Synthesis of Finely Controllable Sizes of Au Nanoparticles on a Silica Template and Their Nanozyme Properties

The precise synthesis of fine-sized nanoparticles is critical for realizing the advantages of nanoparticles for various applications. We developed a technique for preparing finely controllable sizes of gold nanoparticles (Au NPs) on a silica template, using the seed-mediated growth and interval dropping methods. These Au NPs, embedded on silica nanospheres (SiO2@Au NPs), possess peroxidase-like activity as nanozymes and have several advantages over other nanoparticle-based nanozymes. We confirmed their peroxidase activity; in addition, factors affecting the activity were investigated by varying the reaction conditions, such as concentrations of tetramethyl benzidine and H2O2, pH, particle amount, reaction time, and termination time. We found that SiO2@Au NPs are highly stable under long-term storage and reusable for five cycles. Our study, therefore, provides a novel method for controlling the properties of nanoparticles and for developing nanoparticle-based nanozymes.

Design of Optimal Controllers for Unknown Dynamic Systems through the Nelder–Mead Simplex Method

This paper presents an efficient method for designing optimal controllers. First, we established a performance index according to the system characteristics. In order to ensure that this performance index is applicable even when the state/output of the system is not within the allowable range, we added a penalty function. When we use a certain controller, if the state/output of the system remains within the allowable range within the preset time interval, the penalty function value is zero. Conversely, if the system state/output is not within the allowable range before the preset termination time, the experiment/simulation is terminated immediately, and the penalty function value is proportional to the time difference between the preset termination time and the time at which the experiment was terminated. Then, we used the Nelder–Mead simplex method to search for the optimal controller parameters. The proposed method has the following advantages: (1) the dynamic equation of the system need not be known; (2) the method can be used regardless of the stability of the open-loop system; (3) this method can be used in nonlinear systems; (4) this method can be used in systems with measurement noise; and (5) the method can improve design efficiency.

Reliability Test Plan for an Extended Birnbaum-Saunders Distribution

Birnbaum-Saunders distribution has been widely studied in statistical literature because this distribution accommodates several interesting properties. The purpose of this paper is to introduce a new parametric distribution based on the Birnbaum-Saunders model and develop a new acceptance sampling plans for derived extended Birnbaum-Saunders distribution when the mean lifetime test is truncated at a predetermined time. For various acceptance numbers, confidence levels and values of the ratio of the fixed experimental time to the specified mean life, the minimum sample size necessary to assure a specified mean lifetime worked out. The results are illustrated by a numerical example. The operating characteristic functions of the sampling plans and producer’s risk and the ratio of true mean life to a specified mean life that ensures acceptance with a pre-assigned probability are tabulated. This paper presents relevant characteristics of the new distribution and a new acceptance sampling plans when the lifetime of a product adopts an extended Birnbaum-Saunders distribution. Based on this study, the optimal number of testers demanded is decreases as test termination time increases. Moreover, the operating characteristic values increases as the mean life ratio increases, which indicate that items with increased mean life will be accepted with higher probability compared with items with lower mean life ratio.

Synthesis of Finely Controllable Sizes of Au Nanoparticles on a Silica Template and Their Nanozyme Properties

The precise synthesis of fine-sized nanoparticles is critical for realizing the advantages of nanoparticles for various applications. We developed a technique for preparing finely controllable sizes of gold nanoparticles (Au NPs) on a silica template using the seed-mediated growth and interval dropping methods. These Au NPs, embedded on silica nanospheres (SiO2@Au NPs), possess peroxidase-like activity as nanozymes and have several advantages over other nanoparticle-based nanozymes. We confirmed their peroxidase activity; in addition, factors affecting the activity were investigated by varying the reaction conditions such as concentrations of tetramethyl benzidine and H2O2, pH, particle amount, reaction time, and termination time. We found that SiO2@Au NPs are highly stable under long-term storage and reusable for five cycles. Our study, therefore, provides a novel method for controlling the properties of nanoparticles and for developing nanoparticle-based nanozymes.

