Consecutive Components Research Articles

Reliability of a consecutive k-out-of-n: G system with protection blocks

This paper studies the reliability of consecutive k-out-of-n: G systems with protection blocks. The system consists of n components, and it functions if at least k consecutive components are operational. Protection blocks can be used to increase system reliability by reducing the failure rates of exactly k consecutive components. However, the protection blocks also have their own failure rates. System reliability is assessed by calculating the probability of successful operation over a specified time period, taking into account the failure dynamics of both components and protection blocks. Binary decision diagram (BDD) is used to identify combinations of component states that lead to system success. The probability for each combination is then evaluated, considering the states of both the components and the protection blocks. By integrating these probabilities, the overall system reliability is determined. Numerical examples are provided to illustrate the application of this method.

An Approximate Algorithm for Simulating Stationary Discrete Random Processes with Bivariate Distributions of Their Consecutive Components in the Form of Mixtures of Gaussian Distributions

An Approximate Algorithm for Simulating Stationary Discrete Random Processes with Bivariate Distributions of Their Consecutive Components in the Form of Mixtures of Gaussian Distributions

An agent-based simulation model for the growth of the Sydney Trains network

Agent-based models are computational methods for simulating the actions and reactions of autonomous entities with the ability to capture their effects on a system through interaction rules. This study develops an agent-based simulation model (RANGE) to replicate the growth of Sydney Trains network by given exogenous historical evolution in land use. A set of locational rules has been defined to find a sequence of optimal stations from an initial seed. The model framework is an iterative process that includes five consecutive components including environment loading, measuring access, locating stations, connecting stations, and evaluating connections. In each iteration, following the locating/connecting process in each line of railways network, the accessibility will be calculated, and land use will be updated. Based on the compilation of network topology and properties, each iteration will be a year-on-year time step analysis. The network evolves based on a set of locational rules in regards to changes in the historic land use. Also, two coverage indices are defined to evaluate the fitness of the simulated lines in comparison to the Sydney tram and train network.

Reliability assessment for consecutive-[formula omitted]-out-of-[formula omitted]: F retrial systems under Poisson shocks

This paper derives reliability indices of a linear consecutive-k-out-of-n: F system with retrial under Poisson shocks. The system fails if and only if at least k consecutive components from n components fail and is maintained by one repairman. When a component fails during the repairman’s unavailability, it will be waiting until the repairmen becomes available. The failure of a component may be caused by its intrinsic characteristics such as ageing and deterioration or extrinsic factors such as shocks. It is assumed that a component will fail once the magnitude of a shock is greater than a threshold. At any time, a component is at one of the three states: working, waiting for repair, and under repair. For some systems, we need to obtain reliability indices for practical use. Hence, this paper uses the Markov chain to model the transition between states and obtains several reliability indices. The parameter sensitivity of the system reliability indices is analysed with numerical experiments.

Mean-preserving interpolation with splines for solar radiation modeling

Interpolation is a fundamental process in solar resource assessment that glues consecutive components of the modeling chain. Most interpolation techniques assume that the interpolating function must go through the interpolation points. However, this assumption does not fit with averaged datasets or variables that must be conserved across interpolation. Here I present a mean-preserving splines method for interpolating one-dimensional data that conserves the interpolated field and is appropriate for averaged datasets. It uses second-order polynomial splines to minimize the fluctuations of the interpolated field, restricts the interpolation results to user-provided limits to prevent unphysical values, deals with periodic boundary conditions in the interpolated field, and can work with non-uniform averaging grids. The validity and performance of the method are illustrated against regular second- and third-order splines using relevant case examples in the solar resource assessment realm.

Optimal maintenance policies for linear consecutive [formula omitted]-out-of-[formula omitted]:F systems susceptible to dependent failures

A linear consecutive k-out-of-n:F system is an ordered sequence of n-components that fails if and only if k consecutive components in positions i, (i+1), …, (i+k−1) fail. This modeling paradigm is suitable for several modern systems such as wireless communication, which may be unable to send messages if several adjacent transmission stations fail. Although these systems are susceptible to correlated and dependent failures from geospatial events such as extreme weather, only a handful of consecutive-k-out-of-n:F models in the literature assume failures are not statistically independent and even fewer consider maintenance of consecutive-k-out-of-n:F systems subject to dependent failures. To address this limitation, this paper develops a novel formulation of the linear consecutive-k-out-of-n:F model subject to dependent failures and derives maintenance models. A sequence of illustrative examples demonstrates the ability of the model to explicitly characterize the influence of dependence on several reliability measures and shows how the model enables the identification of optimal age replacement policies to minimize cost or maximize availability despite dependence.

