Merger Model Research Articles

MRI-drivenαΩ dynamos in protoneutron stars

Context.Magnetars are highly magnetized neutron stars that can produce a wide diversity of X-ray and soft gamma-ray emissions that are powered by magnetic dissipation. Their magnetic dipole is constrained in the range of 1014–1015G by the measurement of their spin-down. In addition to fast rotation, these strong fields are also invoked to explain extreme stellar explosions, such as hypernovae, which are associated with long gamma-ray bursts and superluminous supernovae. A promising mechanism for explaining magnetar formation is the amplification of the magnetic field by the magnetorotational instability (MRI) in fast-rotating protoneutron stars (PNS). This scenario is supported by recent global incompressible models, which showed that a dipole field with magnetar-like intensity can be generated from small-scale turbulence. However, the impact of important physical ingredients, such as buoyancy and density stratification, on the efficiency of the MRI in generating a dipole field is still unknown.Aims.We assess the impact of the density and entropy profiles on the MRI dynamo in a global model of a fast-rotating PNS. The model focuses on the outer stratified region of the PNS that is stable to convection.Methods.Using the pseudo-spectral code MagIC, we performed 3D Boussinesq and anelastic magnetohydrodynamics simulations in spherical geometry with explicit diffusivities and with differential rotation forced at the outer boundary. The thermodynamic background of the anelastic models was retrieved from the data of 1D core-collapse supernova simulations from the Garching group. We performed a parameter study in which we investigated the influence of different approximations and the effect of the thermal diffusion through the Prandtl number.Results.We obtain a self-sustained turbulent MRI-driven dynamo. This confirms most of our previous incompressible results when they are rescaled for density. The MRI generates a strong turbulent magnetic field and a nondominant equatorial dipole, which represents about 4.3% of the averaged magnetic field strength. Interestingly, an axisymmetric magnetic field at large scales is observed to oscillate with time, which can be described as a mean-fieldαΩ dynamo. By comparing these results with models without buoyancy or density stratification, we find that the key ingredient explaining the appearance of this mean-field behavior is the density gradient. Buoyancy due to the entropy gradient damps turbulence in the equatorial plane, but it has a relatively weak influence in the low Prandtl number regime overall, as expected from neutrino diffusion. However, the buoyancy starts to strongly impact the MRI dynamo for Prandtl numbers close to unity.Conclusions.Our results support the hypothesis that the MRI is able to generate magnetar-like large-scale magnetic fields. The results furthermore predict the presence of aαΩ dynamo in the protoneutron star, which could be important to model in-situ magnetic field amplification in global models of core-collapse supernovae or binary neutron star mergers.

Experimental investigation on evolution characteristics of high- and low-speed streaks in supersonic turbulent boundary layer

High-speed and low-speed streak structures in the near wall region of a turbulent boundary layer with a Mach number of 3 are experimentally examined by employing the spatiotemporally resolved nanoparticle plane laser scattering technique. The time evolution characteristics of the high-speed and low-speed streaks in the supersonic turbulent boundary layer are systematically investigated through the speed field sequence results at various time intervals. The obtained results reveal that the dynamic behavior of the bands is chiefly represented by the translation along the flow direction. The process of dissipation of the existing streaks and the formation of a new streak is also observed and analyzed. The duration values of the high-speed and low-speed streak structures are assessed by utilizing the time-resolved characteristics of the speed field, and the predicted duration of the streak structure and the maximum flow length exceed 306 µs and 23.6 times the thickness of the boundary layers, respectively. Finally, the merging phenomenon of medium and low-speed streaks in the turbulent boundary layer is carefully scrutinized. The merging of low-speed streaks observed under supersonic conditions is consistent with the vortex packet merging model proposed by Tomkins and Adrian.

