Internal Variables Research Articles

Modeling of the unsteady aerodynamic characteristics of the NACA 0015 airfoil from the data of numerical calculations of the flow

The possible application of the results of numerical modeling in developing an approximate phenomenological mathematical aerodynamic model applicable in solving the problems of dynamics is studied with reference to the example of the unsteady flow past the NACA 0015 airfoil oscillating in the angle of attackat different frequencies, amplitudes, and mean angles of attack. For this purpose, the Reynolds equations are solved in both steady and unsteady formulations, together with thek–ω-SST turbulence model. The results of the calculations are validated by means of comparing them with the experimental data. The model of the normal force and the longitudinal moment formulated within the frameworkof an approach introducing an internal dynamic variable is identified according to the data of calculations. The results of the modeling are compared with the numerical and experimental data. The comparison with the conventional approach to the modeling based on the linear unsteady model with the use of dynamic derivatives is also carried out.

A matrix-separation-based integral inequality for aperiodic sampled-data synchronization of delayed neural networks considering communication delay

This paper achieves the synchronization of delayed neural networks (DNNs) considering aperiodic sampled-data control and communication delay. First of all, based on the master-slave DNNs with aperiodic sampling synchronization controller, a synchronization error system is constructed. Then, an augmented functional containing both the error state and its derivative is constructed. Compared with the existing researches, the augmented functional introduces more cross information of error states to the criterion. Next, an integral inequality based on the separation of internal integral variable and matrix is developed. Compared to the inequalities that treat the internal variable and the matrix as unified ones, the developed inequality provides a tighter estimate of the derivative of the augmented functional. On this basis, a criterion with less conservative is developed for the aperiodic sampled-data synchronization of DNNs considering communication delay. Finally, to indicate the superiority of the developed method on improving the acceptable sampling upper bound of synchronization, three numerical examples are provided.

Menstrual Cycle Phases and Elite Female Soccer During Training: Exercise Load Perception and External Workload Monitoring

BACKGROUND: Female soccer has grown exponentially in the last years, however studies on women soccer players are very few compared with male ones and several inconsistencies are reported in the literature for female players. Physiological hormonal fluctuations during the different moments of menstrual cycle could have important implications on soccer performance, therefore, the aim of the present study was to investigate the impact of menstrual cycle phases on external and internal loads in elite women’ soccer players during an in-season training period, and to describe the internal-external training load relationship, in relation to different menstrual cycle moments. METHODS: 16 elite players from Italian soccer first division were monitored for 12 weeks. The main internal parameter (rate of perceived exertion - RPE), external variables (total time, total distance, high speed running - HSR, numbers of accelerations/decelerations) and session-RPE were collected during training sessions and analyzed trough a repeated-measures ANOVA to identify differences in the MC weeks. Menstrual cycle was monitored through daily questionnaires and was divided into four phases: menstruation week, pre-ovulation, post-ovulation, and pre-cycle. RESULTS: HSR and total distance were significantly lower during menstruation week than post-ovulation week (18318.70 ±1802.04 m vs 20358.41 ± 1639.27 m, respectively; p=0.022). A significant correlation was found in pre-cycle week between RPE and total distance (r=0.545; p=0.029), and between session-RPE with total distance (r=0.514; p=0.042) and total time (r=0.502; p=0.048). When considering the whole menstrual cycle, weak and moderate correlations were found for RPE and session-RPE with total time, total distance and HSR. CONCLUSION: Appropriate menstrual cycle monitoring is required for better interpretation of players’ response in elite women’s soccer training, given that during menstruation week, external load variables could be impaired. RPE and session-RPE values do not change statistically with changes in external variables, and their relationship showed unclear results, highlighting caution when interpreting them, and suggesting their use in combination with other parameters, especially during early follicular phase.

Model-free chemomechanical interfaces: History-dependent damage under transient mass diffusion

