Categorizing Senators’ Tweets and Styles of Communication

2021 ◽  
pp. 81-96
Author(s):  
Annelise Russell
Keyword(s):  
Coming Out ◽  
Strategic Communication ◽  
Communication Styles ◽  
Data Set ◽  
The Individual

Senators get to decide how to buttress their reputation with their rhetorical agendas, reflecting lawmakers’ diverse interests. The challenge is understanding what leads senators to adopt the communication styles that they do and to explain the individual patterns of these rhetorical agendas. This chapter offers a typology of senators’ rhetorical agendas on Twitter and details what it means for representation when senators adopt policy, constituent, and partisan styles of communication. Senators make the decision to connect with constituents as a policy wonk, a constituent servant, or a partisan warrior. The chapter details the collection and systematic coding of more than 180,000 tweets, using this data set to examine what leads senators to the priorities that drive their strategic communication. Senators have added capacity to influence the narratives coming out of Congress, and that influence over the supply of information affects both the framing and substance of congressional communication.

Algorithms for automated montage synthesis of images from laser-scanning confocal microscopes

1995 ◽  
Vol 53 ◽  
pp. 650-651
Author(s):  
D. E. Becker
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Laser Scanning ◽  
Cell Counting ◽  
Wide Area ◽  
Data Set ◽  
Computational Synthesis ◽  
Automated Cell Counting ◽  
Partial View ◽  
The Individual

An efficient, robust, and widely-applicable technique is presented for computational synthesis of high-resolution, wide-area images of a specimen from a series of overlapping partial views. This technique can also be used to combine the results of various forms of image analysis, such as segmentation, automated cell counting, deblurring, and neuron tracing, to generate representations that are equivalent to processing the large wide-area image, rather than the individual partial views. This can be a first step towards quantitation of the higher-level tissue architecture. The computational approach overcomes mechanical limitations, such as hysterisis and backlash, of microscope stages. It also automates a procedure that is currently done manually. One application is the high-resolution visualization and/or quantitation of large batches of specimens that are much wider than the field of view of the microscope.The automated montage synthesis begins by computing a concise set of landmark points for each partial view. The type of landmarks used can vary greatly depending on the images of interest. In many cases, image analysis performed on each data set can provide useful landmarks. Even when no such “natural” landmarks are available, image processing can often provide useful landmarks.

Territorial Distribution of Alcohol and Drug Addictions Mortality Concerning Regional Disparities in the Slovak Republic from Year 1996 to Year 2015

2020 ◽  
Keyword(s):  
Mortality Rate ◽  
Slovak Republic ◽  
Regional Disparities ◽  
Point Of View ◽  
Extreme Position ◽  
Data Set ◽  
Female Sex ◽  
Male Sex ◽  
The Individual ◽  
High Level

BACKGROUND: This paper deals with territorial distribution of the alcohol and drug addictions mortality at a level of the districts of the Slovak Republic. AIM: The aim of the paper is to explore the relations within the administrative territorial division of the Slovak Republic, that is, between the individual districts and hence, to reveal possibly hidden relation in alcohol and drug mortality. METHODS: The analysis is divided and executed into the two fragments – one belongs to the female sex, the other one belongs to the male sex. The standardised mortality rate is computed according to a sequence of the mathematical relations. The Euclidean distance is employed to compute the similarity within each pair of a whole data set. The cluster analysis examines is performed. The clusters are created by means of the mutual distances of the districts. The data is collected from the database of the Statistical Office of the Slovak Republic for all the districts of the Slovak Republic. The covered time span begins in the year 1996 and ends in the year 2015. RESULTS: The most substantial point is that the Slovak Republic possesses the regional disparities in a field of mortality expressed by the standardised mortality rate computed particularly for the diagnoses assigned to the alcohol and drug addictions at a considerably high level. However, the female sex and the male sex have the different outcome. The Bratislava III District keeps absolutely the most extreme position. It forms an own cluster for the both sexes too. The Topoľčany District bears a similar extreme position from a point of view of the male sex. All the Bratislava districts keep their mutual notable dissimilarity. Contrariwise, evaluation of a development of the regional disparities among the districts looks like notably heterogeneously. CONCLUSIONS: There are considerable regional discrepancies throughout the districts of the Slovak Republic. Hence, it is necessary to create a common platform how to proceed with the solution of this issue.