Building a Merging and Acquisition Simulator by Knapsack and Dynamic Algorithm

Abstract: This research paper’s goal is to build a merger and acquisition simulator. Essentially, the simulation produces choices that can be compared, evaluated, and used to make decisions. The computer model was created so that users may alter the crucial decision-making factors that are involved in the purchase process. The simulator is a transaction analytics tool that proposes stock-level asset or product category swaps between a set of participating companies within an industry that optimize their positions in the market and are also cash efficient in execution. The user can define a set of rules, which set the boundaries of the proposed transactions that are evaluated in the simulation. The simulation tool is a transaction analytics tool that proposes portfolio-level asset or product category swaps between a set of participating companies within an industry that optimize their positions in the market and are also cash efficient in execution. Overview: The simulator offers a practical tool for developing and assessing various growth and diversification plans. If this procedure is oversimplified, the actual effects of the merger on the parent firm will become less clear, making both long-term and short-term financial planning very challenging. A model has been devised that makes use of a computer's capacity to quickly handle large amounts of data in order to get around several of these drawbacks. The long-term merger and acquisition computer model that has been created will optimize the impact that an acquisition will have on the parent company's earnings per share while taking into account the dividends received and the market value per share of the acquired firm.

Conflict management techniques for model merging: a systematic mapping review

Model merging conflicts occur when different stakeholders aim to integrate their contradicting changes that are applied concurrently to update software models. We conduct an extensive systematic mapping study on conflict management techniques and relevant collaboration attributes to the versioning and merging models from 2001 to the middle of 2021. This study follows the standard guidelines within the software engineering domain. We analyzed a total of 105 articles extracted from an initial pool of more than 1800 articles to infer a taxonomy for conflict management techniques. We use this taxonomy to classify existing approaches to understand characteristics, shortcomings, and challenges on conflict management techniques in merging models. It also provides a solid foundation for future work in this area. We show that syntactic conflicts are the most studied type and that the top three popular conflict detection techniques are constraint violation, change overlapping, and pattern matching. We observe the lack of a comprehensive state-of-the-art comparison between academic or industrial tools, as well as the need for real-world case studies. Finally, we show that recent trends have focused on online collaboration, where teams of stakeholders work on large-scale models.

Hostile takeovers or friendly mergers? Real options analysis

This study analyzes a real options model of mergers and acquisitions between two firms facing different but correlated uncertainties in profits. It is assumed that firms can choose between two alternatives: a hostile takeover or a friendly merger. The bidder firm obtains extra value in a hostile takeover but incurs takeover costs. Although both firms do not bear takeover costs in a friendly merger, they share extra value through Nash bargaining. We formally define an equilibrium in our timing game under competition and then characterize the equilibrium types to discuss the influences of demand uncertainty, and takeover cost on which firm will act as a bidder and which form of amalgamation will emerge. We show that various types of equilibria can emerge because of the introduction of takeover costs. We also show that a smaller firm can be a bidder to a larger firm in a hostile manner, which is occasionally observed in actual markets. Finally, we also show that a preemptive equilibrium is likely to emerge if the takeover cost (premium) increases, which is consistent with the empirical results.

Combined Safety and Coordination of Connected Automated Vehicles in Merging Area with Featuring Optimal Merging Positions

Freeway on-ramp merging area is deemed to be typical bottlenecks section, which leads to low traffic efficiency, congestions, and frequent accidents. Most existing studies on merging for the connected and automated vehicles focus on merging at a single fixed merging point. However, the problem of coordination between merging vehicle and arterial traffic flow in the acceleration lane is ignored in the existing studies. This study proposes a merging model, which combined safety and coordination of CAVs with featuring optimal merging positions. The proposed model has two stages: one is analysis of merging velocity of the insertable gap and the other one is determining constraint condition of cooperative merging. The outputs of first stage are interval of merging speed and the mergeable range. The outputs of second stage are optional insertable gap and the corresponding driving scheme. Then, a traffic simulation experiment is designed to evaluate the proposed model. The simulation results show that the proposed model can effectively guarantee driving safety and make the merging process smoother with 28.7% reduction in travel time for the CAV merging. Furthermore, the proposed model does not sacrifice the interests of surrounding traffic to assist in CAV merging. The results indicate the promising potential of using the proposed methods can approximately get a fair use of road resources for each CAV.

