Current Models Research Articles

General model of nonradiative excitation energy migration on a spherical nanoparticle with attached chromophores

Theory of multistep excitation energy migration within the set of chemically identical chromophores distributed on the surface of a spherical nanoparticle is presented. The Green function solution to the master equation is expanded as a diagrammatic series. Topological reduction of the series leads to the expression for emission anisotropy decay. The solution obtained behaves very well over the whole time range and it remains accurate even for a high number of the attached chromophores. Emission anisotropy decay depends strongly not only on the number of fluorophores linked to the spherical nanoparticle but also on the ratio of critical radius to spherical nanoparticle radius, which may be crucial for optimal design of antenna-like fluorescent nanostructures. The results for mean squared excitation displacement are provided as well. Excellent quantitative agreement between the theoretical model and Monte–Carlo simulation results was found. The current model shows clear advantage over previously elaborated approach based on the Padé approximant.

Dynamic pricing on maximum concurrency for heterogeneous instances using hyperparameter optimization in dueling deep reinforcement learning in a multi-cloud scenario

Users possess the option to rent instances of various sorts, in a variety of regions, and a variety of availability zones, thanks to cloud service carriers like AWS, GCP, and Azure. In the cloud business right now, fixed price models are king when it comes to pricing. However, as the diversity of cloud providers and users grows, this approach is unable to accurately reflect the market’s current needs for cost savings. As a consequence, a dynamic pricing strategy has become a desirable tactic to better handle the erratic cloud demand. In this study, a deep learning model was used to propose a dynamic pricing structure that ensures service providers are treated fairly in a multi-cloud context. The computational optimization of DL approaches can be severely hampered by the requirement for human hyperparameter selection. Traditional automated solutions to this issue have inadequate durability or fail in specific circumstances. To choose the hyper-parameters in the Dueling Deep Q-Network (DDQN), the hybrid DL approach in this study uses the concept-based wild horse optimization (WHO) method. A community of untamed horses is evolved, and the fitness of the population is evaluated concurrently to estimate the optimum hyper-parameters. The plan changes the price appropriately to promote the use of underutilized resources and discourage the use of overutilized resources. The evaluation’s findings demonstrated that the suggested strategy can lower end-user costs while conducting compute- and data-intensive activities in a multi-cloud environment. The research was concluded by comparing current models after the results were analyzed using various performance indicators.

A new model for spatial rods incorporating surface energy effects

A new non-classical model for spatial rods incorporating surface energy effects is developed using a surface elasticity theory. A variational formulation based on the principle of minimum total potential energy is employed, which leads to the simultaneous determination of the equilibrium equations and complete boundary conditions. The newly developed spatial rod model contains three surface elasticity constants to account for surface energy effects. The new model recovers the classical elasticity-based Kirchhoff rod model as a special case when the surface energy effects are not considered. To illustrate the new spatial rod model, two sample problems are analytically solved by directly applying the general formulas derived. The first one is the buckling of an elastic rod of circular cross-section with fixed-pinned supports, and the other is the equilibrium analysis of a helical rod deformed from a straight rod. An analytical formula is derived for the critical buckling load required to perturb the axially compressed straight rod, and two closed-form expressions are obtained for the force and couple needed in deforming the helical rod. These formulas reduce to those based on classical elasticity when the surface energy effects are suppressed. For the buckling problem, it is found that the critical buckling load predicted by the current new model is always higher than that given by the classical elasticity-based model, and the difference between the two sets of predicted values is significantly large when the radius of the rod is sufficiently small but diminishes as the rod radius increases. For the helical rod problem, the numerical results reveal that the force and couple predicted by the current model are, respectively, significantly larger and smaller than those predicted by the classical model when the rod radius is very small, but the difference is diminishing with the increase of the rod radius.

On the Inadequacy of the Current Transgenic Animal Models of Alzheimer's Disease: The Path Forward.

