New approach to analyze relationships between agritouristic supply and territory

This paper defines the phenomenon of agritourism in Friuli Venezia Giulia (NE Italy) at the end of 2009, in the light of the multifunctionality of agritouristic farms and taking into account the land use. The proposed statistical approach to outline the situation includes (a) the classification of the variables linked to agritouristic supply to find the main supply types, (b) the Principal Component Analysis (PCA) in order to classify the regional agritourisms according to their supply and (c) the Canonical Correspondence Analysis (CCA) to investigate the relationships between agritouristic supply, agricultural land use and territory. Since the CCA is widely used only in social and environmental sciences, this work represents its first application in agribusiness field. The method becomes important during the agricultural policy planning processes because it provides decision makers with a means of rapid assessment of the relationships between rural supply and land uses on the territory.Rural Tourism, Agritourism, Canonical Correspondence Analysis (CCA), Agricultural Policy., Agribusiness, Agricultural and Food Policy, Q13, Q18.,

Lactobacillus casei group: identification, characterization and genetic evaluation of the stress response

Lactic acid bacteria (LAB) are an heterogeneous group of microorganisms used as starter and/or adjunctive cultures in the production of fermented foods to improve the shelf-life, the organoleptic properties and promote health. Many of these species, in fact, have been extensively characterized as probiotics several studies and clinical tests to substantiate health claims are available for several of them. During use, formulation and preservation as starter, adjunctive and/or probiotic cultures LAB are subjected to physical and chemical stresses that can influence growth, cell viability and fermentation capabilities, changing the technological fitness of the strains. This thesis focused on Lactobacillus casei, L. rhamnosus and L. paracasei with the aim to encrease the knowledge on this strains. These microbial species are involved in the fermentation of various food matrices (meat, vegetable and dairy products) and they could be used as probiotics or for the development of new functional products, as many studies reported the presence of several strains belonging to these species with probiotic features. Considering the hardness existing in the correct identification of these strains, so genetically close to each other, a wide collection of strains isolated from several sources and previously identified as belonging to L. casei group was collected (201 total strains), and a species-specific PCR, multiplex PCR, group-specific PCR and HRM analyses have been performed or developed to identify L. casei, L. rhamnosus and L. paracasei strains. Almost all the techniques resulted effective for the identification, but the group-specific PCR had to be applied as the first step of identification. Anyway, the attribution to one of the species of the group remained uncertain for some strains. Therefore, all the strains were characterized using three different assays (Rep-PCR, RAPD-PCR and Sau-PCR), in order to have a complete point of view of their genotype. As a result, a high variability was found among strains with all the three performed assays, confirming the presence of a high number of genotipes. Therafter 45 strains were selected for the development of an MLST scheme based on the analysis of internal fragments (loci) of stress related genes. The results confirmed the presence of a high variability among strains and it was not surprising to found strains with different STs. Considering that the analysis was performed on 45 strains, and the high number of STs that has been found, it would be interesting to charachterize other strains, in order to find possible correlation between the source of isolation or a specific stress response behaviour. Four-teen strains were selected for the whole genome sequencing and core-genome and pan-genome comparisons were performed, obtaining a clear distinction among L. paracasei and L. rhamnosus strains. Nonetheless, a L. paracasei and two L. casei strains grouped in L. rhamnosus cluster, confirming how hard is the discrimination among these species, because of their high level of similarity. SAPD-PCR analysis were also performed, confirming a high genomic variability among strains. The same strains where then subjected to the evaluation of their mucus binding capabilities. The binding assays were performed in vitro and the strains were tested before and after oxidative stress exposure. The behaviour of the microorganisms analysed resulted strain-dependent and analysis allowed the selection of few strains with interesting binding properties, that will be further analysed for their probiotic characteristics before to do in vivo analysis and to understand their adhesion mechanisms. At least, a strain of L. paracasei was selected for its ability to conduct malolactic fermentation under different EtOH and pH conditions studing how the expression of stress related genes was affected in the different tested conditions. The strain resulted able to performe MLF under all the tested conditions, and as expected, the lower concentration of glucose, corresponding to the lower final concentration of alcohol, demonstrated to be less stressful. Considering that the strain was able to conduct MLF also when in the presence of a concentration of glucose, corresponding to 15% v/v of ethanol, it can be considered as a potential good MLF starter culture. Another topic for the future research could be the evaluation of the stress response of this strain during MLF when adapted in a respiratory envinronment before the inoculatio

