12 resultados para Multivariate Linkage Analysis

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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The present PhD thesis was focused on the development and application of chemical methodology (Py-GC-MS) and data-processing method by multivariate data analysis (chemometrics). The chromatographic and mass spectrometric data obtained with this technique are particularly suitable to be interpreted by chemometric methods such as PCA (Principal Component Analysis) as regards data exploration and SIMCA (Soft Independent Models of Class Analogy) for the classification. As a first approach, some issues related to the field of cultural heritage were discussed with a particular attention to the differentiation of binders used in pictorial field. A marker of egg tempera the phosphoric acid esterified, a pyrolysis product of lecithin, was determined using HMDS (hexamethyldisilazane) rather than the TMAH (tetramethylammonium hydroxide) as a derivatizing reagent. The validity of analytical pyrolysis as tool to characterize and classify different types of bacteria was verified. The FAMEs chromatographic profiles represent an important tool for the bacterial identification. Because of the complexity of the chromatograms, it was possible to characterize the bacteria only according to their genus, while the differentiation at the species level has been achieved by means of chemometric analysis. To perform this study, normalized areas peaks relevant to fatty acids were taken into account. Chemometric methods were applied to experimental datasets. The obtained results demonstrate the effectiveness of analytical pyrolysis and chemometric analysis for the rapid characterization of bacterial species. Application to a samples of bacterial (Pseudomonas Mendocina), fungal (Pleorotus ostreatus) and mixed- biofilms was also performed. A comparison with the chromatographic profiles established the possibility to: • Differentiate the bacterial and fungal biofilms according to the (FAMEs) profile. • Characterize the fungal biofilm by means the typical pattern of pyrolytic fragments derived from saccharides present in the cell wall. • Individuate the markers of bacterial and fungal biofilm in the same mixed-biofilm sample.

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Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.

