Electronic devices and circuits with negative differential resistance (NDR) are widely used in oscillators, memory devices, frequency multipliers, mixers, etc. Such devices and circuits usually have an N-, S-, or Λ-type current-voltage characteristics. In the known NDR devices and circuits, it is practically impossible to increase the negative resistance without changing the type or the dimensions of transistors. Moreover, some of them have three terminals assuming two power supplies. In this paper, a new NDR circuit that comprises a combination of a field effect transistor (FET) and a simple bipolar junction transistor (BJT) current mirror (CM) with multiple outputs is proposed. A distinctive feature of the proposed circuit is the ability to change the magnitude of the NDR by increasing the number of outputs in the CM. Mathematical expressions are derived to calculate the threshold currents and voltages of the N-type current-voltage characteristics for various types of FET. The calculated current and voltage thresholds are compared with the simulation results. The possible applications of the proposed NDR circuit for designing single-frequency oscillators and voltage-controlled oscillators (VCO) are considered. The designed NDR VCO has a very low level of phase noise and has one of the best values of a standard figure of merit (FOM) among recently published VCOs. The effectiveness of the proposed oscillators is confirmed by the simulation results and the implemented prototype.

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This study proposes a new criterion for choosing the optimal decision in a game against nature under a partial a priori uncertainty. The paper's main novelty consists in examining the situation when a part of the a priori probabilities of states of nature is known, and the other part is unknown. We prove the theorems for choosing the optimal decision as for the payoff and risk matrix, as well as for the profit matrix in the situation of a partial a priori uncertainty. The proposed approach also generalizes the Bayes, Wald, Savage, Hurwicz, and Laplace criteria since the minimum average payoff (or risk) for each of these criteria we can quickly obtain from the article's derived formulas. A practical example of a game against nature under a partial a priori uncertainty illustrates the proposed approach and shows its effectiveness compared to well-known criteria. We show that the introduced criterion provides the choice of a decision that is also optimal in conditions of risk, which indicates the effective use of the vector of known a priori probabilities.

Among the different maintenance techniques applied to wind turbine (WT) components, online condition monitoring is probably the most promising technique. The maintenance models based on online condition monitoring have been examined in many studies. However, no study has considered preventive maintenance models with incorporated probabilities of correct and incorrect decisions made during continuous condition monitoring. This article presents a mathematical model of preventive maintenance, with imperfect continuous condition monitoring of the WT components. For the first time, the article introduces generalized expressions for calculating the interval probabilities of false positive, true positive, false negative, and true negative when continuously monitoring the condition of a WT component. Mathematical equations that allow for calculating the expected cost of maintenance per unit of time and the average lifetime maintenance cost are derived for an arbitrary distribution of time to degradation failure. A numerical example of WT blades maintenance illustrates that preventive maintenance with online condition monitoring reduces the average lifetime maintenance cost by 11.8 times, as compared to corrective maintenance, and by at least 4.2 and 2.6 times, compared with predetermined preventive maintenance for low and high crack initiation rates, respectively.

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