The Future Change in Evaporation Based on the CMIP6 Merged Data Generated by Deep-Learning Method in China

Land evaporation (LET) is an important variable in climate change, water cycle and water resources management. Mastering the projected changes in LET is significant for crop water requirements and the energy cycle. The global climate model (GCM) is a vital tool for future climate change research. However, the GCMs have low spatial resolution and relatively high errors. We use a deep learning (DL)-based model to deal with this problem. The DL approach can downscale the model data and merge simultaneously. We applied the DL approach to a suit of models from the Coupled Model Intercomparison Project 6th edition (CMIP6) LET data. From the result of all the evaluation metrics, the DL merged data greatly improved in both spatial and time dimensions. The mean RMSE is 5.85 mm and the correlation is 0.95 between the DL merged data and reference data (historical reliable evaporation data). The future LET evidently increases in four scenarios (SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5), and the upward intensity rises from the low to high emission scenarios. The highest increasing regions are in the Tibet Plateau and the south of China and the trend is larger than 10 mm/decade in the high scenarios. From the seasonal point of view, the increasing trend in spring and summer is far larger than for autumn and winter. The Tibet Plateau and the northeast of China have the largest upward trend in the spring of SSP5–8.5, higher than 1.6 mm/decade.

Geometric Singular Perturbation Analysis of a Multiple Time-scale Model for Diabetes and COVID-19 Comorbidity

More and more information on mortality and morbidity indicates that in order to fight the COVID-19 pandemic, it is important to focus our attention on comorbidities. Several reports evidence of how many elderly patients who become severely ill exhibit underlying illness such as cardiovascular disease, kidney disease, tumor, and more to our special attention here, type 2 diabetes. Better understanding of the mechanism underlying the comorbidity between different diseases requires merging models of systems across different time-scales. The model homogenization across multiple spatial and time scales poses an important challenge to researchers in the field of medical science. An approach that has been found relatively efficient in the analysis of such models is the use of singular perturbation technique. Here, we study a differential equation model system with multiple time scales which describes the diabetes and COVID-19 comorbidity. It tracks the changes in levels of plasma glucose, insulin, and functional-cells, incorporating insulin resistance and inflammation responses. The model is analyzed with the geometric singular perturbation technique, by which conditions on the system parameters may be derived to identify regions in which the system exhibits different dynamic behavior, whether the system would be stable, or eventually oscillate in a sustained fashion. Discussion of these conditions allows us to better understand how comorbidity mediates the development of life-threatening symptoms in a diabetic patient in order that proper care and treatment may be prescribed.

From Fiction to Function: Imagining New Instruments through Design Workshops

Abstract This article introduces a series of workshop activities carried out with expert musicians to imagine new musical instruments through design fiction. At the workshop, participants crafted nonfunctional prototypes of instruments they would want to use in their own performance practice. Through analysis of the workshop activities, a set of design specifications was developed that can be applied to the design of new digital musical instruments intended for use in real-world artistic practice. In addition to generating tangible elements for instrument design, the theories and models utilized, drawn from human–computer interaction and human-centered design, are offered as a possible model for merging the generation of creative ideas with functional design outputs in a variety of applications within and beyond music and the arts.

Simultaneous liver steatosis, fibrosis and iron deposition quantification with mDixon quant based on radiomics analysis in a rabbit model

PurposeTo evaluate the feasibility of simultaneous quantification of liver fibrosis, liver steatosis and abnormal iron deposition using mDixon Quant based on radiomics analysis, and to eliminate the interference among different histopathologic features. MethodsOne hundred and twenty rabbits that were administered CCl4 for 4–16 weeks and a cholesterol rich diet for the initial 4 weeks in the experimental group and 20 rabbits in the control group were examined using mDixon. Radiomics features of the whole liver were extracted from PDFF and R2* and radiomics models for discriminating steatosis: S0-S1 vs. S2-S4, fibrosis: F0–F2 vs. F3–F4 and iron deposition: normal vs. abnormal were constructed respectively and evaluated using receiver operating characteristic (ROC) curves with the histopathological results as reference standard. Combined corrected models merging the radscore and the other two histopathologic features were evaluated using multiple logistic regression analyses and compared with radiomics models. ResultsThe area under the ROC curve (AUC) of the radiomics model with PDFF features was 0.886 and 0.843 in the training and the test set, respectively, for the diagnosis of liver steatosis grade S0–1 and S2-S4. The radiomics model based on R2* features were 0.815 and 0.801 for distinguishing F0-F2 and F3-F4 and 0.831 and 0.738 for discriminating abnormal iron deposition in the training and test set, respectively. The corrected model for liver steatosis and fibrosis (0.944 and 0.912 in the test set) outperformed the radiomics models by eliminating the interference of histopathologic features(P < 0.05), but had comparable diagnostic performance for abnormal iron deposition(P > 0.05). ConclusionsIt is feasible for mDixon to simultaneously quantify whole liver steatosis, fibrosis and iron deposition based on radiomics analysis. It is valuable to minimize the interference of different pathological features for the assessment of liver steatosis and fibrosis.