Towards a unifying basis of auditory thresholds: Thresholds for multicomponent stimuli

Sounds consisting of multiple simultaneous or consecutive components can be detected by listeners when the stimulus levels of the components are lower than those needed to detect the individual components alone. The mechanisms underlying such spectral, spectrotemporal, temporal, or across-ear integration are not completely understood. Here, we report threshold measurements from human subjects for multicomponent stimuli (tone complexes, tone sequences, diotic or dichotic tones) and for their individual sinusoidal components in quiet. We examine whether the data are compatible with the detection model developed by Heil, Matysiak, and Neubauer (HMN model) to account for temporal integration (Heil et al. 2017), and we compare its performance to that of the statistical summation model (Green 1958), the model commonly used to account for spectral and spectrotemporal integration. In addition, we compare the performance of both models with respect to previously published thresholds for sequences of identical tones and for diotic tones. The HMN model is similar to the statistical summation model but is based on the assumption that the decision variable is a number of sensory events generated by the components via independent Poisson point processes. The rate of events is low without stimulation and increases with stimulation. The increase is proportional to the time-varying amplitude envelope of the bandpass-filtered component(s) raised to an exponent of 3. For an ideal observer, the decision variable is the sum of the events from all channels carrying information, for as long as they carry information. We find that the HMN model provides a better account of the thresholds for multicomponent stimuli than the statistical summation model, and it offers a unifying account of spectral, spectrotemporal, temporal, and across-ear integration at threshold.

Association between grade brain tumors and the interleukin‐10 receptor subunit alpha based on surface‐enhanced Raman spectroscopy and multivariate analysis

AbstractWe present herein a label‐free method based on surface‐enhanced Raman spectroscopy (SERS) that was performed using a silicon‐based SERS platform. The differentiation between primary and secondary brain tumors SERS data was completed partial least squares (PLS) method with a very high 85% of accuracy (in only first and second factors), whereas calculated using principal component analysis (PCA) method gives 74% (in two consecutive components). Additionally, due to the fact that the interleukin‐10 (IL‐10) cytokine receptor may act in cancer as both an immunosuppressive and an immunostimulant factor, the correlation between the tumor grading and the cytokine receptor are presented. Obtained data indicate that the function of IL‐10 cytokine receptor subunit alpha most probably depends or is closely related to the tumor stage.

Algorithm for Solving the Component Assignment Problem in a Multistate Sliding Window System

The multistate sliding window system (SWS) comprises [Formula: see text] multistate components arranged in a line; each group of [Formula: see text] consecutive multistate components is considered as a window. If the total performance rate in a window does not meet the predetermined demand [Formula: see text], then that window is regarded as a failure. The SWS fails if and only if there exists at least one failed window. Several researchers have considered the component assignment problem for the SWS with the aim of finding an appropriate component arrangement that maximizes system reliability. Such an arrangement is called the optimal arrangement. Although several metaheuristic and heuristic algorithms have been proposed, an exact algorithm for solving the component assignment problem of the SWS has not been developed thus far. Therefore, in this study, a branch-and-bound-based algorithm is developed to determine the optimal arrangement of the SWS efficiently. Furthermore, a recursive method is proposed to compute the system reliability. Combining the branch-and-bound-based algorithm with the recursive method enables reduction of the complexity of the reliability computations for determining the optimal arrangement. To investigate the efficiency of the branch-and-bound-based algorithm, numerical experiments were conducted; it was observed that the parameters [Formula: see text] and [Formula: see text] have the maximum effect on computation time, whereas parameter [Formula: see text] has minimal effect. The proposed algorithm is useful for improving the reliability of a practical system that can be expressed as an SWS. In addition, the optimal arrangements can be used to measure the heuristic and metaheuristic performances because they guarantee global optimality.