On the Estimation Problems for Exponentiated Exponential Distribution under Generalized Progressive Hybrid Censoring

In this article, we considered the statistical inference for the unknown parameters of exponentiated exponential distribution based on a generalized progressive hybrid censored sample under classical paradigm. We have obtained maximum likelihood estimators of the unknown parameters and confidence intervals utilizing asymptotic theory. Entropy measures, such as Shannon entropy and Awad sub-entropy, have been obtained to measure loss of information owing to censoring. Further, the expected total time of the test and expected number of failures, which are useful during the execution of an experiment, also have been computed. The performance of the estimators have been discussed based on mean squared errors. Moreover, the effect of choice of parameters, termination time T, and m on the ETTT and ETNFs also have been observed. For illustrating the proposed methodology, a real data set is considered.

Controlling COVID-19 Outbreaks with Financial Incentives

In this paper, we consider controlling coronavirus disease 2019 (COVID-19) outbreaks with financial incentives. We use the recently developed susceptible-unidentified infected-confirmed (SUC) epidemic model. The unidentified infected population is defined as the infected people who are not yet identified and isolated and can spread the disease to susceptible individuals. It is important to quickly identify and isolate infected people among the unidentified infected population to prevent the infectious disease from spreading. Considering financial incentives as a strategy to control the spread of disease, we predict the effect of the strategy through a mathematical model. Although incentive costs are required, the duration of the disease can be shortened. First, we estimate the unidentified infected cases of COVID-19 in South Korea using the SUC model, and compute two parameters such as the disease transmission rate and the inverse of the average time for confirming infected individuals. We assume that when financial incentives are provided, there are changes in the proportion of confirmed patients out of unidentified infected people in the SUC model. We evaluate the numbers of confirmed and unidentified infected cases with respect to one parameter while fixing the other estimated parameters. We investigate the effect of the incentives on the termination time of the spread of the disease. The larger the incentive budget is, the faster the epidemic will end. Therefore, financial incentives can have the advantage of reducing the total cost required to prevent the spread of the disease, treat confirmed patients, and recover overall economic losses.

Optimal decisions on software release and post-release testing: A unified approach

In this research, a novel approach is developed where a testing team delivers the software product first and extends the testing process for additional time in the user environment. During the operational phase, users also participate in the fault detection process and notify the defects to the software. In this study, a reliability growth model is proposed using a unified approach based on the expenditure of efforts during the testing process. Besides, debugging process is considered imperfect as new faults may enter the software during each fault removal. The developed model further considers that the developer's rate of defect identification changes with a software release. Thus, the software time-to-market acts as a change-point for the failure observation phenomenon. It is asserted that the accuracy of a software reliability estimation improves by implementing the concept of change-point. The main aim of the paper is to evaluate the optimal release time and testing termination time based on two attributes, particularly, reliability, and cost. A multi-attribute utility theory (MAUT) is applied to find a trade-off between the two conflicting attributes. Finally, a numerical example is presented by using the historical fault count data. The behavior of two decision variables is measured and compared with the existing release time strategy.

Statistical Techniques for Detecting Cyberattacks on Computer Networks Based on an Analysis of Abnormal Traffic Behavior

Represented paper is currently topical, because of year on year increasing quantity and diversity of attacks on computer networks that causes significant losses for companies. This work provides abilities of such problems solving as: existing methods of location of anomalies and current hazards at networks, statistical methods consideration, as effective methods of anomaly detection and experimental discovery of choosed method effectiveness. The method of network traffic capture and analysis during the network segment passive monitoring is considered in this work. Also, the processing way of numerous network traffic indexes for further network information safety level evaluation is proposed. Represented methods and concepts usage allows increasing of network segment reliability at the expense of operative network anomalies capturing, that could testify about possible hazards and such information is very useful for the network administrator. To get a proof of the method effectiveness, several network attacks, whose data is storing in specialised DARPA dataset, were chosen. Relevant parameters for every attack type were calculated. In such a way, start and termination time of the attack could be obtained by this method with insignificant error for some methods.