A global test of jet structure and delay time distribution of short-duration gamma-ray bursts

ABSTRACTThe multimessenger joint observations of GW170817 and GRB170817A shed new light on the study of short-duration gamma-ray bursts (SGRBs). Not only did it substantiate the assumption that SGRBs originate from binary neutron star (BNS) mergers, but it also confirms that the jet generated by this type of merger must be structured, hence the observed energy of an SGRB depends on the viewing angle from the observer. However, the precise structure of the jet is still subject to debate. Moreover, whether a single unified jet model can be applied to all SGRBs is not known. Another uncertainty is the delay time-scale of BNS mergers with respect to star-formation history of the Universe. In this paper, we conduct a global test of both delay and jet models of BNS mergers across a wide parameter space with simulated SGRBs. We compare the simulated peak flux, redshift, and luminosity distributions with the observed ones and test the goodness-of-fit for a set of models and parameter combinations. Our simulations suggest that GW170817/GRB 170817A and all SGRBs can be understood within the framework of a universal structured jet viewed at different viewing angles. Furthermore, model invoking a jet plus cocoon structure with a lognormal delay time-scale is most favoured. Some other combinations (e.g. a Gaussian delay with a power-law jet model) are also acceptable. However, the Gaussian delay with Gaussian jet model and the entire set of power-law delay models are disfavoured.

Colour evolution of Betelgeuse and Antares over two millennia, derived from historical records, as a new constraint on mass and age

ABSTRACT After core hydrogen burning, massive stars evolve from blue-white dwarfs to red supergiants by expanding, brightening, and cooling within few millennia. We discuss a previously neglected constraint on mass, age, and evolutionary state of Betelgeuse and Antares, namely their observed colour evolution over historical times: We place all 236 stars bright enough for their colour to be discerned by the unaided eye (V ≤ 3.3 mag) on the colour-magnitude-diagram (CMD), and focus on those in the Hertzsprung gap. We study pre-telescopic records on star colour with historically critical methods to find stars that have evolved noticeably in colour within the last millennia. Our main result is that Betelgeuse was recorded with a colour significantly different (non-red) than today (red, B − V = 1.78 ± 0.05 mag). Hyginus (Rome) and Sima Qian (China) independently report it two millennia ago as appearing like Saturn (B − V = 1.09 ± 0.16 mag) in colour and ‘yellow’ (quantifiable as B − V = 0.95 ± 0.35 mag), respectively (together, 5.1σ different from today). The colour change of Betelgeuse is a new, tight constraint for single-star theoretical evolutionary models (or merger models). It is most likely located less than one millennium past the bottom of the red giant branch, before which rapid colour evolution is expected. Evolutionary tracks from MIST consistent with both its colour evolution and its location on the CMD suggest a mass of ∼14 M⊙ at ∼14 Myr. The (roughly) constant colour of Antares for the last three millennia also constrains its mass and age. Wezen was reported white historically, but is now yellow.

Electromagnetic follow-up observations of binary neutron star mergers with early warnings from decihertz gravitational-wave observatories

ABSTRACT We investigate the prospects of electromagnetic follow-up observations for binary neutron star (BNS) mergers, with the help of early warnings from decihertz gravitational-wave (GW) observatories, B-DECIGO and DO-Optimal. Extending the previous work, we not only give quick assessments of joint short γ-ray burst (sGRB) detection rates for different γ-ray satellites and BNS population models, but also elaborate on the analyses and results on multiband kilonova detections for survey telescopes with different limiting magnitudes. During an assumed 4-yr mission time for decihertz GW observatories, we find that for the goals of electromagnetic follow-ups, DO-Optimal performs better than B-DECIGO as a whole on the detection rate, and has a larger detectable distance for joint sGRB/kilonova searches. Taking the lognormal population model for BNS mergers and a 1-d early-warning time as an example, we discuss the accuracy in localization and timing, as well as the redshift distributions for various synergy observations with electromagnetic facilities and decihertz GW detectors. Based on our analyses, we propose a feasible ‘wait-for’ pattern as a novel detecting mode for future multimessenger astrophysics.