scholarly journals Autonomous feature type selection based on environment using expectation maximization in self-localization

2018 ◽  
Vol 15 (6) ◽  
pp. 172988141881470
Author(s):  
Nezih Ergin Özkucur ◽  
H Levent Akın
Keyword(s):  
Expectation Maximization ◽  
Autonomous Robots ◽  
Expectation Maximization Algorithm ◽  
Sensory Information ◽  
Ground Truth ◽  
Local Environment ◽  
Localization Algorithm ◽  
Data Set ◽  
Public Data ◽  
The Individual

Self-localization in autonomous robots is one of the fundamental issues in the development of intelligent robots, and processing of raw sensory information into useful features is an integral part of this problem. In a typical scenario, there are several choices for the feature extraction algorithm, and each has its weaknesses and strengths depending on the characteristics of the environment. In this work, we introduce a localization algorithm that is capable of capturing the quality of a feature type based on the local environment and makes soft selection of feature types throughout different regions. A batch expectation–maximization algorithm is developed for both discrete and Monte Carlo localization models, exploiting the probabilistic pose estimations of the robot without requiring ground truth poses and also considering different observation types as blackbox algorithms. We tested our method in simulations, data collected from an indoor environment with a custom robot platform and a public data set. The results are compared with the individual feature types as well as naive fusion strategy.

scholarly journals Inhomogeneities in PNIPAM Aqueous Solutions: The Inside View by Spin Probe EPR Spectroscopy

Polymers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3829
Author(s):  
Ekaterina M. Zubanova ◽  
Sergei V. Kostjuk ◽  
Peter S. Timashev ◽  
Yury A. Rochev ◽  
Alexander I. Kokorin ◽  
...  
Keyword(s):  
Aqueous Solutions ◽  
Coming Out ◽  
Epr Spectroscopy ◽  
Spin Probe ◽  
Guest Molecule ◽  
Continuous Wave ◽  
Paramagnetic Resonance ◽  
Molten Globules ◽  
The Individual ◽  
Tempo Radical

Coil to globule transition in poly(N-isopropylacrylamide) aqueous solutions was studied using spin probe continuous-wave electronic paramagnetic resonance (CW EPR) spectroscopy with an amphiphilic TEMPO radical as a guest molecule. Using Cu(II) ions as the “quencher” for fast-moving radicals in the liquid phase allowed obtaining the individual spectra of TEMPO radicals in polymer globule and observing inhomogeneities in solutions before globule collapsing. EPR spectra simulations confirm the formation of molten globules at the first step with further collapsing and water molecules coming out of the globule, making it denser.

scholarly journals The promiscuous and highly mobile resistome of a superbug

2021 ◽  
Author(s):  
Ismael Hernández-González ◽  
Valeria Mateo-Estrada ◽  
Santiago Castillo-Ramírez
Keyword(s):  
Population Dynamics ◽  
Gene Content ◽  
Massive Data ◽  
Nosocomial Pathogen ◽  
Data Set ◽  
Massive Data Set ◽  
The Individual ◽  
Global Threat ◽  
And Control ◽  
Global Population

AbstractAntimicrobial resistance (AR) is a major global threat to public health. Understanding the population dynamics of AR is critical to restrain and control this issue. However, no study has provided a global picture of the resistome of Acinetobacter baumannii, a very important nosocomial pathogen. Here we analyze 1450+ genomes (covering > 40 countries and > 4 decades) to infer the global population dynamics of the resistome of this species. We show that gene flow and horizontal transfer have driven the dissemination of AR genes in A. baumannii. We found considerable variation in AR gene content across lineages. Although the individual AR gene histories have been affected by recombination, the AR gene content has been shaped by the phylogeny. Furthermore, many AR genes have been transferred to other well-known pathogens, such as Pseudomonas aeruginosa or Klebsiella pneumoniae. Finally, despite using this massive data set, we were not able to sample the whole diversity of AR genes, which suggests that this species has an open resistome. Ours results highlight the high mobilization risk of AR genes between important pathogens. On a broader perspective, this study gives a framework for an emerging perspective (resistome-centric) on the genome epidemiology (and surveillance) of bacterial pathogens.

