Nodulation of Stylosanthes guyanensis: prediction of Rhizobium effectiveness response with seed isozyme patterns

1976 ◽  
Vol 27 (3) ◽  
pp. 381 ◽  
Author(s):  
PJ Robinson ◽  
RA Date ◽  
RG Megarrity
Keyword(s):  
Nitrogen Fixation ◽  
Acid Phosphatase ◽  
Pattern Analysis ◽  
Isozyme Analysis ◽  
Rapid Screening ◽  
Isozyme Patterns ◽  
Wide Range ◽  
Response Groups ◽  
Response Group

Forty-nine introductions of S. guyanensis were tested against 22 strains of Rhizobium for effectiveness of the symbiosis in nitrogen fixation. A wide range of effectiveness between strains on individual accessions, and significant strain x accession interactions, were obtained. Two major groups of accessions were obtained on pattern analysis, a wide effectiveness response group with an average of 42% strains effective (containing 30 accessions) and a narrow response group with only 6% strains effective (19 accessions). The seed isozyme patterns (esterase and acid phosphatase) were also determined on the 49 introductions. Classification of these data also revealed two major groups containing 28 and 21 accessions which corresponded on a broad basis with the accessions containcd in Lhc wide and narrow effectiveness response groups respectively. The use of seed isozyme analysis as a guide to Rhizobium effectiveness response is proposed as a rapid screening technique for introductions of S. guyanensis.

A brief history of Nitrogen fixation

2018 ◽  
Vol 10 (2) ◽  
pp. 86
Author(s):  
George J. Leigh
Keyword(s):  
Nitrogen Fixation ◽  
Wide Range ◽  
History Of ◽  
Chemical Problem

<div>Nitrogen furation has been a subject of great interest to chemists for the best part of a century. As a chemical problem it is possibly unique because the research has really been led by biologists for most of this time. Currently it is being studied by a wide range of scientists of many different stripes, and the interplay between them lends fascination to the topic. Even more, nitrogen futation has been used by humans for at least two thousand years even though the primitive agriculturalists could not have been aware of what was going on.</div><div> </div>

scholarly journals Modes of Interaction in Naturally Occurring Medical Encounters With General Practitioners: The “One in a Million” Study

2021 ◽  
pp. 104973232199379
Author(s):  
Olaug S. Lian ◽  
Sarah Nettleton ◽  
Åge Wifstad ◽  
Christopher Dowrick
Keyword(s):  
General Practitioners ◽  
Narrative Analysis ◽  
Mode Competition ◽  
General Applicability ◽  
Naturally Occurring ◽  
Wide Range ◽  
The One ◽  
Narrative Mode ◽  
Modes Of Interaction

In this article, we qualitatively explore the manner and style in which medical encounters between patients and general practitioners (GPs) are mutually conducted, as exhibited in situ in 10 consultations sourced from the One in a Million: Primary Care Consultations Archive in England. Our main objectives are to identify interactional modes, to develop a classification of these modes, and to uncover how modes emerge and shift both within and between consultations. Deploying an interactional perspective and a thematic and narrative analysis of consultation transcripts, we identified five distinctive interactional modes: question and answer (Q&A) mode, lecture mode, probabilistic mode, competition mode, and narrative mode. Most modes are GP-led. Mode shifts within consultations generally map on to the chronology of the medical encounter. Patient-led narrative modes are initiated by patients themselves, which demonstrates agency. Our classification of modes derives from complete naturally occurring consultations, covering a wide range of symptoms, and may have general applicability.

scholarly journals Uncertainty-Aware Deep Learning-Based Cardiac Arrhythmias Classification Model of Electrocardiogram Signals

Computers ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 82
Author(s):  
Ahmad O. Aseeri
Keyword(s):  
Deep Learning ◽  
Cardiac Arrhythmias ◽  
Large Scale ◽  
Clinical Decision Making ◽  
Probabilistic Approach ◽  
Classification Model ◽  
Gating Mechanism ◽  
Uncertainty Estimates ◽  
Wide Range