This paper presents a data-driven framework based on distance functional for chemo-mechanical cohesive interfaces to capture transient diffusion and resulting interfacial damage evolution. The framework eliminates reliance on complex constitutive models and phenomenological assumptions, especially avoiding the coupling tangent terms with a given material database. The interfacial chemical potential and its jumps are used to expand the phase space for describing the chemical states of interfaces. Subsequently, a novel chemo-mechanical distance norm, including traction-separation pair, interfacial chemical potential-concentration pair and corresponding chemical potential jump-flux pair, is presented. Momentum conservation law for interfacial tractions and mass conservation law for interfacial concentration are enforced via Lagrange multipliers. For tracking the history-dependent state of the interface damage, an internal variable, termed interface integrity, is introduced to condition the interfacial database and manage the subsets mapping strategies, following physically motivated evolution constraints. Numerical examples are conducted to investigate the efficiency and capability of the present framework. A monotonic loading test validates a good numerical convergence relative to the number of data points. Subsequent cyclic loading simulations, compared with the reference solutions, show that the algorithm is well suitable to predict the history-dependent interface damage evolution under complex loading paths. Finally, the chemo-mechanically coupled examples capture phenomena such as interfacial swelling and interface degradation induced by transient diffusion and stress-driven diffusion. The current work provides a promising tool for understanding chemo-mechanical behaviors of interfaces within heterogeneous composites.

Enhancing Internal Factors Unlocks Profit in Saudi Banks

General Background: Banks' profitability is crucial for financial stability and economic growth. Specific Background: Internal factors such as capital adequacy, asset quality, and management effectiveness play a significant role in determining profitability. However, the impact of these variables on Saudi banks needs further exploration. Knowledge Gap: Existing research lacks a comprehensive analysis of how these internal variables affect the profitability of Saudi banks over a long period. Aims: This study examines the effect of changes in capital adequacy, asset quality, management effectiveness, and liquidity on the bank profit index, measured by the return on assets (ROA) at Saudi Fransi Bank from 2000 to 2022. Results: Quantitative analysis reveals that capital adequacy and asset quality have a significant positive impact on ROA, with 1% increases in each leading to 20% and 76% increases in ROA, respectively. In contrast, increased liquidity and management inefficiency negatively affect ROA, decreasing it by 33% and a significant margin, respectively. The internal variables account for about 96.4% of the variation in profitability. Novelty: This study offers a detailed long-term analysis of internal factors affecting bank profitability in Saudi Arabia. Implications: Enhancing asset quality and management effectiveness is crucial for improving profitability and reducing costs, benefiting both Banque Saudi Fransi and the broader banking sector. Highlights: Positive Impact: Capital adequacy and asset quality enhance bank profitability. Negative Impact: Higher liquidity and management inefficiency reduce profitability. High Explanatory Power: Internal variables explain 96.4% of profitability variation. Keywords: Bank Profitability, Return on Assets, Capital Adequacy, Asset Quality, Management Effectiveness

Homogenization of high-contrast media in finite-strain elastoplasticity

This work is devoted to the analysis of the interplay between internal variables and high-contrast microstructure in inelastic solids. As a concrete case-study, by means of variational techniques, we derive a macroscopic description for an elastoplastic medium. Specifically, we consider a composite obtained by filling the voids of a periodically perforated stiff matrix by soft inclusions. We study the Γ-convergence of the related energy functionals as the periodicity tends to zero, the main challenge being posed by the lack of coercivity brought about by the degeneracy of the material properties in the soft part. We prove that the Γ-limit, which we compute with respect to a suitable notion of convergence, is the sum of the contributions resulting from each of the two components separately. Eventually, convergence of the energy minimizing configurations is obtained.

A photo-chemo-mechanical coupling constitutive model for photopolymerization-based 3D printing hydrogels

Photopolymerization-based 3D printing has emerged as a key technology in hydrogel manufacturing, broadening the attributes of hydrogels and extending their applications into diverse engineering fields. However, the mechanical properties of hydrogels dramatically impact the functionality and quality in practice. It is necessary to develop an appropriate theoretical model to predict the evolution of the mechanical properties of hydrogels during the photopolymerization process. In this work, systematical experiments were performed to investigate mechanical properties of PAAm hydrogel under different photopolymerization condition. The results reveal a noticeable increasement in both elastic and viscous behavior of hydrogel with the advancement of polymerization. To fully capture the experimental observations, we developed a coupled photo-chemo-mechanical theoretical framework that integrates reaction kinetics with a physically-based viscoelastic constitutive model. Within this model, the degree of conversion serves as an internal variable, which related to microscopic structures such as correlation length, and tube diameter. The developed model exhibits remarkable prediction ability for hydrogels with various degree of polymerization. The current work paves a potentially new avenue for understanding the evolution of mechanical properties in photopolymerized hydrogels, providing theoretical guidance for the manufacturing of hydrogels through photopolymerization-based 3D printing.

