Behavioral measures of pain

2021 ◽  
pp. 400-412
Author(s):  
Jill M. Chorney ◽  
C. Meghan McMurtry
Keyword(s):  
Gold Standard ◽  
Self Report ◽  
Scoring Method ◽  
Behavioral Measures ◽  
Cultural Considerations ◽  
Current State ◽  
Behavioral Observations ◽  
Similarities And Differences ◽  
Source Of Information

Though self-report has historically been considered the “gold-standard” measure of pain, behavioral observations are an important source of information and can address a number of limitations of self-report. In this chapter, we will review the current state of evidence on behavioral measures of pain in children and adolescents, including a brief discussion of future directions. We focus on measures that are considered to be well-established or have been included in recent systematic reviews, and provide an overview of the contexts of use (population, settings) and scoring method of each measure. We highlight areas of special consideration, including cross-cultural considerations, automaticity of behavior, and similarities and differences between behavioral conceptualizations of pain, fear, anxiety, and distress. To demonstrate the utility of behavioral scales, we also include a case study.

Motivations for Emotions in Bipolar Disorder

2021 ◽  
pp. 216770262097958
Author(s):  
Yael Millgram ◽  
June Gruber ◽  
Cynthia M. Villanueva ◽  
Anna Rapoport ◽  
Maya Tamir
Keyword(s):  
Bipolar Disorder ◽  
Recent Work ◽  
Affective Disorders ◽  
Self Report ◽  
Emotional Instability ◽  
Behavioral Measures ◽  
Increased Risk ◽  
Self Reports ◽  
Similarities And Differences

Recent work has begun to examine the link between motivation for specific emotions and psychopathology. Yet research on this topic to date has focused primarily on depression. To understand patterns of motivation for emotions within and across affective disorders, we assessed motivation for emotions in adults at increased risk for and diagnosed with bipolar disorder (BD). We focused on motivation for negative (i.e., sadness) and positive (i.e., happiness) emotions and for emotional instability using self-report and behavioral measures. Both increased BD risk and diagnosis of BD were associated with increased motivation for sadness and decreased motivation for happiness as assessed by behavioral measures. Such motivational tendencies were less consistent when assessed by self-reports. Higher BD risk was associated with increased self-reported motivation for emotional instability (Studies 1–3), although this association was not evident in BD (Study 4). Findings suggest both similarities and differences in motivation for emotions in affective disorders.

scholarly journals Editorial vs Political Commentary: Establishment of the Genres in Siberian Regional Press (a Case Study of Minusinsk Newspaper Texts in the Period of 1906-1917)

2020 ◽  
Vol 9 (2) ◽  
pp. 282-299
Author(s):  
Julia Kostyakova
Keyword(s):  
Information Sources ◽  
Point Of View ◽  
Political Issues ◽  
Political Commentary ◽  
Current State ◽  
Similarities And Differences ◽  
Newspaper Text ◽  
Set Up

The article deals with editorial and political commentary as journalistic genres, reveals their typological features, similarities and differences. The author gives reasons for saving these genres and considering them as those belonging to the group of analytical genres, since their basis is the logical analysis of real events, phenomena or facts. The author studies the historical transformation of editorial and political commentary in the pre-revolutionary, Soviet and post-Soviet periods, and determines the causes of the changes. The author infers that currently, editorial is best developing in the context of columnism, whereas political commentary is most successful in the Internet. This foregrounds the study of both current state and historical conditions for the development of these genres, especially in Siberian regional press at the establishment stage in the early XX century. The analysis of papers issued consecutively from 1906 to 1917 in Minusinsk, the central town of Yenisei province, shows the main trends in the change of the content of these types of newspaper text. An editorial containing comments on political issues was an indicator of particular quality of the newspaper, since the readers were provided with the editors or leading journalists reasoned point of view on the events and phenomena of those days. The choice of the topic and the content of the coverage were determines by the censorship and historical conditions, availability of information sources and the writers experience. Despite similarities in the topic and content, editorial and political commentary had different headlines and references to the author. Moreover, in the Bolshevists press, which became legalized in the time of the February Revolution, editorial was used as a means of agitation, and thus set up the tradition for the Soviet press.

