Balanced Number Research Articles

Performance Evaluation of Reconfiguration Policy in Reconfigurable Manufacturing Systems including Multi-Spindle Machines: An Assessment by Simulation

Reconfigurable manufacturing systems (RMSs) are extensively studied and employed to address demand uncertainties. RMS machines are designed to be modular and adaptable to changing requirements. A recent innovation is the introduction of multi-spindle reconfigurable machines (MRMTs). This study evaluates the impact of MRMTs’ introduction into an RMS, considering factors such as the number of MRMT machines and reconfiguration policies. A simulation model incorporating failures, process time variability, and part inter-arrival supports the analysis. The numerical results aid decision makers in determining the optimal RMS configuration with MRMTs. The simulation outcomes indicate that a balanced number of multi-spindle machines can significantly enhance performance compared with an unbalanced distribution.

Binary Numeration System with Alternating Signed Digits and Its Graph Theoretical Relationship

The binary number system is the basic number representation in computing. We can encode natural numbers with finite 0-1 sequences. The representation of natural numbers is based on this system. However, this poses problems and is technically not perfect. Several attempts have been made to handle integers (signed numbers). We mention only two: the balanced triple number system and the number system with base −2. Our paper introduces new possibilities. We also shed light on the graph theoretical background of the new number systems.

Effect of Obstacle Training in Frailty among Geriatric Population

Background: This study was developed to determine the effectiveness of obstacle training in frailty amonggeriatric population.Purpose: The purpose of the study is to evaluate the effectiveness of obstacle training in frailty among geriatricpopulation and to analyze the balance and gait analysis and number of falls.Method: A quasi experimental study was done in geriatric old age home with 30 samples by convenient samplingtechnique, allotted in a single group. In phase 1 the prevalence of frailty among Geriatric population will beexamined using the Edmonton frail scale. In phase 2 the Tinetti scale and morse fall scale were used as outcomemeasures.Results: According to the statistical analysis there is a clinically significant in groups, p value >o.oo1.Conclusion: We concluded that obstacle training has an improvement in reducing risk of frailty among geriatricage group population.

Deliberation, mood response, and the confirmation bias in the religious belief domain

A novel task was developed to examine the confirmation bias in religious beliefs, which compares to a classic political confirmation bias task. In Study 1, a balanced number of Christian versus non-religious (liberals and conservative) participants were recruited (n = 402). The data showed strong confirmation bias evidence in both the religious and political beliefs domains, and this bias appears to be enhanced by deliberation. In Study 2, a distinct set of n = 402 Christians and non-religious participants were administered the same religious beliefs task with added mood elicitation. The hypothesis tested was whether dissonant arguments promote negative mood, and whether this negative mood moderates the confirmation bias. The data from Study 2 supported these hypotheses. Data collection, hypotheses, and analysis plans for both studies were preregistered on the Open Science Framework. This paper documents the confirmation bias in the domain of religious beliefs, and results suggest the biological foundation of the confirmation bias includes both deliberative and emotional input, which may imply that comprehensive neural inputs from multiple brain regions promote this behavioral bias. This has implications not only regarding religious beliefs, but it also furthers our understanding of the brain-to-behavior pathway of the confirmation bias.

Bidimensional extensions of balancing and Lucas-balancing numbers

In this article bidimensional extensions of balancing and Lucas-balancing numbers are introduced, as well as some properties of these new bidimensional sequences.

The Evolution of Physical Activity and Health Research in China: A Bibliometric Analysis of Study Areas and Sex Balance in Authorship.

This article evaluates the evolution of physical activity and health research in China through a bibliometric analysis focused on number of publications, study areas, and sex balance in authorship. A systematic review was conducted by the Global Observatory for Physical Activity for "physical activity and health" publications between 1950 and 2019. Here, we focus on the 610 Chinese publications identified, defined as those in which data collection took place in China. We assessed the number of publications, classified them into 5 areas (1)surveillance, (2)correlates and determinants, (3)health consequences, (4)interventions, and (5)policy, and analyzed female participation in authorship. The first Chinese publication identified in the review was in 1990. Since, the average number of physical activity and health publications increased from one per year in the 1990s to 7.6 per year in the 2000s, and to 47 per year in the 2010s. Most publications focused on the correlates and determinants (38.7%) and the health consequences of physical activity (35.9%). Physical activity policy accounted for 2.3% of the publications. In the 1990s, 64% of the publications included at least one female author; this proportion increased to 90% in the 2010s. Despite a slow start, China's research on physical activity and health has grown rapidly since 2000. The distribution of publications by study areas and female participation in authorship is similar to that observed globally, with fewer publications focused on interventions and policy as compared with other topics.