가정 내 영유아 인성교육 실행에 영향을 미치는 부모 변인 분석

Objectives This study investigated how the variables parents' perception of character education(importance, interest), parents' character education capabilities(readiness, degree of education attendance, degree of understanding of character education concept), parents' internal variables(Self-esteem, self-efficacy, emotional value of children) affect the implementation of character education at home. Methods After surveying 403 parents; at care-giving centers and kindergartens in the gyeonggi-do area, prequency analysis, technical statistics, pearson correlation and multiple-regression analysis were conducted with the SPSS 18.0 program. Results The variables of parents' perception of character education(importance, interest), parents' character education capabilities(readiness, degree of education attendance, degree of understanding of character education concept), parents' internal variables(Self-esteem, self-efficacy, emotional value of children) were found to have a significant statics correlation with the implementation of character education at home. The respecting explanatory power was observed of parents' character education capabilities(readiness, degree of understanding of character education concept), parents' perception of character education(interest), parents' internal variables(emotional value of children). Conclusions The results of this study suggest that in order to implement character education at home, not only parents' awareness of character education for infants and toddlers, but also parents' preparation and effort to implement character education, and internal variables such as positive views of the value of their children are very important.

Forecasting energy consumption with a novel ensemble deep learning framework

Energy baseline development is a central and significant component of an energy management system. In commercial buildings where a wide variety of internal and external variables might impact the electricity usage, having a robust forecasting method is elemental to evaluate and enhance the energy performance over time. Due to extensive progress in data analytics, a number of single prediction methods have been developed recently. Nevertheless, either development of the theoretical study or application of ensemble learning methods to enhance prediction performance and stability find lacking in energy management of commercial sectors. This research proposes a novel heterogeneous ensemble model framework for short-term electricity consumption prediction under the hourly and daily granularity to bridge this research gap. The framework is composed of two levels. The first uses five stand-alone deep learning models including Recurrent Neural Network (RNN), Long Short-term Memory (LSTM), Bidirectional-LSTM (Bi-LSTM), Gated Recurrent Unit (GRU) and Convolutional Neural Network (CNN) as base models. In contrast, the second level applies the predicted outputs of the base models as feature inputs of k nearest neighbors (KNN), which is a strong model. The Grid Search is also used to search for the key optimal hyper parameters of the base models and the strong model. To demonstrate the developed model's effectiveness, four different space types of real-world educational buildings are used for verification. The extensive database has been setup for this study to collect data from Jan. 2018 to Dec. 2022. The quantitative analysis of the model was conducted in contrast with the base models and prevalent machine learning methods, including artificial neural network (ANN), KNN, support vector regression (SVR), AdaBoost, and linear regression (LR) during the testing phase. The prediction accuracy has improved substantially, with roughly a 95 % reduction in CV-RMSE compared to that of AdaBoost and SVR. Moreover, the results signify the introduced model outperforms the base models and the ML methods in all studied buildings, thereby providing a foundation for developing effective management policies.

Internal and External Factors on the Performance of Halal Food MSMEs in Bekasi Regency

This study analyzes the performance of halal food MSMEs in Bekasi Regency. Internal factors of information technology and external factors of cooperation influence the performance of MSMEs. The unit of analysis in this study amounted to 100 halal food MSME players in Bekasi Regency. The findings in this study further strengthen the findings of previous studies where internal factors of information technology affect the performance of MSMEs with a p-value of 0.009 and external factors of cooperation affect the performance of MSMEs with a p-value of 0.000. This study further strengthens previous findings regarding information technology and cooperation. This research is new to previous research conducted on the halal food industry in the Bekasi district. The selection of internal variables with the Resource Base View (RBV) and Market Base View (MBV) theories is a novelty in this study.

Quantifying internal and external training loads in collegiate male volleyball players during a competitive season

