Cube Method Research Articles

Fast Screening of Protein-Protein Interactions Using Förster Resonance Energy Transfer (FRET-) Based Fluorescence Plate Reader Assay in Live Cells.

Protein-protein interactions (PPIs) have great importance for intracellular signal transduction and sustaining the homeostasis of an organism. Thus, the identification of PPIs is necessary to better understand the downstream signaling functions of the proteins in healthy and pathological conditions. Förster resonance energy transfer (FRET) between fluorescent proteins (FPs) is a powerful tool for detecting PPIs in living cells. In literature, FRET analysis methods such as donor photobleaching (FLIM), acceptor photobleaching, spectral imaging, and the three-filter cube method (sensitized emission) are abundantly applied to investigate PPIs; however, they require various expensive instrumentations, and their calculation methods are very time consuming. Since confocal microscopy applications and live cell-based techniques of FRET are very costly, scientists sometimes prefer plate readers for FRET experiments. However, plate reader applications also have many disadvantages and considerations compared to confocal fluorescence microscopy, and complex calculation procedures should be performed. To overcome these problems, we propose a FRET-based high-throughput assay method with a standard monochromator-based microplate reader, which is generally available in most biochemistry laboratories, and an alternative calculation procedure. This rapid, low cost, and effective analysis method enables the scientists to prescreen PPIs in living cells as a preliminary study and quick glance at the experiment before preparing the whole experimental setup with the expensive instrumentations. Additionally, the alternative calculation procedure provides the FRET area comparison without complex bleed-through calculations in a non-conventional manner by shortening the analysis processes with this quick and uncomplicated spectral representation.

Continuous Capsule Network Method for Improving Electroencephalogram-Based Emotion Recognition

The convolution process in the Capsule Network method can result in a loss of spatial data from the Electroencephalogram signal, despite its ability to characterize spatial information from Electroencephalogram signals. Therefore, this study applied the Continuous Capsule Network method to overcome problems associated with emotion recognition based on Electroencephalogram signals using the optimal architecture of the (1) 1st, 2nd, 3rd, and 4th Continuous Convolution layers with values of 64, 128, 256, and 64, respectively, and (2) kernel sizes of 2×2×4, 2×2×64, and 2×2×128 for the 1st, 2nd, and 3rd Continuous Convolution layers, and 1×1×256 for the 4th. Several methods were also used to support the Continuous Capsule Network process, such as the Differential Entropy and 3D Cube methods for the feature extraction and representation processes. These methods were chosen based on their ability to characterize spatial and low-frequency information from Electroencephalogram signals. By testing the DEAP dataset, these proposed methods achieved accuracies of 91.35, 93.67, and 92.82% for the four categories of emotions, two categories of arousal, and valence, respectively. Furthermore, on the DREAMER dataset, these proposed methods achieved accuracies of 94.23, 96.66, and 96.05% for the four categories of emotions, the two categories of arousal, and valence, respectively. Finally, on the AMIGOS dataset, these proposed methods achieved accuracies of 96.20, 97.96, and 97.32% for the four categories of emotions, the two categories of arousal, and valence, respectively. Doi: 10.28991/ESJ-2023-07-01-09 Full Text: PDF

Node, place, ridership, and time model for rail-transit stations: a case study

Nowadays, Transit-Oriented Development (TOD) plays a vital role for public transport planners in developing potential city facilities. Knowing the necessity of this concept indicates that TOD effective parameters such as network accessibility (node value) and station-area land use (place value) should be considered in city development projects. To manage the coordination between these two factors, we need to consider ridership and peak and off-peak hours as essential enablers in our investigations. To aim this, we conducted our research on Chengdu rail-transit stations as a case study to propose our Node-Place-Ridership-Time (NPRT) model. We applied the Multiple Linear Regression (MLR) to examine the impacts of node value and place value on ridership. Finally, K-Means and Cube Methods were used to classify the stations based on the NPRT model results. This research indicates that our NPRT model could provide accurate results compared with the previous models to evaluate rail-transit stations.

