Abundance-based approaches

2021 ◽  
pp. 133-150
Author(s):  
Jonas Knape ◽  
Andreas Lindén
Keyword(s):  
Growth Models ◽  
Demographic Data ◽  
Additive Models ◽  
State Space Models ◽  
Abundance Data ◽  
Wide Range ◽  
Demographic Processes ◽  
Auto Regressive ◽  
Regression Techniques ◽  
Dynamics Of Populations

Across a wide range of different organisms, abundance data form one of the backbones for understanding the dynamics of populations. This type of data consists of measures of population size over time or space in the form of numbers of individuals, biomass, areal cover, or other measures. Abundance data contain no direct information about demographic processes but are available at larger scales or higher resolution in space and time than direct demographic data. This chapter introduces some of the basic statistical modeling strategies that can be used to learn about populations from abundance data in the absence of information about demographic details. These strategies include standard but flexible regression techniques, including mixed and additive models, time-series methods such as auto-regressive and state-space models, as well as simple population growth models derived from ecological theory.

scholarly journals Non-contact vital-sign monitoring of patients undergoing haemodialysis treatment

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mauricio Villarroel ◽  
João Jorge ◽  
David Meredith ◽  
Sheera Sutherland ◽  
Chris Pugh ◽  
...  
Keyword(s):  
Heart Rate ◽  
Respiratory Rate ◽  
Reference Values ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Recording Time ◽  
Wide Range ◽  
Auto Regressive ◽  
The Mean ◽  
Haemodialysis Treatment

Abstract A clinical study was designed to record a wide range of physiological values from patients undergoing haemodialysis treatment in the Renal Unit of the Churchill Hospital in Oxford. Video was recorded for a total of 84 dialysis sessions from 40 patients during the course of 1 year, comprising an overall video recording time of approximately 304.1 h. Reference values were provided by two devices in regular clinical use. The mean absolute error between the heart rate estimates from the camera and the average from two reference pulse oximeters (positioned at the finger and earlobe) was 2.8 beats/min for over 65% of the time the patient was stable. The mean absolute error between the respiratory rate estimates from the camera and the reference values (computed from the Electrocardiogram and a thoracic expansion sensor—chest belt) was 2.1 breaths/min for over 69% of the time for which the reference signals were valid. To increase the robustness of the algorithms, novel methods were devised for cancelling out aliased frequency components caused by the artificial light sources in the hospital, using auto-regressive modelling and pole cancellation. Maps of the spatial distribution of heart rate and respiratory rate information were developed from the coefficients of the auto-regressive models. Most of the periods for which the camera could not produce a reliable heart rate estimate lasted under 3 min, thus opening the possibility to monitor heart rate continuously in a clinical environment.

scholarly journals Knowledge and attitude of Iraqi pharmacists in Baghdad community toward ‎adverse drug reactions monitoring

2017 ◽  
Vol 10 (4) ◽  
pp. 219
Author(s):  
Samer Imad Mohammed ◽  
Amna Fouad Abdul Al-razaq
Keyword(s):  
Adverse Drug Reactions ◽  
Demographic Data ◽  
Monitoring Program ◽  
Drug Reactions ◽  
Pv System ◽  
Cross Sectional ◽  
Convenience Sample ◽  
Herbal Products ◽  
High Tendency ◽  
Wide Range