Deep Learning-based methods have emerged to be one of the most effective and practical solutions in a wide range of medical problems, including the diagnosis of cardiac arrhythmias. A critical step to a precocious diagnosis in many heart dysfunctions diseases starts with the accurate detection and classification of cardiac arrhythmias, which can be achieved via electrocardiograms (ECGs). Motivated by the desire to enhance conventional clinical methods in diagnosing cardiac arrhythmias, we introduce an uncertainty-aware deep learning-based predictive model design for accurate large-scale classification of cardiac arrhythmias successfully trained and evaluated using three benchmark medical datasets. In addition, considering that the quantification of uncertainty estimates is vital for clinical decision-making, our method incorporates a probabilistic approach to capture the model’s uncertainty using a Bayesian-based approximation method without introducing additional parameters or significant changes to the network’s architecture. Although many arrhythmias classification solutions with various ECG feature engineering techniques have been reported in the literature, the introduced AI-based probabilistic-enabled method in this paper outperforms the results of existing methods in outstanding multiclass classification results that manifest F1 scores of 98.62% and 96.73% with (MIT-BIH) dataset of 20 annotations, and 99.23% and 96.94% with (INCART) dataset of eight annotations, and 97.25% and 96.73% with (BIDMC) dataset of six annotations, for the deep ensemble and probabilistic mode, respectively. We demonstrate our method’s high-performing and statistical reliability results in numerical experiments on the language modeling using the gating mechanism of Recurrent Neural Networks.

scholarly journals Classification of unlabeled online media

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sakthi Kumar Arul Prakash ◽  
Conrad Tucker
Keyword(s):  
Social Media ◽  
Real World ◽  
Graphical Model ◽  
Ground Truth ◽  
Classification Problem ◽  
Machine Learning Algorithms ◽  
Social Media Networks ◽  
Online Social Media ◽  
Wide Range

AbstractThis work investigates the ability to classify misinformation in online social media networks in a manner that avoids the need for ground truth labels. Rather than approach the classification problem as a task for humans or machine learning algorithms, this work leverages user–user and user–media (i.e.,media likes) interactions to infer the type of information (fake vs. authentic) being spread, without needing to know the actual details of the information itself. To study the inception and evolution of user–user and user–media interactions over time, we create an experimental platform that mimics the functionality of real-world social media networks. We develop a graphical model that considers the evolution of this network topology to model the uncertainty (entropy) propagation when fake and authentic media disseminates across the network. The creation of a real-world social media network enables a wide range of hypotheses to be tested pertaining to users, their interactions with other users, and with media content. The discovery that the entropy of user–user and user–media interactions approximate fake and authentic media likes, enables us to classify fake media in an unsupervised learning manner.

scholarly journals Sequence data from isolated lichen-associated melanized fungi enhance delimitation of two new lineages within Chaetothyriomycetidae

2021 ◽  
Vol 20 (7) ◽  
pp. 911-927
Author(s):  
Lucia Muggia ◽  
Yu Quan ◽  
Cécile Gueidan ◽  
Abdullah M. S. Al-Hatmi ◽  
Martin Grube ◽  
...  
Keyword(s):  
Sequence Data ◽  
Single Species ◽  
Sister Group ◽  
Asexual Propagation ◽  
Dna Sequence Data ◽  
Wide Range ◽  
The Family ◽  
Rock Inhabiting Fungi ◽  
Stable Habitat