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Autism is a neurodevelpmental disorder characterized by impaired verbal communication, limited reciprocal social interaction, restricted interests and repetitive behaviours. Twin and family studies indicate a large genetic contribution to ASDs (Autism Spectrum Disorders). During my Ph.D. I have been involved in several projects in which I used different genetic approaches in order to identify susceptibility genes in autism on chromosomes 2, 7 and X: 1)High-density SNP association and CNV analysis of two Autism Susceptibility Loci. The International Molecular Genetic Study of Autism Consortium (IMGSAC) previously identified linkage loci on chromosomes 7 and 2, termed AUTS1 and AUTS5, respectively. In this study, we evaluated the patterns of linkage disequilibrium (LD) and the distribution of haplotype blocks, utilising data from the HapMap project, across the two strongest peaks of linkage on chromosome 2 and 7. More than 3000 SNPs have been selected in each locus in all known genes, as well as SNPs in non-genic highly conserved sequences. All markers have been genotyped to perform a high-density association analysis and to explore copy number variation within these regions. The study sample consisted of 127 and 126 multiplex families, showing linkage to the AUTS1 and AUTS5 regions, respectively, and 188 gender-matched controls. Association and CNV analysis implicated several new genes, including IMMP2L and DOCK4 on chromosome 7 and ZNF533 and NOSTRIN on the chromosome 2. Particularly, my contribution to this project focused on the characterization of the best candidate gene in each locus: On the AUTS5 locus I carried out a transcript study of ZNF533 in different human tissues to verify which isoforms and start exons were expressed. High transcript variability and a new exon, never described before, has been identified in this analysis. Furthermore, I selected 31 probands for the risk haplotype and performed a mutation screen of all known exons in order to identify novel coding variants associated to autism. On the AUTS1 locus a duplication was detected in one multiplex family that was transmitted from father to an affected son. This duplication interrupts two genes: IMMP2L and DOCK4 and warranted further analysis. Thus, I performed a screening of the cohort of IMGSAC collection (285 multiplex families), using a QMPSF assay (Quantitative Multiplex PCR of Short fluorescent Fragments) to analyse if CNVs in this genic region segregate with autism phenotype and compare their frequency with a sample of 475 UK controls. Evidence for a role of DOCK4 in autism susceptibility was supported by independent replication of association at rs2217262 and the finding of a deletion segregating in a sib-pair family. 2)Analysis of X chromosome inactivation. Skewed X chromosome inactivation (XCI) is observed in females carrying gene mutations involved in several X-linked syndromes. We aimed to estimate the role of X-linked genes in ASD susceptibility by ascertaining the XCI pattern in a sample of 543 informative mothers of children with ASD and in a sample of 164 affected girls. The study sample included families from different european consortia. I analysed the XCI inactivation pattern in a sample of italian mothers from singletons families with ASD and also a control groups (144 adult females and 40 young females). We observed no significant excess of skewed XCI in families with ASD. Interestingly, two mothers and one girl carrying known mutations in X-linked genes (NLGN3, ATRX, MECP2) showed highly skewed XCI, suggesting that ascertainment of XCI could reveal families with X-linked mutations. Linkage analysis was carried out in the subgroup of multiplex families with skewed XCI (≥80:20) and a modest increased allele sharing was obtained in the Xq27-Xq28 region, with a peak Z score of 1.75 close to rs719489. In this region FMR1 and MECP2 have been associated in some cases with austim and therefore represent candidates for the disorder. I performed a mutation screen of MECP2 in 33 unrelated probands from IMGSAC and italian families, showing XCI skewness. Recently, Xq28 duplications including MECP2, have been identified in families with MR, with asymptomatic carrier females showing extreme (>85%) skewing of XCI. For these reason I used the sample of probands from X-skewed families to perform CNV analysis by Real-time quantitative PCR. No duplications have been found in our sample. I have also confirmed all data using as alternative method the MLPA assay (Multiplex Ligation dependent Probe Amplification). 3)ASMT as functional candidate gene for autism. Recently, a possible involvement of the acetylserotonin O-methyltransferase (ASMT) gene in susceptibility to ASDs has been reported: mutation screening of the ASMT gene in 250 individuals from the PARIS collection revealed several rare variants with a likely functional role; Moreover, significant association was reported for two SNPs (rs4446909 and rs5989681) located in one of the two alternative promoters of the gene. To further investigate these findings, I carried out a replication study using a sample of 263 affected individuals from the IMGSAC collection and 390 control individuals. Several rare mutations were identified, including the splice site mutation IVS5+2T>C and the L326F substitution previously reported by Melke et al (2007), but the same rare variants have been found also in control individuals in our study. Interestingly, a new R319X stop mutation was found in a single autism proband of Italian origin and is absent from the entire control sample. Furthermore, no replication has been found in our case-control study typing the SNPs on the ASMT promoter B.

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PROBLEM In the last few years farm tourism or agritourism as it is also referred to has enjoyed increasing success because of its generally acknowledged role as a promoter of economic and social development of rural areas. As a consequence, a plethora of studies have been dedicated to this tourist sector, focusing on a variety of issues. Nevertheless, despite the difficulties of many farmers to orient their business towards potential customers, the contribution of the marketing literature has been moderate. PURPOSE This dissertation builds upon studies which advocate the necessity of farm tourism to innovate itself according to the increasingly demanding needs of customers. Henceforth, the purpose of this dissertation is to critically evaluate the level of professionalism reached in the farm tourism market within a marketing approach. METHODOLOGY This dissertation is a cross-country perspective incorporating the marketing of farm tourism studied in Germany and Italy. Hence, the marketing channels of this tourist sector are examined both from the supply and the demand side by means of five exploratory studies. The data collection has been conducted in the timeframe of 2006 to 2009 in manifold ways (online survey, catalogues of industry associations, face-to-face interviews, etc.) according to the purpose of the research of each study project. The data have been analyzed using multivariate statistical analysis. FINDINGS A comprehensive literature review provides the state of the art of the main differences and similarities of farm tourism in the two countries of study. The main findings contained in the empirical chapters provide insights on many aspects of agritourism including how the expectations of farm operators and customers differ, which development scenarios of farm tourism are more likely to meet individuals’ needs, how new technologies can impact the demand for farm tourism, etc. ORIGINALITY/VALUE The value of this study is in the investigation of the process by which farmers’ participation in the development of this sector intersects with consumer consumption patterns. Focusing on this process should allow farm operators and others including related businesses to more efficiently allocate resources.