Approaches for agro-energy land planning

The aim of the work is to present the X-land software application that, using an interdisciplinary approach, allows to plan agro-fuel supply chain at the regional level, integrating different informative layers (soil parameters, climate, field management and location with respect to collecting centres, processing plants and road network). X-land is designed to evaluate the potential use of the land for energy production and its side effects, supplying the existing processing plants and accomplishing with economic, energy and environmental targets

境界層レーダー・ドップラーライダー・タイムラプスカメラの高解像度観測を用いたウェーブレット解析による積雲の生成過程に関する多面的研究

京都大学新制・課程博士博士(工学)甲第24208号工博第5036号京都大学大学院工学研究科社会基盤工学専攻(主査)教授 中北 英一, 准教授 山口 弘誠, 教授 田中 賢治学位規則第4条第1項該当Doctor of Philosophy (Engineering)Kyoto UniversityDFA

System simulation by SEMoLa

SEMoLa is a platform, developed at DISA since 1992, for system knowledge integration and modelling. It allows to create computer models for dynamic systems and to manage different types of information. It is formed by several parts, each dealing with different forms of knowledge, in an integrated way: a graphical user interface (GUI), a declarative language for modelling, a set of commands with a procedural scripting language, a specific editor with code highlighting (SemEdit), a visual modelling application (SemDraw), a data base management system (SemData), plotting data capabilities (SemPlot), a raster maps management system (SemGrid), a large library of random number generators for uncertainty analysis, support for fuzzy logic expert systems, a neural networks builder and various statistical tools (basic statistics, multiple and non-linear regression, moving statistics, etc.). The core part of the platform is the declarative modelling language (SEMoLa; simple, easy to use, modelling language). It relies on System Dynamics principles and uses an integrated view to represent dynamic systems through different modelling approaches (state/individual-based, continuous/discrete, deterministic/stochastic) without requiring specific programming skills. SEMoLa language is based on a ontology closer to human reasoning rather than computer logic and constitutes also a paradigm for knowledge management. SEMoLa platform permits to simplify the routinely tasks of creating, debugging, evaluating and deploying computer simulation models but also to create user libraries of script commands. It is able to communicate with other frameworks exchanging - with standard formats - data, modules and model components

DATA OPTIMIZATION OF RAIN RADAR AND ITS COVERAGE EXPANSION USING RADAR NETWORK

This research developed network of two Santanu rain radars of the Center for Atmospheric Science and Technology LAPAN installed in Bandung (SANTANU 1) and Sumedang (SANTANU 2). The objective is to get larger coverage area which also comply data each other. The first step is data optimation to each radar detection results, particularly due to rain attenuation, and then validation with the transportable radar image. The shape analysis on a rain object detected in the slice of both radar images indicates 0.8672 of R2 which show the width of both objectcs has a good similarity. Data optimation due to rain attenuation using attenuation correction for regional weather radar (KA) and path-integrated attenuation (PIA) indicate that the reflectivity improvement by KA is 10 times better than PIA. The object detected by Santanu rain radar is similar to the transportable radar for reflectivity larger than 30 dBZ.  The next step is integration of both rain radar images to create mosaic image and then validation using the transportable radar data. The production of the mosaic image is tried out using three methods: image stitching, averaging, and Cressman scheme. The best result is presented by Cressman scheme which show more integrated slice area and maintain the features of the object. However, the processing time of this scheme is 17 minutes which is longer than  image stitching method. The processing time depend on the number of grid data and the hardware memory. Validation on the mosaic result by using transportable radar data by implementing structural similarity index (SSIM) method yields 0,32 of average value. The improvement on SSIM value is obtained if speckle removal is applied by recording 59% of enhancemen

