A Simple Algorithm for Calculating Approximately the Reliability of Almost Arbitrary Large Networks

Author(s):  
Elart von Collani
2018 ◽  
Author(s):  
Darren Whitaker ◽  
Kevin Hayes

Raman Spectroscopy is a widely used analytical technique, favoured when molecular specificity with minimal sample preparation is required.<br>The majority of Raman instruments use charge-coupled device (CCD) detectors, these are susceptible to cosmic rays and as such multiple spurious spikes can occur in the measurement. These spikes are problematic as they may hinder subsequent analysis, particularly if multivariate data analysis is required. In this work we present a new algorithm to remove these spikes from spectra after acquisition. Specifically we use calculation of modified <i>Z</i> scores to locate spikes followed by a simple moving average filter to remove them. The algorithm is very simple and its execution is essentially instantaneous, resulting in spike-free spectra with minimal distortion of actual Raman data. The presented algorithm represents an improvement on existing spike removal methods by utilising simple, easy to understand mathematical concepts, making it ideal for experts and non-experts alike. <br>


2018 ◽  
Author(s):  
Darren Whitaker ◽  
Kevin Hayes

Raman Spectroscopy is a widely used analytical technique, favoured when molecular specificity with minimal sample preparation is required.<br>The majority of Raman instruments use charge-coupled device (CCD) detectors, these are susceptible to cosmic rays and as such multiple spurious spikes can occur in the measurement. These spikes are problematic as they may hinder subsequent analysis, particularly if multivariate data analysis is required. In this work we present a new algorithm to remove these spikes from spectra after acquisition. Specifically we use calculation of modified <i>Z</i> scores to locate spikes followed by a simple moving average filter to remove them. The algorithm is very simple and its execution is essentially instantaneous, resulting in spike-free spectra with minimal distortion of actual Raman data. The presented algorithm represents an improvement on existing spike removal methods by utilising simple, easy to understand mathematical concepts, making it ideal for experts and non-experts alike. <br>


2018 ◽  
Author(s):  
Darren Whitaker ◽  
Kevin Hayes

Raman Spectroscopy is a widely used analytical technique, favoured when molecular specificity with minimal sample preparation is required.<br>The majority of Raman instruments use charge-coupled device (CCD) detectors, these are susceptible to cosmic rays and as such multiple spurious spikes can occur in the measurement. These spikes are problematic as they may hinder subsequent analysis, particularly if multivariate data analysis is required. In this work we present a new algorithm to remove these spikes from spectra after acquisition. Specifically we use calculation of modified <i>Z</i> scores to locate spikes followed by a simple moving average filter to remove them. The algorithm is very simple and its execution is essentially instantaneous, resulting in spike-free spectra with minimal distortion of actual Raman data. The presented algorithm represents an improvement on existing spike removal methods by utilising simple, easy to understand mathematical concepts, making it ideal for experts and non-experts alike. <br>


Author(s):  
Yang Ni ◽  
Veerabhadran Baladandayuthapani ◽  
Marina Vannucci ◽  
Francesco C. Stingo

AbstractGraphical models are powerful tools that are regularly used to investigate complex dependence structures in high-throughput biomedical datasets. They allow for holistic, systems-level view of the various biological processes, for intuitive and rigorous understanding and interpretations. In the context of large networks, Bayesian approaches are particularly suitable because it encourages sparsity of the graphs, incorporate prior information, and most importantly account for uncertainty in the graph structure. These features are particularly important in applications with limited sample size, including genomics and imaging studies. In this paper, we review several recently developed techniques for the analysis of large networks under non-standard settings, including but not limited to, multiple graphs for data observed from multiple related subgroups, graphical regression approaches used for the analysis of networks that change with covariates, and other complex sampling and structural settings. We also illustrate the practical utility of some of these methods using examples in cancer genomics and neuroimaging.


Author(s):  
Zhengyan Chang ◽  
Zhengwei Zhang ◽  
Qiang Deng ◽  
Zheren Li

The artificial potential field method is usually applied to the path planning problem of driverless cars or mobile robots. For example, it has been applied for the obstacle avoidance problem of intelligent cars and the autonomous navigation system of storage robots. However, there have been few studies on its application to intelligent bridge cranes. The artificial potential field method has the advantages of being a simple algorithm with short operation times. However, it is also prone to problems of unreachable targets and local minima. Based on the analysis of the operating characteristics of bridge cranes, a two-dimensional intelligent running environment model of a bridge crane was constructed in MATLAB. According to the basic theory of the artificial potential field method, the double-layer artificial potential field method was deduced, and the path and track fuzzy processing method was proposed. These two methods were implemented in MATLAB simulations. The results showed that the improved artificial potential field method could avoid static obstacles efficiently.


2021 ◽  
Vol 13 ◽  
pp. 175883592199298
Author(s):  
Orthi Shahzad ◽  
Nicola Thompson ◽  
Gerry Clare ◽  
Sarah Welsh ◽  
Erika Damato ◽  
...  

Ocular immune-related adverse events (IrAEs) associated with use of checkpoint inhibitors (CPIs) in cancer therapeutics are relatively rare, occurring in approximately 1% of treated patients. Recognition and early intervention are essential because the degree of tissue damage may be disproportionate to the symptoms, and lack of appropriate treatment risks permanent loss of vision. International guidelines on managing ocular IrAEs provide limited advice only. Importantly, local interventions can be effective and may avoid the need for systemic corticosteroids, thereby permitting the continuation of CPIs. We present a single institution case series of eight affected patients managed by our multidisciplinary team. Consistent with previously published series and case reports, we identified anterior uveitis as the most common ocular IrAE associated with CPIs requiring intervention. Based on our experience, as well as published guidance, we generated a simple algorithm to assist clinicians efficiently manage patients developing ocular symptoms during treatment with CPIs. In addition, we make recommendations for optimising treatment of uveitis and address implications for ongoing CPI therapy.


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