For at least two reasons, the current transgenic animal models of Alzheimer's disease (AD) appear to be patently inadequate. They may be useful in many respects, the AD models; however, they are not. First, they are incapable of developing the full spectrum of the AD pathology. Second, they respond spectacularly well to drugs that are completely ineffective in the treatment of symptomatic AD. These observations indicate that both the transgenic animal models and the drugs faithfully reflect the theory that guided the design and development of both, the amyloid cascade hypothesis (ACH), and that both are inadequate because their underlying theory is. This conclusion necessitated the formulation of a new, all-encompassing theory of conventional AD-the ACH2.0. The two principal attributes of the ACH2.0 are the following. One, in conventional AD, the agent that causes the disease and drives its pathology is the intraneuronal amyloid-β (iAβ) produced in two distinctly different pathways. Two, following the commencement of AD, the bulk of Aβ is generated independently of Aβ protein precursor (AβPP) and is retained inside the neuron as iAβ. Within the framework of the ACH2.0, AβPP-derived iAβ accumulates physiologically in a lifelong process. It cannot reach levels required to support the progression of AD; it does, however, cause the disease. Indeed, conventional AD occurs if and when the levels of AβPP-derived iAβ cross the critical threshold, elicit the neuronal integrated stress response (ISR), and trigger the activation of the AβPP-independent iAβ generation pathway; the disease commences only when this pathway is operational. The iAβ produced in this pathway reaches levels sufficient to drive the AD pathology; it also propagates its own production and thus sustains the activity of the pathway and perpetuates its operation. The present study analyzes the reason underlying the evident inadequacy of the current transgenic animal models of AD. It concludes that they model, in fact, not Alzheimer's disease but rather the effects of the neuronal ISR sustained by AβPP-derived iAβ, that this is due to the lack of the operational AβPP-independent iAβ production pathway, and that this mechanism must be incorporated into any successful AD model faithfully emulating the disease. The study dissects the plausible molecular mechanisms of the AβPP-independent iAβ production and the pathways leading to their activation, and introduces the concept of conventional versus unconventional Alzheimer's disease. It also proposes the path forward, posits the principles of design of productive transgenic animal models of the disease, and describes the molecular details of their construction.

A novel cost-palatability bi-objective approach to the menu planning problem with an innovative similarity metric using a path relinking algorithm

Bad eating habits are considered with low exercise, tobacco, and alcohol use, among the greatest health risk factors in high-income countries. Here, the spread of non-communicable diseases related to diet contrasts with the increasing availability of diet guidelines and health information. We are all left wondering, why are we not eating healthier? Palatability and cost appear as the two most important barriers to adherence to any prescribed diet. This work aims to generate high-adherence healthy menus attending to Mediterranean standards, modelling and solving a cost palatability bi-objective optimisation problem. Although the latter is implicitly considered in most current models, its use as a quantifiable objective is novel. For this, a novel Similarity Function is introduced, which evaluates the proximity of two different menus and returns a similarity metric between 0 and 1. A multi-criteria optimisation method is used to design nutritious menu plans and analyse the trade-off between the cost and palatability of menus. A Path Relinking algorithm is later applied to improve the objective values, with specific considerations to palatability, designing healthy menus that can beat those adherence barriers.

Constraints on regional projections of mean and extreme precipitation under warming

The projected changes in the hydrological cycle under global warming remain highly uncertain across current climate models. Here, we demonstrate that the observational past warming trend can be utilized to effectively co1nstrain future projections in mean and extreme precipitation on both global and regional scales. The physical basis for such constraints relies on the relatively constant climate sensitivity in individual models and the reasonable consistency of regional hydrological sensitivity among the models, which is dominated and regulated by the increases in atmospheric moisture. For the high-emission scenario, on the global average, the projected changes in mean precipitation are lowered from 6.9 to 5.2% and those in extreme precipitation from 24.5 to 18.1%, with the inter-model variances reduced by 31.0 and 22.7%, respectively. Moreover, the constraint can be applied to regions in middle-to-high latitudes, particularly over land. These constraints result in spatially resolved corrections that deviate substantially and inhomogeneously from the global mean corrections. This study provides regionally constrained hydrological responses over the globe, with direct implications for climate adaptation in specific areas.