Objectives:Adverse drug reactions (ADR‎s) can lead to many complications associated with the use of medications .In Iraq where a wide range of medications misused widely due to different reasons, the Iraqi pharmacovigilance program started out few years ago to collect information about adverse drugs reactions and since the success of this program depends on the effective participation of all medical staffs including pharmacists in this program. This study aimed to assess the knowledge, attitude, and degree of awareness of Iraqi pharmacists in Baghdad community toward adverse drugs reactions monitoring and pharmacovigilance program.Methods: This study was a cross-sectional descriptive survey based on individual questionnairethat administered in the English language to a convenience sample of 150 pharmacists working in 3 colleges of pharmacy, 20 community pharmacies and 3 hospitals situated in different areas of Baghdad which are the capital of Iraq. The questionnaire consists of three parts that collect demographic data on the ‎participants and their knowledge, attitudes toward Pharmacovigilance‎. Results: Although about (62%) of pharmacists have observed ADRs in their practice‎ only half of the respondents have heard about the term pharmacovigilance, 48% were aware of the national PV program ‎‎.Moreover , (‎47.33%‎) of the respondents mentioned that ADRs associated with herbal ‎products should not be reported. Although ‎79% of the respondents thought that reporting ADRs is a pharmacist’s duty nevertheless 82% of them  ‎thought that ADRs reporting in Iraq is not widely promoted by the relevant authority .The study showed a high tendency for participation in an adverse drug reaction  monitoring program. Interestingly,‎ 60% of respondents report that their workplace ‎doesn’t encourage them for reporting ADRs, while 48% of respondents indicated that they don’t ‎have enough time for reporting ADRs and 38% of them declared their fearing of facing ‎legal problem from that .  ‎Conclusion: Iraqi pharmacists although have a high tendency in participation in ADR monitoring  program but have  a poor knowledge about pharmacovigilance practices; they lack ‎understanding of the details about the national PV system and ADRs ‎reporting process and may need more information on how ADRs ‎reporting are performed. Keywords: Knowledge, Attitudes, Adverse drug reactions, Pharmacovigilance.

scholarly journals Proposals for Nothofagus antarctica diameter growth estimation: simple vs. global models

2014 ◽  
Vol 60 (No. 8) ◽  
pp. 307-317 ◽  
Author(s):  
H. Ivancich ◽  
G.J. Martínez Pastur ◽  
M.V. Lencinas ◽  
J.M. Cellini ◽  
P.L. Peri
Keyword(s):  
Tree Growth ◽  
Growth Models ◽  
Site Quality ◽  
Diameter Growth ◽  
Wide Range ◽  
Nothofagus Antarctica ◽  
Simple Growth ◽  
Simple Equations ◽  
Diameter Growth Models ◽  
Stand Conditions

Tree growth is one of the main variables needed for forest management planning. The use of simple models containing traditional equations to describe tree growth is common. However, equations that incorporate different factors (e.g. site quality of the stands, crown classes of the trees, silvicultural treatments) may improve their accuracy in a wide range of stand conditions. The aim of this work was to compare the accuracy of tree diameter growth models using (i) a family of simple equations adjusted by stand site quality and crown class of trees, and (ii) <br /> a unique global equation including stand and individual tree variables. Samplings were conducted in 136 natural even-aged Nothofagus antarctica (Forster f.) Oersted stands in Southern Patagonia (Argentina) covering age (20&ndash;200 years), <br /> crown class and site quality gradients. The following diameter growth models were fitted: 16 simple equations using two independent variables (age and one equation for each stand site quality or crown class) based on Richards model, plus a unique global equation using three independent variables (age, stand site quality and crown class). Simple equations showed higher variability in their accuracy, explained between 54% and 92% of the data variation. The global model presented similar accuracy like the better equations of the simple growth models. The unification of the simple growth models into a unique global equation did not greatly improve the accuracy of estimations, but positively influenced the biological response of the model. Another advantage of the global equation is the simple use under a wide range of natural stand conditions. The proposed global model allows to explain the tree growth of N. antarctica trees along the natural studied gradients. &nbsp; &nbsp;

Testing across vegetation types for common environmental dependencies of Gross Primary Production

2020 ◽  
Author(s):  
Keith Bloomfield ◽  
Benjamin Stocker ◽  
Colin Prentice
Keyword(s):  
Soil Moisture ◽  
Primary Production ◽  
Eddy Covariance ◽  
Empirical Analysis ◽  
Gross Primary Production ◽  
Incident Light ◽  
Vapour Pressure Deficit ◽  
Additive Models ◽  
Theoretical Modelling ◽  
Wide Range