Comparative Study of Algorithms for the Conversion From Surface Mesh Models to Volume Mesh Models

The study delves into the performance of different algorithms in the process of converting surface mesh models (SMMs) into volume mesh models (VMMs) required for finite element analysis. The experiment compared the Initial mesh, Delaunay, Frontal, and HXT algorithms, analyzing their central processing unit (CPU) runtime, node count, element count, and model size when processing simple models under default control parameters. The results showed that the Frontal algorithm performed the best in the conversion of simple models with a CPU runtime of 0.001 s, while the Delaunay algorithm took relatively longer. For complex models, the Initial mesh, Delaunay, and Frontal algorithms were all successful in completing the conversion, but the HXT algorithm failed, highlighting the importance of algorithm selection. The Delaunay algorithm performed best in terms of efficiency and model size, while the Frontal algorithm had an advantage in model refinement. Although the Initial mesh algorithm had a more balanced number of nodes and elements, its longer CPU runtime indicates potential for efficiency improvement. In addition, the randomness of the HXT algorithm in mesh generation led to variations in results, which requires further optimization to improve the consistency and robustness of the algorithm. Future research will focus on algorithm optimization, particularly enhancing the HXT algorithm’s ability to handle complex models, developing automated parameter selection mechanisms, exploring the application of algorithms in other engineering fields, and achieving better integration of algorithms with computer‐aided design (CAD)/computer‐aided engineering (CAE) workflows.

Burst-Aware Time-Triggered Flow Scheduling With Enhanced Multi-CQF in Time-Sensitive Networks

Deterministic transmission guarantee in time-sensitive networks (TSN) relies on queue models (such as CQF, TAS, ATS) and resource scheduling algorithms. Thanks to its ease of use, the CQF queue model has been widely adopted. However, the existing resource scheduling algorithms of CQF model only focus on periodic time-triggered (TT) flows without consideration of bursting flows. Considering that the bursting flows often carry high-priority data in real systems, in this paper we investigate the mixed-flow (i.e., TT and bursting flows) scheduling problem in CQF-based TSN aiming to maximize the number of schedulable flows and system load balance while satisfying the deterministic demands of delay, jitter, and reliability for both TT and bursting flows. Unfortunately, it is challenging to schedule the mixed flows with the original CQF model because of the huge difference between TT and bursting flows. To resolve this problem, we firstly design an enhanced Multi-CQF model to satisfy the basic demands of bursting flows sent at any time without affecting the deterministic transmission of TT flows. Given the complexity of mixed-flow scheduling and the proposed queue model, it is difficult for traditional algorithms to fully utilize network resources. Thus, we further propose a time-correlated DRL resource scheduling (TimeDRS) algorithm to optimize the resource allocation. TimeDRS can be extended to other time-related resource scheduling scenarios, such as TDMA-based scheduling. Experimental results demonstrate that our proposed approaches can greatly reduce frame loss and end-to-end latency for bursting flows, and well balance runtime and schedulability compared with state-of-the-art benchmarks.

Financial Reporting Quality During COVID-19 Pandemic: International Evidence

This paper examines the effect of the COVID-19 pandemic on financial reporting quality proxied by earnings conservatism and value relevance of accounting information. Our final sample consists of 10,510 firm-year observations from 29 countries with a balanced number of 5,255 observations for pandemic and pre-pandemic periods. The results show that during the pandemic, the financial statements of companies with a financial year end of 31 March 2020 have different qualities than those in the pre-pandemic period. Lower earnings conservatism is demonstrated in the pandemic period compared to the pre-pandemic period, supporting the argument that business tends to slow the recognition of bad news as the pandemic starts. The value relevance of accounting information declined in the pandemic period, primarily affected by the reduced value relevance of the book value of equity. The findings of this study can help investors evaluate the quality of accounting information and make smarter investment decisions, especially when most companies are in financial trouble.