Evaluating and Improving the Metropolitan Economic Freedom Index

AbstractThe Metropolitan Economic Freedom Index (MEFI) ranks cities based on their support of free market enterprise. In its current state, MEFI purports to measure three constructs (government spending, taxation, and labor market freedom) with three equally weighted variables for each one, assuming perfect substitutability of variables. This study investigates the statistical consistency of MEFI through Confirmatory Factor Analysis. Multiple models investigate current variable selection by providing a potentially better indicator of labor market freedom, aggregation assumptions by removing the requirements for fixed and equal weights, and statistical consistency by evaluating the fit between the data and models. Results indicate that the current MEFI model is not statistically consistent with the data, that weighting of variables should not be equal, that variable selection should be investigated, and that constructs should be re-imagined. The models investigated provide an initial starting point for redefining MEFI.

(007) Impact of Non-Invasive Oestrus Synchronization on Sexual Behavior in Intact Sprague Dawley Rats

Abstract Introduction Female sexual behavior animal translation data do not translate to acute results and neither current synchronization invasive models (ovariectomy+Estrogen “E2”+Progesterone “P4”) guarantee hormonal physiological values. Objective Therefore, our study investigated the effect of non-invasive oestrus synchronization on sexual behavior. Methods Methods: Twelve week old Sprague Dawley intact rats were synchronized and randomly divided into three groups each of n=8-10. Each group received a dose of prostaglandin F2α “PGF2α” (75, 125 and 250 μg) at days 0 and 3, and 1 mg of progesterone at day four. Vaginal cytology was performed to determine the point of the cycle and the animals underwent an incentive test. To investigate the sexual behavior, the synchronized female rats were paired with trained male rats, and behavior recorded. The videos were quantified by trained operators. Sexual behavior was quantified as paracopulatory (hops, darts, ear wiggling, sniffing from male and from female) or copulatory (male mounting female, thrusting from male, intromission, ejaculation, female for sniffing position, lordosis, orgasm, female mounting on male, female rotation in her axis and female licking itself), E2 and Follicle Stimulating hormone (FSH) in plasma and E2 in vaginal fluid were quantified by immune assay. Results Based on the vaginal cytology, the proportion of animals in proestrus (p), estrus (e) or metestrus (m) was calculated with values of 0.5 (p), 0.25 (e) and 0.25 (m) for the group which received 0.75 μg PGF2α; 0.4 (p), and 0.6 (e) for the group which received 0.125 μg PGF2α; 0.2 (p), 0.5 (e), and 0.3 (m) for the group which received 250 μg PGF2α. The numbers of hops was higher in the proestrus compared to the metestrus, and of mounts higher in the estrus compared to the metestrus phase. The sexual encounter profile and E2 levels were unchanged with the different PGF2α doses, but in the high-dose group no hops were observed. The levels of sexual behavior was comparable to previous studies of hormone substituted ovariectomized rats, but E2 and FSH plasma levels were in a physiological range. Conclusions In summary, the non-invasive synchronization protocol could substitute the state-of-the-art used ovariectomized+hormone (E2) model. Our findings suggest the largest part of rats were synchronized in the oestrus phase with 125 μg PGF2α. but the 250 μg had also a positive profile. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: Initiator Pharma A/S.

Enhancing TCR specificity predictions by combined pan- and peptide-specific training, loss-scaling, and sequence similarity integration.