scholarly journals Health Care Professionalism Without Doctors

2018 ◽  
Vol 5 (2) ◽  
pp. 72-94 ◽  
Author(s):  
Marie Østergaard Møller
Keyword(s):  
Health Professionals ◽  
Qualitative Data ◽  
Nationwide Survey ◽  
Relational Theory ◽  
Local Health ◽  
Medical Field ◽  
Data Set ◽  
The Individual ◽  
The Relationship ◽  
Larger Sample

The article uses the organization of health houses in Denmark as a case to study the relationship between spatial surroundings and professionalization. The question is whether these new local health houses comprise an alternative to the medical view on health or ––even in the absence of the hospital–– script the professionals to identify themselves as agents from the medical field? In this article, macro-structural theory is combined with micro-relational theory in order to identify how macro structures such as professionalization nest the way social interaction takes place in concrete spatial situations and surroundings. The argument put forward is that we need to identity this process at the level of the individual in order to qualify and anchor our understanding of professionalization as a macro phenomenon. The empirical basis is two dissimilar locations (health houses), selected from a larger qualitative data set of interviews with health professionals and citizens and observations of health houses, originally selected from a nationwide survey. The presented analysis zooms in on selected places and situations and relates analyses to the overall picture of differences and similarities identified in the larger sample. The analysis shows how entrances, receptions, information screens and coffee tables not only design houses, but also script styles of interaction between health professionals and citizens as well as they work as signs creating expectations about professional roles and how to reflect and act as a professional in a given physical and social setting. The main finding is that spatial surroundings facilitate processes of identification and counter-identification crucial to a new kind of health professionals such as the ones under study here.

scholarly journals The Impact of Customer Contact on Collective Human Energy in Firms

2018 ◽  
Vol 44 (5) ◽  
pp. 915-952
Author(s):  
Petra Kipfelsberger ◽  
Heike Bruch ◽  
Dennis Herhausen
Keyword(s):  
Transformational Leadership ◽  
Organizational Level ◽  
Data Set ◽  
Customer Contact ◽  
Individual Level ◽  
Moderated Mediation Model ◽  
Human Energy ◽  
The Individual ◽  
High Level ◽  
The Impact

This article investigates how and when a firm’s level of customer contact influences the collective organizational energy. For this purpose, we bridge the literature on collective human energy at work with the job impact framework and organizational sensemaking processes and argue that a firm’s level of customer contact is positively linked to the collective organizational energy because a high level of customer contact might make the experience of prosocial impact across the firm more likely. However, as prior research at the individual level has indicated that customers could also deplete employees’ energy, we introduce transformational leadership climate as a novel contingency factor for this linkage at the organizational level. We propose that a medium to high transformational leadership climate is necessary to derive positive meaning from customer contact, whereas firms with a low transformational leadership climate do not get energized by customer contact. We tested the proposed moderated mediation model with multilevel modeling and a multisource data set comprising 9,094 employees and 75 key informants in 75 firms. The results support our hypotheses and offer important theoretical contributions for research on collective human energy in organizations and its interplay with customers.