&lt;p&gt;Accurate simulations of gross primary production (GPP) are vital for Earth System Models that must inform public policy decisions. &amp;#160;The instantaneous controls of leaf-level photosynthesis, which can be measured in manipulative experiments, are well established. &amp;#160;At the canopy scale, however, there is no consensus on how GPP depends on (a) light or (b) other aspects of the physical environment such as temperature and CO&lt;sub&gt;2&lt;/sub&gt;. &amp;#160;Models of GPP make a variety of different assumptions when &amp;#8216;scaling-up&amp;#8217; the standard model of photosynthesis. &amp;#160;As a troublesome consequence, they make a variety of different predictions about how GPP responds to contemporary environmental change.&lt;/p&gt;&lt;p&gt;This problem can be tackled by theoretically based modelling, or by empirical analysis of GPP as reconstructed from eddy-covariance flux measurements. &amp;#160;Theoretical modelling has provided an explanation for why &amp;#8216;light-use efficiency&amp;#8217; (LUE) models work well at time scales of a week or longer. &amp;#160;The same logic provides a justification for the use of LUE as a key metric in an empirical analysis. &amp;#160;By focusing on LUE, we can isolate the controls of GPP that are distinct from its over-riding control by absorbed light. &amp;#160;We have used open-access eddy covariance data from over 100 sites, collated over 20 years (the number of sites has grown with time). &amp;#160;These sites, located in a wide range of biomes and climate zones, form part of the FLUXNET network. &amp;#160;We have combined the flux data with a satellite product (FPAR from MODIS) that provides spatial estimates of the fraction of incident light absorbed by green vegetation. &amp;#160;Soil moisture at flux sites was estimated using the SPLASH model, with appropriate meteorological inputs, and soil water-holding capacity derived using SoilGrids. &amp;#160;LUE was then calculated as the amount of carbon fixed per unit of absorbed light. &amp;#160;We then considered additive models (incorporating multiple explanatory factors) that support non-linear responses, including a peaked response to temperature. &amp;#160;Recognising that our longitudinal data are not fully independent, we controlled for the hierarchical nature of the dataset through a variance structure that nests measurement year within site location.&lt;/p&gt;&lt;p&gt;In arriving at a final parsimonious model, we show that daytime air temperature and vapour pressure deficit, and soil moisture content, are all salient predictors of LUE. &amp;#160;The same explanatory terms are retained in iterations of this analysis run at timescales from weeks to months. &amp;#160;Model performance was not significantly improved by inclusion of additional variables such as rainfall, site elevation or vegetation category (e.g. Plant Functional Type, PFT). &amp;#160;This empirical analysis supports the notion that GPP is predictable using a single model structure that is common to different PFTs.&lt;/p&gt;

Variation in plasticity within the S. 23 cultivar of Lolium perenne L.

1975 ◽  
Vol 85 (1) ◽  
pp. 111-121 ◽  
Author(s):  
J. Valentine ◽  
A. H. Charles
Keyword(s):  
Phenotypic Plasticity ◽  
Lolium Perenne ◽  
Dry Matter ◽  
Controlled Growth ◽  
Nitrogen Application ◽  
Lolium Perenne L ◽  
N Level ◽  
Wide Range ◽  
Growth Room ◽  
Regression Techniques

SUMMARYThe S. 23 cultivar of Lolium perenne L. has the ability to perform well in a wide range of environments and an experiment was designed to examine the phenotypic plasticity of S. 23 genotypes with particular reference to the level of nitrogen application.Genotypes of S. 23 grown in a controlled growth room at close spacing (5 cm) showed a wide range of dry-matter yields with the highest yielding 144 times that of the lowest at the last of six cuts taken at 4-week intervals. Genotypes maintained much the same order of yield from one nitrogen level to another, but there were exceptions. Regression techniques were used to further quantify genotype-environment behaviour and to measure response to the environment in which the plants were grown. Considerable variation in this character occurred and the correlation of mean yield and response was incomplete. Some of the genotypes combined the desirable characters of high mean yield and good response to improved environments, while others had high mean yields, but were not as well adapted to the highest N level.In the experiment no significant effects could be traced to differences in age of seed, but plants which had been maintained vegetatively for 7 years showed reduced vigour.

scholarly journals Founder Mutation for a-sarcoglycan-LGMD2D in a Magdalen Islands Acadian Cluster

