A dual-quenched ECL immunosensor for ultrasensitive detection of retinol binding protein 4 based on luminol@AuPt/ZIF-67 and MnO2@CNTs

Background Retinol binding protein 4 (RBP4) has been regarded as an important serological biomarker for type 2 diabetes mellitus (T2DM). Hence, the construction of a highly sensitive detection method for RBP4 is the key to early prevention and multidisciplinary intervention of T2DM. In this work, a dual-quenched electrochemiluminescence (ECL) immunosensor has been fabricated for ultrasensitive detection of RBP4 by combining zeolitic imidazolate framework-67/AuPt-supported luminol (luminol@AuPt/ZIF-67) with MnO2 nanosheets-grown on carbon nanotubes (MnO2@CNTs). Results AuPt/ZIF-67 hybrids with high-efficiency peroxidase-like activity could provide multipoint binding sites for luminol and antibodies and significantly boost the amplified initial signal of the ECL immunosensor. Upon glutathione/H2O2 coreactants system, MnO2@CNTs composites could quench the initial signal by inhibiting mimic peroxidase activity of luminol@AuPt/ZIF-67. Moreover, the absorption spectrum of the MnO2@CNTs composites completely overlaps with the emission spectrum of luminol, which can further reduce initial signal by ECL resonance energy transfer (ECL-RET). Conclusions Benefiting from the above-mentioned properties, the designed immunoassay sensitivity exhibited excellent sensitivity and relative stability for RBP4 detection range from 0.0001 to 100 ng mL−1 with a low detection limit of 43 fg mL−1. Therefore, our ECL immunosensor provides an alternative assaying strategy for early diagnosis of T2DM. Graphic abstract

ANALISIS PENGARUH PROFITABILITAS DAN LIKUIDITAS TERHADAP OPINI AUDIT GOING CONCERN

Companies that receive a going concern audit opinion show events and conditions that would cause the auditor to doubt about the going concern of the company. This opinion can be used as an initial signal for users of financial statements to avoid mistakes when making a decision. Regarding the factors that influence going-concern audit opinion, many previous studies have been carried out. However, it has inconsistencies in the results of the study. Thus, the research aims to carry out retesting related "factors that influence going concern audit opinion". The variables tested include Profitability and Liquidity. The research sample uses manufactur companies in the consumer goods industry which were listed on the Indonesian Stock Exchange for the period 2018-2019. The sampling technique was purposive sampling, which obtained 102 companies’ data that matched the criteria. Logistic regression analysis was used to test the hypothesis of this study. Hypothesis testing results that partially the profitability and liquidity variables have no effect on going-concern audit opinion.

Experimental Study on Sampling Theorem in Signal Processing

This practicum is to define the study properties of the sampling theorem. Understand the effect of selecting the sample size and its effect on the signal recovery process. The experiment utilizes a computer or portable workstation to run an examination of the hypothesis reenactment program. From the test information gotten, it can be concluded that the more noteworthy the frequency of the signal to be inspected, the closer the signal will be to the initial signal. The time and frequency of the examining signal are conversely relative. The higher the frequency, the lower the time will be. The magnitude of the amplitude of the output signal is indeterminate.

A Mathematical Analysis of Memory Lifetime in a Simple Network Model of Memory

We study the learning of an external signal by a neural network and the time to forget it when this network is submitted to noise. The presentation of an external stimulus to the recurrent network of binary neurons may change the state of the synapses. Multiple presentations of a unique signal lead to its learning. Then, during the forgetting time, the presentation of other signals (noise) may also modify the synaptic weights. We construct an estimator of the initial signal using the synaptic currents and in this way define a probability of error. In our model, these synaptic currents evolve as Markov chains. We study the dynamics of these Markov chains and obtain a lower bound on the number of external stimuli that the network can receive before the initial signal is considered forgotten (probability of error above a given threshold). Our results are based on a finite-time analysis rather than large-time asymptotic. We finally present numerical illustrations of our results.

Virtual Hybrid Synthesizer Application

Hybrid synthesizers can be syntheses with digital or analog signals on a hardware device. In this article hybrid means make a virtual digital synthesis which combines several synthesis methods. The method used is the synthesis method of additive, substractive, and amplitude modulation (AM). Where the initial signal is an oscillator by making waves with the form Sinusoide Wave, Square Wave and Saw Tooth Wave. This virtual synthesis produces sound that has the same fundamental frequency as the fundamental frequency of notes. Keywords: Hibrid Synthesizer, Additive, Substractive, Amplitude Modulation

METHOD FOR STEP-BY-STEP ADAPTATION OF THE WIDTH OF MEASUREMENT INTERVAL TO SIGNAL PARAMETERS

Указывается, что известные методы измерений исходного сигнала приводят к погрешностям, если ширина измерительных интервалов пошагово не адаптируется к меняющимся параметрам сигнала. Использован новый подход к измерению, раскрывающий единую физическую основу измерения и инструментального вычисления. Алгоритм, следствие указанного подхода, предназначен для получения дискретной последовательности отсчетов сигнала, соответствующих локально определяемым интервалам усреднения. Последовательность получаемых интервалов усреднения приближается к оптимальной и обеспечивает при измерении или решении вычислительной задачи уменьшение погрешности изменяющейся величины. Приведены результаты моделирования на трёх массивах отсчётов с фиксированными и адаптируемыми интервалами усреднения. It is indicated that the known methods for measuring some initial signal lead to errors if the width of the measuring intervals does not step by step adapt to changing signal parameters. A new approach to measurement is used, revealing a unified physical basis for measurement and instrumental computation. A new algorithm as a consequence of this approach is designed to obtain a sequence of discrete samples that matched to locally determined averaging intervals. Resulting sequence of averaging intervals ensures a decrease in the measurement or computing error. The results of calculations on three arrays of samples are presented with fixed and adaptable averaging intervals.