Bayesian Inference for Stochastic Cusp Catastrophe Model with Partially Observed Data

The purpose of this paper is to develop a data augmentation technique for statistical inference concerning stochastic cusp catastrophe model subject to missing data and partially observed observations. We propose a Bayesian inference solution that naturally treats missing observations as parameters and we validate this novel approach by conducting a series of Monte Carlo simulation studies assuming the cusp catastrophe model as the underlying model. We demonstrate that this Bayesian data augmentation technique can recover and estimate the underlying parameters from the stochastic cusp catastrophe model.

Scalable Species Tree Inference with External Constraints

Species tree inference under the multi-species coalescent (MSC) model is a basic step in biological discovery. Despite the developments in recent years of methods that are proven statistically consistent and that have high accuracy, large datasets create computational challenges. Although there is gener- ally some information available about the species trees that could be used to speed up the estimation, only one method, ASTRAL-J, a recent development in the ASTRAL family of methods, is able to use this information. Here we describe two new methods, NJst-J and FASTRAL-J, that can estimate the species tree given partial knowledge of the species tree in the form of a non-binary unrooted constraint tree.. We show that both NJst-J and FASTRAL-J are much faster than ASTRAL-J and we prove that all three methods are statistically consistent under the multi-species coalescent model subject to this constraint. Our extensive simulation study shows that both FASTRAL-J and NJst-J provide advantages over ASTRAL-J: both are faster (and NJst-J is particularly fast), and FASTRAL-J is generally at least as accurate as ASTRAL-J. An analysis of the Avian Phylogenomics project dataset with 48 species and 14,446 genes presents additional evidence of the value of FASTRAL-J over ASTRAL-J (and both over ASTRAL), with dramatic reductions in running time (20 hours for default ASTRAL, and minutes or seconds for ASTRAL-J and FASTRAL-J, respectively). Availability: FASTRAL-J and NJst-J are available in open source form at https://github.com/ RuneBlaze/FASTRAL-constrained and https://github.com/RuneBlaze/NJst-constrained. Locations of the datasets used in this study and detailed commands needed to reproduce the study are provided in the supplementary materials at http://tandy.cs.illinois.edu/baqiao-suppl.pdf.

Effects of Refuge Prey on Stability of the Prey-Predator Model Subject to Immigrants: A Mathematical Modelling Approach

Prey-predator system is enormously complex and nonlinear interaction between species. Such complexity regularly requires development of new approaches which involves more factors in analysis of its population dynamics. In this paper, we formulate a modified Lotka-Volterra model that incorporates factors such as refuge prey and immigrants. We investigate the effects of refuge prey and immigrants by varying the refuge factor, with and without immigrants. The results show that with Holling’s type I functional response, the proposed model is asymptotically convergent when a refuge prey factor is introduced. Moreover, with Holling’s type II functional response, the proposed mathematical model is unstable and does not converge. However, with Holling’s type III functional response in a system, the proposed mathematical model is asymptotically stable. These results point out the following remarks: The effects of refuge prey on stability of the dynamical system vary depending on the type of functional response, and when the predator population increases, the likelihood of prey extinction declines when the proportion of preys in refuge population increases. Hence, the factor of refuge prey is crucial for controlling the population of the predator and obtaining balances between prey and predator in the ecosystem. Keywords: Refuge prey, stability, prey-predator, immigrants, Mathematical modelling

On the Effect of Nonlinear Energy Sink Damping in Seismic Vibration Attenuation

Nonlinear Energy Sinks (NESs) have been proposed for passively reducing the amplitude of vibrations in different types of structures. The main advantage of NES over traditional Tuned Mass Dampers (TMDs) lies in its capability to redistribute the vibrating energy inside a primary structure, what effectively reduces the amplitude of the structure oscillations over a wide range of frequencies. However, the performance of an NES can be substantially affected even by small variations on input energy as in the case of buildings under seismic ground excitation. In this work it is shown that the NES energy sensibility can be significantly reduced by properly selecting the NES damping coefficient. A three stories shear building model subject to seismic ground excitation is used to numerically study the effect that NES damping has on its vibration reduction performance.