Operating principles of circular toggle polygons

Decoding the dynamics of cellular decision-making and cell differentiation is a central question in cell and developmental biology. A common network motif involved in many cell-fate decisions is a mutually inhibitory feedback loop between two self-activating ‘master regulators’ A and B, also called as toggle switch. Typically, it can allow for three stable states—(high A, low B), (low A, high B) and (medium A, medium B). A toggle triad—three mutually repressing regulators A, B and C, i.e. three toggle switches arranged circularly (between A and B, between B and C, and between A and C)—can allow for six stable states: three ‘single positive’ and three ‘double positive’ ones. However, the operating principles of larger toggle polygons, i.e. toggle switches arranged circularly to form a polygon, remain unclear. Here, we simulate using both discrete and continuous methods the dynamics of different sized toggle polygons. We observed a pattern in their steady state frequency depending on whether the polygon was an even or odd numbered one. The even-numbered toggle polygons result in two dominant states with consecutive components of the network expressing alternating high and low levels. The odd-numbered toggle polygons, on the other hand, enable more number of states, usually twice the number of components with the states that follow ‘circular permutation’ patterns in their composition. Incorporating self-activations preserved these trends while increasing the frequency of multistability in the corresponding network. Our results offer insights into design principles of circular arrangement of regulatory units involved in cell-fate decision making, and can offer design strategies for synthesizing genetic circuits.

A novel computational approach for predicting complex phenotypes in Drosophila (starvation-sensitive and sterile) by deriving their gene expression signatures from public data.

Many research teams perform numerous genetic, transcriptomic, proteomic and other types of omic experiments to understand molecular, cellular and physiological mechanisms of disease and health. Often (but not always), the results of these experiments are deposited in publicly available repository databases. These data records often include phenotypic characteristics following genetic and environmental perturbations, with the aim of discovering underlying molecular mechanisms leading to the phenotypic responses. A constrained set of phenotypic characteristics is usually recorded and these are mostly hypothesis driven of possible to record within financial or practical constraints. We present a novel proof-of-principal computational approach for combining publicly available gene-expression data from control/mutant animal experiments that exhibit a particular phenotype, and we use this approach to predict unobserved phenotypic characteristics in new experiments (data derived from EBI's ArrayExpress and ExpressionAtlas respectively). We utilised available microarray gene-expression data for two phenotypes (starvation-sensitive and sterile) in Drosophila. The data were combined using a linear-mixed effects model with the inclusion of consecutive principal components to account for variability between experiments in conjunction with Gene Ontology enrichment analysis. We present how available data can be ranked in accordance to a phenotypic likelihood of exhibiting these two phenotypes using random forest. The results from our study show that it is possible to integrate seemingly different gene-expression microarray data and predict a potential phenotypic manifestation with a relatively high degree of confidence (>80% AUC). This provides thus far unexplored opportunities for inferring unknown and unbiased phenotypic characteristics from already performed experiments, in order to identify studies for future analyses. Molecular mechanisms associated with gene and environment perturbations are intrinsically linked and give rise to a variety of phenotypic manifestations. Therefore, unravelling the phenotypic spectrum can help to gain insights into disease mechanisms associated with gene and environmental perturbations. Our approach uses public data that are set to increase in volume, thus providing value for money.

Improved Layouts and Performance of Single- and Double-Flash Steam Geothermal Plants Generated by the Heatsep Method

Abstract Single- and double-flash steam power plants are commonly used in the utilization of high enthalpy liquid-dominated geothermal resources. In these plants, the expansion line in the wet steam region results in significant penalties of turbine isentropic efficiency and power output. Accordingly, the “self-superheating” and “interstage heating” plant modifications have been recently proposed in the literature, where the saturated steam at turbine inlet is superheated by using the heat of the geothermal liquid, which is cooled before the flashing process. In this study, the aforementioned and additional new flash steam plant layouts are generated by using a systematic method, called Heatsep, for the optimum design of energy systems. All the thermal connections between consecutive basic plant components are “cut” to let these temperatures vary and in turn generate additional hot and cold streams, which are combined to enhance the overall performance of the system. It is demonstrated that the single-flash plant with self-superheating is simply obtained by cutting two out of five thermal links. In the double-flash plant, the higher number of components allows for a higher number of thermal cuts and heat integration options. Unlike the existing literature, the maximum power output is not constrained by a predefined heat transfer network. The optimization results show that the maximum power output of the novel single- and double-flash steam plants exceeds by 5.5–9.2% and 3.9–7.7% the maximum attainable by the corresponding traditional plants without internal heat integration.