A deterministic approach to investigate nonlinear evolution equations for large balance numbers

When the balance number is greater than one, the modified simple equation (MSE) method typically fails to yield analytical wave solutions for nonlinear evolution equations (NLEEs) that appear in engineering and mathematical physics. We have addressed this shortcoming in this article and established a technique to implement the MSE approach to investigate NLEEs for balancing number two. Two NLEEs, namely, the regularized long wave and the Jimbo-Miwa equations, have been investigated in order to affirm the approach. Through this method, we found further generic wave solutions related to physical parameters, and when the parameters receive particular values, solitons emerge from the exact solutions. Graphs are used to investigate the solitary wave features of the attained solution functions, which illustrate the usefulness, validity, and compatibility of the scheme.

Immune targets to stop future SARS-CoV-2 variants

ABSTRACT The SARS-COV-2 variants of concern (VOCs) accumulated mutations that confer to the viral particle a higher infectivity as well as a capacity to escape neutralizing antibodies (NAbs) elicited by vaccines. In this study, we aimed to identify immune determinants that can be targeted to control future SARS-CoV-2 VOC. Using an immunoinformatics pipeline, we constructed a first data set consisting of 215 spike (S) protein amino acid sequences of the wild-type SARS-CoV-2, as well as of the Alpha, Beta, Delta, Gamma, and Omicron variants/subvariants (BA.1, BA.2, BA.4, BA.5, XBB, and BQ.1). A second data set was composed of epitope amino acid sequences for NAb as well as for T-cells involved in anti-viral activity, retrieved from the Immune Epitope Database (IEDB). Epitope conservation and population coverage analyses were carried out using the data sets. The localization of fully conserved epitopes in the S protein was performed using PyMOL. As main results, (i) fully conserved epitopes were identified: 28 for NAbs and 53 and 99 for class-I and class-II human leukocyte antigen, respectively; (ii) the fully conserved epitopes were shown to have high coverage in the world population (99.77% class combined); and (iii) the receptor-binding domain (RBD) of the S protein better balanced numbers of epitopes for NAb and T-cells, while the subunit two concentrated the highest numbers of T-cell epitopes. These results indicate that the RBD region holds different kinds of immune targets that could be used in an escape mutation-proof vaccine antigen to control future SARS-CoV-2 variants. IMPORTANCE The emergence of SARS-CoV-2 had a major impact across the world. It is true that the collaboration of scientists from all over the world resulted in a rapid response against COVID-19, mainly with the development of vaccines against the disease. However, many viral genetic variants that threaten vaccines have emerged. Our study reveals highly conserved antigenic regions in the vaccines have emerged. Our study reveals highly conserved antigenic regions in the spike protein in all variants of concern (Alpha, Beta, Gamma, Delta, and Omicron) as well as in the wild-type virus. Such immune targets can be used to fight future SARS-CoV-2 variants.

Almost balancers, almost cobalancers, almost Lucas-balancers and almost Lucas-cobalancers

In this work, the general terms of almost balancers, almost cobalancers, almost Lucas-balancers and almost Lucas-cobalancers of first and second type are determined in terms of balancing and Lucas-balancing numbers. Later some relations on all almost balancing numbers and all almost balancers are obtained. Further the general terms of all balancing numbers, Pell numbers and Pell–Lucas number are determined in terms of almost balancers, almost Lucas-balancers, almost cobalancers and almost Lucas-cobalancers of first and second type.

Performance of the 23-gene Expression Profile (23-GEP) Test by Histopathological Evaluation in an Independent, Multi-Center Performance Cohort of Cutaneous Melanocytic Neoplasms

Histopathologic evaluation can effectively diagnose most melanocytic neoplasms; however, lesions considered to be difficult-to-diagnose pose challenges for accurate classification of malignant potential, which can lead to over- or under-treatment. Ancillary testing to provide additional information is available for such cases. The validated diagnostic 23-GEP test provides an objective result of benign, malignant, or intermediate. In this large, independent cohort, the performance of the 23-GEP in its current laboratory is presented. Lesions from patients ≥18 years old were enrolled from eight centers or from melanoma cases clinically submitted for prognostic 31-GEP testing. Lesions were independently reviewed by 3–5 dermatopathologists and included in the study if they were fully concordant or non-concordant without conflicting diagnoses (i.e., both benign and malignant designations) or majority of unknown malignant potential designations, resulting in a cohort (n=2512) of benign nevi (n=1140) and malignant melanomas (n=1372). Accuracy metrics and two-tailed 95% confidence intervals (CIs) were calculated using resampling x10,000 iterations to establish a balanced number of benign versus malignant samples. The 23-GEP performance within this cohort was 91.3% (95% CI, 89.2–93.2%) sensitivity, 91.9% (89.8–93.8%) specificity, 92.2% (9.30–94.0%) positive predictive value, and 91.0% (89.0–92.9%) negative predictive value; 7.8% of lesions received an intermediate result. These metrics do not deviate significantly from previously published studies. These data demonstrate that the 23-GEP has an overall accuracy of 91.6% (90.1–93.0%), further supporting its use as an ancillary test that can be integrated with clinical and histopathologic information to guide final diagnosis.