Scenario Weights for Importance Measurement (SWIM) – an R package for sensitivity analysis

The Scenario Weights for Importance Measurement (SWIM) package implements a flexible sensitivity analysis framework, based primarily on results and tools developed by Pesenti et al. (2019). SWIM provides a stressed version of a stochastic model, subject to model components (random variables) fulfilling given probabilistic constraints (stresses). Possible stresses can be applied on moments, probabilities of given events, and risk measures such as Value-At-Risk and Expected Shortfall. SWIM operates upon a single set of simulated scenarios from a stochastic model, returning scenario weights, which encode the required stress and allow monitoring the impact of the stress on all model components. The scenario weights are calculated to minimise the relative entropy with respect to the baseline model, subject to the stress applied. As well as calculating scenario weights, the package provides tools for the analysis of stressed models, including plotting facilities and evaluation of sensitivity measures. SWIM does not require additional evaluations of the simulation model or explicit knowledge of its underlying statistical and functional relations; hence, it is suitable for the analysis of black box models. The capabilities of SWIM are demonstrated through a case study of a credit portfolio model.

Direct Communication Between Brains: A Systematic PRISMA Review of Brain-To-Brain Interface

This paper aims to review the current state of brain-to-brain interface (B2BI) technology and its potential. B2BIs function via a brain-computer interface (BCI) to read a sender's brain activity and a computer-brain interface (CBI) to write a pattern to a receiving brain, transmitting information. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to systematically review current literature related to B2BI, resulting in 15 relevant publications. Experimental papers primarily used transcranial magnetic stimulation (tMS) for the CBI portion of their B2BI. Most targeted the visual cortex to produce phosphenes. In terms of study design, 73.3% (11) are unidirectional and 86.7% (13) use only a 1:1 collaboration model (subject to subject). Limitations are apparent, as the CBI method varied greatly between studies indicating no agreed upon neurostimulatory method for transmitting information. Furthermore, only 12.4% (2) studies are more complicated than a 1:1 model and few researchers studied direct bidirectional B2BI. These studies show B2BI can offer advances in human communication and collaboration, but more design and experiments are needed to prove potential. B2BIs may allow rehabilitation therapists to pass information mentally, activating a patient's brain to aid in stroke recovery and adding more complex bidirectionality may allow for increased behavioral synchronization between users. The field is very young, but applications of B2BI technology to neuroergonomics and human factors engineering clearly warrant more research.

Kurikulum ISMUBA di SD Muhammadiyah Banguntapan

Pendidikan Agama Islam di sekolah Muhammadiyah memiliki kekhasan yang berbeda dengan sekolah umum dengan karakteristik Kemuhammadiyahan. Penelitian ini bertujuan untuk mendeskripiskan kurikulum ISMUBA yang menjadi kekhasan di SD Muhammadiyah Banguntapan. Jenis Penelitian yang digunakan oleh penelitian adalah penelitian kualitatif studi kasus, yaitu jenis penelitian yang berupaya menjelaskan ragam keadaan yang didapatkan oleh peneliti di lokus penelitian tentang hal-hal yang terkait dengan pelaksanaan kurikulum ISMUBA. Data-data pada peneltian ini bersumber dari guru pengampu mata pelajaran ISMUBA, dan beberapa guru mata pelajaran lain, termasuk kepala sekolah dan guru kelas. Hasil penelitian menunjukkan bahwa kurikulum ISMUBA yang diselenggaakan memadukan antara Kurikulum Kemendikbud, Kementrian Agama, dan Majelis Dikdasmen PP Muhammadiyah. Kurikulum ISMUBA di SD Muhammadiyah Banguntapan terdiri dari mata pelajaran Aqidah, Akhlak, Ibadah/Muamalah, Tarikh, Al-Qur’an, Kemuhammadiyahan, dan Bahasa Arab. Kecenderungan desain kurikulum ISMUBA pada model subject center design. Akan menjadi baik pengembangan pada masa yang akan datang, dikembangkan menjadi bentuk learner center design, dan problem based design. Demikian itu lebih mengintegrasikan pengetahuan peserta didik dengan lingkungan sekitar.