Covariance modelling and inference for multivariate discrete data in ecology

In this thesis we use discrete copulas to develop novel methods to model multivariate abundance data in ecology. These data, which consist of measures of abundance for many species at a set of sites, occur naturally in ecological sampling. Multivariate abundance data are therefore very common, but also challenging to analyse. The responses are discrete and sparse, with many variables relative to sample size. We propose the use of Gaussian copulas, combined with covariance modelling, to create flexible models for multivariate abundance data that take the aforementioned properties into account. Copulas are not commonly used in ecology, but are well suited to modelling multivariate abundance data due to their flexibility. The modelling framework we propose extends the flexibility of copulas further, by combining any set of discrete or continuous response distributions, with any covariance modelling algorithm designed for Gaussian data. We first propose a novel estimation method for such models, and explore the use of these models to study patterns in correlation between species, using covariance modelling techniques. Then we introduce a tool to visualise species interactions using copula Gaussian graphical models. We demonstrate this on a large dataset of New Zealand native forest species, where we are able to uncover known species relationships as well as generate new hypotheses for how species interact. We then use Gaussian copula models to carry out marginal inference. In particular, when it comes to marginal hypothesis testing and model selection, the likelihood based inference implemented with Gaussian copulas has several advantages over the commonly used approach based on generalised estimating equations

A New Approach to Evaluation of University Teaching Considering Heterogeneity of Students’ Preferences

AbstractStudents’ evaluations of teaching are increasingly used by universities to evaluate teaching performance. However, these evaluations are controversial mainly due to fact that students value various aspects of excellent teaching differently. Therefore, in this paper we propose a new approach to student evaluation of university teaching based on data from conjoint analysis. Conjoint analysis is a multivariate technique used to analyze the structure of individuals’ preference. In particular, our approach accounts for different importance students attach to various aspects of teaching. Moreover, it accounts explicitly for heterogeneity arising from student preferences, and incorporates it to form comprehensive teaching evaluation score. We have conducted survey and confirmed applicability and efficiency of the proposed approach

A general algorithm for covariance modeling of discrete data

We propose an algorithm that generalizes to discrete data any given covariance modeling algorithm originally intended for Gaussian responses, via a Gaussian copula approach. Covariance modeling is a powerful tool for extracting meaning from multivariate data, and fast algorithms for Gaussian data, such as factor analysis and Gaussian graphical models, are widely available. Our algorithm makes these tools generally available to analysts of discrete data and can combine any likelihood-based covariance modeling method for Gaussian data with any set of discrete marginal distributions. Previously, tools for discrete data were generally specific to one family of distributions or covariance modeling paradigm, or otherwise did not exist. Our algorithm is more flexible than alternate methods, takes advantage of existing fast algorithms for Gaussian data, and simulations suggest that it outperforms competing graphical modeling and factor analysis procedures for count and binomial data. We additionally show that in a Gaussian copula graphical model with discrete margins, conditional independence relationships in the latent Gaussian variables are inherited by the discrete observations. Our method is illustrated with a graphical model and factor analysis on an overdispersed ecological count dataset of species abundances

Metabolic Syndrome and C-reactive protein in patients with depressive disorder on antidepressive medication

Introduction Recurrent depression is a psychiatric disorder of which etiology and pathogenesis might be related to immune response. Metabolic Syndrome (MetS) and its components are also strongly associated with elevated inflammatory indicators, as so as the body mass index (BMI) and total cholesterol levels. Objective Objective of this study was to investigate if there was any difference in C-reactive protein (CRP) levels in patients with recurrent depressive disorder, treated with antidepressants, compared to a healthy control group of subjects and if there was an association between increased CRP levels and the presence of MetS in these two groups. Methods Sixty subjects entered the study; of these 35 patients with the diagnosis of recurrent depressive disorder, while the healthy control group included 25 subjects. MetS was defined according to the NCEP ATP III criteria. The cut-off point for CRP was set at >5 mg /L. Results There was no statistically significant difference in the prevalence of MetS and CRP values between the studied groups. Waist circumference and total cholesterol levels were significantly higher in the experimental group. Patients that fulfilled the criteria for MetS showed significantly higher values of central obesity and arterial hypertension in the experimental group as well. The elevated CRP levels were associated with increased frequency of MetS in depressed patients. Conclusion Both CRP levels and metabolic risk profile screening, according to the international criteria, may be beneficial in order to obtain better assessment for depressive long term medicated patients

Procena trofičkog statusa akumulacije očaga (Lazarevac, Srbija) posredstvom Carlsonovog indeksa