Uncertainty-aware Cube algorithm for medium-term collision risk assessment

The number of Earth orbiting objects is constantly growing, and some orbital regions are becoming risky environments for space assets of interest, which are increasingly threatened by accidental collisions with other objects, especially in Low-Earth Orbit (LEO). Collision risk assessment is performed by various methods, both covariance and non-covariance based. The Cube algorithm is a non-covariance-based method used to estimate the collision rates between space objects, whose concept consists in dividing the space in cubes of fixed dimension and, at each time instant, checking if two or more objects share the same cube. Up to now its application has been limited to the long-term scenarios of orbital debris evolutionary models, where considering the uncertainties is not necessary and impractical. Within operative contexts, instead, medium-term collision risk analysis may be an important task, in which the propagation-related uncertainties play a prominent role, but the timescale poses challenges for the application of standard covariance-based conjunction analysis techniques. In this framework, this paper presents an approach for the evaluation of the medium-term collision frequency for objects in LEO, called Uncertainty-aware Cube method. It is a modified version of the Cube, able to take the possible errors in the space objects’ position into account for the detection of the conjunctions. As an object’s orbit is propagated, the along-track position error grows more and more, and each object could potentially be in a different position with respect to the one determined by numerical propagation and, thus, in a different cube. Considering the uncertainties, at each time instant the algorithm associates more than one cube to each object and checks if they share at least one cube. If so, a conjunction is detected and a degree of confidence is evaluated. The performance of the method is assessed in different LEO scenarios and compared to the original Cube method.

Robust optimization of the aerodynamic design of a helicopter rotor blade based on multi-fidelity meta-models

Robust optimization (RO) of designs becomes indispensable to deal with inherent manufacturing uncertainties. Yet, RO is still too expensive to solve complex problems such as the design of helicopter rotor blades. A promising way to reduce this cost is to use the multi-fidelity meta-model-based optimization (MFMBO), which combines low fidelity models (LFM), high fidelity models (HFM), meta-models, design of experiment (DoE), and optimization techniques. The field of MFMBO is not been completely explored despite the high number of proposed strategies. This paper contributes to the MFMBO cost-effectiveness improvement by proposing a new strategy. The main feature of the latter is the mutual adaptive refinement of the HFM and LFM DoE sets. A new idea is proposed to generate initial nested DoEs, which is implemented using an ordinary and an optimal Latin Hyper Cube method. These DoEs are refined adaptively and mutually using an improved MaxMin-distance criterion. The expensive HFM is used only to define a correction C of the LFM. C is used to adjust LFM evaluations during MBO. Meta-models are constructed using the Radial Basis Functions technique. The strategy is tested with two RO techniques, namely, the Non-Dominated Sorting Genetic Algorithm (NSGA-II) and the Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D). The implemented strategy is validated on three different mathematical benchmarks, compared with four different MFMBO strategies and applied on a helicopter rotor blade. This validation shows that the proposed MFMBO is competitive and can produce solutions as accurate as the HFM-based MBO while reducing significantly the overall computation time (up to 40%).

A Scalable Parallel Algorithm for Balanced Sampling (Student Abstract)

We present a novel parallel algorithm for drawing balanced samples from large populations. When auxiliary variables about the population units are known, balanced sampling improves the quality of the estimations obtained from the sample. Available algorithms, e.g., the cube method, are inherently sequential, and do not scale to large populations. Our parallel algorithm is based on a variant of the cube method for stratified populations. It has the same sample quality as sequential algorithms, and almost ideal parallel speedup.

