scholarly journals Ecological Quality Status of the Algiers coastal waters by using macroalgae assemblages as bioindicators (Algeria, Mediterranean Sea)

2018 ◽  
pp. 305
Author(s):  
CHABANE KHADIDJA ◽  
BAHBAH LAMIA ◽  
SERIDI HALIMA
Keyword(s):  
Sampling Site ◽  
Monitoring Program ◽  
Ecological Status ◽  
Stress Index ◽  
Species Number ◽  
Anthropogenic Stress ◽  
Anthropogenic Pressures ◽  
Wide Range ◽  
Quality Element

Macroalgae assemblages have been used as a quality element for the assessment of the Ecological Status Classes (ESC) of coastal water bodies for the implementation of the European Water Framework Directive (WFD, 2000/60/EC). To assess the suitability of this quality element in Algiers coasts, seven sampling sites with five (5) replications covering a wide range of anthropogenic pressures were studied during spring and summer 2015. Coverage data of macroalgae in each sampling site were analyzed on species, i.e., structural (species number, nMDS, clustering, K-dominance and Simper analysis on Bray–Curtis similarity) and on Ecological Status Groups, i.e., functional (nMDS, clustering, K-dominance, Ecological Evaluation Index/EEI-c) biological levels. Key water variables (temperature, salinity and pH) along with the anthropogenic stress index MALUSI were also estimated. The obtained results revealed a significant effect of anthropogenic stress in the macroalgal assemblages. The structural analysis showed: (1) species richness of 86 taxa in total, (2) dominance of Cystoseira amentacea var. stricta (late-successional) associated by Lithophyllum incrustans, and Jania rubens in non-impacted sites and of Ulva rigida, Ulva intestinalis and Caulerpa cylindracea (opportunistic) species in impacted sites, and (3) record a higher proportion of low abundance of species in polluted communities than in less polluted communities. The functional analysis showed: (1) classification of sites based on multivariate and K-dominance analyses in four groups, three in agreement with water degradation, and one for low salinity influence, (2) classification of sites into “Bad”, ”High”, “Moderate” and “Good” ESC’s by EEI-c index, (3) a strong non-linear relationship (R²=0.85) of EEI-c index with MALUSI index. Therefore, to implement a national monitoring program within the scope WFD in Algeria coasts, the EEI-c index will be a suitable tool.

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 The Influence of Flow Regime on Ecological Quality, Bird Diversity, and Shellfish Fisheries in a Lowland Mediterranean River and Its Coastal Area

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 918 ◽  
Author(s):  
Oscar Belmar ◽  
Carles Ibáñez ◽  
Ana Forner ◽  
Nuno Caiola
Keyword(s):  
Aquatic Vegetation ◽  
Environmental Flows ◽  
Ecological Status ◽  
Model Performance ◽  
Habitat Characteristics ◽  
Bird Diversity ◽  
Ecological Quality ◽  
Anthropogenic Pressures ◽  
Discharge Data ◽  
Mantis Shrimp

Designing environmental flows in lowland river sections and estuaries is a challenge for researchers and managers, given their complexity and their importance, both for nature conservation and economy. The Ebro River and its delta belong to a Mediterranean area with marked anthropogenic pressures. This study presents an assessment of the relationships between mean flows (discharges) computed at different time scales and (i) ecological quality based on fish populations in the lower Ebro, (ii) bird populations, and (iii) two shellfish fishery species of socioeconomic importance (prawn, or Penaeus kerathurus, and mantis shrimp, or Squilla mantis). Daily discharge data from 2000 to 2015 were used for analyses. Mean annual discharge was able to explain the variation in fish-based ecological quality, and model performance increased when aquatic vegetation was incorporated. Our results indicate that a good ecological status cannot be reached only through changes on discharge, and that habitat characteristics, such as the coverage of macrophytes, must be taken into account. In addition, among the different bird groups identified in our study area, predators were related to river discharge. This was likely due to its influence on available resources. Finally, prawn and mantis shrimp productivity were influenced up to a certain degree by discharge and physicochemical variables, as inputs from rivers constitute major sources of nutrients in oligotrophic environments such as the Mediterranean Sea. Such outcomes allowed revisiting the environmental flow regimes designed for the study area, which provides information for water management in this or in other similar Mediterranean zones.

scholarly journals Monitoring Skeletal Anomalies in Big-Scale Sand Smelt, Atherina boyeri, as a Potential Complementary Tool for Early Detection of Effects of Anthropic Pressure in Coastal Lagoons

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 159
Author(s):  
Chiara Leone ◽  
Francesca De Luca ◽  
Eleonora Ciccotti ◽  
Arianna Martini ◽  
Clara Boglione
Keyword(s):  
Early Detection ◽  
Habitat Degradation ◽  
Anthropogenic Impacts ◽  
Coastal Lagoons ◽  
Ecological Status ◽  
Detection Methods ◽  
Anthropogenic Pressures ◽  
Morphological Examination ◽  
Skeletal Anomalies

