributions of kinematic models including circular motions, axisymmetric radial flows, bisymmetric flows, and harmonic decomposition of the LoS velocity. In this way, kinematic models are obtained by pure sampling methods, rather than standard minimization techniques based on the Χ2. All together, XookSuut represents a sophisticated tool for deriving rotational curves and to explore the error distribution and covariance between parameters.

Bilby in space: Bayesian inference for transient gravitational-wave signals observed with LISA

ABSTRACT The Laser Interferometer Space Antenna (LISA) is scheduled to launch in the mid-2030s, and is expected to observe gravitational-wave candidates from massive black hole binary mergers, extreme mass ratio inspirals, and more. Accurately inferring the source properties from the observed gravitational-wave signals is crucial to maximize the scientific return of the LISA mission. bilby, the user-friendly Bayesian inference library, is regularly used for performing gravitational-wave inference on data from existing ground-based gravitational-wave detectors. Given that Bayesian inference with LISA includes additional subtitles and complexities beyond its ground-based counterpart, in this work we introduce bilby_lisa , a python package that extends bilby to perform parameter estimation with LISA. We show that full nested sampling can be performed to accurately infer the properties of LISA sources from transient gravitational-wave signals in (a) zero noise and (b) idealized instrumental noise. By focusing on massive black hole binary mergers, we demonstrate that higher order multipole waveform models can be used to analyse a year’s worth of simulated LISA data, and discuss the computational cost and performance of full nested sampling compared with techniques for optimizing likelihood calculations, such as the heterodyned likelihood.

Multidisciplinary providers’ perceptions of care delivery for sleep disorders: A qualitative case study

ObjectivesSleep disorders are wide-ranging in their causes and impacts on other physical and mental health conditions. Thus, sleep disorders could benefit from a multidisciplinary approach to assessment and treatment. An integrated care model is often recommended but is costly to implement. We sought to understand how, in the absence of an established organizational structure for integrated sleep care, providers from different clinics work together to provide care for sleep disorders. MethodsA qualitative case study at one U.S. Department of Veterans Affairs (VA) medical center. We used a purposeful nested sampling strategy, combining maximum variation sampling and snowball sampling to recruit key staff involved in sleep care. ResultsWe interviewed providers (N = 10) from sleep medicine, primary care, and mental health services. Providers identified the ubiquity of sleep disorders and a concomitant need for multidisciplinary care. However, they described limited opportunities for multidisciplinary interactions and consequently a negative impact on clinical care. Providers described fragmentation in two areas: among sleep specialists and between sleep specialists and other referring and managing providers. ConclusionsA range of interventions, based on setting and resources, could improve care coordination both among sleep specialists and between sleep and nonsleep providers. While integrated sleep specialist clinics could reduce care fragmentation, they may not directly impact coordination with referring providers, like primary care and general mental health, who are essential in managing chronic conditions. Future work should continue to explore improving care coordination for sleep problems to ensure patients receive high-quality, timely, patient-centered care.

Parameter Inference of a State-of-the-Art Physical Afterglow Model for GRB 190114C

A state-of-the-art semi-analytic gamma-ray burst (GRB) afterglow model with synchrotron self-Compton (SSC) emission has been applied for the first time for parameter inference using real GRB data. We analyzed the famous GRB 190114C as a case study. GRB 190114C, characterized by its long duration and high luminosity, was observed by many ground-based and orbiting telescopes spanning a wide range of electromagnetic wavelengths, from radio to GeV gamma rays. We used two advanced algorithms for inference: a nested sampling algorithm called UltraNest and an MCMC algorithm emcee. Evoking the standard afterglow model, the inference result and the best-fit values lead to an initial bulk Lorentz factor (a rough estimate of Γ=526), which aligns with the values often seen in GRBs identified by the Fermi-LAT instrument. Similarly to the best-fit values of other studies in the literature, the derived values of microphysical parameters, the circumburst density, and the kinetic efficiency are consistent with those found after modeling the multi-wavelength observations in GRB 190114C. We show that the SSC from the forward-shock region can only describe the highest-energy photons above a few GeVs.

Swiftlet Bird's Nest (Collocalia fuciphaga) from West Sumatra as a Functional Food and Its Nutritional Content

Functional foods contain biologically active components and compounds that have physiological effects on the human body, such as promoting health and decreasing the risk of sickness. The swiftlet, which belongs to the Collocalini family, is an insect-eating bird that migrates across the Indian Ocean, Southeast Asia, and northern Australia to the Pacific Ocean. Swiftlet bird's nests (SBN) contain protein, fats, carbohydrates, iron, calcium, phosphorus, inorganic salts, fiber, and water. The objective of this study is to determine the nutritional content of swiftlet bird nests in different regions of West Sumatra. Samples of swiftlet bird's nests (SBN) were collected from Padang City (PD), Bukittinggi City (BK), and Pesisir Selatan Regency (PS). Nutritional content was analyzed using proximate methods, including moisture, protein, and fat, and the nitrite concentration was measured using UV-Vis spectrophotometry. The study found that SBN in West Sumatra contains 47.65–50.55% protein, 1.48–2.47% fat, 21.77–22.77% water, and 24.75–32.72 ppm nitrite. The results indicate that the nutritional content varies among the samples, and the protein content found in SBN is higher, making it suitable for use as a functional food. Additionally, SBN has many health benefits and biological activities, such as mitogenic response and cell growth, enhanced immunity, and improved bone strength.