AbstractLichen thalli provide a long-lived and stable habitat for colonization by a wide range of microorganisms. Increased interest in these lichen-associated microbial communities has revealed an impressive diversity of fungi, including several novel lineages which still await formal taxonomic recognition. Among these, members of the Eurotiomycetes and Dothideomycetes usually occur asymptomatically in the lichen thalli, even if they share ancestry with fungi that may be parasitic on their host. Mycelia of the isolates are characterized by melanized cell walls and the fungi display exclusively asexual propagation. Their taxonomic placement requires, therefore, the use of DNA sequence data. Here, we consider recently published sequence data from lichen-associated fungi and characterize and formally describe two new, individually monophyletic lineages at family, genus, and species levels. The Pleostigmataceae fam. nov. and Melanina gen. nov. both comprise rock-inhabiting fungi that associate with epilithic, crust-forming lichens in subalpine habitats. The phylogenetic placement and the monophyly of Pleostigmataceae lack statistical support, but the family was resolved as sister to the order Verrucariales. This family comprises the species Pleostigma alpinum sp. nov., P. frigidum sp. nov., P. jungermannicola, and P. lichenophilum sp. nov. The placement of the genus Melanina is supported as a lineage within the Chaetothyriales. To date, this genus comprises the single species M. gunde-cimermaniae sp. nov. and forms a sister group to a large lineage including Herpotrichiellaceae, Chaetothyriaceae, Cyphellophoraceae, and Trichomeriaceae. The new phylogenetic analysis of the subclass Chaetothyiomycetidae provides new insight into genus and family level delimitation and classification of this ecologically diverse group of fungi.

scholarly journals Phosphatase synthesis in Klebsiella (Aerobacter) aerogenes growing in continuous culture

1972 ◽  
Vol 127 (1) ◽  
pp. 87-96 ◽  
Author(s):  
P. G. Bolton ◽  
A. C. R. Dean
Keyword(s):  
Alkaline Phosphatase ◽  
Acid Phosphatase ◽  
Continuous Culture ◽  
Activity Profile ◽  
Glucose Effect ◽  
Ph Values ◽  
Nitrophenyl Phosphate ◽  
Wide Range ◽  
Rate Of Hydrolysis ◽  
Hydrolysis Of

1. Phosphatase synthesis was studied in Klebsiella aerogenes grown in a wide range of continuous-culture systems. 2. Maximum acid phosphatase synthesis was associated with nutrient-limited, particularly carbohydrate-limited, growth at a relatively low rate, glucose-limited cells exhibiting the highest activity. Compared with glucose as the carbon-limiting growth material, other sugars not only altered the activity but also changed the pH–activity profile of the enzyme(s). 3. The affinity of the acid phosphatase in glucose-limited cells towards p-nitrophenyl phosphate (Km 0.25–0.43mm) was similar to that of staphylococcal acid phosphatase but was ten times greater than that of the Escherichia coli enzyme. 4. PO43−-limitation derepressed alkaline phosphatase synthesis but the amounts of activity were largely independent of the carbon source used for growth. 5. The enzymes were further differentiated by the effect of adding inhibitors (F−, PO43−) and sugars to the reaction mixture during the assays. In particular, it was shown that adding glucose, but not other sugars, stimulated the rate of hydrolysis of p-nitrophenyl phosphate by the acid phosphatase in carbohydrate-limited cells at low pH values (<4.6) but inhibited it at high pH values (>4.6). Alkaline phosphatase activity was unaffected. 6. The function of phosphatases in general is discussed and possible mechanisms for the glucose effect are outlined.

scholarly journals Optimization of Plant Extract Purification Procedure for Rapid Screening Analysis of Sixteen Phenolics by Liquid Chromatography

Separations ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 13
Author(s):  
Petra Ranušová ◽  
Ildikó Matušíková ◽  
Peter Nemeček
Keyword(s):  
Liquid Chromatography ◽  
High Performance ◽  
Solid Phase ◽  
Low Cost ◽  
Sinapic Acid ◽  
Rapid Screening ◽  
Coumaric Acid ◽  
Laboratory Equipment ◽  
Wide Range ◽  
Methoxycinnamic Acid