Trofički status se može definisati kao ukupna težina živog biološkog materijala (biomase) u nekom vodenom telu na određenom lokalitetu i u određeno vreme. Trofički status nekog vodenog tela može se proceniti na osnovu merenja specifičnih parametara i predstavlja biološki odgovor na spoljašnje faktore, kao što su količina nutrijenata, sezonske promene, ispaša, mešanje vode itd. Procena trofičkog statusa jezera ili akumulacije je od velikog značaja. Postoje različiti kriterijumi za procenu trofičkog stanja jezera, kao što su: koncentracija nutrijenata, produktivnost, kvantitativni i kvalitativni sastav flore i faune, dostupnost kiseonika i morfometrija jezera. Međutim, imajući u vidu da je multiparametarski indeks nepraktičan, Carlson je predložio indekse trofičkog stanja (TSIs) koji su znatno jednostavniji za upotrebu od multiparametarskog indeksa. Ovi indeksi kao bazu za klasifikaciju trofičkih stanja koriste algalnu biomasu. U tom smislu koriste se tri parametra za izračunavanje ovih indeksa: koncentracija hlorofila a, ukupni fosfor i providnost izmerena Secchi diskom. Svaka od ove tri promenljive se može koristiti za klasifikaciju statusa vodenog tela, ali je hlorofila a najznačajniji parametar s obzirom da je direktni pokazatelj algalne biomase. Opseg Carlson-ovog trofičnog indeksa obuhvata vrednosti od 0 do 100. Vrednosti ispod 40 odgovaraju oligotrofnim, od 40 do 50 mezotrofnim, od 50 do 70 eutrofnim, a preko 70 hipereutrofnim jezerima i akumulacijama. Glavna prednost ovog indeksa je što odnos između tri parametra može ukazati na određene uslove koji vladaju u datom jezeru ili akumulaciji, a tiču se faktora koji limitiraju algalnu biomasu ili utiču na izmerene parametre. Iako određivanje trofičkog statusa vode nekog vodenog tela ne treba poistovećivati sa samim kvalitetom vode, ono, svakako, predstavlja značajan aspekt istog. Cilj ovog istraživanja bio je određivanje trofičkog statusa jezera Očaga na osnovu Carlson-ovog trofičnog indeksa i ispitivanje veze između izračunatih indeksa za hlorofil a (TSI(CHL)), ukupni fosfor (TSI(TP)) i providnost merenu Secchi diskom (TSI(SD)). Veštačko jezero Očaga nalazi se u blizini Lazarevca i isključivo se koristi za rekreaciju. Ispitivanje vode rađeno je jednom nedeljno tokom jula i avgusta, od 2012. do 2014. godine. Sve analize urađene su u Zavodu za javno zdravlje iz Beograda. Vrednosti dobijenih indeksa (TSIs) varirale su od 41 do 86.25, u ispitanom periodu, a jezero je menjalo status od mezotrofnog, preko eutrofnog do hipereutrofnog, pri čemu su eutrofni uslovi preovladavali. Hipereutrofija je zabeležena tokom avgusta 2013. Godine, kada su bile izmerene i najveće vrednosti sva tri parametra, što je, verovatno, rezultat organskog opterećenja vodenog ekosistema i vremenskih uslova. Prema podacima RHMZ-a, 2013. godina je bila jedna od najtoplijih i najsušnijih godina još od 1951. godine. Nasuprot tome, u avgustu 2014. godine izmerene su najmanje vrednosti svih parametara, što ukazuje na mezotrofne uslove u jezeru te godine. Mezotrofni status jezera je, verovatno, posledica velike količine padavina u prvoj polovini te godine, ali i pražnjenja i ponovnog punjenja jezera nakon majskih poplava

Gamma-Glutamyltransferase and C-Reactive Protein in Stable Chronic Obstructive Pulmonary Disease

Systemic inflammation and oxidative stress are the most important features of chronic obstructive pulmonary disease (COPD). The presence of oxidative stress in the airways of smokers, the largest population of COPD patients, is a consequence of direct inhalation of cigarette smoke and increased inflammation-related production of reactive oxygen species. On the other hand, oxidative stress appears to be the key component of many processes associated with chronic inflammation. We intend to examine whether serum C-reactive protein (CRP) concentration and gamma-glutamyltransferase (GGT) activity might be used as auxiliary markers in monitoring level of oxidative stress and inflammation in clinically stable COPD. We also investigated influence of cigarette smoking on these two systemic parameters. Catalytic activity of GGT and concentration of CRP were determined in sera of COPD patients (N=109) and in healthy controls (N=51) by using standard spectrophotometric method and immunoturbidimetric method, respectively. Concentration of CRP and activity of GGT were increased in COPD patients, as compared to healthy controls (p<0.05). We found a significant positive correlation between those two parameters in COPD patients (r=0.202, p=0.0371). Our results showed no difference in GGT activity (p=0.606) or CRP concentration (p=0.573) between groups of patients when subdivided according to the severity of the disease. Smoking did not have a significant impact on CRP and GGT values in COPD patients and healthy controls. We showed an increase of serum CRP and GGT values in COPD patients, and we suggest that serum GGT activity might also represent an inflammation/oxidative stress marker. It seems that COPD patients present higher serum CRP and GGT values than healthy subjects independently from their smoking habits

