Developmental Toxicity Risk Assessment: A Rough Sets Approach

1993 ◽  
Vol 32 (01) ◽  
pp. 47-54 ◽  
Author(s):  
F. R. Jelovsek ◽  
M. Razzaghi ◽  
R. R. Hashemi
Keyword(s):  
Discriminant Analysis ◽  
Rough Sets ◽  
Human Subjects ◽  
Developmental Toxicity ◽  
Original Data ◽  
Original Form ◽  
Data Set ◽  
Predictive Values ◽  
Study Results ◽  
Toxicity Risk

Abstract:A rough-sets approach was applied to a data set consisting of animal study results and other compound characteristics to generate local and global (certain/possible) sets of rules for prediction of developmental toxicity in human subjects. A modified version of the rough-sets approach is proposed to allow the construction of an approximate set of rules to use for prediction in a manner similar to that of discriminant analysis. The modified rough-sets approach is superior in predictability to the original form of rough-sets methodology. In comparison to discriminant analysis, modified rough sets (approximate rules) appear to be better in overall classification, sensitivity, positive and negative predictive values. The findings were supported by applying the modified rough sets and discriminant analysis on a test data set generated from the original data set by using a resampling plan.

scholarly journals Using set theory to reduce redundancy in pathway sets

2018 ◽  
Author(s):  
Ruth Stoney ◽  
Jean-Mark Schwartz ◽  
David L Robertson ◽  
Goran Nenadic
Keyword(s):  
Size Control ◽  
Original Data ◽  
Set Cover ◽  
Biological Knowledge ◽  
Original Form ◽  
Data Set ◽  
Gene Set ◽  
Alternative Approach ◽  
Gene Coverage ◽  
Pathway Databases

1.Abstract1.01BackgroundThe consolidation of pathway databases, such as KEGG[1], Reactome[2]and ConsensusPathDB[3], has generated widespread biological interest, however the issue of pathway redundancy impedes the use of these consolidated datasets. Attempts to reduce this redundancy have focused on visualizing pathway overlap or merging pathways, but the resulting pathways may be of heterogeneous sizes and cover multiple biological functions. Efforts have also been made to deal with redundancy in pathway data by consolidating enriched pathways into a number of clusters or concepts. We present an alternative approach, which generates pathway subsets capable of covering all of genes presented within either pathway databases or enrichment results, generating substantial reductions in redundancy.1.02ResultsWe propose a method that uses set cover to reduce pathway redundancy, without merging pathways. The proposed approach considers three objectives: removal of pathway redundancy, controlling pathway size and coverage of the gene set. By applying set cover to the ConsensusPathDB dataset we were able to produce a reduced set of pathways, representing 100% of the genes in the original data set with 74% less redundancy, or 95% of the genes with 88% less redundancy. We also developed an algorithm to simplify enrichment data and applied it to a set of enriched osteoarthritis pathways, revealing that within the top ten pathways, five were redundant subsets of more enriched pathways. Applying set cover to the enrichment results removed these redundant pathways allowing more informative pathways to take their place.1.03ConclusionOur method provides an alternative approach for handling pathway redundancy, while ensuring that the pathways are of homogeneous size and gene coverage is maximised. Pathways are not altered from their original form, allowing biological knowledge regarding the data set to be directly applicable. We demonstrate the ability of the algorithms to prioritise redundancy reduction, pathway size control or gene set coverage. The application of set cover to pathway enrichment results produces an optimised summary of the pathways that best represent the differentially regulated gene set.

An alternative classification method for northern Wisconsin lakes

1999 ◽  
Vol 56 (4) ◽  
pp. 661-669 ◽  
Author(s):  
Edward E Emmons ◽  
Martin J Jennings ◽  
Clayton Edwards
Keyword(s):  
Discriminant Analysis ◽  
Model Building ◽  
Classification Tree ◽  
Hierarchical Classification ◽  
Original Data ◽  
Validation Data ◽  
Data Set ◽  
Alternative Approaches ◽  
Decision Tree Method

Wisconsin has nearly 15 000 lakes with great variation in limnology, morphometry, and origin. Classification of lakes into groups is a continuing goal. This study examines two alternative approaches to lake classification, one common and the other somewhat novel. Both approaches used lake morphometry and limnological variables and were compared for ability to form groups and assign lakes to groups with a high probability of correct classification. The first approach used nonhierarchical cluster analysis to form lake groups and discriminant analysis to put lakes into these groups. The second approach formed lake groups by iterative dichotomous splitting of the sampling space into smaller and smaller subspaces. Each binary split was done using nonhierarchical cluster analyses on a subset of the original variables. This iterative splitting resulted in a hierarchical classification tree with reduced dimensionality in comparison with the original data set. At each branch, multiple logistic regression was used to place lakes into nodes of the tree. Validation of both approaches was performed with a resubstitution analysis of the model building data set as well as a separate validation data set. The decision tree method yielded significantly lower rates of misclassification and was more easily interpreted than the discriminant analysis approach.