Predicting the interaction between Major Histocompatibility Complex (MHC) class I-presented peptides and T-cell receptors (TCR) holds significant implications for vaccine development, cancer treatment, and autoimmune disease therapies. However, limited paired-chain TCR data, skewed towards well-studied epitopes, hampers the development of pan-specific machine-learning (ML) models. Leveraging a larger peptide-TCR dataset, we explore various alterations to the ML architectures and training strategies to address data imbalance. This leads to an overall improved performance, particularly for peptides with scant TCR data. However, challenges persist for unseen peptides, especially those distant from training examples. We demonstrate that such ML models can be used to detect potential outliers, which when removed from training, leads to augmented performance. Integrating pan-specific and peptide-specific models alongside with similarity-based predictions, further improves the overall performance, especially when a low false positive rate is desirable. In the context of the IMMREP22 benchmark, this modeling framework attained state-of-the-art performance. Moreover, combining these strategies results in acceptable predictive accuracy for peptides characterized with as little as 15 positive TCRs. This observation places great promise on rapidly expanding the peptide covering of the current models for predicting TCR specificity. The NetTCR 2.2 model incorporating these advances is available on GitHub (https://github.com/mnielLab/NetTCR-2.2) and as a web server at https://services.healthtech.dtu.dk/services/NetTCR-2.2/.

Time-dependent Darcy–Forchheimer flow of Casson hybrid nanofluid comprising the CNTs through a Riga plate with nonlinear thermal radiation and viscous dissipation

Abstract Carbon nanotubes (CNTs) are gaining popularity due to their expanding uses in industrial and technical processes, such as geothermal reservoirs, water and air filters, coatings, solar collection, ceramic material reinforcement, electrostatic dissipation, etc. In addition, the CNTs have superior electrical conductivity and biocompatibility. Based on the aforementioned applications, the current work examines the time-dependent and Darcy–Forchheimer flow of water/glycerin-based Casson hybrid nanofluid formed by single-walled CNTs and multi-walled CNTs over a Riga plate under velocity slip. The energy expression is modeled through nonlinear thermal radiation and viscous dissipation impacts. The incorporation of convective boundary condition into the current model improves its realism. By employing suitable variables, the governing models are re-framed into ordinary differential equations. The bvp4c and the homotopy analysis method are used to find the computational results of the re-framed equations and boundary conditions. The novel characteristics of a variety of physical parameters on velocity, temperature, skin friction coefficient (SFC), and local Nusselt number (LNN) are discussed via graphs, charts, and tables. It is found that the fluid velocity decays when enriching the Forchheimer number, unsteady and porosity parameters. The radiation parameter plays an opposite role in convective heating and cooling cases. The modified Hartmann number enhances the surface drag force, and the Forchheimer number declines the SFC. The unsteady parameter develops the heat transfer rate, and the Forchheimer number suppresses the LNN. The simulated flow problem has many applications in engineering sectors, including ceramic manufacture, heating and cooling systems, energy storage units, thermodynamic processes, and other fields.

Site-specific regulation of Th2 differentiation within lymph node microenvironments.

T helper 2 (Th2) responses protect against pathogens while also driving allergic inflammation, yet how large-scale Th2 responses are generated in tissue context remains unclear. Here, we used quantitative imaging to investigate early Th2 differentiation within lymph nodes (LNs) following cutaneous allergen administration. Contrary to current models, we observed extensive activation and "macro-clustering" of early Th2 cells with migratory type-2 dendritic cells (cDC2s), generating specialized Th2-promoting microenvironments. Macro-clustering was integrin-mediated and promoted localized cytokine exchange among T cells to reinforce differentiation, which contrasted the behavior during Th1 responses. Unexpectedly, formation of Th2 macro-clusters was dependent on the site of skin sensitization. Differences between sites were driven by divergent activation states of migratory cDC2 from different dermal tissues, with enhanced costimulatory molecule expression by cDC2 in Th2-generating LNs promoting prolonged T cell activation, macro-clustering, and cytokine sensing. Thus, the generation of dedicated Th2 priming microenvironments through enhanced costimulatory molecule signaling initiates Th2 responses in vivo and occurs in a skin site-specific manner.