BackgroundThe long-term monitoring of internal and external training load is crucial for the training effectiveness of athletes. This study aims to quantify the internal and external training loads of collegiate male volleyball players during the competitive season. The internal and external training load variables were analyzed across mesocycles and playing positions.MethodsFourteen participants with age of 20.2 ± 1.3 years, height of 1.81 ± 0.05 m, and body weight of 70.8 ± 5.9 kg were recruited. The data were collected over a 29-week period that was divided into four mesocycles: preparation 1 (P1, weeks 1–7), competition 1 (C1, weeks 8–14, including a 5-day tournament in week 14), preparation 2 (P2, weeks 15–23), and competition 2 (C2, weeks 24–29, including a 6-day tournament in week 29). Each participant wore an inertial measurement unit and reported the rating of perceived exertion in each training session. The internal training load variables included weekly session rating of perceived exertion, acute: chronic workload ratio, and training monotony and strain. The external training load variables included jump count and height and the percentage of jumps exceeding 80% of maximal height.ResultsC2 had the highest average weekly internal training load (3022 ± 849 AU), whereas P2 had the highest average weekly acute: chronic workload ratio (1.46 ± 0.13 AU). The number of weekly jumps in C1 (466.0 ± 176.8) was significantly higher than in other mesocycles. Weekly jump height was significantly higher in C1, P2, and C2. Internal training load was positively correlated with jump count (ρ = 0.477, p < 0.001). Jump count was negatively correlated with jump height (ρ = −0.089, p = 0.006) and the percentage of jumps exceeding 80% of maximal height (ρ = −0.388, p < 0.001). The internal and external training load variables were similar among different playing positions.ConclusionThe participants exhibited significantly higher internal training load in C2 and higher jump height after P1. A high jump count was associated with higher internal training load and lower jump height. Excessive jumps may result in fatigue and reduce height.

(Invited) Thermoelectric Analysis of Dielectric Materials Properties for Neuromorphic Technologies

The effort made in recent years in the development of new memories has led to a significant advance in emerging technologies, which have proven their usefulness not only in the field of memories, but also to obtain devices that perform an artificial synapse and thus emulate biological neurons. Among the novel concepts, resistive-switching random access memory (RRAM), or memristive device, has attracted a great deal of interest for its ability to store multiple states. In fact, its operation is based on the so-called resistive switching, which consists of the formation of conductive filaments through a dielectric that separates two metal electrodes, allowing current to flow between them. The conductive filaments can be partially dissolved and re-formed, which explains the variation in conductivity and thus the existence of several different states, opening up possibilities for analog applications and brain-inspired computing systems. In the field of memories, two clearly differentiated states are used, called low resistance (LRS, when the filament is formed) and high resistance (HRS, when the filament is partially dissolved and does not completely join the two electrodes). The set process takes the structure to the LRS state, while the reset takes it to the HRS. Since the resistance of the memristor is not constant but depends on the previous states it has gone through, this device is non-volatile, i.e., it remembers its history [1].At the present time, when artificial intelligence-based applications are experiencing considerable momentum, there is a call for intensified research into memristive devices-based neuromorphic computing systems [2]. To achieve efficient, high-performance neuromorphic circuits, it is not enough to be able to switch the device resistance between two distinct values. In addition, the specific value of the conductivity at each time instant must be properly controlled so that the synaptic weights can be encoded. For this purpose, it is necessary to focus on the analysis of the dynamic evolution of the internal variables of the memristive devices, which necessarily implies a deeper understanding of the underlying physical processes that cause the variation of their resistance [3].In this work, a thermoelectric analysis of memristive devices is carried out, with special emphasis on time response and multilevel control. The studied structures are TiN/Ti/HfO2/W and TiN/Ti/HfO2/Pt/Cr metal-insulator-metal (MIM) capacitors, with several HfO2 -thickness values varying between 8 and 20 nm. Dielectric layers were atomic layer deposited (ALD). It is known that in the case of hafnium oxide layers sandwiched between these specific electrode materials, the resistive switching phenomenon is related to the distribution of oxygen vacancies inside the dielectric film, which occurs when oxygen atoms are drawn to the electrodes [4].Fig.1 shows the control of intermediate states in multilevel behavior, both in terms of I-V and small signals (conductance and capacitance measured at 500 kHz). The current evolution in the reset process after applying -0.8 V height-voltage pulse trains can be seen in Fig.2, which also shows the schematic of the experimental setup. On the other hand, Fig.3 depicts some results of the transient analysis; the amplitude of the current transients in both set and reset states have been superimposed on the external I-V loop. An example of the study of set and reset dynamics performed by applying variable speed voltage ramps is shown in Fig. 4, together with the experimental setup, this analysis has been carried out at different temperatures, between 77 and 350 K. All results shown in Figs. 1-4 correspond to a TiN/Ti/10 nm-HfO2/W structures, being TiN the top electrode and W the bottom one. Bias voltage is applied between top and bottom electrodes.The influence of the dielectric thickness on the resistive switching modes that the structures can exhibit is also addressed. Finally, some results on the physical and geometrical morphology of the conductive filaments, obtained from the analysis of the conduction mechanisms, are discussed.REFERENCES “Memristive devices for brain-inspired computing”. Edited by S. Spiga et al. Woodhead Publishing (2020). https://www.sciencedirect.com/science/article/pii/B9780081027820000253?via%3DihubLanza et al. Science 376, 6597 (2022). https://doi.org/10.1126/science.abj9979 García et al. J. of Phys. D: Appl. Phys. 56, 365108 (2023) https://iopscience.iop.org/article/10.1088/1361-6463/acdae0/meta C. Jasmin “Filamentary model in resisitive switching materials”. AIP Conf. Proc. 1901, 060004 (2017). https://doi.org/10.1063/1.5010507 Figure 1

Training Load Monitoring in Elite Youth Women's Artistic Gymnasts: A Pilot Study.