Performance of modified ResNet model for calcium score from non-contrast computed tomography

Abstract Aims Calcium score measured from non-contrast CT is considered as the reference method for risk assessment of coronary artery disease. We aimed to develop a modified ResNet layers model for calcium score assessment in a cohort of multi-ethnic Asian patients with suspected coronary artery disease. Methods This is a multicenter study which performs CT scans in 5000 Asian Admixture patients in Singapore from 3 different hospitals (APOLLO study). In this current study, 369 subjects (mean age 56 ± 11 years; 147 female) were analyzed. Of these patients, 36% were shown to have very low risk (CAC = 0), 49% had mildly increased risk (CAC = 1–99), 11% had moderately increased risk (CAC = 100–299), and 5% had moderate to severe risk (CAC>300). The number of labelled 2D axial calcium lesions were as follows: LAD – 929, LM – 101, LCX – 545 and RCA – 940. Data augmentation was carried out to increase the overall sample size and balance number of labelled calcium lesions in the dataset. The dataset was split at the patient level prior to data augmentation to prevent any data leakage issues (60% Training: 20% Validation and 20% Test). The calcium score model was developed by consisting of three modified ResNet layers (MRN), and a series of fully connected layers. Axial, coronal and sagittal CT images were fed into the modified ResNet individually and the output of the model was the probability of the calcium lesion being in any of the four arteries. Cross-entropy loss was used as the loss function during the training process, while F1 score was used to evaluate the model performance at per-voxel level. Results The correlation coefficient between our MRN model and clinical ground truth for the total calcium score was r = 0.90 (P < 0.0001). The MRN model performed well in detecting the location of calcium lesions belonging to any of the three arteries, with accuracies of 0.95 in LAD, 0.90 in LCX, and 0.80 in RCA. Additionally, the MRN model demonstrated good diagnostic accuracy, F1 score, and intra-class correlation coefficient (ICC) of 0.80, 0.79, and 0.92, respectively, in predicting the CAC risk categories (low, mildly increased risk, moderately increased risk, and moderately to severely increased risk). A confusion matrix for the CAC risk category between the expert reader and MRN is shown in Figure 1. Conclusion Our modified ResNet-based machine learning model attained excellent prediction of calcium score using non-contrast CT. Figure 1.Confusion matrix for CAC risk.

Solutions of the Diophantine EquationsBr=Js+JtandCr=Js+Jt

LetBrr≥0,Jrr≥0, andCrr≥0be the balancing, Jacobsthal, and Lucas balancing numbers, respectively. In this paper, the diophantine equationsBr=Js+JtandCr=Js+Jtare completely solved. The solutions rely basically on Matveev’s theorem on linear forms in logarithms of algebraic numbers and a procedure of reducing the upper bound due to Dujella and Pethö.

Retrieval of optical solitons: Drinfeld-Sokolov-Satsuma-Hirota Equation

In the present study, we focus on obtaining the optical soliton solutions of the Drinfeld-Sokolov-Satsuma-Hirota (DSSH) equation using Kudryhashov methods. First, a wave transformation is applied to the DSSH equation, resulting in a nonlinear ordinary differential equation (NLODE). A balance number is deduced through the balancing of this NLODE. Subsequently, candidate solutions, inclusive of their respective derivatives and the wave transformation, are inserted into the DSSH equation. This results in an equation in polynomial form. Terms with equal power are grouped together in the new equation, and their coefficients are set to zero, leading to a system of algebraic equations. Solving this algebraic system facilitates the identification of undetermined parameters within the candidate solutions, thus yielding the solutions for the DSSH equation. Visualization of these solutions is executed through contour plots as well as two- and three-dimensional graphical representations. The contributions of this study are of substantial relevance for subsequent research in nonlinear science.

