A Quantitative Measure of the Effects of IT Investment on the Risk of Bankruptcy in Small and Medium-Sized Companies

2013 ◽  
Author(s):  
Carlos Piieiro-SSnchez
Keyword(s):  
Quantitative Measure ◽  
It Investment

Procedures for the Quantitative Determination of Autoprothrombin C

1962 ◽  
Vol 08 (03) ◽  
pp. 434-441 ◽  
Author(s):  
Edmond R Cole ◽  
Ewa Marciniak ◽  
Walter H Seegers
Keyword(s):  
Quantitative Determination ◽  
Plasma Sample ◽  
Quantitative Measure ◽  
The Other ◽  
Clotting Time ◽  
Bovine Plasma ◽  
Autoprothrombin C

SummaryTwo quantitative procedures for autoprothrombin C are described. In one of these purified prothrombin is used as a substrate, and the activity of autoprothrombin C can be measured even if thrombin is in the preparation. In this procedure a reaction mixture is used wherein the thrombin titer which develops in 20 minutes is proportional to the autoprothrombin C in the reaction mixture. A unit is defined as the amount which will generate 70 units of thrombin in the standardized reaction mixture. In the other method thrombin interferes with the result, because a standard bovine plasma sample is recalcified and the clotting time is noted. Autoprothrombin C shortens the clotting time, and the extent of this is a quantitative measure of autoprothrombin C activity.

Epigenetic Target Prediction with Accurate Machine Learning Models

2021 ◽  
Author(s):  
Norberto Sánchez-Cruz ◽  
Jose L. Medina-Franco
Keyword(s):  
Machine Learning ◽  
Small Molecules ◽  
Predictive Models ◽  
Large Scale ◽  
Target Prediction ◽  
Quantitative Measure ◽  
Learning Models ◽  
Discovery Research ◽  
Drug Discovery Research ◽  
Machine Learning Models

<p>Epigenetic targets are a significant focus for drug discovery research, as demonstrated by the eight approved epigenetic drugs for treatment of cancer and the increasing availability of chemogenomic data related to epigenetics. This data represents a large amount of structure-activity relationships that has not been exploited thus far for the development of predictive models to support medicinal chemistry efforts. Herein, we report the first large-scale study of 26318 compounds with a quantitative measure of biological activity for 55 protein targets with epigenetic activity. Through a systematic comparison of machine learning models trained on molecular fingerprints of different design, we built predictive models with high accuracy for the epigenetic target profiling of small molecules. The models were thoroughly validated showing mean precisions up to 0.952 for the epigenetic target prediction task. Our results indicate that the herein reported models have considerable potential to identify small molecules with epigenetic activity. Therefore, our results were implemented as freely accessible and easy-to-use web application.</p>

Mobile Based Quantitative Measure of Stress

2018 ◽  
Author(s):  
Einat Yehene ◽  
Oren Fuerst ◽  
Alexandre Domingues ◽  
Teresa Paiva
Keyword(s):  
Quantitative Measure

Trading places [IT investment]

2006 ◽  
Vol 3 (4) ◽  
pp. 28-31
Author(s):  
S. Turner
Keyword(s):  
It Investment

Information on evolutionary age in redundancy of complex network

2019 ◽  
Vol 33 (27) ◽  
pp. 1950331
Author(s):  
Shiguo Deng ◽  
Henggang Ren ◽  
Tongfeng Weng ◽  
Changgui Gu ◽  
Huijie Yang
Keyword(s):  
Principal Component Analysis ◽  
Complex Networks ◽  
Metabolic Network ◽  
Complex Network ◽  
Cellular Networks ◽  
Topological Structure ◽  
Quantitative Measure ◽  
Principal Component ◽  
Evolutionary Information ◽  
Local Patterns

Evolutionary processes of many complex networks in reality are dominated by duplication and divergence. This mechanism leads to redundant structures, i.e. some nodes share most of their neighbors and some local patterns are similar, called redundancy of network. An interesting reverse problem is to discover evolutionary information from the present topological structure. We propose a quantitative measure of redundancy of network from the perspective of principal component analysis. The redundancy of a community in the empirical human metabolic network is negatively and closely related with its evolutionary age, which is consistent with that for the communities in the modeling protein–protein network. This behavior can be used to find the evolutionary difference stored in cellular networks.

scholarly journals From Abbott Thayer to the present day: what have we learned about the function of countershading?

2008 ◽  
Vol 364 (1516) ◽  
pp. 519-527 ◽  
Author(s):  
Hannah M Rowland
Keyword(s):  
Empirical Work ◽  
Quantitative Measure ◽  
Convincing Evidence ◽  
Colour Pattern ◽  
Protective Effects ◽  
Empirical Testing ◽  
Background Matching ◽  
Visual Characteristics ◽  
Subjective Evidence ◽  
The Many

Of the many visual characteristics of animals, countershading (darker pigmentation on those surfaces exposed to the most lighting) is one of the most common, and paradoxically one of the least well understood. Countershading has been hypothesized to reduce the detectability of prey to visually hunting predators, and while the function of a countershaded colour pattern was proposed over 100 years ago, the field has progressed slowly; convincing evidence for the protective effects of countershading has only recently emerged. Several mechanisms have been invoked for the concealing function of countershading and are discussed in this review, but the actual mechanisms by which countershading functions to reduce attacks by predators lack firm empirical testing. While there is some subjective evidence that countershaded animals match the background on which they rest, no quantitative measure of background matching has been published for countershaded animals; I now present the first such results. Most studies also fail to consider plausible alternative explanations for the colour pattern, such as protection from UV or abrasion, and thermoregulation. This paper examines the evidence to support each of these possible explanations for countershading and discusses the need for future empirical work.

A quantitative measure of the degree of output controllability for output regulation control systems: Concept, approach, and applications

2021 ◽  
pp. 107754632110201
Author(s):  
Yaping Xia ◽  
Ruiyu Li ◽  
Minghui Yin ◽  
Yun Zou
Keyword(s):  
Structural Parameters ◽  
Quantitative Measure ◽  
Output Regulation ◽  
State Regulation ◽  
Control Effect ◽  
Pendulum System ◽  
Design And Optimization ◽  
Inverted Pendulum System ◽  
State Regulator ◽  
Output Controllability

Currently, many research studies reveal that for state regulator problems, the higher the degree of controllability is, the better the control effect likely is. Note that for the output regulator problems, the control performance is often evaluated by outputs. This article hence generalizes the concept and applications of degree of controllability to the case of output regulator. To this end, a kind of degree of output controllability is presented. Furthermore, simulations on wind turbines and the inverted pendulum system demonstrate that better control effect may be achieved by increasing the degree of output controllability measure. These results imply that similar to the case of degree of controllability for state regulation control, the degree of output controllability measure is likely a feasible candidate index for the design and optimization of the structural parameters of controlled plants in the case of output regulation control.

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