A Comprehensive Analysis of Image Forensics Techniques: Challenges and future Direction

2019 ◽  
Vol 13 ◽  
Author(s):  
Mohd Dilshad Ansari ◽  
Ekbal Rashid ◽  
S Siva Skandha ◽  
Suneet Kumar Gupta
Keyword(s):  
Image Forensics ◽  
Digital Era ◽  
Current State ◽  
Benchmark Datasets ◽  
Passive Authentication ◽  
Prime Objective ◽  
Future Direction ◽  
Source Of Information ◽  
Research Domain ◽  
Open Issues

Background: image forensics deal with the problem of authentication of pictures or their origins. There are two types of forensics techniques namely active and passive. Passive forgery is also known as blind forensics technique. In passive forgery, copy-move (cloning) image forensics is most common forgery technique. In this approach, an object or region of a picture is copied and positioned somewhere else in the same image. Active method used watermarking to solve picture genuineness problem. It has limitations like human involvement or particularly equipped cameras. To overwhelm these limitations, numerous passive authentication approaches have been developed. Moreover, both approaches do not require any prior information about the picture. Objective: The prime objective of this survey is to provide an inclusive summary as well as recent advancement, challenges and future direction in image forensics. In Today’s digital era the digital pictures and videos are having great impact on our life as well as society, as they became the important source of information. Though earlier it was very difficult to doctor the picture, nowadays digital pictures can be doctored easily with the help of editing tools and internet. These practices make pictures as well as videos genuineness deceptive. Conclusion: This paper presents the current state-of- the-art of passive (cloning) image forensics techniques, challenges and future direction of this research domain. Further, the major open issues in developing a robust cloning image forensics detector with their performance are discussed. Lastly, the available benchmark datasets are also discussed

scholarly journals Extending Geodemographics Using Data Primitives: A Review and a Methodological Proposal

2021 ◽  
Vol 10 (6) ◽  
pp. 386
Author(s):  
Jennie Gray ◽  
Lisa Buckner ◽  
Alexis Comber
Keyword(s):  
Social Dynamics ◽  
Feature Space ◽  
Social Processes ◽  
Multiple Time ◽  
Current State ◽  
Cluster Label ◽  
Static Data ◽  
The Social ◽  
Using Data

This paper reviews geodemographic classifications and developments in contemporary classifications. It develops a critique of current approaches and identifiea a number of key limitations. These include the problems associated with the geodemographic cluster label (few cluster members are typical or have the same properties as the cluster centre) and the failure of the static label to describe anything about the underlying neighbourhood processes and dynamics. To address these limitations, this paper proposed a data primitives approach. Data primitives are the fundamental dimensions or measurements that capture the processes of interest. They can be used to describe the current state of an area in a multivariate feature space, and states can be compared over multiple time periods for which data are available, through for example a change vector approach. In this way, emergent social processes, which may be too weak to result in a change in a cluster label, but are nonetheless important signals, can be captured. As states are updated (for example, as new data become available), inferences about different social processes can be made, as well as classification updates if required. State changes can also be used to determine neighbourhood trajectories and to predict or infer future states. A list of data primitives was suggested from a review of the mechanisms driving a number of neighbourhood-level social processes, with the aim of improving the wider understanding of the interaction of complex neighbourhood processes and their effects. A small case study was provided to illustrate the approach. In this way, the methods outlined in this paper suggest a more nuanced approach to geodemographic research, away from a focus on classifications and static data, towards approaches that capture the social dynamics experienced by neighbourhoods.

scholarly journals Mining Open Government Data for Business Intelligence Using Data Visualization: A Two-Industry Case Study

2021 ◽  
Vol 16 (4) ◽  
pp. 1042-1065
Author(s):  
Anne Gottfried ◽  
Caroline Hartmann ◽  
Donald Yates
Keyword(s):  
Data Visualization ◽  
Business Intelligence ◽  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
Open Government ◽  
Open Government Data ◽  
Market Opportunities ◽  
Government Data ◽  
Source Of Information

