H/D isotope effect on charge-inverted hydrogen-bonded systems: Systematic classification of three different types in H3XH…YH3(X = C, Si, or Ge, and Y = B, Al, or Ga) with multicomponent calculation

2015 ◽  
Vol 36 (22) ◽  
pp. 1647-1654 ◽  
Author(s):  
Taro Udagawa ◽  
Masanori Tachikawa
Keyword(s):  
Isotope Effect ◽  
Systematic Classification ◽  
Different Types ◽  
Hydrogen Bonded Systems ◽  
Hydrogen Bonded

The Isotope Effect in Hydrogen-Bonded Systems

1998 ◽  
Vol 12 (29n31) ◽  
pp. 3406-3408
Author(s):  
A. Bussmann-Holder ◽  
K.-H. Michel
Keyword(s):  
Transition Temperature ◽  
Isotope Effect ◽  
Proton Tunneling ◽  
Organic Systems ◽  
Hydrogen Bonded Systems ◽  
Hydrogen Bonded

The giant isotope effect on the ferro- and antiferroelectric transition temperature upon deuteration of hydrogen-bonded systems is well known experimentally since various decades. Yet, theoretically only recently a microscopic understanding of this effect has been achieved which, specifically, took into account the geometry of the O ⋯ H ⋯ O bond. The implications of this modeling are multiple as numerous hydrogen-bonded organic systems show the same effects as ferro- and antiferroelectrics, i.e., cooperative proton tunneling at a well-defined temperature.

scholarly journals Types of Behavior of Flood Victims around Floodwaters. Correlation with Situational and Demographic Factors

2020 ◽  
Vol 12 (11) ◽  
pp. 4409 ◽  
Author(s):  
Michalis Diakakis
Keyword(s):  
Human Behavior ◽  
Risk Taking ◽  
High Accuracy ◽  
Situational Factors ◽  
Strong Indication ◽  
Systematic Classification ◽  
Surrounding Environment ◽  
Different Types ◽  
Risk Taking Behaviors

Recently, human behavior around floodwaters has been acknowledged as one of the factors that influence the risk of fatal incidents. The present study analyzes the behavior of flood victims by developing a systematic classification of their actions at the time of the flood. Based on this taxonomy, the study examines a flood fatality database for Greece (1960–2019) to quantify the different types of behavior and to examine potential correlations with various demographical and situational factors. Results show that three-quarters of the victims exhibit a risk-taking behavior by deliberately coming in contact with floodwaters. Statistically significant associations were found between behavior and the demographics of the victims, the type surrounding environment, and the use of vehicles, indicating that certain situations and certain individuals are more prone to risk-taking behaviors than others. A statistical model shows that the behavior of a flood victim can be predicted with high accuracy by knowing certain variables of a fatal incident. The prevalence of risk-taking actions identified is a strong indication that human behavior is a crucial factor in flood mortality. The present study shows that a systematic classification of behaviors can help future interventions by highlighting the most common mechanisms of fatal incidents.

Dual stain kit for the microscopic gram classification of ocular infection bacteria

1993 ◽  
Vol 51 ◽  
pp. 248-249
Author(s):  
Jacob S. Hanker ◽  
Dale N. Holdren ◽  
Kenneth L. Cohen ◽  
Beverly L. Giammara
Keyword(s):  
Contact Lenses ◽  
Ocular Infection ◽  
Gram Negative Bacteria ◽  
Gram Negative ◽  
Gram Staining ◽  
Ocular Infections ◽  
Different Types ◽  
Culture Positive ◽  
Increased Susceptibility

Keratitis and conjunctivitis (infections of the cornea or conjunctiva) are ocular infections caused by various bacteria, fungi, viruses or parasites; bacteria, however, are usually prominent. Systemic conditions such as alcoholism, diabetes, debilitating disease, AIDS and immunosuppressive therapy can lead to increased susceptibility but trauma and contact lens use are very important factors. Gram-negative bacteria are most frequently cultured in these situations and Pseudomonas aeruginosa is most usually isolated from culture-positive ulcers of patients using contact lenses. Smears for staining can be obtained with a special swab or spatula and Gram staining frequently guides choice of a therapeutic rinse prior to the report of the culture results upon which specific antibiotic therapy is based. In some cases staining of the direct smear may be diagnostic in situations where the culture will not grow. In these cases different types of stains occasionally assist in guiding therapy.

Explanatory Power for Medical Expert Systems: Studies in the Representation of Causal Relationships for Clinical Consultations

1982 ◽  
Vol 21 (03) ◽  
pp. 127-136 ◽  
Author(s):  
J. W. Wallis ◽  
E. H. Shortliffe
Keyword(s):  
Explanatory Power ◽  
Prototype System ◽  
Inference Rules ◽  
Medical Expert ◽  
Comprehensive Knowledge ◽  
Different Types ◽  
Medical Expert Systems ◽  
Explanation System ◽  
Systems Studies

This paper reports on experiments designed to identify and implement mechanisms for enhancing the explanation capabilities of reasoning programs for medical consultation. The goals of an explanation system are discussed, as is the additional knowledge needed to meet these goals in a medical domain. We have focussed on the generation of explanations that are appropriate for different types of system users. This task requires a knowledge of what is complex and what is important; it is further strengthened by a classification of the associations or causal mechanisms inherent in the inference rules. A causal representation can also be used to aid in refining a comprehensive knowledge base so that the reasoning and explanations are more adequate. We describe a prototype system which reasons from causal inference rules and generates explanations that are appropriate for the user.

scholarly journals Deep Learning Methods for Classification of Certain Abnormalities in Echocardiography

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 495
Author(s):  
Imayanmosha Wahlang ◽  
Arnab Kumar Maji ◽  
Goutam Saha ◽  
Prasun Chakrabarti ◽  
Michal Jasinski ◽  
...  
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Support Vector ◽  
Variational Autoencoder ◽  
Different Types ◽  
Static Images ◽  
Long Short Term Memory ◽  
2D And 3D ◽  
Better Than

This article experiments with deep learning methodologies in echocardiogram (echo), a promising and vigorously researched technique in the preponderance field. This paper involves two different kinds of classification in the echo. Firstly, classification into normal (absence of abnormalities) or abnormal (presence of abnormalities) has been done, using 2D echo images, 3D Doppler images, and videographic images. Secondly, based on different types of regurgitation, namely, Mitral Regurgitation (MR), Aortic Regurgitation (AR), Tricuspid Regurgitation (TR), and a combination of the three types of regurgitation are classified using videographic echo images. Two deep-learning methodologies are used for these purposes, a Recurrent Neural Network (RNN) based methodology (Long Short Term Memory (LSTM)) and an Autoencoder based methodology (Variational AutoEncoder (VAE)). The use of videographic images distinguished this work from the existing work using SVM (Support Vector Machine) and also application of deep-learning methodologies is the first of many in this particular field. It was found that deep-learning methodologies perform better than SVM methodology in normal or abnormal classification. Overall, VAE performs better in 2D and 3D Doppler images (static images) while LSTM performs better in the case of videographic images.

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