Analisis Faktor Kesalahan Dalam Proses Pengisian Saldo Kedalam Dompet Digital Yang Dituju Dengan Aplikasi BCA Mobile

Digital money has become a modern transaction tool used today in the form of a number of balances for buying and selling transactions. Apart from the ease of making transactions with digital money innovations, it is possible that errors may occur in sending the balance to the intended digital wallet. This research aims to determine the influence of display quality factors, system services, and information service factors in the process of topping up balances into digital wallets. This research method uses a quantitative method by collecting data using a questionnaire by distributing questions using Google Form tools to 200 respondents who use the BCA Mobile application in Indonesia. The research results obtained by carrying out the f square test illustrate that the Visual Quality factor has a very significant impact on errors in topping up balances to digital wallets, then the System services factor also has quite a significant impact on errors in topping up balances to digital wallets, and on the factors Information quality does not have a significant impact on errors in filling in balances to digital wallets.

Strophes in Peshitta Psalms? A Study of Selected Examples

As the Peshitta plays an essential role in literary and textual criticism, the literary features of the Peshitta must be examined not only from the perspective of translation technique but also from the perspective of other factors, such as poetical devices and form. Little attention has been paid to the translation technique in the Peshitta Psalms despite the substantial research conducted on the Peshitta. Most studies have focused on the relationship between the Peshitta Psalms, the Hebrew Masoretic text, and other ancient versions. Therefore, the Peshitta Psalms have yet to be examined from the perspective of classical Syriac poetry. This study investigates how well the Syriac translator employed poetical devices to produce strophic structures and poetic style in the psalms, with particular attention to potential approaches to strophic structure that have not previously been explored. The paper addresses the question of whether the Peshitta Psalms are strophic. The study indicates that Peshitta Psalms 29, 96, 136, and 148 use strophic markers such as word repetition, alliteration, repetition of syntactical structures, parallelism and a balanced number of syllables and words.

A Genetic Algorithm-based Group Formation to Assign Student with Academic Advisor: A Study on User Acceptance using UTAUT

Group formation to assign students with academic advisors based on student demography can be exhaustive as various possibilities and combinations can be formed. Hence, this paper proposed a genetic algorithm-based approach to automate group formation based on student demography to assign students to their academic advisors. The genetic algorithm (GA) will optimize the group formation of students with a balanced number of nationalities, races, and genders. Also, this paper examines the user acceptance of the proposed genetic algorithm-based application to automate group formation using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. The survey aims to study the impact of independent and moderating variables on dependent variables. The result proved that all the independent variables, Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Condition (FC), have a positive impact on the dependent variable, Behavioral Intention (BI). In contrast, the moderating variable Experience (EX) and Voluntariness of Use (VU) have a negative impact on Behavioral Intention (BI). Thus, this paper concludes that the proposed application can increase the performance and efficiency of group formation and automatically assign students to academic advisors. However, respondents are reluctant and not ready to use the system. Thus, training and workshops can be conducted to introduce and train the users to utilize the system. Future works can be done where the application of the proposed genetic algorithm-based system can be further expanded to different academic purposes such as team formation for group assignment and team member selection for competition.

Intelligent recognition of greenhouse cucumber canopy vine top with deep learning model

In order to solve the problem of low recognition accuracy of cucumber canopy vine tops image caused by the high density and intermingling of the cucumber canopy vine, an image recognition model of cucumber canopy tops based on the deep learning model of improved YOLOv5 is proposed in this paper. A combination of online and offline augmentation is used to amplify the original data to ensure a balanced number of images in different types of datasets during training and testing. Considering the small leaves characteristics of the cucumber canopy vine tops, the CA mechanism module (YOLOv5-CA) is introduced into the backbone network of the YOLOv5 model to improve the recognition accuracy of the small leaf target. On this basis, the regression Loss GIOU of the target position was changed to EIOU and the cross-entropy function of confidence loss was changed to Focal Loss function (YOLOv5-CA-LS) to reduce the influence of the imbalance of difficult and easy samples on the detection results. The models before and after optimization were compared. The results show that compared with the YOLOv5 model, the accuracy, recall rate, mAP@0.5 and mAP@0.5:0.95 of the YOLOv5-CA-LS model is improved by 4.4%, 5.0%, 1.3% and 1.8% respectively. And average recognition accuracy value of the instance of the cucumber canopy tops adopted the YOLOv5-CA-LS model is 97.1% under different angle and cloudy conditions, which can meet the recognition requirement of high density and intermingling of the cucumber canopy vine tops.