Finding the best-fit background function for whole-powder-pattern fitting using LASSO combined with tree search

2021 ◽  
Vol 54 (2) ◽  
Author(s):  
Hideo Toraya
Keyword(s):  
Linear Regression Analysis ◽  
Powder Pattern ◽  
Tree Search ◽  
Data Set ◽  
Tree Structures ◽  
Root Node ◽  
X Ray Crystallography ◽  
Pattern Decomposition ◽  
The Individual ◽  
Best Fit

A new linear function for modelling the background in whole-powder-pattern fitting has been derived by applying LASSO (least absolute shrinkage and selection operator) and the technique of tree search. The background function (BGF) consists of terms b n L(2θ/180)−n/2 and b n H(1 − 2θ/180)−n/2 for the low- and high-angle sides, respectively. Some variable parameters of the BGF should be fixed at zero while others should be varied in order to find the best fit for a given data set without inducing overfitting. The LASSO algorithm can automatically select the variables in linear regression analysis. However, it finds the best-fit BGF with a set of adjustable parameters for a given data set while it derives a different set of parameters for a different data set. Thus, LASSO derives multiple solutions depending on the data set used. By regarding the individual solutions from LASSO as nodes of trees, tree structures were constructed from these solutions. The root node has the maximum number of adjustable parameters, P. P decreases with descending levels of the tree one by one, and leaf nodes have just one parameter. By evaluating individual solutions (nodes) by their χ2 index, the best-fit single path from a root node to a leaf node was found. The present BGF can be used simply by varying P in the range 1–10. The BGF thus derived as a final single solution was incorporated into computer programs for Pawley-based whole-powder-pattern decomposition and Rietveld refinement, and the performance of the BGF was tested in comparison with the polynomials currently widely used as the BGF. The present BGF has been demonstrated to be stable and to give an excellent fit, comparable to polynomials but with a smaller number of adjustable parameters and without introducing undulation into the calculated background curve. Basic algorithms used in statistics and machine learning have been demonstrated to be useful in developing an analytical model in X-ray crystallography.

Multimodal of Ear and Face Biometric Recognition Using AARK Threshold segmentation and Classifier with Score level fusion

2021 ◽  
Author(s):  
SANTHAM BHARATHY ALAGARSAMY ◽  
Kalpana Murugan
Keyword(s):  
Projection Data ◽  
Biometric System ◽  
Biometric Recognition ◽  
Data Set ◽  
Score Level Fusion ◽  
Multimodal Biometric System ◽  
The Individual ◽  
Individual Scores ◽  
Face Biometrics ◽  
Level Fusion

Abstract More than one biometric methodology of an individual is utilized by a multimodal biometric system to moderate a portion of the impediments of a unimodal biometric system and upgrade its precision, security, and so forth. In this paper, an incorporated multimodal biometric system has proposed for the identification of people utilizing ear and face as input and pre-preparing, ring projection, data standardization, AARK limit division, extraction of DWT highlights and classifiers are utilized. Afterward, singular matches gathered from the different modalities produce the individual scores. The proposed framework indicated got brings about the investigations than singular ear and face biometrics tried. To certify the individual as genuine or an impostor, the eventual outcomes are then utilized. On the IIT Delhi ear information base and ORL face data set, the proposed framework has checked and indicated an individual exactness of 96.24%

Lookable User Interfaces and 3D

2018 ◽  
pp. 119-137
Author(s):  
Alan Radley
Keyword(s):  
Virtual Reality ◽  
User Interface ◽  
User Interfaces ◽  
Interface Design ◽  
Maximum Degree ◽  
Apparent Distance ◽  
User Interface Design ◽  
Perspective View ◽  
Data Set ◽  
The Individual

A new philosophy of user interface design is described. Named the “Lookable User Interface,” or LUI, the approach is based on the concept of a Personal Reality (PR) system. Here the computer adapts to the user's worldview in a personalized way, and according to the specific requirements, behaviors, and perceptive skills of the individual. Typically, a PR system creates and adjusts (in real-time) 3D perspective view(s) of a data-set, including (potentially) the field of view of a scene and the apparent distance and scale of objects, whilst also creating an aesthetic “eye-friendly” context for computing operations. A Lookable User Interface (LUI) affords the maximum degree of visual accessibility to digital content. The authors examine the results of testing a Lookable User Interface. Spectasia is one example of a Personal Virtual Reality (PVR) that can be used to visualize links between universals and particulars within digital worlds.

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