2011 ◽  
Vol 38 (5) ◽  
pp. 747-752 ◽  
Author(s):  
M. Tétreault ◽  
M. Srour ◽  
J. Allyson ◽  
I. Thiffault ◽  
L. Loisel ◽  
...  
Keyword(s):  
Founder Mutation ◽  
Demographic Data ◽  
Homozygosity Mapping ◽  
Childhood Onset ◽  
Genome Wide ◽  
Wide Range ◽  
Progression Of Disease ◽  
High Carrier ◽  
Progressive Weakness ◽  
Magdalen Islands

ABSTRACT:Background:We have recruited a group of four living and reviewed the records of six deceased distantly related French-Canadians of Acadian descent affected by a childhood-onset form of recessive limb-girdle muscular dystrophy (LGMD). All cases originate from the small archipelago of the Magdalen Islands (population: 13,000) isolated in the Gulf of St-Lawrence.Methods:Based on the likely sharing of the same founder mutation we completed a 319K SNPs genome-wide scan to identify the disease locus and then screen candidate genes in this region.Results:All patients had normal initial motor milestones. They presented with limb girdle weakness at the average age of seven years (5-11). Progressive weakness led to loss of ambulation at a wide range of ages (10-39). Patients also developed macroglossia, large calves and mild to moderate contractures, hyperlordosis and decreased pulmonary function. Creatine kinase levels were elevated (1,800-10,000 U/L) in the first decades, but decreased with progression of disease. Homozygosity mapping uncovered a shared chromosomal region of 6.33Mb. The alpha sarcoglycan (SGCA) gene, mutated in LGMD2D, lay in this candidate interval. Sequencing of all SGCA exons uncovered a shared homozygous missense mutation (c.229C>T, p.R77C), the most common SGCA mutation internationally reported. Using demographic data, we estimated a high carrier rate of 1/22.Conclusion:The p.R77C mutation has also been observed in many populations, including in France and Spain (Basques). This corresponds to the first reported recessive founder disease for the Magdalen Islands, an archipelago settled in the XlXth century, largely by Acadian immigrants.

scholarly journals ПІДГОТОВКА МАЙБУТНІХ СОЦІОЛОГІВ ДО КОМП’ЮТЕРНОГО АНАЛІЗУ ДЕМОГРАФІЧНИХ ПРОЦЕСІВ І СТРУКТУР

2018 ◽  
Vol 65 (3) ◽  
pp. 166
Author(s):  
Liubov F. Panchenko
Keyword(s):  
Graphical Representation ◽  
Demographic Data ◽  
Practical Application ◽  
Population Pyramid ◽  
Computer Tools ◽  
Modern Computer ◽  
Age Pyramid ◽  
Demographic Processes ◽  
Independent Work ◽  
Modern Era

In the modern era of digital globalization, it is becoming more and more important to train sociology students in the field of demographics and demographic statistics based not only on demographic theories but also on the practical application of the new computer tools and technologies, databases and Internet services. The article analyzes the capabilities of modern computer tools for the analysis of demographic processes and structures in training sociology students; substantiates the use of the R environment as a tool for analysis and graphical representation of demographic data. It presents the idea of teaching students to perform computer analysis of demographic data using a combination of Excel spreadsheets, SPSS statistical package, R environment illustrated by two examples. The first example concerns building and comparing the gender-age pyramid of the population of Ukraine at different years and includes searching for the relevant data, building the pyramid using standard diagram building Excel tools, using SPSS tools (Chart Builder, Histogram, Population Pyramid), and using pyramid package of R environment. The second example relates to calculation of childcare and grandparent care load coefficients, visualizing their dynamics, and includes an introduction to the demographic passport of Ukraine. The article presents the developed methodological support for teaching sociology students to perform demographic data analysis, including presentation-lectures on the fundamental principles of work in R and R Studio environment, laboratory works (theory summary, detailed operative instructions, control questions, tasks for students ‘ independent work); data packages attached to every assignment. The author has analyzed the didactic capabilities of the free Gapminder service that includes the list of the tools titled `Play with Data`, bubble chart, maps, ranking, trends, age pyramids. This provides colorful and dynamic data visualization for chosen demographic criteria (depending on the research objectives) by countries and continents over time that stimulates the students to conduct additional scientific research.

scholarly journals A Size-Perimeter Discrete Growth Model for Percolation Clusters