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The CL/P are the most common and easily recognizable craniofacial malformations with a complex etiology that requires the involvement of genetic and environmental components. The analysis of the genetic component shows more than 14 loci and genes involved in the onset of the disease. I’ve selected and investigated some of the possible candidate genes for CL/P. MYH14 gene, that maps on chromosome 19, on the OFC3 locus, and shows a strong homology with MYH9 gene. I’ve also investigated TP63 and MID1 genes, that are responsible respectively for EEC syndrome and Opitz syndrome, both of them presenting cleft. I’ve also decided to investigate JAG2 because TP63 product regulates the this gene, and both of them are component of the Notch signalling pathway. I’ve, also, studied the MKX and LMO4 genes. MKX is an important development regulator that is highly expressed in palatal mesenchyme, and map in the region responsible for Twirler mutation that cause cleft in mouse. LMO4 is necessary for neural tube development and cooperating with Grhl3, promotes cellular migration during morphogenetic events like “in utero” cleft healing. Low folate levels and high levels of homocysteine increase the risk of cleft, genes involved in their metabolism may be of interest in cleft occurrence. I’ve decided to investigate BHMT and CBS genes coding for enzymes involved in homocysteine metabolism. I’ve also investigated BHMT2 gene that maps close to BHMT and presents with him a 73% of homology. I’ve performed a linkage analysis using SNPs mapping in the genes and their boundaries, for each gene, for MKX and LMO4 I’ve also performed a sequencing analysis. My results for MID1 and CBS genes support the hypothesis of a possible role of these genes in cleft. I’ve found borderline association values for JAG2, MKX and LMO4 genes.

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The aim of this work is to contribute to the development of new multifunctional nanocarriers for improved encapsulation and delivery of anticancer and antiviral drugs. The work focused on water soluble and biocompatible oligosaccharides, the cyclodextrins (CyDs), and a new family of nanostructured, biodegradable carrier materials made of porous metal-organic frameworks (nanoMOFs). The drugs of choice were the anticancer doxorubicin (DOX), azidothymidine (AZT) and its phosphate derivatives and artemisinin (ART). DOX possesses a pharmacological drawback due to its self-aggregation tendency in water. The non covalent binding of DOX to a series of CyD derivatives, such as g-CyD, an epichlorohydrin crosslinked b-CyD polymer (pb-CyD) and a citric acid crosslinked g-CyD polymer (pg-CyD) was studied by UV visible absorption, circular dichroism and fluorescence. Multivariate global analysis of multiwavelength data from spectroscopic titrations allowed identification and characterization of the stable complexes. pg-CyD proved to be the best carrier showing both high association constants and ability to monomerize DOX. AZT is an important antiretroviral drug. The active form is AZT-triphosphate (AZT-TP), formed in metabolic paths of low efficiency. Direct administration of AZT-TP is limited by its poor stability in biological media. So the development of suitable carriers is highly important. In this context we studied the binding of some phosphorilated derivatives to nanoMOFs by spectroscopic methods. The results obtained with iron(III)-trimesate nanoMOFs allowed to prove that the binding of these drugs mainly occurs by strong iono-covalent bonds to iron(III) centers. On the basis of these and other results obtained in partner laboratories, it was possible to propose this highly versatile and “green” carrier system for delivery of phosphorylated nucleoside analogues. The interaction of DOX with nanoMOFs was also studied. Finally the binding of the antimalarial drug, artemisinin (ART) with two cyclodextrin-based carriers,the pb-CyD and a light responsive bis(b-CyD) host, was also studied.

