The recent advent of 3D in electron microscopy (EM) has allowed for detection of nanometer resolution structures. This has caused an explosion in dataset size, necessitating the development of ...automated workflows. Moreover, large 3D EM datasets typically require hours to days to be acquired and accelerated imaging typically results in noisy data. Advanced denoising techniques can alleviate this, but tend to be less accessible to the community due to low-level programming environments, complex parameter tuning or a computational bottleneck. We present DenoisEM: an interactive and GPU accelerated denoising plugin for ImageJ that ensures fast parameter tuning and processing through parallel computing. Experimental results show that DenoisEM is one order of magnitude faster than related software and can accelerate data acquisition by a factor of 4 without significantly affecting data quality. Lastly, we show that image denoising benefits visualization and (semi-)automated segmentation and analysis of ultrastructure in various volume EM datasets.
We present a modular and extendable software suite, DJMol, for performing molecular simulations and it is demonstrated with DFTB+, Siesta, Atomic Simulation Environment, and OpenMD codes. It supports ...many of the standard features of an integrated development environment and consists of a structure builder and viewer, which could be connected with these electronic structure codes along with a set of data analyzers. This program comprises Java and Python modules and its libraries to carry out a different set of modeling tasks in materials science and chemistry. By adopting a Python interpreter into the software, a range of scriptable Python codes, such as Pymatgen can be incorporated into this programmable modeling platform. DJMol, through its common application programming interface (API), supports multiple modeling codes in the backend and several post‐processing tools. It benefits an experienced user by increasing efficiency, while a nonexpert user by easy to use API.
An integrated development environment with Python scripting assists modeling and pythonic data analysis.
Abstract
Smart power plant is to establish a modern energy power system to achieve safe, efficient, green, and low-carbon power generation. Its characteristics are that the production process can be ...independently optimized, the relevant systems can collect, analyze, judge, and plan their own behavior, and intelligently and dynamically optimize equipment configuration and its parameters. This paper focuses on the optimal recognition state of MFCC in smart power plants. In this paper, we propose that by changing the number of filters and the order of MFCC to view the expression effect of the final MFCC parameter, the evaluation index of the effect is “accuracy”, the evaluation index—accuracy in the neural network. In this paper, the network is built through a Python programming environment, and the comparative experiment is adopted to analyze the influence of each parameter on the speech information expression effect of MFCC parameters.
•A linear power flow formulation for direct current networks is presented.•Taylor's series expansion is used to obtain an equivalent linear power flow model.•Gauss–Seidel and Newton–Raphson methods ...are used to validate the proposed approach.•SDP via CVX toolbox is employed to compare the proposed linear approximation.•Processing times are tested through MATLAB and DEV C++ programming languages.
This paper presents a reformulation of the power flow problem in low-voltage dc (LVDC) power grids via Taylor's series expansion. The solution of the original nonlinear quadratic model is achieved with this proposed formulation with minimal error when the dc network has a well defined operative conditions. The proposed approach provides an explicit solution of the power flow equations system, which avoids the use of iterative methods. Such a characteristic enables to provide accurate results with very short processing times when real operating scenarios of dc power grids are analyzed. Simulation results verify the precision and speed of the proposed method in comparison to classical numerical methods for both radial and mesh configurations. Those simulations were performed using C++ and MATLAB, which are programming environments commonly adopted to solve power flows.
The potential benefits from the introduction of programming environments such as Scratch for learning mathematics has reactivated research in this area. Nonetheless, there are few studies which ...attempt to analyse their influence at the stage of Primary Education. We present the results of a quasi-experimental piece of research with sixth-grade students which studies the influence of Scratch both on the acquisition of mathematical concepts, and on the development of computational thinking. The experiment consisted of two different phases, a programming phase linked to the instruction in Scratch and focused on the acquisition of basic concepts of computational thinking (sequences, iterations, conditionals, and events-handling), and a mathematical phase completely oriented towards the resolution of mathematical tasks. In particular, the mathematical phase focused on word problems whose resolution involves the use of the least common multiple and the greatest common divisor. In order to evaluate the aims of the study, results from tests before and after instruction, both in computational thinking and in the mathematical standards, were compared. The results seem to indicate that Scratch can be used to develop both students' mathematical ideas and computational thinking.
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The increasing power demand in the world’s energy basket and the focus on reducing carbon emission, in tandem with upgrade constraints on conventional grids, has elicited the ...employment of renewable energies. Specifically, answering the power and cooling/heating demands of remote areas where the grid cannot or can merely supports using locally available and utilizable renewable energies is a focal topic. Herein, a cogeneration system driven by solar energy through parabolic trough collector (PTC) utilization integrated with organic Rankine cycle (ORC), and diffusion absorption refrigeration (DAR) cooling system is proposed. The system is backed up by phase-change material (PCM) and battery bank for solving the intermittence nature of solar energy, and targeted at being employed in a residential building in Shahr Asb, a village in Yazd province, Iran, with a population of less than 600. The system is appraised through exergy evaluation to gauge the efficiency and performance of the system, and life cycle assessment analyses (exergoenvironmental evaluation), to present beneficial data on the mutual impact of the system’s performance and environmental conditions. The HYSYS, MATLAB, TRNSYS, and HOMER software and programming environments were utilized to model the cogeneration system. The exergy analysis indicated that the PTC field contributed to the highest exergy destruction (31.80 kW) of the system (67.89 kW) with PTC and system exergy efficiency of 55.23% and 67.89%, respectively. Consistent with the exergoenvironmental analysis, the highest values of cumulative environmental impacts were pertinent to EX-101 expander, (204.02 Pts/h - 29.49%) and E-102 heat exchanger (154.44 Pts/h - 22.33%), individually. Consequently, to mitigate the system’s undesirable environmental impacts, the operating conditions of these devices must be amended. The parametric analysis showed that the rise in mole fraction of hydrogen as the inert gas of the DAR system positively affects the evaporator duty and temperature. The required power (10.76 kW) and cooling (44.55 kW) are provisioned by utilizing 80.76 kW and 364.30 kW of heat duty in the DAR and ORC system, respectively, which is met by the battery bank and PCM when solar energy is absent during the night.
Block-based programming (BBP) environments have become increasingly commonplace computer science education. Despite a rapidly expanding ecosystem of BBP environments, text-based languages remain the ...dominant programming paradigm, motivating the transition from BBP to text-based programming (TBP). Support students in transitioning from BBP to TBP is an important and open design question. This work identifies 101 unique BBP environments, analyzes the 46 of them and identifies different design approaches used to support the transition to TBP. The contribution of this work is to provide a snapshot of the current state of BBP environments and how they support learners in transitioning to TBP.
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