Women's artistic gymnastics (WAG) is a complex aesthetic sport in which athletes start at a young age and are exposed to high loads during their careers. Little is known about the external and internal training load characteristics among elite young gymnasts. High training loads, with variations over the weeks, are expected. There is a relationship between external and internal load variables. Cohort study. Level 3. Seven elite-level Brazilian youth artistic gymnasts (age, 11.3 ± 0.4 years; mass, 33.0 ± 7.0 kg; height, 137.7 ± 10.6 cm; experience, 4.0 ± 1.2 years) participated in this study. Five nonconsecutive microcycles were monitored. Both external and internal training loads were quantified by counting the number of elements in video recordings of training sessions and by the session rating of perceived exertion method. A total of 168 individual training sessions were monitored. The microcycle that succeeded the main competition showed a significantly lower training load than ≥3 of the other 4 microcycles for all training load variables, except for vault elements, of which microcycle 4 was inferior only to the microcycle before the competition. Significant correlations were found between weekly internal training load and the total of elements and elements performed on uneven bars. Youth women's artistic gymnasts present fluctuations in external and internal training load variables over the weeks close to a major competition. Training load management in this sport must consider the specificity of each apparatus, as they have different demands and training load behaviors. A better comprehension of external and internal training loads in youth WAG and its apparatuses can benefit coaches and support staff and provide more information to overcome the challenge of training load management in gymnastics.

A computational approach for phase-field model of quasi-brittle fracture under dynamic loading

AbstractA computational model is formulated for studying dynamic crack propagation in quasi-brittle materials exposed to time-dependent loading conditions. Under such conditions, inertial effects of structural components play an important role in modelling crack propagation problems. The computational model is proposed within the theory of regularised cracks which uses a damage-like internal variable. Here, fracture considers phase-field damage which gives rise to a material degradation in a narrow material strip defining the regularised crack. Based on the energy formulation using the Lagrangian of the system, the proposed computational approach introduces a staggered scheme adopted to solve the coupled system and providing it in a variational form within the time stepping procedure. The numerical data are obtained by quadratic programming algorithms implemented together with a finite element code.

Dynamic event‐triggered leader‐following bipartite consensus of second‐order multi‐agent systems under DoS attacks

AbstractThis article investigates the bipartite secure consensus of the second‐order leader‐follower multi‐agent systems (MASs) against aperiodic denial of service (DoS) attacks. First, a new dynamic event‐triggered strategy is proposed for the consensus control. Compared with the static event‐triggered strategy, the dynamic event‐triggered protocol can reduce the trigger times and save resources by introducing an internal dynamic variable. Different from the secure consensus results which only discussed the cooperative links, based on the theory of the structurally balanced graph, this article considers cooperative and antagonistic interactions among agents simultaneously for complex behaviors of them. Besides, the characteristics of the DoS attacks are analyzed in detail and the secure consensus is achieved by utilizing the Lyapunov theory and inductive methods. Finally, the Zeno behavior is excluded and the availability of the designed algorithms is demonstrated by numerical simulations.

The Influence of Audit Characteristics and Company Characteristics on Audit Report Lag

This study investigates the impact of audit characteristics, including Audit Opinion, Audit Industry Specialization, and Audit Reputation, along with company characteristics such as Company Age and Financial Distress, on Audit Report Lag in non-primary consumer sector companies listed on the Indonesian Stock Exchange from 2011 to 2022. Analyzing data from 61 companies over 12 years with 732 observations, the research employs multiple linear regression analysis in EViews12. Findings reveal that collectively, audit opinion, industry specialization, audit reputation, company age, and financial distress significantly influence Audit Report Lag. Specifically, audit opinion, industry specialization, audit reputation, and financial distress exhibit a negative impact on Audit Report Lag, while company age has a positive effect. The study recommends future research to explore other sectors and include internal company variables like independent commissioners and institutional ownership for a more comprehensive analysis. The focus solely on auditor-related variables suggests avenues for broader investigations into internal company dynamic