Above and Beyond Number of Illnesses: A Two-Sample Replication of Current Approaches to Depressive Symptoms in Multimorbidity

ABSTRACT Objectives To expand current models of depressive symptoms in older adults with multimorbidity (MM) beyond the number of illnesses as a predictor of worsened mental health. Methods Two-sample replication study of adults ≥62 years old with ≥ two chronic illnesses, who completed validated questionnaires assessing depressive symptoms, and disease- and treatment-related stressors. Data were analyzed using hierarchical linear regression. Results The model of cumulative number of illnesses was worse at explaining variance in depressive symptoms (Sample 1 R2 = .035; Sample 2 R2 = .029), compared to models including disease- and treatment-related stressors (Sample 1 R2 = .37; Sample 2 R2 = .47). Disease-related stressors were the strongest factor associated with depressive symptoms, specifically, poor subjective cognitive function (Sample 1: b = -.202, p = .013; Sample 2: b = -.288, p < .001) and greater somatic symptoms (b = .455, p < .001; Sample 2: b = .355, p < .001). Conclusions Using the number of illnesses to understand depressive symptoms in MM is a limited approach. Models that move beyond descriptive relationships between MM and depressive symptoms are needed. Clinical implications Providers should consider the role of somatic symptom management in patients with MM and depressive symptoms.

Accelerating randomized image secret sharing with GPU: contrast enhancement and secure reconstruction using progressive and convolutional approaches

AbstractImage Secret Sharing (ISS) is a cryptographic technique used to distribute secret images among multiple users. However, current Visual Secret Sharing (VSS) schemes produce a halftone image with only 50% contrast when reconstructing the original image. To overcome this limitation, the Randomized Image Secret Sharing (RISS) scheme was introduced. RISS achieves a higher contrast of 70% when extracting the secret image but comes with a high computational cost. This research paper presents a novel approach called Graphics Processing Unit (GPU)-based Randomized Image Secret Sharing (GRISS), which utilizes data parallelism within the RISS pipeline. The proposed technique also incorporates an Autoencoder-based Single Image Super-Resolution (ASISR) to enhance the contrast of the recovered image. The performance of GRISS is evaluated against RISS, and the contrast of the ASISR images is compared to current benchmark models. The results demonstrate that GRISS outperforms state-of-the-art models in both efficiency and effectiveness.

From pre-clinical to translational brain metastasis research: current challenges and emerging opportunities.

Brain metastasis, characterized by poor clinical outcomes, is a devastating disease. Despite significant mechanistic and therapeutic advances in recent years, pivotal improvements in clinical interventions have remained elusive. The heterogeneous nature of the primary tumor of origin, complications in drug delivery across the blood-brain barrier, and the distinct microenvironment collectively pose formidable clinical challenges in developing new treatments for patients with brain metastasis. Although current preclinical models have deepened our basic understanding of the disease, much of the existing research on brain metastasis has employed a reductionist approach. This approach, which often relies on either in vitro systems or in vivo injection models in young and treatment-naive mouse models, does not give sufficient consideration to the clinical context. Given the translational importance of brain metastasis research, we advocate for the design of preclinical experimental models that take into account these unique clinical challenges and align more closely with current clinical practices. We anticipate that aligning and simulating real-world patient conditions will facilitate the development of more translatable treatment regimens. This brief review outlines the most pressing clinical challenges, the current state of research in addressing them, and offers perspectives on innovative metastasis models and tools aimed at identifying novel strategies for more effective management of clinical brain metastasis.

“At the End of the Day it’s Their choice”: An Exploratory Qualitative Study of Pregnancy Options Counseling

ABSTRACT This study’s purpose was to explore the current models and approaches of pregnancy options counseling across three types of agency settings in a Northeastern state. Additionally, this study aimed to determine if individuals who receive pregnancy options counseling obtained medically factual, non-directive, and non-biased information needed to make informed decisions related to their pregnancy decisions. Using qualitative research methodology, semi-structured interviews were conducted with 10 participants across three different agency settings in one state in the Northeastern United States. Results indicated agencies shared a definition of pregnancy options counseling. Outcomes also suggest agency type impacted how pregnancy options counseling was delivered, as variations were found in education provided to patients. Lastly, the interviews imply no standardized model or training for pregnancy options counselors is currently being used.

