Stochastic Events in Nanoelectrochemical Systems

2015 ◽  
pp. 241-292 ◽  
Author(s):  
Allen Bard ◽  
Aliaksei Boika ◽  
Seong Kwon ◽  
Jun Park ◽  
Scott Thorgaard
Keyword(s):  
Author(s):  
Stefan Thurner ◽  
Rudolf Hanel ◽  
Peter Klimekl

Phenomena, systems, and processes are rarely purely deterministic, but contain stochastic,probabilistic, or random components. For that reason, a probabilistic descriptionof most phenomena is necessary. Probability theory provides us with the tools for thistask. Here, we provide a crash course on the most important notions of probabilityand random processes, such as odds, probability, expectation, variance, and so on. Wedescribe the most elementary stochastic event—the trial—and develop the notion of urnmodels. We discuss basic facts about random variables and the elementary operationsthat can be performed on them. We learn how to compose simple stochastic processesfrom elementary stochastic events, and discuss random processes as temporal sequencesof trials, such as Bernoulli and Markov processes. We touch upon the basic logic ofBayesian reasoning. We discuss a number of classical distribution functions, includingpower laws and other fat- or heavy-tailed distributions.


Aerospace ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 28
Author(s):  
Rasoul Sanaei ◽  
Brian Alphonse Pinto ◽  
Volker Gollnick

The European Air Traffic Management Network (EATMN) is comprised of various stakeholders and actors. Accordingly, the operations within EATMN are planned up to six months ahead of target date (tactical phase). However, stochastic events and the built-in operational flexibility (robustness), along with other factors, result in demand and capacity imbalances that lead to delayed flights. The size of the EATMN and its complexity challenge the prediction of the total network delay using analytical methods or optimization approaches. We face this challenge by proposing a deep convolutional neural network (DCNN), which takes capacity regulations as the input. DCNN architecture successfully improves the prediction results by 50 percent (compared to random forest as the baseline model). In fact, the trained model on 2016 and 2017 data is able to predict 2018 with a mean absolute percentage error of 22% and 14% for the delay and delayed traffic, respectively. This study presents a method to provide more accurate situational awareness, which is a must for the topic of network resiliency.


Cancers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 3575
Author(s):  
Dimitris Karagiannis ◽  
Theodoros Rampias

Intra-tumoral heterogeneity presents a major obstacle to cancer therapeutics, including conventional chemotherapy, immunotherapy, and targeted therapies. Stochastic events such as mutations, chromosomal aberrations, and epigenetic dysregulation, as well as micro-environmental selection pressures related to nutrient and oxygen availability, immune infiltration, and immunoediting processes can drive immense phenotypic variability in tumor cells. Here, we discuss how histone deacetylase inhibitors, a prominent class of epigenetic drugs, can be leveraged to counter tumor heterogeneity. We examine their effects on cellular processes that contribute to heterogeneity and provide insights on their mechanisms of action that could assist in the development of future therapeutic approaches.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ziyou Yang ◽  
Jing Li ◽  
Yongxiang Han ◽  
Chris J. Hassell ◽  
Kar-Sin Katherine Leung ◽  
...  

Abstract Background Despite an increasing number of surveys and a growing interest in birdwatching, the population and distribution of Asian Dowitcher (Limnodromus semipalmatus), a species endemic to the East Asian–Australasian and Central Asian Flyways, remains poorly understood, and published information about the species is largely outdated. In boreal spring 2019, over 22,432 Asian Dowitchers were recorded in a coastal wetland at Lianyungang, Jiangsu Province, China, constituting 97.5% of its estimated global population. Methods In 2019 and 2020, we conducted field surveys at Lianyungang to determine the numbers of Asian Dowitchers using the area during both southward and northward migrations. We also assessed the distribution and abundance of Asian Dowitchers elsewhere along the China coast by searching literature and consulting expert opinion. Results The coastal wetlands of Lianyungang are the most important stopover site for Asian Dowitchers during both northward and southward migrations; they supported over 90% of the estimated global population during northward migration in two consecutive years (May 2019 and 2020). This area also supported at least 15.83% and 28.42% (or 30.74% and 53.51% using modelled estimates) of the global population during southward migration in 2019 and 2020 respectively. Coastal wetlands in the west and north of Bohai Bay also have been important stopover sites for the species since the 1990s. Although comprehensive, long-term monitoring data are lacking, available evidence suggests that the population of the species may have declined. Conclusions The high concentration of Asian Dowitchers at Lianyungang during migration means the species is highly susceptible to human disturbances and natural stochastic events. The coastal wetlands of Lianyungang should be protected and potentially qualify for inclusion in China’s forthcoming nomination for World Heritage listing of Migratory Bird Sanctuaries along the Coast of Yellow Sea-Bohai Gulf of China (Phase II) in 2023. Additional research is needed to understand Asian Dowitchers’ distribution and ecology, as well as why such a high proportion of their population rely on the Lianyungang coast.


2018 ◽  
Vol 03 (03n04) ◽  
pp. 1840002 ◽  
Author(s):  
Dandan Lyu ◽  
Shaofan Li

The development of crystal plasticity theory based on dislocation patterns dynamics has been an outstanding problem in materials science and condensed matter of physics. Dislocation is the origin of crystal plasticity, and it is both the individual dislocation behavior as well as the aggregated dislocations behaviors that govern the plastic flow. The interactions among dislocations are complex statistical and stochastic events, in which the spontaneous emergence of organized dislocation patterns formations is the most critical and intriguing events. Dislocation patterns consist of quasi-periodic dislocation-rich and dislocation poor regions, e.g. cells, veins, labyrinths, ladders structures, etc. during cyclic loadings. Dislocation patterns have prominent and decisive effects on work hardening and plastic strain localization, and thus these dislocation micro-structures are responsible to material properties at macroscale. This paper reviews the recent developments of experimental observation, physical modeling, and computer modeling on dislocation microstructure. In particular, we focus on examining the mechanism towards plastic deformation. The progress and limitations of different experiments and modeling approaches are discussed and compared. Finally, we share our perspectives on current issues and future challenges in both experimental, analytical modeling, and computational aspects of dislocation pattern dynamics.