A solid-phase extraction (SPE) procedure was developed for simultaneous monitoring of sixteen different phenolics of various polarity, quantified by high-performance liquid chromatography (HPLC). The procedure allowed screening the accumulation of intermediates in different metabolic pathways that play a crucial role in plant physiology and/or are beneficial for human health. Metabolites mostly involved in phenylpropanoid, shikimate, and polyketide pathways comprise chlorogenic acid, gentisic acid, vanillic acid, caffeic acid, protocatechuic acid, ferulic acid, rutin, quercetin, epicatechin, gallic acid, sinapic acid, p-coumaric acid, o-coumaric acid, vanillin; two rarely quantified metabolites, 2,5-dimethoxybenzoic acid and 4-methoxycinnamic acid, were included as well. The procedure offered low cost, good overall efficiency, and applicability in laboratories with standard laboratory equipment. SPE recoveries were up to 99.8% at various concentration levels. The method allowed for routine analysis of compounds with a wide range of polarity within a single run, while its applicability was demonstrated for various model plant species (tobacco, wheat, and soybean), as well as different tissue types (shoots and roots).

Introduction of a new AAC symbol classification system: the multidimensional quaternary symbol continuum (MQSC)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Eliada Pampoulou ◽  
Donald R. Fuller
Keyword(s):  
Peer Review ◽  
Classification System ◽  
Augmentative And Alternative Communication ◽  
Social Issues ◽  
Content Type ◽  
Design Attributes ◽  
Wide Range ◽  
Current Classification ◽  
Symbol Classification

PurposeWhen the augmentative and alternative communication (ACC) model (Lloyd et al., 1990) was proposed, these components of symbols were not considered, nor were they contemplated when superordinate (Lloyd and Fuller, 1986) and subordinate levels (Fuller et al., 1992) of AAC symbol taxonomy were developed. The purpose of this paper is to revisit the ACC model and propose a new symbol classification system called multidimensional quaternary symbol continuum (MQSC)Design/methodology/approachThe field of AAC is evolving at a rapid rate in terms of its clinical, social, research and theoretical underpinnings. Advances in assessment and intervention methods, technology and social issues are all responsible to some degree for the significant changes that have occurred in the field of AAC over the last 30 years. For example, the number of aided symbol collections has increased almost exponentially over the past couple of decades. The proliferation of such a large variety of symbol collections represents a wide range of design attributes, physical attributes and linguistic characteristics for aided symbols and design attributes and linguistic characteristics for unaided symbols.FindingsTherefore, it may be time to revisit the AAC model and more specifically, one of its transmission processes referred to as the means to represent.Originality/valueThe focus of this theoretical paper then, is on the current classification of symbols, issues with respect to the current classification of symbols in terms of ambiguity of terminology and the evolution of symbols, and a proposal for a new means of classifying the means to represent.Peer reviewThe peer review history for this article is available at: https://publons.com/publon10.1108/JET-04-2021-0024

scholarly journals Classification of Fake Product Ratings Using a Timeline Based Approach

2017 ◽  
Vol 3 (2) ◽  
pp. 12 ◽  
Author(s):  
Neha Thomas ◽  
Susan Elias
Keyword(s):  
Language Processing ◽  
Opinion Mining ◽  
Optimal Point ◽  
Linear Classifiers ◽  
Wide Range ◽  
Text Content ◽  
Classification Tool ◽  
Fake Reviews ◽  
Product Ratings

 Abstract— Detection of fake review and reviewers is currently a challenging problem in cyber space. It is challenging primarily due to the dynamic nature of the methodology used to fake the review. There are several aspects to be considered when analyzing reviews to classify them effective into genuine and fake. Sentiment analysis, opinion mining and intend mining are fields of research that try to accomplish the goal through Natural Language Processing of the text content of the review.  In this paper, an approach that uses the review ratings evaluated along a timeline is presented. An Amazon dataset comprising of ratings indicated for a wide range of products was used for the analysis presented here. The analysis of the ratings was carried out for an electronic product over a period of six years.  The computed average rating helps to identify linear classifiers that define solution boundaries within the dataspace. This enables a product specific classification of review ratings and suitable recommendations can also be generated automatically. The paper explains a methodology to evaluate the average product ratings over time and presents the research outcomes using a novel classification tool. The proposed approach helps to determine the optimal point to distinguish between fake and genuine ratings for each product.    Index Terms: Fake reviews, Fake Ratings, Product Ratings, Online Shopping, Amazon Dataset.

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