Rotational Characteristics of the Green Solar Corona: 1947-1991

1994 ◽  
Vol 144 ◽  
pp. 139-141 ◽  
Author(s):  
J. Rybák ◽  
V. Rušin ◽  
M. Rybanský
Keyword(s):  
Solar Corona ◽  
World Wide ◽  
Rotation Period ◽  
Original Data ◽  
Coronal Emission ◽  
Time Intervals ◽  
Data Set ◽  
The World ◽  
Coronal Emission Line ◽  
Homogeneous Data

AbstractFe XIV 530.3 nm coronal emission line observations have been used for the estimation of the green solar corona rotation. A homogeneous data set, created from measurements of the world-wide coronagraphic network, has been examined with a help of correlation analysis to reveal the averaged synodic rotation period as a function of latitude and time over the epoch from 1947 to 1991.The values of the synodic rotation period obtained for this epoch for the whole range of latitudes and a latitude band ±30° are 27.52±0.12 days and 26.95±0.21 days, resp. A differential rotation of green solar corona, with local period maxima around ±60° and minimum of the rotation period at the equator, was confirmed. No clear cyclic variation of the rotation has been found for examinated epoch but some monotonic trends for some time intervals are presented.A detailed investigation of the original data and their correlation functions has shown that an existence of sufficiently reliable tracers is not evident for the whole set of examinated data. This should be taken into account in future more precise estimations of the green corona rotation period.

Delay Discounting in Impulsive Behavior

2019 ◽  
Vol 24 (4) ◽  
pp. 312-321 ◽  
Author(s):  
Diana Moreira ◽  
Fernando Barbosa
Keyword(s):  
Delay Discounting ◽  
Human Subjects ◽  
Empirical Studies ◽  
Cochrane Collaboration ◽  
Initial Assessment ◽  
Impulsive Behavior ◽  
Manual Search ◽  
Study Results ◽  
Depth Analysis ◽  
The Future

Abstract. Delay discounting (DD) is the process of devaluing results that happen in the future. With this review, we intend to identify specificities in the processes of DD in impulsive behavior. Studies were retrieved from multiple literature databases, through rigorous criteria (we included systematic reviews and empirical studies with adult human subjects), following the procedures of the Cochrane Collaboration initiative. Of the 174 documents obtained, 19 were considered eligible for inclusion and were retained for in-depth analysis. In addition, 13 studies from the manual search were included. Thus, a total of 32 studies were selected for review. The objectives/hypotheses, results, and the main conclusion(s) were extracted from each study. Results show that people with pronounced traits of impulsivity discount rewards more markedly, that is, they prefer immediate rewards, though of less value, or postponed losses, even though they worsen in the future. Taken together, the existing data suggest the importance of inserting DD as a tool for initial assessment in conjunction with measures of addiction and stress level, as well as the consideration of new therapies.

Electing the Senate

2017 ◽  
Author(s):  
Wendy J. Schiller ◽  
Charles Stewart III
Keyword(s):  
Original Data ◽  
State Legislators ◽  
Internal Conflict ◽  
Data Set ◽  
Senate Elections ◽  
Political Actors ◽  
The Public ◽  
Seventeenth Amendment ◽  
The People ◽  
Election Process

From 1789 to 1913, U.S. senators were not directly elected by the people—instead the Constitution mandated that they be chosen by state legislators. This radically changed in 1913, when the Seventeenth Amendment to the Constitution was ratified, giving the public a direct vote. This book investigates the electoral connections among constituents, state legislators, political parties, and U.S. senators during the age of indirect elections. The book finds that even though parties controlled the partisan affiliation of the winning candidate for Senate, they had much less control over the universe of candidates who competed for votes in Senate elections and the parties did not always succeed in resolving internal conflict among their rank and file. Party politics, money, and personal ambition dominated the election process, in a system originally designed to insulate the Senate from public pressure. The book uses an original data set of all the roll call votes cast by state legislators for U.S. senators from 1871 to 1913 and all state legislators who served during this time. Newspaper and biographical accounts uncover vivid stories of the political maneuvering, corruption, and partisanship—played out by elite political actors, from elected officials, to party machine bosses, to wealthy business owners—that dominated the indirect Senate elections process. The book raises important questions about the effectiveness of Constitutional reforms, such as the Seventeenth Amendment, that promised to produce a more responsive and accountable government.