Mediterranean coastal lagoons are increasingly affected by several threats, all concurrently leading to habitat degradation and loss. Methods based on fish for the assessment of the ecological status are under implementation for the Water Framework Directive requirements, to assess the overall quality of coastal lagoons. Complementary tools based on the use of single fish species as biological indicators could be useful as early detection methods of anthropogenic impacts. The analysis of skeletal anomalies in the big-scale sand smelt, Atherina boyeri, from nine Mediterranean coastal lagoons in Italy was carried out. Along with the morphological examination of fish, the environmental status of the nine lagoons was evaluated using a method based on expert judgement, by selecting and quantifying several environmental descriptors of direct and indirect human pressures acting on lagoon ecosystems. The average individual anomaly load and the frequency of individuals with severe anomalies allow to discriminate big-scale sand smelt samples on the basis of the site and of its quality status. Furthermore, a relationship between skeletal anomalies and the environmental quality of specific lagoons, driven by the anthropogenic pressures acting on them, was found. These findings support the potentiality of skeletal anomalies monitoring in big-scale sand smelt as a tool for early detection of anthropogenic impacts in coastal lagoons of the Mediterranean region.

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 Practical Applications of a Multisensor UAV Platform Based on Multispectral, Thermal and RGB High Resolution Images in Precision Viticulture

Agriculture ◽  
2018 ◽  
Vol 8 (7) ◽  
pp. 116 ◽  
Author(s):  
Alessandro Matese ◽  
Salvatore Di Gennaro
Keyword(s):  
Water Stress ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Stress Index ◽  
Crop Water Stress Index ◽  
Practical Applications ◽  
Water Stress Index ◽  
Sensing Applications ◽  
Wide Range ◽  
Precision Viticulture

High spatial ground resolution and highly flexible and timely control due to reduced planning time are the strengths of unmanned aerial vehicle (UAV) platforms for remote sensing applications. These characteristics make them ideal especially in the medium–small agricultural systems typical of many Italian viticulture areas of excellence. UAV can be equipped with a wide range of sensors useful for several applications. Numerous assessments have been made using several imaging sensors with different flight times. This paper describes the implementation of a multisensor UAV system capable of flying with three sensors simultaneously to perform different monitoring options. The intra-vineyard variability was assessed in terms of characterization of the state of vines vigor using a multispectral camera, leaf temperature with a thermal camera and an innovative approach of missing plants analysis with a high spatial resolution RGB camera. The normalized difference vegetation index (NDVI) values detected in different vigor blocks were compared with shoot weights, obtaining a good regression (R2 = 0.69). The crop water stress index (CWSI) map, produced after canopy pure pixel filtering, highlighted the homogeneous water stress areas. The performance index developed from RGB images shows that the method identified 80% of total missing plants. The applicability of a UAV platform to use RGB, multispectral and thermal sensors was tested for specific purposes in precision viticulture and was demonstrated to be a valuable tool for fast multipurpose monitoring in a vineyard.

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.

scholarly journals Establishement of a national monitoring program based on environmental DNA for amphibians and the chytrid fungus Batrachochytrium dendrobatidis     

2021 ◽  
Vol 4 ◽  
Author(s):  
Omneya Osman ◽  
Johan Andersson ◽  
Tomas Larsson ◽  
Mats Töpel ◽  
Alexander Eiler
Keyword(s):  
Batrachochytrium Dendrobatidis ◽  
National Level ◽  
Monitoring Program ◽  
12S Rrna ◽  
Rrna Gene ◽  
Chytrid Fungus ◽  
Rana Arvalis ◽  
Amphibian Species ◽  
National Monitoring ◽  
Wide Range

National monitoring programs provide the basis for evaluating the integrity of ecosystems, their responses to disturbances, and the success of actions taken to conserve or recover biodiversity. In this study, we successfully established a national program for the invasive chytrid fungus Batrachochytrium dendrobatidis (Bd) based on dual TaqMan assays. Amphibian diversity based on metabarcoding of the mitochondrial 12S rRNA gene was also performed. Assays were optimized for sensitive detection of target species from a wide range of amphibian ponds with variable potential of inhibitions for eDNA based detection. An amphibian mock community of 5 species was used to validate the metabarcoding approach while internal standards were used in the case of the dual TaqMan assays. First sampling of over 170 ponds in Norway resulted in Bd detection in 12 environmental samples and one swab sample taken over multiple years indicating the establishment of Bd in Norway. Five amphibian species Bufo bufo, Lissotriton vulgaris, Triturus cristatus, Rana arvalis and Rana temporaria as predicted from data in long-term citizen science reporting systems were widely detected in the collected eDNA samples. Our large scale-monitoring program indicates a low risk of a Bd outbreak and amphibian decline caused by chytridiomycosis but continued monitoring is recommended in the future. These findings indicate that eDNA is an effective method to detect invasive species, and to monitor endangered amphibian species. Still, several shortcomings (such as PCR inhibitors and sample volume) were identified that need to be addressed to improve eDNA-based monitoring at the national level.

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