Author(s):  
Shabnam Rezapour ◽  
Ramakrishnan S. Srinivasan ◽  
Jeffrey Tew ◽  
Janet K. Allen ◽  
Farrokh Mistree

A fail-safe network is one that mitigates the impact of different uncertainty sources and provides the most profitable level of service. This is achieved by having 1) a structurally fail-safe topology against rare but high magnitude stochastic events called disruptions and 2) an operationally fail-safe flow dynamic against frequent but low magnitude stochastic events called variations. A structurally fail-safe network should be robust and resilient against disruptions. Robustness and resilience respectively determine how well and how quickly disruptions are handled by the SN. Flow planning must be reliable in an operationally fail-safe supply network against variations to provide the most profitable service level to customers. We formulate the problem of designing/redesigning fail-safe supply networks as a compromise Decision Support Problem. We analyze the correlations among robustness, resilience, and profit for supply networks and propose a method for supply network managers to use when they need to find a compromise among robustness, resilience, and profit.


2012 ◽  
Vol 459 ◽  
pp. 432-436
Author(s):  
Jun Liu ◽  
Ye Nan Wang ◽  
Jian Hua Li ◽  
Rui Shen Chen

In this study, a new system performance evaluation method is introduced to the two-machine line. After that, the extended system aggregation model is developed and corresponding aggregation formulations are deduced.Different from traditional production models, the production line features unreliable buffers and multiple stochastic failure modes of the machines. The method is applicable to analyzing the cases arising from two or more stochastic events or more complex production lines


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ulrich K. Steiner ◽  
Shripad Tuljapurkar ◽  
Deborah A. Roach

AbstractSimple demographic events, the survival and reproduction of individuals, drive population dynamics. These demographic events are influenced by genetic and environmental parameters, and are the focus of many evolutionary and ecological investigations that aim to predict and understand population change. However, such a focus often neglects the stochastic events that individuals experience throughout their lives. These stochastic events also influence survival and reproduction and thereby evolutionary and ecological dynamics. Here, we illustrate the influence of such non-selective demographic variability on population dynamics using population projection models of an experimental population of Plantago lanceolata. Our analysis shows that the variability in survival and reproduction among individuals is largely due to demographic stochastic variation with only modest effects of differences in environment, genes, and their interaction. Common expectations of population growth, based on expected lifetime reproduction and generation time, can be misleading when demographic stochastic variation is large. Large demographic stochastic variation exhibited within genotypes can lower population growth and slow evolutionary adaptive dynamics. Our results accompany recent investigations that call for more focus on stochastic variation in fitness components, such as survival, reproduction, and functional traits, rather than dismissal of this variation as uninformative noise.


PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5444
Author(s):  
Judith Sánchez-Blanco ◽  
Ernesto V. Vega-Peña ◽  
Francisco J. Espinosa-García

BackgroundDespite numerous tests of Darwin’s naturalization hypothesis (DNH) evidence for its support or rejection is still contradictory. We tested a DNH derived prediction stating that nonnative species (NNS) without native congeneric relatives (NCR) will spread to a greater number of localities than species with close relatives in the new range. This test controlled the effect of residence time (Rt) on the spread of NNS and used naturalized species beyond their lag phase to avoid the effect of stochastic events in the establishment and the lag phases that could obscure the NCR effects on NNS.MethodsWe compared the number of localities (spread) occupied by NNS with and without NCR using 13,977 herbarium records for 305 NNS of weeds. We regressed the number of localities occupied by NNSversus Rtto determine the effect of time on the spread of NNS. Then, we selected the species withRtgreater than the expected span of the lag phase, whose residuals were above and below the regression confidence limits; these NNS were classified as widespread (those occupying more localities than expected byRt) and limited-spread (those occupying fewer localities than expected). These sets were again subclassified into two groups: NNS with and without NCR at the genus level. The number of NNS with and without NCR was compared usingχ2tests and Spearman correlations between the residuals and the number of relatives. Then, we grouped the NNS using 34 biological attributes and five usages to identify the groups’ possible associations with spread and to test DNH. To identify species groups, we performed a nonmetric multidimensional scaling (NMDS) analysis and evaluated the influences of the number of relatives, localities, herbarium specimens,Rt, and residuals of regression. The Spearman correlation and the Mann–WhitneyUtest were used to determine if the DNH prediction was met. Additionally, we used the clustering objects on subsets of attributes (COSA) method to identify possible syndromes (sets of biological attributes and usages) associated to four groups of NNS useful to test DNH (those with and without NCR and those in more and fewer localities than expected byRt).ResultsResidence time explained 33% of the variation in localities occupied by nonnative trees and shrubs and 46% of the variation for herbs and subshrubs. The residuals of the regression for NNS were not associated with the number or presence of NCR. In each of the NMDS groups, the number of localities occupied by NNS with and without NCR did not significantly differ. The COSA analysis detected that only NNS with NCR in more and fewer localities than expected share biological attributes and usages, but they differ in their relative importance.DiscussionOur results suggest that DNH does not explain the spread of naturalized species in a highly heterogeneous country. Thus, the presence of NCR is not a useful characteristic in risk analyses for naturalized NNS.


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