Styles of Representation in Constituencies in the Homeland and Abroad: The Case of Italy

2020 ◽  
Author(s):  
Eva Østergaard-Nielsen ◽  
Stefano Camatarri
Keyword(s):  
Original Data ◽  
Role Orientation ◽  
International Mobility ◽  
Data Set ◽  
Democratic Representation ◽  
Public Debates ◽  
At Home

Abstract The role orientation of political representatives and candidates is a longstanding concern in studies of democratic representation. The growing trend in countries to allow citizens abroad to candidate in homeland elections from afar provides an interesting opportunity for understanding how international mobility and context influences ideas of representation among these emigrant candidates. In public debates, emigrant candidates are often portrayed as delegates of the emigrant constituencies. However, drawing on the paradigmatic case of Italy and an original data set comprising emigrant candidates, we show that the perceptions of styles of representation abroad are more complex. Systemic differences between electoral districts at home and abroad are relevant for explaining why and how candidates develop a trustee or delegate orientation.

Do the Heterogeneous Determinants of Repayment Affect Differently across Borrowers of Diverse Credit Sources in Rural Assam? A Double Hurdle Approach

2021 ◽  
pp. 245513332110316
Author(s):  
Tiken Das ◽  
Pradyut Guha ◽  
Diganta Das
Keyword(s):  
Rural Areas ◽  
Probit Model ◽  
Original Data ◽  
Community Based ◽  
Data Set ◽  
Brahmaputra Valley ◽  
Double Hurdle ◽  
Instrumental Variable Probit ◽  
Instrumental Variable Probit Model

This study made an attempt to answer the question: Do the heterogeneous determinants of repayment affect the borrowers of diverse credit sources differently? The study is based on data collected from 240 households from three districts in the lower Brahmaputra valley of Assam through a carefully designed primary survey. Besides, the study uses the double hurdle approach and the instrumental variable probit model to reduce possible selection bias. It observes better repayment performance among formal borrowers, followed by semiformal borrowers, while occupation wise it is prominent among organised employees. It has been found that in general, the household characteristics, loan characteristics and location-specific characteristics significantly affect repayment performance of borrowers. However, the nature of impact of the factors influencing repayment performance is remarkably different across credit sources. It ignores the role of traditional community-based organisations in rural Assam while analysing the determinants of repayment performance. The study also recommends for ensuring productive opportunities and efficient market linkages in rural areas of Assam. The study is based on an original data set that has specially been collected to examine question that—do the heterogeneous determinants of repayment affect the borrowers of diverse credit sources differently in the lower Brahmaputra valley of Assam—which has not been studied before.

scholarly journals Data Augmentation Using Generative Adversarial Network for Automatic Machine Fault Detection Based on Vibration Signals

2021 ◽  
Vol 11 (5) ◽  
pp. 2166
Author(s):  
Van Bui ◽  
Tung Lam Pham ◽  
Huy Nguyen ◽  
Yeong Min Jang
Keyword(s):  
Fault Detection ◽  
Data Augmentation ◽  
Model Performance ◽  
Original Data ◽  
Fault Classification ◽  
Training Process ◽  
Generative Adversarial Network ◽  
Data Set ◽  
Adversarial Network ◽  
Machine Fault

In the last decade, predictive maintenance has attracted a lot of attention in industrial factories because of its wide use of the Internet of Things and artificial intelligence algorithms for data management. However, in the early phases where the abnormal and faulty machines rarely appeared in factories, there were limited sets of machine fault samples. With limited fault samples, it is difficult to perform a training process for fault classification due to the imbalance of input data. Therefore, data augmentation was required to increase the accuracy of the learning model. However, there were limited methods to generate and evaluate the data applied for data analysis. In this paper, we introduce a method of using the generative adversarial network as the fault signal augmentation method to enrich the dataset. The enhanced data set could increase the accuracy of the machine fault detection model in the training process. We also performed fault detection using a variety of preprocessing approaches and classified the models to evaluate the similarities between the generated data and authentic data. The generated fault data has high similarity with the original data and it significantly improves the accuracy of the model. The accuracy of fault machine detection reaches 99.41% with 20% original fault machine data set and 93.1% with 0% original fault machine data set (only use generate data only). Based on this, we concluded that the generated data could be used to mix with original data and improve the model performance.