The business intelligence (BI) market has grown at a tremendous rate in the past decade due to technological advancements, big data and the availability of open source content. Despite this growth, the use of open government data (OGD) as a source of information is very limited among the private sector due to a lack of knowledge as to its benefits. Scant evidence on the use of OGD by private organizations suggests that it can lead to the creation of innovative ideas as well as assist in making better informed decisions. Given the benefits but lack of use of OGD to generate business intelligence, we extend research in this area by exploring how OGD can be used to generate business intelligence for the identification of market opportunities and strategy formulation; an area of research that is still in its infancy. Using a two-industry case study approach (footwear and lumber), we use latent Dirichlet allocation (LDA) topic modeling to extract emerging topics in these two industries from OGD, and a data visualization tool (pyLDAVis) to visualize the topics in order to interpret and transform the data into business intelligence. Additionally, we perform an environmental scanning of the environment for the two industries to validate the usability of the information obtained. The results provide evidence that OGD can be a valuable source of information for generating business intelligence and demonstrate how topic modeling and visualization tools can assist organizations in extracting and analyzing information for the identification of market opportunities.

scholarly journals Defining and Quantifying Intermittency in the Power Sector

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3366
Author(s):  
Daniel Suchet ◽  
Adrien Jeantet ◽  
Thomas Elghozi ◽  
Zacharie Jehl
Keyword(s):  
Power Source ◽  
Production Data ◽  
Power Sector ◽  
Predictive Capacity ◽  
The Public ◽  
Current State ◽  
Definition Of ◽  
Quantitative Definition ◽  
The Impact

The lack of a systematic definition of intermittency in the power sector blurs the use of this term in the public debate: the same power source can be described as stable or intermittent, depending on the standpoint of the authors. This work tackles a quantitative definition of intermittency adapted to the power sector, linked to the nature of the source, and not to the current state of the energy mix or the production predictive capacity. A quantitative indicator is devised, discussed and graphically depicted. A case study is illustrated by the analysis of the 2018 production data in France and then developed further to evaluate the impact of two methods often considered to reduce intermittency: aggregation and complementarity between wind and solar productions.

The Role of Constraints and Human Interaction in Evolving MEMS Designs: Microresonator Case Study

2004 ◽  
Author(s):  
Raffi Kamalian ◽  
Alice M. Agogino ◽  
Hideyuki Takagi
Keyword(s):  
Genetic Algorithms ◽  
Geometric Constraints ◽  
Human Interaction ◽  
Design System ◽  
Current State ◽  
Mems Resonator ◽  
Computer Aided ◽  
Generative Methods

In this paper we review the current state of automated MEMS synthesis with a focus on generative methods. We use the design of a MEMS resonator as a case study and explore the role that geometric constraints and human interaction play in a computer-aided MEMS design system based on genetic algorithms.

scholarly journals Neural networks for increased accuracy of allergenic pollen monitoring

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marcel Polling ◽  
Chen Li ◽  
Lu Cao ◽  
Fons Verbeek ◽  
Letty A. de Weger ◽  
...  
Keyword(s):  
Neural Networks ◽  
Airborne Pollen ◽  
Pollen Grains ◽  
Allergenic Pollen ◽  
Herbarium Specimens ◽  
Pollen Monitoring ◽  
Pollen Concentrations ◽  
Source Of Information ◽  
Urticaceae Pollen

AbstractMonitoring of airborne pollen concentrations provides an important source of information for the globally increasing number of hay fever patients. Airborne pollen is traditionally counted under the microscope, but with the latest developments in image recognition methods, automating this process has become feasible. A challenge that persists, however, is that many pollen grains cannot be distinguished beyond the genus or family level using a microscope. Here, we assess the use of Convolutional Neural Networks (CNNs) to increase taxonomic accuracy for airborne pollen. As a case study we use the nettle family (Urticaceae), which contains two main genera (Urtica and Parietaria) common in European landscapes which pollen cannot be separated by trained specialists. While pollen from Urtica species has very low allergenic relevance, pollen from several species of Parietaria is severely allergenic. We collect pollen from both fresh as well as from herbarium specimens and use these without the often used acetolysis step to train the CNN model. The models show that unacetolyzed Urticaceae pollen grains can be distinguished with > 98% accuracy. We then apply our model on before unseen Urticaceae pollen collected from aerobiological samples and show that the genera can be confidently distinguished, despite the more challenging input images that are often overlain by debris. Our method can also be applied to other pollen families in the future and will thus help to make allergenic pollen monitoring more specific.

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