Unveiling the origin of the optical and UV emission during the 2017 giant outburst of the Galactic ULX pulsar Swift J0243.6+6124

Context. From late September 2017 to January 2018, the Be X-ray binary (BeXB) Swift J0243.6+6124 underwent a giant outburst that was unprecedently bright. The reported X-ray luminosities were so high that the system was classified as an ultraluminous X-ray source (ULX). It was also the first BeXB pulsar to show radio jet emission. The source was not only bright in X-rays and radio, but also in the optical and ultraviolet (UV) wavelenghts as well. Aims. In this work, we aim to understand the origin of the observed optical/UV fluxes simultaneous to the X-ray emission. Methods. We studied the optical/UV light curves in comparison with the X-ray fluxes along the outburst. We considered the main mechanisms that can explain the optical/UV emission in X-ray binaries. Due to the tight correlation observed between the optical/UV and X-ray light curves, reprocessing of X-rays seems to be the most plausible explanation. We calculated the timescales of the light curve decays and studied the correlation indexes between the optical and X-ray emission. Finally, we built a physical model that considers the X-ray heating of the surface of the donor star, irradiation of the accretion disk, and emission from a viscously heated accretion disk, so that we could reproduce the observed optical/UV spectral energy distributions (SEDs) along the outburst. In our model, we considered the Be circumstellar disk to be co-planar to the orbit and then we neglected its irradiation in the current model. As an input for the model, we used as incident X-ray luminosities those calculated from the bolometric X-ray fluxes obtained from the spectral fit of the Swift/XRT and BAT observations. Results. The timescales of the exponential decay of the outburst are between two and four times longer for the UV and optical light curves than for the X-ray light curve. The correlation index between the optical/UV and X-ray fluxes varies between optical/UV filters and when different X-ray bands are considered and is larger for the rise than for the decay phase of the outburst for the fluxes at redder wavelengths. The modelling of the SED shows that X-ray heating of the companion star surface is the main mechanism contributing to the UV emission and contributes significantly to the optical emission during the whole outburst. The X-ray irradiation of the accretion disk is necessary to reproduce the optical observed fluxes from MJD 58047 to 58120 and contributes significantly to the UV fluxes close to the peak of the outburst. As a first attempt, the fits yield an increasing value of the outer radius of the accretion disk along the outburst. An alternative interpretation points to variations in the geometry of the inner flow and the fraction of reprocessed X-ray emission during the outburst. On the other hand, variations in the geometry of the Be circumstellar disk could also play a role, but they have not been considered in the current model. Conclusions. Reprocessing of X-rays via the X-ray heating of the Be star surface and as irradiation of the accretion disk is the main mechanism that can reproduce the observed optical/UV emission during the 2017−2018 giant outburst of Swift J0243.6+6124.

Flow resistance of phloem sieve plates revisited using an experimental model

Flow resistance of phloem sieve plates revisited using an experimental model

Estimates of Southern Hemispheric Gravity Wave Momentum Fluxes across Observations, Reanalyses, and Kilometer-Scale Numerical Weather Prediction Model