scholarly journals Vielfalt and diversité: how local actors in France and Germany evaluate immigration and socio-cultural heterogeneity

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Maria Schiller ◽  
Christine Lang ◽  
Karen Schönwälder ◽  
Michalis Moutselos
Keyword(s):  
Local Politics ◽  
Original Data ◽  
National Politics ◽  
Data Set ◽  
Large Cities ◽  
Cultural Heterogeneity ◽  
Societal Actors ◽  
Local Actors ◽  
Urban Level ◽  
And Migration

AbstractIn both Germany and France, perceptions of immigration, diversity and their societal consequences have undergone important transformations in the past two decades. However, existing research has only partially captured such processes. The “grand narratives” of national approaches, while still influential, no longer explain contemporary realities. Further, analyses of national politics and discourses may not sufficiently reflect the realities across localities and society more broadly. While emerging in different national contexts, little is known about how diversity is actually perceived by political stakeholders at the urban level. Given the key role of immigration and diversity in current conflicts over Europe’s future, it is imperative to assess present-day conceptualisations of migration-related diversity among important societal actors.This article investigates perceptions and evaluations of socio-cultural heterogeneity by important societal actors in large cities. We contribute to existing literature by capturing an unusually broad set of actors from state and civil society. We also present data drawn from an unusually large number of cities. How influential is the perception of current society as heterogeneous, and what forms of heterogeneity are salient? And is socio-cultural and migration-related heterogeneity evaluated as threatening or rather as beneficial? Based on an original data set, this study explores the shared and contested ideas, the cognitive roadmaps of state and non-state actors involved in local politics.We argue that, in both German and French cities, socio-cultural heterogeneity is nowadays widely recognized as marking cities and often positively connoted. At the same time, perceptions of the main features of diversity and of the benefits and challenges attached to it vary. We find commonalities between French and German local actors, but also clear differences. In concluding, we suggest how and why national contexts importantly shape evaluations of diversity.

Do intraday week effect in currencies hourly trading reflect leverage and asymmetric anomalies? Policy implications for traders

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wajid Shakeel Ahmed ◽  
Muhammad Sohaib ◽  
Jamal Maqsood ◽  
Ateeb Siddiqui
Keyword(s):  
Emerging Economies ◽  
Garch Model ◽  
Study Data ◽  
Policy Implications ◽  
Asymmetric Effect ◽  
Data Set ◽  
Content Type ◽  
Study Results ◽  
Rational Choices ◽  
Trading Pattern

Purpose The purpose of this study is to determine if intraday week (IDW) effect of the currencies reflect leverage and asymmetric impact in currencies market. The study data set comprises of intraday patterns of 15 currencies from developed and emerging economies. Design methodology approach The study applies the exponential generalized autoregressive conditional heteroscedasticity (E-GARCH) model technique to observe the IDW leverage and asymmetric effect after introducing hourly dummies variables, namely, IDWmon, IDWwed, IDWfrid and IDWfrid-mon. Findings The study results favor the propositions and confirm that IDW effect do exist in the international forex markets in relation to hourly trading pattern for respective currencies. Mostly, currencies do depreciate on Monday and Wednesday compared to the rest of the days. However, on the last trading day, i.e. Friday currencies observe an appreciation pattern which is for both economies. The results have an evidence of leverage and asymmetric effect confirmed by the E-GARCH model as a result of press releases and influence by micro-factors in the currency markets. Practical implications The study believes to have theoretical connection related to the better understanding of currencies trend for developed and emerging economies, as the IDW effect exists. Moreover, confirmation of both the leverage and asymmetric effect in observed currencies would be able to assist the investors in making rational choices during the trading hours and would confirm considerable profits through profit incentivized strategies. Originality value The study not only add knowledge to the previous study work in relation to the hourly trading pattern of currencies with reference to the IDW effects but also highlights the leverage and asymmetric effect in currencies that will help in formulating future trading strategies particular to emerging economies.

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