Application of Spatiotemporal Pattern Mining Methods for Land Use Transition Research: A Case Study of Baiyun District in Guangzhou

The use of spatio-temporal statistical combination method to explore the land use transition in urban suburbs provides an essential resource for promoting urban-rural integration and management of further urbanization. A combination of Space Time Cube and Geodetector methods was used to quantitatively identify the dominant morphology of land use change, and explore the recessive morphology and driving mechanism in Baiyun District, a suburb of Guangzhou from 1980 to 2020. Between these years, the land use changes were dominated by the expansion of built-up land and the shrinkage of cropland. The expansion took place in southern (1990-2000) to central (2000-2005) areas of the jurisdiction, followed by large-scale decentralization (2005-2010). Land use activities showed a downward trend. A continuous cold spot was mainly distributed in the southeast and remote areas near the urban center, whereas a continuous hot spot was spatially characterized by a multinuclear pattern, mainly concentrated in the center and south. Socioeconomic factors significantly affected the spatial pattern of land use activities. The trend turning in land use morphology of land use change can be divided into four stages: land primitivation from 1980 to 1990, land fragmentation from 1990 to 2000, land overflow from 2000 to 2010, and land intensification from 2010 to the present. Baiyun District is at the forefront of China’s development and has typical “suburban” characteristics, which can provide a reference for other suburbs in China to develop in stages. Today, urban suburbs in China face the problems of limited land resources and mixed land use space. Taking advantage of the new national strategic environment could effectively solve these land use issues in urban suburbs and achieve sustainable development. New trends in land use morphology research, also considering land use effects and land use change mechanisms in an integrated manner, are conducive to further deepening the understanding of land use transitions. Moreover, spatiotemporal statistical methods have innovated the field of mining the spatiotemporal characteristics of land use. Based on a scientific method for spatiotemporal analysis, we were able to reconstruct the three-dimensional space of land and improve the methods applied for research into land use change.

Some Solutions Inspired by Survey Sampling Theory to Build Effective Clinical Trials

SummaryThe organisation of a design of experiments, for example, for the realisation of a clinical trial, is crucial. It is often desirable to balance designs so that the means of the covariates are approximately the same in the test and control groups. In survey sampling theory, balanced sampling and calibration are two techniques that improve the precision of estimates. In this paper, we show the links between the two areas. We begin by assessing the gain in precision between a balanced design and a simple random sampling for the least squares estimators and the estimator by differences. We compare rerandomisation techniques and the cube method in order to balance the design. We propose a new method, particularly efficient, which combines the cube method with multivariate matching. A set of simulations is carried out in order to evaluate the different methods. The interest of the calibration is shown even if the design is almost balanced. It is thus shown that tools used by survey statisticians can be useful for experimental designs and clinical trials.

A Two-Step Surface Reconstruction Method Using Signed Marching Cubes

In this paper, we explore a new approach, a two-step surface reconstruction method to extract the target isosurface from a given implicit function efficiently. Our main contribution is that we improve the surface reconstruction process by accelerating the speed of evaluation using signed marching cubes. The basic strategy is to filter the invalid voxels that do not intersect with the target isosurface in a low-cost manner, and to evaluate the valid voxels that intersect with the target isosurface accurately. The improved signed marching cubes method consists of a rough evaluation step and an exact evaluation step. The coarse evaluation step evaluates the points of all voxels using the fast multipole method with a lower order. After the rough evaluation step, the voxels that intersect with the target isosurface are screened out. Then, the exact evaluation step evaluates the points of filtered voxels using the fast multipole method with a higher order. The experimental results show that, compared with the traditional marching cubes method, the improved reconstruction method reduces the amounts of calculation for invalid voxels that do not intersect with the target isosurfaces, which is useful to improve the efficiency of surface reconstruction.

Large-Scale Topology Optimization of Transient Incompressible Flow with Building-Cube Method

In recent years, topology optimization methods have been adopted not only for structural problems but also for fluid flow problems. Topology optimization for unsteady flows requires a fine mesh, which is computationally expensive. Therefore, we propose an transient incompressible flow topology optimization method based on the building cube method (BCM), which is suitable for massively parallel computing. BCM is a type of hierarchical Cartesian mesh method that has been reported to have very good scalability. The transient Navier-Stokes equations in the topology optimization procedure are solved by a finite volume discretization based on the BCM. The sensitivity of the objective function is obtained by continuous sensitivity analysis based on the adjoint variables method.