Reliability and importance measures for a general consecutive-type system

ABSTRACT A general consecutive-type system, called -consecutive-,-out-of-:F system, is considered. Such a system consists of linearly or circularly ordered components and fails if and only if there are at least -overlapping runs of consecutive failed components. For systems with statistically independent components, the system reliability is obtained via recursive schemes and simulation. Reliability importance measures for system components are calculated and analyzed as well. Illustrative analytic and numerical examples demonstrate further the theoretical results.

Performability analysis of multi-state sliding window systems

This paper models and evaluates the performability of a sliding window system (SWS) with multi-state components. Different components may have different numbers of states, characterized by state probability and performance rate distributions. Multiple consecutive components form groups with identical or different sizes. The accumulation (sum) of performance rates of components within the same group defines the group performance; the minimum of the group performance defines the system performance. The performability of an SWS is concerned with the probability that the system performs at a particular system performance. In this paper, a multi-valued decision diagram (MDD)-based analytical approach is proposed for the performability analysis of SWSs. The approach encompasses a compact system MDD generation based on the group MDD generation and combination, and evaluation of the resultant MDD model to obtain the system performability measures. Case studies are performed to demonstrate the proposed MDD approach as well as effects of component allocation on the system performability.

Reliability And Failure Probability Functions Of The Consecutive-k-out-of-m-from-n: F System With Mul-tiple Failure Criteria

The consecutive-k-out-of-m-from-n: F system with multiple failure criteria consists of n sequentially ordered components (K= (k1, k2,..., kH), m = (m1, m2,..., mH)). The system fails if among any m1, m2,..., mH consecutive components there are at least k1, k2,..., kH components in the failed state. In this paper, the ordinary consecutive-k-out-of-m-from-n: F system played a pivotal role in achieving the reliability and failure probability functions of the consecutive-k-out-of-m-from-n: F linear and circular system with multiple failure criteria. We proved that the failure states of the multiple failure criteria system is a union of all failure state of the consecutive-ki-out-of-mi-from-n: F system, while the functioning state is an intersection of the functioning states of the consecutive-ki-out-of-mi-from-n: F system for . The maximum number of failed components of the functioning consecutive k-out-of-m-from-n: F system with multiple failure criteria is computed.

Antipredator function of vigilance re-examined: vigilant birds delay escape

Vigilance is considered an effective antipredator behaviour in animals, and hence it should reflect fearfulness. While numerous aspects of vigilance have been extensively studied, there is a paucity of evidence regarding the role of vigilance in escaping from predators. In a multispecies approach, we measured vigilance (as the proportion of time spent in a head-up posture) and three consecutive components of escape behaviour, predetection distance, assessment interval and flight initiation distance, of wild birds in urban and rural habitats in three European countries. Escape behaviour was induced by a human observer walking towards the focal bird whose vigilance was measured beforehand. More vigilant individuals did not detect predators earlier than less vigilant ones. In addition, more vigilant individuals spent more time on risk assessment and escaped later. Body mass was positively correlated with vigilance for birds on higher perches, where we expected vigilance to be less important. Finally, urban birds were more vigilant than rural birds, suggesting that distractions in urban habitats might have a more profound impact on vigilance than the expected lower predation risk. These results challenge the underlying assumption that more vigilant individuals have a higher perceived risk of predation and hence better odds at avoiding predation. We explain our results in the context that higher levels of vigilance compensate for environmental distractions and for innate deficiencies or lack of experience that constrain the detection of predators. We suggest that a re-examination of the basic functions and markers of vigilance is needed before using it as a measure of fearfulness in birds.