Supplementary data for article: Tasić, G.; Simić, M. R.; Popovic, S.; Husinec, S.; Maslak, V.; Savić, V. Indirect N-Vinylation of Indoles via Isomerisation of N-Allyl Derivatives: Synthesis of (+/-)-Debromoarborescidine B. Tetrahedron Letters 2013, 54 (34), 4536–4539. https://doi.org/10.1016/j.tetlet.2013.06.069

Supplementary material for: [https://doi.org/10.1016/j.tetlet.2013.06.069]Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/1382

Untangling direct species associations from indirect mediator species effects with graphical models

Ecologists often investigate co‐occurrence patterns in multi‐species data in order to gain insight into the ecological causes of observed co‐occurrences. Apart from direct associations between the two species of interest, they may co‐occur because of indirect effects, where both species respond to another variable, whether environmental or biotic (e.g. a mediator species). A wide variety of methods are now available for modelling how environmental filtering drives species distributions. In contrast, methods for studying other causes of co‐occurence are much more limited. “Graphical” methods, which can be used to study how mediator species impact co‐occurrence patterns, have recently been proposed for use in ecology. However, available methods are limited to presence/absence data or methods assuming multivariate normality, which is problematic when analysing abundances. We propose Gaussian copula graphical models (GCGMs) for studying the effect of mediator species on co‐occurence patterns. GCGMs are a flexible type of graphical model which naturally accommodates all data types, for example binary (presence/absence), counts, as well as ordinal data and biomass, in a unified framework. Simulations demonstrate that GCGMs can be applied to a much broader range of data types than the methods currently used in ecology, and perform as well as or better than existing methods in many settings. We apply GCGMs to counts of hunting spiders, in order to visualise associations between species. We also analyse abundance data of New Zealand native forest cover (on an ordinal scale) to show how GCGMs can be used analyse large and complex datasets. In these data, we were able to reproduce known species relationships as well as generate new ecological hypotheses about species associations.F.K.C.H. is supported by an ANU cross‐disciplinary research grant. D.I.W. was supported by an Australian Research Council Future Fellowship (FT120100501). G.C.P. was supported by the Australia Postgraduate Award and ARC Discovery Project scheme (DP180103543). A.T.M. is supported by an Australia Research Council Discovery Grant (DP180100836). F.J.T. is supported from the Marsden Fast‐Start Fund and the Royal Society of New Zealand

Uticaj međuredne kultivacije i vremena osnovne obrade zemljišta na prinos soje

Timely and correct application of agro technical measures in the production of soybean is a condition for obtaining high and stable yields, both in favorable years and in unfavorable years for production. The aim of this research is to examine the influence of interrelated cultivation and the time of basic soil treatment on soybean yield. One intermediate cultivation increases the yield by an average of 2.45%, by 2.08% for autumn cultivation and 2.82% for spring basic land cultivation. Two intercropping cultivars increase the average yield by 3.54%, by 2.59% for autumn harvesting and 4.49% for spring basic soil cultivation. Spring ground cultivation reduced the yield of 21.33%, and the decrease ranged from 6.45% in favorable year, to 36.21% in the unfavorable year for soybean production.Pravovremena i pravilna primena agrotehničkih mera u proizvodnji soje je uslov za dobijanje visokih i stabilnih prinosa, kako u povoljnim godinama, tako i u nepovoljnim godinama za proizvodnju. Cilj ovih istraživanja je sagledavanje uticaja međuredne kultivacije i vremena osnovne obrade zemljišta na prinos soje. Jedna međuredna kultivacija povećava prinos u proseku za 2,45% i to za 2,08% kod jesenje osnovne obrade i 2,82% kod prolećne osnovne obrade zemljišta. Dve međuredne kultivacije povećavaju prinos soje u proseku za 3,54% i to za 2,59% kod jesenje osnovne obrade i 4,49% kod prolećne osnovne obrade zemljišta. Prolećna osnovna obrada zemljišta smanjuje prinos 21,33%, a smanjenje se kretalo od 6,45% u povoljnoj godini, do 36,21% u nepovoljnoj godini za proizvodnju soje