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INTRODUZIONE Pochi studi in Letteratura hanno indagato la correlazione tra la sintomatologia dolorosa associata all’interruzione farmacologica di gravidanza (IVG) e i livelli d’ansia pre-trattamento. L’obiettivo primario del nostro studio è stato di valutare la correlazione tra la sintomatologia dolorosa in corso di IVG farmacologica e i livelli d’ansia pre-trattamento. Inoltre, sono stati indagati i fattori predittivi di dolore e la correlazione con l’epoca gestazionale. MATERIALI E METODI È stato condotto uno studio osservazionale, prospettico, multicentrico presso l’Unità Operativa di Ostetricia e Ginecologia dell’Azienda USL e presso l’Unità Operativa di Ginecologia dell’IRCCS Sant’Orsola Malpighi di Bologna. Sono state incluse le pazienti sottoposte a IVG farmacologica tra giugno 2021 e novembre 2021, che rispettassero i criteri di inclusione ed esclusione. Sono stati somministrati 5 questionari (GHQ-12, GAD-7, STAI-6, VAS) e raccolti i dati anamnestici ed ecografici. I potenziali fattori di rischio sono stati, quindi, selezionati per l’inclusione nell'analisi di regressione multivariata. RISULTATI Delle 242 pazienti incluse, il 38,0% ha riferito una sintomatologia dolorosa severa (VAS >70). Dall’analisi di regressione multivariata, la dismenorrea intensa è risultata essere il fattore di rischio più forte per il dolore (OR = 6,30, IC 95% 2,66 – 14,91), seguita da alti livelli di ansia valutati mediante il punteggio del GHQ-12 > 9 (OR = 3,33, IC 95% 1,43 – 7,76). Al contrario, la nostra analisi ha confermato che un precedente parto vaginale rappresentava una caratteristica protettiva contro il dolore (OR 0,26, IC 95% 0,14 – 0,50). CONCLUSIONI Nel nostro studio alti livelli d’ansia pre-trattamento e la dismenorrea sono associati ad intensa sintomatologia dolorosa, mentre il parto vaginale è risultato protettivo. L’IVG farmacologica è una metodica efficace e sicura, ma spesso associata a sintomatologia dolorosa. È quindi fondamentale delineare fattori di predittivi di dolore ed individuare le pazienti a maggior rischio a cui somministrare un’idonea terapia antalgica.

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This thesis presents a creative and practical approach to dealing with the problem of selection bias. Selection bias may be the most important vexing problem in program evaluation or in any line of research that attempts to assert causality. Some of the greatest minds in economics and statistics have scrutinized the problem of selection bias, with the resulting approaches – Rubin’s Potential Outcome Approach(Rosenbaum and Rubin,1983; Rubin, 1991,2001,2004) or Heckman’s Selection model (Heckman, 1979) – being widely accepted and used as the best fixes. These solutions to the bias that arises in particular from self selection are imperfect, and many researchers, when feasible, reserve their strongest causal inference for data from experimental rather than observational studies. The innovative aspect of this thesis is to propose a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The approach involves the construction of a multi-dimensional conditional space of the X matrix in which the bias associated with the treatment assignment has been eliminated. Specifically, we propose the use of a partial dependence analysis of the X-space as a tool for investigating the dependence relationship between a set of observable pre-treatment categorical covariates X and a treatment indicator variable T, in order to obtain a measure of bias according to their dependence structure. The measure of selection bias is then expressed in terms of inertia due to the dependence between X and T that has been eliminated. Given the measure of selection bias, we propose a multivariate test of imbalance in order to check if the detected bias is significant, by using the asymptotical distribution of inertia due to T (Estadella et al. 2005) , and by preserving the multivariate nature of data. Further, we propose the use of a clustering procedure as a tool to find groups of comparable units on which estimate local causal effects, and the use of the multivariate test of imbalance as a stopping rule in choosing the best cluster solution set. The method is non parametric, it does not call for modeling the data, based on some underlying theory or assumption about the selection process, but instead it calls for using the existing variability within the data and letting the data to speak. The idea of proposing this multivariate approach to measure selection bias and test balance comes from the consideration that in applied research all aspects of multivariate balance, not represented in the univariate variable- by-variable summaries, are ignored. The first part contains an introduction to evaluation methods as part of public and private decision process and a review of the literature of evaluation methods. The attention is focused on Rubin Potential Outcome Approach, matching methods, and briefly on Heckman’s Selection Model. The second part focuses on some resulting limitations of conventional methods, with particular attention to the problem of how testing in the correct way balancing. The third part contains the original contribution proposed , a simulation study that allows to check the performance of the method for a given dependence setting and an application to a real data set. Finally, we discuss, conclude and explain our future perspectives.