Engineering 2‐oxoglutarate dehydrogenase to a 2‐oxo aliphatic dehydrogenase complex by optimizing consecutive components

AbstractMultienzyme complexes have the potential for green catalysis of sequential reactions. The Escherichia coli 2‐oxoglutarate dehydrogenase complex (OGDHc) was converted from a 2‐oxoglutarate dehydrogenase to a 2‐oxo aliphatic dehydrogenase complex by engineering consecutive components. OGDHc catalyzes succinyl‐CoA synthesis in the Krebs cycle. OGDHc is composed of three components: E1o, 2‐oxoglutarate dehydrogenase; E2o, dihydrolipoylsuccinyl transferase; E3, dihydrolipoyl dehydrogenase. There are three substrate checkpoints. One is in E1o and two in E2o. OGDHc was reprogrammed to accept alternative substrates by evolving the E1o and E2o components. Wt‐ODGHc does not accept aliphatic substrates. E1o was previously engineered to accept a non‐natural aliphatic substrate, 2‐oxovalerate (2‐OV). E2o also required engineering to accept 2‐OV in the overall reaction. Hence, saturation mutagenesis libraries of E2o were screened for 2‐OV activity. E2o‐S333M, E2o‐H348F, E2o‐H348Q, and E2o‐H348Y were identified to show activity for 2‐OV in the reconstituted complex. Variants also displayed activity for larger aliphatic substrates.

Eurasian lynx fitness shows little variation across Scandinavian human-dominated landscapes

Despite extensive research on the ecology and behavioural adaptations of large carnivores in human-dominated landscapes, information about the fitness consequences of sharing landscapes is still limited. We assessed the variation in three consecutive components of female fitness: the probability of reproduction, litter size and juvenile survival in relation to environmental and human factors in a solitary carnivore, the Eurasian lynx (Lynx lynx), occurring in human-dominated landscapes in Scandinavia. We used demographic data from 57 radio-collared adult females between 1995–2011 (126 radio-years). Overall, the yearly probability of female reproduction was 0.80, mean litter size was 2.34 (range 1–4) and the probability to find a female that reproduced in the spring being accompanied by at least one offspring during the subsequent winter was 0.70. We did not find evidence that food availability was a key factor influencing female fitness. Female lynx may adapt to food availability when establishing their home ranges by adopting an obstinate strategy, ensuring a minimum amount of prey necessary for survival and reproduction even during periods of prey scarcity. In human-dominated landscapes, where sufficient prey are available for lynx, mortality risk may have a larger influence on lynx population dynamics compared to food availability. Our results suggest that lynx population dynamics in human-dominated landscapes may be mainly driven by human impacts on survival.

Dynamic demand satisfaction probability of consecutive sliding window systems with warm standby components

Motivated by practical applications such as heating systems, radar, and sensor monitoring, this paper models and analyzes a linear consecutive multi-state sliding window system with warm standby components (CSWS-WS). The system contains n linearly ordered components, each being a warm standby configuration of multiple elements with heterogeneous time-to-failure distributions and nominal performances. Thus, depending on the currently operating (online) element, each component may exhibit multiple states, corresponding to different failure behaviors and performance rates. The system function depends on the accumulated performance (sum of performance rates) of r consecutive components, referred to as a r-sized window. The system is considered being failed if the accumulated performance in each of at least m consecutive overlapping r-sized windows is lower than a random demand. To evaluate the reliability (demand satisfaction probability) of a CSWS-WS, a probabilistic model is first presented to determine the dynamic performance distribution of each warm standby component; a universal generating function-based method is then suggested for obtaining the dynamic demand satisfaction probability (DSP). Based on the DSP evaluation, the optimal element distribution and sequencing problem is formulated and solved for the CSWS-WS system. As demonstrated through examples, solutions to the considered optimization problems can facilitate a proper choice of element distribution and activation sequencing, maxmizing the minimum instananeous DSP or expected DSP over a certain mission time.

New Bounds for All Types of Multi-state Consecutive $k$ -Out-of-$r$ -From-$n$ : F System Reliability

A multi-state consecutive k-out-of-r-from-n: F system (named MS C(k,r,n:F)) comprises of n linearly ordered components. The MS C(k,r,n:F) and its components have more than 2 states: 0, 1, <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">⋯</sub> ,H. The state of MS C(k, r, n:F) is less than j if any r consecutive components contains k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</sub> or more, for all j ≤ l ≤ H. This system is a model for a large number of applications. The existing methods for system-reliability evaluation are suitable for some special cases only. In this paper, we suggest bounds for MS C(k, r, n:F) reliability. These bounds are suitable for all system types whether in case of equal or unequal components probabilities. The suggested bounds are examined by previously published examples, when available. Also, illustration examples for the new bounds and system modelling are presented. Furthermore, we studied the cases that make the proposed bounds are sharp.