Semi-Infinite Structure Analysis with Bimodular Materials with Infinite Element

The modulus of elasticity of some materials changes under tensile and compressive states is simulated by constructing a typical material nonlinearity in a numerical analysis in this paper. The meshless Finite Block Method (FBM) has been developed to deal with 3D semi-infinite structures in the bimodular materials in this paper. The Lagrange polynomial interpolation is utilized to construct the meshless shape function with the mapping technique to transform the irregular finite domain or semi-infinite physical solids into a normalized domain. A shear modulus strategy is developed to present the nonlinear characteristics of bimodular material. In order to verify the efficiency and accuracy of FBM, the numerical results are compared with both analytical and numerical solutions provided by Finite Element Method (FEM) in four examples.

Automatic discrimination between front and back ensemble locations in HRTF-convolved binaural recordings of music

One of the greatest challenges in the development of binaural machine audition systems is the disambiguation between front and back audio sources, particularly in complex spatial audio scenes. The goal of this work was to develop a method for discriminating between front and back located ensembles in binaural recordings of music. To this end, 22, 496 binaural excerpts, representing either front or back located ensembles, were synthesized by convolving multi-track music recordings with 74 sets of head-related transfer functions (HRTF). The discrimination method was developed based on the traditional approach, involving hand-engineering of features, as well as using a deep learning technique incorporating the convolutional neural network (CNN). According to the results obtained under HRTF-dependent test conditions, CNN showed a very high discrimination accuracy (99.4%), slightly outperforming the traditional method. However, under the HRTF-independent test scenario, CNN performed worse than the traditional algorithm, highlighting the importance of testing the algorithms under HRTF-independent conditions and indicating that the traditional method might be more generalizable than CNN. A minimum of 20 HRTFs are required to achieve a satisfactory generalization performance for the traditional algorithm and 30 HRTFs for CNN. The minimum duration of audio excerpts required by both the traditional and CNN-based methods was assessed as 3 s. Feature importance analysis, based on a gradient attribution mapping technique, revealed that for both the traditional and the deep learning methods, a frequency band between 5 and 6 kHz is particularly important in terms of the discrimination between front and back ensemble locations. Linear-frequency cepstral coefficients, interaural level differences, and audio bandwidth were identified as the key descriptors facilitating the discrimination process using the traditional approach.

Impacts of Climate Change and Variability on Precipitation and Maximum Flows in Devil’s Creek, Tacna, Peru

Global projections of climate change indicate negative impacts on hydrological systems, with significant changes in precipitation and temperature in many parts of the world. As a result, floods and droughts are expected. This article discusses the potential effects of climate change and variability on the maximum precipitation, temperature, and hydrological regime in Devil’s Creek, Tacna, Peru. The outputs of precipitation and daily temperature of fifteen regional climate models were used for the RCP4.5 and RCP8.5 emission scenarios. The methodology used includes the bias correction and downscaling of meteorological variables using the quintiles mapping technique, hydrological modeling, the evaluation of two emission scenarios, and its effect on the maximum flows of the stream. The results of the multi-model ensemble show that the maximum annual precipitation will probably increase by more than 30% for the RCP4.5 and RCP8.5 scenarios for the 2021–2050 period relative to the 1981–2005 period. Likewise, as expected, the maximum flows could increase by 220% and 154% for the RCP4.5 scenarios for the 2021–2050 and 2051–2080 terms, respectively, and 234% and 484% for the RCP8.5 scenarios and for the 2021–2050 and 2051–2080 terms, respectively, concerning the recorded historical value, increasing the probability of flood events and damage in populations located downstream.

Comprehensive assessment of Mahaim accessory pathways’ anatomic distribution

Objective To present the authors’ experience of Mahaim-type accessory pathways (MAPs), focusing on anatomic localizations. Methods Data from consecutive patients who underwent electrophysiological study (EPS) for MAP ablation in two tertiary centres, between January 1998 and June 2020, were retrospectively analysed. Results Of the 55 included patients, 27 (49.1%) were male, and the overall mean age was 29.5 ± 11.6 years (range, 12–66 years). MAPs were ablated at the tricuspid annulus in 43 patients (78.2%), mitral annulus in four patients (7.3%), paraseptal region in three patients (5.5%), and right ventricle mid-apical region in five patients (9.1%). Among 49 patients who planned for ablation therapy, the success rate was 91.8% (45 patients). Conclusion MAPs were most often ablated at the lateral aspect of the tricuspid annuli, sometimes at other sides of the tricuspid and mitral annuli, and infrequently in the right ventricle. The M potential mapping technique is likely to be a useful target for ablation of MAPs.