An implementation of Hill cipher and 3x3x3 rubik's cube to enhance communication security

Message security is must be managed seriously. Therefore, to maintain the confidentiality of any message, cryptography is needed. Cryptography is a science that uses mathematics to encrypt and decrypt messages. Cryptography is used as a tool to protect messages, for example, national secrets and strategies. The method of this research is qualitative research with a literature review. This research implements a hybrid cryptographic algorithm by combining Hill cipher and 3x3x3 Rubik's cube methods with Python software simulation.

Balancing a sample almost perfectly

With a simple modification, we propose a strong improvement of the quality of balancing with the cube method. The units are sorted in descending order according to their Mahalanobis distances to the center of the multivariate data cloud of balancing variables. We then apply the fast implementation of the cube method. The rounding problem on the balancing variables is greatly reduced.

Fast Compression of MCMC Output.

We propose cube thinning, a novel method for compressing the output of an MCMC (Markov chain Monte Carlo) algorithm when control variates are available. It allows resampling of the initial MCMC sample (according to weights derived from control variates), while imposing equality constraints on the averages of these control variates, using the cube method (an approach that originates from survey sampling). The main advantage of cube thinning is that its complexity does not depend on the size of the compressed sample. This compares favourably to previous methods, such as Stein thinning, the complexity of which is quadratic in that quantity.

Teaching English Writing through Cubing Method to the Tenth Grade of High School Students

The main objective of this study was to find out whether it is effective or not to teach English writing through cubing method to the tenth grade students of SMA Rahmaniyah Sekayu. This study used one group pre-test post-test design, where one group that becomes experimental group and used pre-test post-test result to compare the effectiveness in using cubing method. There were four classes or 82 students as the population, and one class or 22 students were taken as the sample. The data collected through test and analyzed by match t-test analysis. The result of test calculation shown that t-obtained was 10.198 it was higher than the critical value in the t-table was 2.0789 so that 10.198 > 2.0798. It means that the reseach hypothesis (Ha) was accepted. It can be concluded that cubing method was significantly effective to teach English writing.

Teaching English Writing through Cubing Method to the Tenth Grade of High School Students

The main objective of this study was to find out whether it is effective or not to teach English writing through cubing method to the tenth grade students of SMA Rahmaniyah Sekayu. This study used one group pre-test post-test design, where one group that becomes experimental group and used pre-test post-test result to compare the effectiveness in using cubing method. There were four classes or 82 students as the population, and one class or 22 students were taken as the sample. The data collected through test and analyzed by match t-test analysis. The result of test calculation shown that t-obtained was 10.198 it was higher than the critical value in the t-table was 2.0789 so that 10.198 > 2.0798. It means that the reseach hypothesis (Ha) was accepted. It can be concluded that cubing method was significantly effective to teach English writing.

Identification and spatiotemporal evolution analysis of high-risk crash spots in urban roads at the microzone-level: Using the space-time cube method

The problem of urban crashes brings huge challenges and threats to local police and governments, especially in many cities in developing countries such as China. To reduce the frequency and severity of urban crashes, the local government in China has gradually taken interest in conducting detailed actions of traffic safety improvement at the microzone-level. Therefore, the primary goal of this study is to try a new method in spatiotemporal data mining techniques, the space-time cube method, to find high-risk crash spots at the spatiotemporal level and to obtain their spatiotemporal evolution patterns. The cumulative frequency curve method was performed to identify high-risk crash spots, and the contributory factors of forming these spots were analyzed by the latent class analysis method. The results showed that: (1) key parameters’ selection is crucial in the space-time cube construction; (2) the exit ramp gore point in interchanges, intersections, and entrances of neighborhoods were prone to have many high-risk crash spots at the spatiotemporal scale; and (3) locations with consecutive, persistent, and sporadic hotspots patterns need different risk monitoring strategies and traffic safety improvement. The feasibility and advantages of the space-time cube method in hotspots identification at the microzone-level were confirmed.