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Due to the growing attention of consumers towards their food, improvement of quality of animal products has become one of the main focus of research. To this aim, the application of modern molecular genetics approaches has been proved extremely useful and effective. This innovative drive includes all livestock species productions, including pork. The Italian pig breeding industry is unique because needs heavy pigs slaughtered at about 160 kg for the production of high quality processed products. For this reason, it requires precise meat quality and carcass characteristics. Two aspects have been considered in this thesis: the application of the transcriptome analysis in post mortem pig muscles as a possible method to evaluate meat quality parameters related to the pre mortem status of the animals, including health, nutrition, welfare, and with potential applications for product traceability (chapters 3 and 4); the study of candidate genes for obesity related traits in order to identify markers associated with fatness in pigs that could be applied to improve carcass quality (chapters 5, 6, and 7). Chapter three addresses the first issue from a methodological point of view. When we considered this issue, it was not obvious that post mortem skeletal muscle could be useful for transcriptomic analysis. Therefore we demonstrated that the quality of RNA extracted from skeletal muscle of pigs sampled at different post mortem intervals (20 minutes, 2 hours, 6 hours, and 24 hours) is good for downstream applications. Degradation occurred starting from 48 h post mortem even if at this time it is still possible to use some RNA products. In the fourth chapter, in order to demonstrate the potential use of RNA obtained up to 24 hours post mortem, we present the results of RNA analysis with the Affymetrix microarray platform that made it possible to assess the level of expression of more of 24000 mRNAs. We did not identify any significant differences between the different post mortem times suggesting that this technique could be applied to retrieve information coming from the transcriptome of skeletal muscle samples not collected just after slaughtering. This study represents the first contribution of this kind applied to pork. In the fifth chapter, we investigated as candidate for fat deposition the TBC1D1 [TBC1 (tre-2/USP6, BUB2, cdc16) gene. This gene is involved in mechanisms regulating energy homeostasis in skeletal muscle and is associated with predisposition to obesity in humans. By resequencing a fragment of the TBC1D1 gene we identified three synonymous mutations localized in exon 2 (g.40A>G, g.151C>T, and g.172T>C) and 2 polymorphisms localized in intron 2 (g.219G>A and g.252G>A). One of these polymorphisms (g.219G>A) was genotyped by high resolution melting (HRM) analysis and PCR-RFLP. Moreover, this gene sequence was mapped by radiation hybrid analysis on porcine chromosome 8. The association study was conducted in 756 performance tested pigs of Italian Large White and Italian Duroc breeds. Significant results were obtained for lean meat content, back fat thickness, visible intermuscular fat and ham weight. In chapter six, a second candidate gene (tribbles homolog 3, TRIB3) is analyzed in a study of association with carcass and meat quality traits. The TRIB3 gene is involved in energy metabolism of skeletal muscle and plays a role as suppressor of adipocyte differentiation. We identified two polymorphisms in the first coding exon of the porcine TRIB3 gene, one is a synonymous SNP (c.132T> C), a second is a missense mutation (c.146C> T, p.P49L). The two polymorphisms appear to be in complete linkage disequilibrium between and within breeds. The in silico analysis of the p.P49L substitution suggests that it might have a functional effect. The association study in about 650 pigs indicates that this marker is associated with back fat thickness in Italian Large White and Italian Duroc breeds in two different experimental designs. This polymorphisms is also associated with lactate content of muscle semimembranosus in Italian Large White pigs. Expression analysis indicated that this gene is transcribed in skeletal muscle and adipose tissue as well as in other tissues. In the seventh chapter, we reported the genotyping results for of 677 SNPs in extreme divergent groups of pigs chosen according to the extreme estimated breeding values for back fat thickness. SNPs were identified by resequencing, literature mining and in silico database mining. analysis, data reported in the literature of 60 candidates genes for obesity. Genotyping was carried out using the GoldenGate (Illumina) platform. Of the analyzed SNPs more that 300 were polymorphic in the genotyped population and had minor allele frequency (MAF) >0.05. Of these SNPs, 65 were associated (P<0.10) with back fat thickness. One of the most significant gene marker was the same TBC1D1 SNPs reported in chapter 5, confirming the role of this gene in fat deposition in pig. These results could be important to better define the pig as a model for human obesity other than for marker assisted selection to improve carcass characteristics.