Abstract Gravity waves (GWs) are among the key drivers of the meridional overturning circulation in the mesosphere and upper stratosphere. Their representation in climate models suffers from insufficient resolution and limited observational constraints on their parameterizations. This obscures assessments of middle atmospheric circulation changes in a changing climate. This study presents a comprehensive analysis of stratospheric GW activity above and downstream of the Andes from 1 to 15 August 2019, with special focus on GW representation ranging from an unprecedented kilometer-scale global forecast model (1.4 km ECMWF IFS), ground-based Rayleigh lidar (CORAL) observations, modern reanalysis (ERA5), to a coarse-resolution climate model (EMAC). Resolved vertical flux of zonal GW momentum (GWMF) is found to be stronger by a factor of at least 2–2.5 in IFS compared to ERA5. Compared to resolved GWMF in IFS, parameterizations in ERA5 and EMAC continue to inaccurately generate excessive GWMF poleward of 60°S, yielding prominent differences between resolved and parameterized GWMFs. A like-to-like validation of GW profiles in IFS and ERA5 reveals similar wave structures. Still, even at ∼1 km resolution, the resolved waves in IFS are weaker than those observed by lidar. Further, GWMF estimates across datasets reveal that temperature-based proxies, based on midfrequency approximations for linear GWs, overestimate GWMF due to simplifications and uncertainties in GW wavelength estimation from data. Overall, the analysis provides GWMF benchmarks for parameterization validation and calls for three-dimensional GW parameterizations, better upper-boundary treatment, and vertical resolution increases commensurate with increases in horizontal resolution in models, for a more realistic GW analysis. Significance Statement Gravity wave–induced momentum forcing forms a key component of the middle atmospheric circulation. However, complete knowledge of gravity waves, their atmospheric effects, and their long-term trends are obscured due to limited global observations, and the inability of current climate models to fully resolve them. This study combines a kilometer-scale forecast model, modern reanalysis, and a coarse-resolution climate model to first compare the resolved and parameterized momentum fluxes by gravity waves generated over the Andes, and then evaluate the fluxes using a state-of-the-art ground-based Rayleigh lidar. Our analysis reveals shortcomings in current model parameterizations of gravity waves in the middle atmosphere and highlights the sensitivity of the estimated flux to the formulation used.

Total r-process Yields of Milky Way Neutron Star Mergers

While it is now known that the mergers of double neutron star binary systems (NSMs) are copious producers of heavy elements, there remains much speculation about whether they are the sole or even principal site of rapid neutron-capture (r-process) nucleosynthesis, one of the primary ways in which heavy elements are produced. The occurrence rates, delay times, and galactic environments of NSMs hold sway over estimating their total contribution to the elemental abundances in the solar system and the Galaxy. Furthermore, the expected elemental yields of NSMs may depend on the merger parameters themselves—such as their stellar masses and radii—which are not currently considered in many galactic chemical evolution models. Using the characteristics of the observed sample of double neutron star (DNS) systems in the Milky Way as a guide, we predict the expected nucleosynthetic yields that a population of DNSs would produce upon merger, and we compare that nucleosynthetic signature to the heavy-element abundance pattern of solar system elements. We find that with our current models, the present DNS population favors the production of lighter r-process elements, while underproducing the heaviest elements relative to the solar system. This inconsistency could imply an additional site for the heaviest elements or a population of DNSs much different from that observed today.

Efficient fault tolerant cost optimized approach for scientific workflow via optimal replication technique within cloud computing ecosystem

&lt;span lang="EN-US"&gt;Cloud computing is one of the dispersed and effective computing models, which offers tremendous opportunity to address scientific issues with big scale characteristics. Despite having such a dynamic computing paradigm, it faces several difficulties and falls short of meeting the necessary quality of services (QoS) standards. For sustainable cloud computing workflow, QoS is very much required and need to be addressed. Recent studies looked on quantitative fault-tolerant programming to reduce the number of copies while still achieving the reliability necessity of a process on the heterogeneous infrastructure as a service (IaaS) cloud. In this study, we create an optimal replication technique (ORT) about fault tolerance as well as cost-driven mechanism and this is known as optimal replication technique with fault tolerance and cost minimization (ORT-FTC). Here ORT-FTC employs an iterative-based method that chooses the virtual machine and its copies that have the shortest makespan in the situation of specific tasks. By creating test cases, ORT-FTC is tested while taking into account scientific workflows like CyberShake, laser interferometer gravitational-wave observatory (LIGO), montage, and sipht. Additionally, ORT-FTC is shown to be only slightly improved over the current model in all cases. &lt;/span&gt;