BIM Education in Higher Learning Institutions: A Scientometric Review and the Malaysia Perspective

Over the last decade, digital applications and Building Information Modelling (BIM) have been introduced in the construction industry to realize a smart construction ecosystem. However, the construction industry has not completely accepted BIM as a standard, and the concept of using BIM applications in universities has not been thoroughly researched. This paper addresses the first scientometric study of BIM education in universities, identifying the state of BIM education practices, skillsets, and the level of BIM education in universities. The paper used scientometric analysis and the VOSviewer mapping technique to assess the most impactful publication sources with the most important impact on BIM education by searching “BIM Education” and using 250 bibliographic data extracted from the Scopus database from 2011-2020 to identify the existing research gaps and research direction. Second, a structured questionnaire was distributed to 343 Year 2 and Year 3 students from two public and two private Malaysian universities that use BIM in their learning. Descriptive data analysis using cross-tabulation in SPSS and relative importance index (RII) were used to analyze the data. The paper revealed two stages of BIM education research; and identified research gaps in the fields of BIM education, architectural education, e-learning, curriculum and information management. The paper also revealed Revit, Cost X and the Glodon Cubicost software as the most used applications, while the common skillsets are design authoring, modelling, and cost estimation. However, both public and private university students mainly design 3D models at BIM Stage 1. The study recommends that institutions and other stakeholders provide continuous BIM training, purchase BIM software, and integrate BIM into the curriculum of Built Environment higher learning institutions for the next generation to be the generation that uses virtual collaborative platforms

Superflares and Starspots: when size does not matter

Within the last decade, space missions have provided a wealth of information about stellar flares. Nevertheless, what triggers these superflares, and whether they are similar to the solar counterparts, remains a great mystery. How are flares connected to active regions and what are the main causes of their occurrence? Here we investigate the activity of two K-type stars, similar in every way from mass to rotation periods and planetary systems. Even if both stars exhibited hundreds of spots, Kepler-411 produced 65 superflares, while Kepler-210 presented none. The spots of both stars were characterised using the planetary transit mapping technique which yields the intensity, temperature, and radius of starspots. The only discrepant parameter was the size of the spots. While the average radius of spots on Kepler-411 was (17 ± 7) × 103 km, for Kepler-210 the mean radius was (39 ± 18) × 103 km. That is, the star with no superflare exhibited spots twice as large as the one with 65 superflares. Thus starspot area appears not to be the main culprit of superflare triggering, but rather the magnetic complexity seems more important, as in the case of the Sun. These are important clues to the magnetic dynamo acting on these solar-type stars.

On the buckling and bending analysis of FG straight-sided quadrilateral nanoplates using a continuum mechanics-based surface elastic model

In this research, an elastic model based on the continuum mechanics is developed to study the static behaviors of functionally graded (FG) arbitrary straight-sided quadrilateral nanoplates. The model is constructed in the framework of Gurtin-Murdoch’s surface and Mindlin’s plate theories to account for the surface energy and shear deformation effects, simultaneously. The variational differential quadrature (VDQ) method is used along with a mapping technique to do the discretization process in a variational framework by means of differential and integral operators. Consequently, a weak form of governing equations is obtained from the energy quadratic representation of the problem. The solution method is of a distinguished feature as it involves just the first-order derivative of the field components in the mapping and discretization. After assuring the effectiveness of presented model by doing comparative studies, the critical buckling load and static deflection of the FG nanoplates with different shapes in geometry are investigated considering the surface effects. It is found that the surface energies effect on the static behavior of the rectangular nanoplates is more significant as compared to the non-rectangular nanoplates.

Assessment of Asymptomatic Severe Aortic Regurgitation by Doppler-Derived Echo Indices: Comparison with Magnetic Resonance Quantification

Reliable quantification of aortic regurgitation (AR) severity is essential for clinical management. We aimed to compare quantitative and indirect echo-Doppler indices to quantitative cardiac magnetic resonance (CMR) parameters in asymptomatic chronic severe AR. Methods and Results: We evaluated 104 consecutive patients using echocardiography and CMR. A comprehensive 2D, 3D, and Doppler echocardiography was performed. The CMR was used to quantify regurgitation fraction (RF) and volume (RV) using the phase-contrast velocity mapping technique. Concordant grading of AR severity with both techniques was observed in 77 (74%) patients. Correlation between RV and RF as assessed by echocardiography and CMR was relatively good (rs = 0.50 for RV, rs = 0.40 for RF, p < 0.0001). The best correlation between indirect echo-Doppler and CMR parameters was found for diastolic flow reversal (DFR) velocity in descending aorta (rs = 0.62 for RV, rs = 0.50 for RF, p < 0.0001) and 3D vena contracta area (VCA) (rs = 0.48 for RV, rs = 0.38 for RF, p < 0.0001). Using receiver operating characteristic analysis, the largest area under curve (AUC) to predict severe AR by CMR RV was observed for DFR velocity (AUC = 0.79). DFR velocity of 19.5 cm/s provided 78% sensitivity and 80% specificity. The AUC for 3D VCA to predict severe AR by CMR RV was 0.73, with optimal cut-off of 26 mm2 (sensitivity 80% and specificity 66%). Conclusions: Out of the indirect echo-Doppler indices of AR severity, DFR velocity in descending aorta and 3D vena contracta area showed the best correlation with CMR-derived RV and RF in patients with chronic severe AR.