A Systematic Literature Review on Critical Thinking in an Undergraduate Accounting Programme

The ability of accountancy students to apply critical thinking in solving problems related to modules offered in accountancy undergraduate programme, has remained a concern for many higher institutions. Accountancy students tend to struggle to apply critical thinking to their course work offered in the programme. To be able to apply critical thinking, accountancy students in undergraduate programmes should be able to apply a series of attributes that can enable them to understand questions asked in case study questions or multiple tasks. This study reviewed various ways in which students can apply critical thinking in an undergraduate accounting programme. A systematic literature review was conducted to examine the challenges undergraduate accounting students in South Africa face in applying critical thinking. This study found some of the barriers for applying critical thinking include redundancy, backwardness, application, extent to which preferences are associated to learning, and the ability to engage in real life accountancy practice. Literature reveals that accounting students can use the cube method which includes six steps: describe, compare, associate, analyse, apply, and argue to address the challenges of applying critical thinking. The study however, proposed some strategies that academics can use to ensure that accountancy students are able to apply critical thinking in solving accounting problems. Students are able to apply critical thinking in problem solving. Suggestions for future research were provided.

A three-dimensional bit-level image encryption algorithm with Rubik’s cube method

This paper proposes a new three-dimensional bit-level image encryption scheme with Rubik’s cube method (3D-BERC). In the permutation process, the Rubik’s cube method and bit-level encryption principle are combined to realize the image scrambling operation in three-dimensional space. Through the contraction mapping principle, the ascending and reducing dimension operation can be implemented effectively. In the diffusion process, we design an improved two-dimensional diffusion structure, which can spread slight change in plain image to the whole cipher image. Experimental results and simulation analysis illustrate the security and the validity of the proposed scheme.

Interior definition of the calyceal orientation suitable for percutaneous nephrolithotripsy via mobile software.

To date, there is no paper on defining the puncture of a kidney from the interior view of the pelvicalyceal system (PCS) to alleviate its performance. The objective of this study isto define the usefulness of the Rubik's Cube method determining calyceal orientation from inside via mobile software for the percutaneous nephrolithotripsy (PCNL). Over September 2019-September 2020, 25 patients with indications for PCNL were enrolled in this single-arm study. All patients underwent computed tomography (CT)-urography. Primary endpoints were the duration of renal cavity puncture, number of attempts and success rate. Complication rate ordered according to Clavien-Dindo classification was analyzed as a secondary endpoint.The stone-free rate was 91%. The same experienced urologist performed all procedures through the single-access PCNL without puncture site reposition. The puncture was made through the upper, middle, and lower calyx in 9, 12 and 4 cases, respectively. The mean duration of cavity puncture was 2.8 ± 1.1min. The mean number of attempts to reach desirable calyx was 1.4 ± 0.6. It should be noted that there were no cases with three and more punctures. The overall complication rate was 28% (7/25) when only one patient experienced ≥ 3 Grade. The proposed Rubik's Cube method facilitates preoperative planning of PCNL and makes that procedure easier for specialists and safer for the patients.

Land suitability assessment for supporting transport planning based on carrying capacity and construction demand.

With the rapid global urbanization, the unlimited increasing transportation infrastructure has met the needs of urban expansion, but it has caused a series of ecological problems lacking consideration of ecological conservation. The land suitability assessment for supporting transport planning based on carrying capacity and demand for construction is an effective way to promote urban socioeconomic development and ecological conservation. Therefore, we constructed a logical framework of resources and environment supporting, traffic construction demand driving, and ecological protection red line and basic farmland constraining, and applied the analytic hierarchy process (AHP), GIS, three-dimensional magic cube method, and gravity model to evaluate the suitability of expressway development in Sichuan Province, China. The results showed that the spatial difference in the carrying capacity of resources and environment and the demand for expressway construction was relatively high in Sichuan, and those in eastern cities were even higher. The land suitability for supporting transport planning was relatively high, and the suitable areas with a grade from 8 to 10, accounted for 20.77% of the total study area, which could almost meet the demand for transportation infrastructure construction. The land suitability performed a circle structure with Chengdu as the core and gradually decreasing to the periphery. Overall, this study adds new insights to transport planning reform in other similar regions around the world and can provide important references for regional development planning and environmental protection.