Determinant Factor Analysis of Financial Performance of Micro, Small and Medium Enterprises with Social Capital as a Moderating Variable During COVID-19 in Aceh, Indonesia

Abstract This study analyzes the problem factors affecting Micro, Small, and Medium Enterprises (MSMEs) performance with social capital variables. The problems are related to developing MSMEs’ financial and non-financial performance and are considered inseparable from various internal and external influences. This research is a quantitative-qualitative research with primary data. The utilization of questionnaires and interviews as methods for data collection. The data analysis technique used was a statistical analysis based on partial least squares (PLS). The study’s results found that internal and external factors had a significant positive effect on the financial performance of MSMEs. The E-commerce factors and social capital significantly positively affected the financial performance of MSMEs. However, the colonial capital did not strengthen the relationship between internal variables, external, and E-commerce on the financial performance of MSMEs.

Comparison and evaluation of different constitutive models for predicting the hot deformation behavior of Mg-Gd-Y-Zr alloy

The popular constitutive models used in the field of hot forming of magnesium alloys can be divided into phenomenological models, machine learning models, and internal state variables (ISV) models based on physical mechanisms. Currently, there is a lack of comparison and evaluation regarding the suitability of different types of models. In this study, Mg-Gd-Y-Zr alloy is taken as the research object. The hot deformation behavior of the alloy was studied systematically. Subsequently, Arrhenius model with strain compensation, artificial neural network (ANN) model, and ISV model involving dynamic recrystallization (DRX), dislocation density and grain size evolution were established. ANN model demonstrates a higher level of accuracy in fitting the original stress-strain curves compared to both ISV model and modified Arrhenius model, but ANN model is not suitable for predicting the experimental results outside of the initial database. ISV model considers the impact of microstructure evolution history on stress, making it highly effective in reflecting the mechanical responses under complex loading condition. The established ISV model is embedded in the ABAQUS software, which shows good ability in calculating the mechanical response, dimension, and microstructure evolution information of the component during hot forming.

Comparison of modulation efficiency between normal and degenerated primate retina.

With electrical stimulation, retinal prostheses bypass dysfunctional photoreceptors and activate the surviving bipolar or retinal ganglion cells (RGCs). Therefore, the effective modulation of RGCs is crucial for developing retinal prostheses. Substantial research has been performed on the ability of an electrical stimulus to generate a reliable RGC response. However, different experimental conditions show varying levels of how well the electrical stimulation evokes RGC spikes. Therefore, in this study, we attempted to extract an indicator to understand how the electrical stimulation effectively evokes RGC spikes. Six cynomolgus monkeys were used: three as controls and three as an N-methyl-N-nitrosourea (MNU)-induced retinal degeneration model. The retinal recordings were performed using 8 × 8 multi-electrode arrays (MEAs). Electrical stimulation consisted of symmetrical biphasic pulses of varying amplitudes and durations. The number of stimulation conditions that resulted in significantly higher post-stimulation firing rates than pre-stimulus firing rates was defined as the modulation efficiency ratio (MER). The MER was significantly lower in degenerated retinas than in normal retinas. We investigated the relationship between the variables and the MER in normal and degenerated primate RGCs. External variables, such as duration and inter-electrode distance, and internal variables, such as average firing rates and statistics (mean, standard deviation, and coefficient of variation [CV]) of inter-spike intervals (ISIs) of spontaneous spikes, were used. External variables had similar effects on MER in normal and degenerated RGCs. In contrast, internal variables affected MER differently in normal and degenerated RGCs. While in normal RGCs, they were not related to MER, in degenerated RGCs, the mean ISIs were positively correlated with MER, and the CV of ISIs was negatively correlated with MER. The most important variable affecting MER was the mean ISI. A shorter ISI indicates hyperactive firing in the degenerated retina, which prevents electrical stimulation from evoking more RGCs. We believe that this hyperactivity in degenerated retinas results in a lower MER than that in the normal retina. Our findings can be used to optimize the selection of stimulation channels for in vitro MEA experiments and practical calibration methods to achieve higher efficiency when testing retinal prostheses.

Analysis The Influence of Internal Audit and Internal Control on Fraud Prevention: Literature Review Articles

The objective of this study is to examine the impact of internal audit and internal control on the prevention of fraud. The used approach involves doing a literature review by examining six (6) primary studies that have investigated the impact of internal audit and inter-nal control on fraud prevention. The research findings indicate that internal audit factors have an impact on fraud prevention, while internal control variables also have an affect on fraud prevention.