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Bendegúz Dezső Bak ◽  
Tamás Kalmár-Nagy
Keyword(s):  
Growth Model ◽  
Branching Process ◽  
Growth Models ◽  
Square Lattice ◽  
Cluster Growth ◽  
Invasion Percolation ◽  
Percolation Clusters ◽  
Proposed Model ◽  
Wide Range ◽  
The Mean

Cluster growth models are utilized for a wide range of scientific and engineering applications, including modeling epidemics and the dynamics of liquid propagation in porous media. Invasion percolation is a stochastic branching process in which a network of sites is getting occupied that leads to the formation of clusters (group of interconnected, occupied sites). The occupation of sites is governed by their resistance distribution; the invasion annexes the sites with the least resistance. An iterative cluster growth model is considered for computing the expected size and perimeter of the growing cluster. A necessary ingredient of the model is the description of the mean perimeter as the function of the cluster size. We propose such a relationship for the site square lattice. The proposed model exhibits (by design) the expected phase transition of percolation models, i.e., it diverges at the percolation threshold p c . We describe an application for the porosimetry percolation model. The calculations of the cluster growth model compare well with simulation results.

scholarly journals Introducing a drift and diffusion framework for childhood growth research

2020 ◽  
Vol 4 ◽  
pp. 71
Author(s):  
Fraser I Lewis ◽  
Godfrey Guga ◽  
Paschal Mdoe ◽  
Esto Mduma ◽  
Cloupas Mahopo ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Population Level ◽  
Child Growth ◽  
Additive Models ◽  
Growth Trajectories ◽  
Trajectory Data ◽  
Childhood Growth ◽  
Individual Level ◽  
Wide Range ◽  
And Diffusion

Background: Growth trajectories are highly variable between children, making epidemiological analyses challenging both to the identification of malnutrition interventions at the population level and also risk assessment at individual level. We introduce stochastic differential equation (SDE) models into child growth research. SDEs describe flexible dynamic processes comprising: drift - gradual smooth changes – such as physiology or gut microbiome, and diffusion - sudden perturbations, such as illness or infection. Methods: We present a case study applying SDE models to child growth trajectory data from the Haydom, Tanzania and Venda, South Africa sites within the MAL-ED cohort. These data comprise n=460 children aged 0-24 months. A comparison with classical curve fitting (linear mixed models) is also presented. Results: The SDE models offered a wide range of new flexible shapes and parameterizations compared to classical additive models, with performance as good or better than standard approaches. The predictions from the SDE models suggest distinct longitudinal clusters that form distinct ‘streams’ hidden by the large between-child variability. Conclusions: Using SDE models to predict future growth trajectories revealed new insights in the observed data, where trajectories appear to cluster together in bands, which may have a future risk assessment application. SDEs offer an attractive approach for child growth modelling and potentially offer new insights.

scholarly journals NetGAM: Using generalized additive models to improve the predictive power of ecological network analyses constructed using time-series data

2021 ◽  
Author(s):  
Samantha J Gleich ◽  
Jacob A Cram ◽  
Jake L Weissman ◽  
David A Caron
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Species Abundance ◽  
Covariance Structure ◽  
Additive Models ◽  
Series Data ◽  
Ecological Network ◽  
Network Analyses ◽  
Abundance Data ◽  
Species Abundance Data

Ecological network analyses are used to identify potential biotic interactions between microorganisms from species abundance data. These analyses are often carried out using time-series data; however, time-series networks have unique statistical challenges. Time-dependent species abundance data can lead to species co-occurrence patterns that are not a result of direct, biotic associations and may therefore result in inaccurate network predictions. Here, we describe a generalize additive model (GAM)-based data transformation that removes time-series signals from species abundance data prior to running network analyses. Validation of the transformation was carried out by generating mock, time-series datasets, with an underlying covariance structure, running network analyses on these datasets with and without our GAM transformation, and comparing the network outputs to the known covariance structure of the simulated data. The results revealed that seasonal abundance patterns substantially decreased the accuracy of the inferred networks. Additionally, the GAM transformation increased the F1 score of inferred ecological networks on average and improved the ability of network inference methods to capture important features of network structure. This study underscores the importance of considering temporal features when carrying out network analyses and describes a simple, effective tool that can be used to improve results.

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