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Analysts, politicians and international players from all over the world look at China as one of the most powerful countries on the international scenario, and as a country whose economic development can significantly impact on the economies of the rest of the world. However many aspects of this country have still to be investigated. First the still fundamental role played by Chinese rural areas for the general development of the country from a political, economic and social point of view. In particular, the way in which the rural areas have influenced the social stability of the whole country has been widely discussed due to their strict relationship with the urban areas where most people from the countryside emigrate searching for a job and a better life. In recent years many studies have mostly focused on the urbanization phenomenon with little interest in the living conditions in rural areas and in the deep changes which have occurred in some, mainly agricultural provinces. An analysis of the level of infrastructure is one of the main aspects which highlights the principal differences in terms of living conditions between rural and urban areas. In this thesis, I first carried out the analysis through the multivariate statistics approach (Principal Component Analysis and Cluster Analysis) in order to define the new map of rural areas based on the analysis of living conditions. In the second part I elaborated an index (Living Conditions Index) through the Fuzzy Expert/Inference System. Finally I compared this index (LCI) to the results obtained from the cluster analysis drawing geographic maps. The data source is the second national agricultural census of China carried out in 2006. In particular, I analysed the data refer to villages but aggregated at province level.

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Questa tesi descrive alcuni studi di messa a punto di metodi di analisi fisici accoppiati con tecniche statistiche multivariate per valutare la qualità e l’autenticità di oli vegetali e prodotti caseari. L’applicazione di strumenti fisici permette di abbattere i costi ed i tempi necessari per le analisi classiche ed allo stesso tempo può fornire un insieme diverso di informazioni che possono riguardare tanto la qualità come l’autenticità di prodotti. Per il buon funzionamento di tali metodi è necessaria la costruzione di modelli statistici robusti che utilizzino set di dati correttamente raccolti e rappresentativi del campo di applicazione. In questo lavoro di tesi sono stati analizzati oli vegetali e alcune tipologie di formaggi (in particolare pecorini per due lavori di ricerca e Parmigiano-Reggiano per un altro). Sono stati utilizzati diversi strumenti di analisi (metodi fisici), in particolare la spettroscopia, l’analisi termica differenziale, il naso elettronico, oltre a metodiche separative tradizionali. I dati ottenuti dalle analisi sono stati trattati mediante diverse tecniche statistiche, soprattutto: minimi quadrati parziali; regressione lineare multipla ed analisi discriminante lineare.

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The goal of many plant scientists’ research is to explain natural phenotypic variation in term of simple changes in DNA sequence. DNA-based molecular markers are extensively used for the construction of genome-wide molecular maps and to perform genetic analysis for simple and complex traits. The PhD thesis was divided into two main research lines according to the different approaches adopted. The first research line is to analyze the genetic diversity in an Italian apple germplasm collection for the identification of markers tightly linked to targeted genes by an association genetic method. This made it possible to identify synomym and homonym accessions and triploids. The fruit red skin color trait has been used to test the reliability of the genetic approaches in this species. The second line is related to the development of molecular markers closely linked to the Rvi13 and Rvi5 scab resistance genes, previously mapped on apple’s chromosome 10 and 17 respectively by using the traditional linkage mapping method. Both region have been fine-mapped with various type of markers that could be used for marker-assisted selection in future breeding programs and to isolate the two resistance genes.