Variety of evidence in multimessenger astronomy

The confirmation of models in multimessenger astronomy requires variety of evidence. Variety of evidence (VoE) should be understood as an eliminative epistemic principle: where multiple and heterogenous types of evidence converge upon model assumptions or predictions, confidence in the representational accuracy of that model and/or its assumptions is made stronger than if sources of evidence were homogenous. Varied evidence increases confidence indirectly by providing grounds upon which to eliminate under-supported alternatives. I discuss the role VoE reasoning plays in multimessenger astronomy, emphasizing the oft-neglected constraint of chronological evidential support to capture the importance of time series and timescales in astronomy. I then show that in a key case, the convergence of varied types of empirical observations lends confirmatory support to the kilonova model of neutron star mergers.11I would like to thank Elisabeth Lloyd, Gary Ebbs, Kirk Ludwig, Lydia Patton, William Vanderburgh, Suzanne Kawamleh, Dan Li, Ryan O'Loughlin, Steve Mischler, and David McCarty for their invaluable feedback and support on earlier drafts of this work.

Analysis of injury severity in rear-end crashes on an expressway involving different types of vehicles using random-parameters logit models with heterogeneity in means and variances

ABSTRACT To examine the difference in contributing factors of rear-end crashes of different injury severity involving different types of vehicles, this paper proposed random-parameters multinomial logit models with heterogeneity in means and variances. A three-year (2017–2019) rear-end crash data collected from Beijing-Shanghai Highways in China was used to calibrate the models. The rear-end crashes were classified as five types (Car-Car, Car-Truck, Truck-Truck, Truck-Car, Others). With two possible injury severity outcomes of medium/severe injury and light injury, a wide range of possible variables including crash, traffic, speed, geometric, and sight characteristics were considered in this study. Likelihood ratio tests revealed the rationality of adopting merged models using the data across three-year periods. Remarkably significant differences were shown in crashes involving different types of vehicles. The results accounting for the possible heterogeneity could be of value to roadway designers and traffic management departments seeking to promote highway safety and raise accurate safety countermeasures.

Study of personnel satisfaction level in the period of mergers on the example of banks

One of the acute problems of companies today is the issue of studying the improvement of produc- tive capacity, efficiency, and work motivation in conditions of varying degrees of complexity in the team. In this article the authors consider the process of psychological «adjustment» to the new adaptive conditions of another organization of employees, which by circumstances had to unite. The authors’ study of the level of satisfaction in connection with the reorganization and changes in the organization’s policies in the new economic conditions and current trends and its connection with the performance of the “new” incoming part-time employees gave the authors very interesting results. The authors suggest that, in the future can help companies and organizations and their employees to rise to a new level and be productive in the labor market and business. The purpose of the study was to examine and influence the self-perception of job satisfaction among bank employees in a state of continuous work process without interruption from the organizational moments. In this article the authors carried out diagnostic research (degree of satisfaction of the personnel with the working conditions and social-psychological climate), namely, components, including determination of level of satisfaction of the personnel of the contact centers of Bank A and Bank B, the comparative table of the existing at that time organizational conditions was presented and the principles of increasing of level of personnel satisfaction were deter- mined taking into account available material and human resources. The result of this study was a program to optimize working conditions and socio-psychological cli- mate of the bank staff. The value of the study lies in the uniqueness of using the situation of the merger of two banking organizations to measure the level of employee satisfaction and find ways to improve it. Including in the planning process integration and training of incoming employees, specialists can build an optimal model of a comfortable merger of employees in the new conditions of the company with its built corporate culture of professional activity, thereby reducing the level of staff turnover and without disturbing the balance, increase the psychological climate in the team. The novelty of the study was a small number of empirical experiments to study the level of staff satisfaction in Kazakhstani banks during the period of their merger. Key words: adaptation conditions, bank personnel, merger, psychological climate, satisfaction.

A bilevel Nash-in-Nash model for hospital mergers: A key to affordable care

The increasing and exorbitant health care prices in the United States combined with a trend of market concentration has resulted in more than 25 million people being without basic health insurance per year. Increasing mortality rates, decreasing quality of life, preventable hospitalizations, and emergency department overcrowding are some of the consequences of the health care access crisis. This work introduces a bilevel Nash-in-Nash approach to model health care market interactions among insurers, hospitals, and patients. We model eight different scenarios to account for horizontal hospital mergers, insurance network expansions, and SARS-CoV-2 effects over a set of market metrics, such as insurance premiums and quality of care. We use the proposed approach to analyze Hillsborough County in Florida, considering a demand of 1.2 million customers, 14 hospitals, 4 health insurers, and 15 diagnosis-related groups. The results show that the quality of care does not increase with hospital mergers and that improving hospital competition can reduce the current insurance premiums by up to 13.7%. We also found that increasing the number of providers per insurance network reduces the premiums in concentrated hospital markets by up to 35%. Further analyses revealed that the changes in demand due to the SARS-CoV-2 pandemic should reduce insurance premiums (between 25% and 31%) and increase hospital reimbursement rates.

An efficient six-parameter perspective motion model for VVC

Tilt and pan camera movements are common in computer games or social media videos. These types of videos contain numerous perspective transforms while today’s video codecs rely on translational and affine motion models for motion compensation. The general perspective motion model with 8 parameters (8PMM) has unreasonably high processing time. In this paper, the eight-parameter perspective transform is simplified into a six-parameter transform to keep the time complexity within an acceptable range while modeling the most relevant transforms. Also, two motion prediction modes, Advanced Perspective Motion Vector Prediction (APMVP) and Perspective Model Merge (PMM), are proposed. The implementation results show an average of 7.0% BD-rate reduction over H.266/VVC Test Model with a maximum of 20% encoding time overhead. The results also show a 71% processing time reduction in comparison to 8PMM while experiencing an average of 5.6% increase in BD-Rate. Much better visual quality is measured through VMAF quality meter.

Introducing a merged precipitation satellite model using satellite precipitation products, land surface temperature, and precipitable water vapor

Satellite precipitation have a lot of uncertainty and the spatial resolution is still quite coarse. Hence, the purpose of this study is to introduce a new approach based on multivariate linear modelling and Artificial Neural Networks (ANN) for the first time using four multisource satellite precipitation products and some other satellite data. Four different satellite precipitation products with different algorithms, along with Precipitable Water Vapor (PWV) and Land Surface Temperature (LST) data on a daily scale were used (to benefit interactions of atmospheric content). Five linear merge models, including five ANN models were introduced and calibrated using harmony search algorithm. The performance of the models was evaluated over Iran using observational rainfall data of 2014 to 2020. The findings of this study highlighted that the model based on ANN, which merged four rainfall products together with LST and PWV has outperformed individual satellite products and other presented models.

Constraining the cosmological parameters using gravitational wave observations of massive black hole binaries and statistical redshift information

Space-borne gravitational wave detectors like TianQin are expected to detect GW signals emitted by the mergers of massive black hole binaries. Luminosity distance information can be obtained from GW observations, and one can perform cosmological inference if redshift information can also be extracted, which would be straightforward if an electromagnetic counterpart exists. In this paper, we concentrate on the conservative scenario where the EM counterparts are not available, and comprehensively study if cosmological parameters can be inferred through a statistical approach, utilizing the non-uniform distribution of galaxies as well as the black hole mass-host galaxy bulge luminosity relationship. By adopting different massive black hole binary merger models, and assuming different detector configurations, we conclude that the statistical inference of cosmological parameters is indeed possible. TianQin is expected to constrain the Hubble constant to a relative error of about 4%-7%, depending on the underlying model. The multidetector network of TianQin and LISA can significantly improve the precision of cosmological parameters. In the most favorable model, it is possible to achieve a level of 1.7% with a network of TianQin and LISA. We find that without EM counterparts, constraints on all other parameters need a larger number of events or more precise sky localization of GW sources, which can be achieved by the multidetector network or under a favorable model for massive black hole mergers. However, in the optimistic case, where EM counterparts are available, one can obtain useful constraints on all cosmological parameters in the Lambda-CDM cosmology, regardless of the population model. Moreover, we can also constrain the equation of state of the dark energy without the EM counterparts, and it is even possible to study the evolution of EoS of the DE when the EM counterparts are observed.