A software application for mapping livestock waste odour dispersion

In developed Countries, coexistence of livestock production and urban settlements is a source of problematic interactions that are regulated by specific legislation, often requiring the evaluation of the potential environmental impact of livestock odour emissions. For this purpose, dispersion models are powerful tools that can be classified as dynamic (Eulerian and Lagrangian) or static (Gaussian). The latter, while presenting some limitations in condition of wind calm and complex orography, are widely adopted for their ease of use. OdiGauss is a free multilingual software application allowing to estimate odour dispersion from multiple point sources and to generate the related maps. Dispersion is calculated according to a Gaussian approach, as a function of wind speed and direction, precipitation, temperature, and solar radiation. OdiGauss incorporates a model of odour emissions from poultry farms (EmiFarm) which makes predictions based on manure production and management. Two case studies of software application on real poultry and swine farms are presented

Osteoporosis, inflammation and ageing

Osteoporosis is a condition characterized by low bone mass and increased bone fragility, putting patients at risk of fractures, which are major causes of morbidity substantially in older people. Osteoporosis is currently attributed to various endocrine, metabolic and mechanical factors. However, emerging clinical and molecular evidence suggests that inflammation also exerts significant influence on bone turnover, inducing osteoporosis. Numerous proinflammatory cytokines have been implicated in the regulation of osteoblasts and osteoclasts, and a shift towards an activated immune profile has been hypothesized as important risk factor. Chronic inflammation and the immune system remodelling characteristic of ageing, as well as of other pathological conditions commonly associated with osteoporosis, may be determinant pathogenetic factors. The present article will review the current perspectives on the interaction between bone and immune system in the elderly, providing an interpretation of osteoporosis in the light of inflamm-ageing

KARAKTERISTIK KETEBALAN LAPISAN BRIGHT BAND HASIL MODEL PROFIL REFLEKTIVITAS DAN GRADIEN REFLEKTIVITAS

Bright band merupakan indikator suatu lapisan pada awan stratus yang ditandai oleh peningkatan reflektivitas radar akibat kristal es yang meleleh. Hal tersebut dapat menyebabkan galat dalam menghitung estimasi presipitasi berdasarkan data radar. Oleh karena itu, deteksi bright band merupakan langkah yang penting untuk dilakukan guna mengoreksi data radar cuaca sebagai acuan dalam pengembangan model estimasi presipitasi. Penelitian ini bertujuan menginvestigasi dua model untuk identifikasi bright band hasil observasi transportable X-band radar dari data range-height indicator (RHI). Model pertama dengan menggunakan function fit, yaitu profil vertikal reflektivitas (VPR; vertical profile of reflectivity) dan model kedua dengan menggunakan gradien reflektivitas (GR). Hasil analisis menunjukkan perbedaan galat dalam menentukan batas atas (batas bawah) untuk VPR adalah 4,51% (3,1%), sedangkan model GR 9,02% (3,9%). Identifikasi bright band dengan menggunakan model VPR lebih baik dibandingkan dengan model GR untuk penentuan batas atas dan batas bawah dari bright band. Pengetahuan mengenai karakteristik ketebalan BB dapat dimanfaatkan untuk analisis lebih lanjut terkait estimasi presipitasi kuantitatif berdasarkan observasi radar

Interplay between neuroendocrine biomarkers and gut microbiota in dogs supplemented with grape proanthocyanidins: Results of dietary intervention study

Several studies on the interaction between gut microbiota and diets, including prebiotics, have been reported in dogs, but no data are available about the effects of dietary administration of grape proanthocyanidins. In the study, 24 healthy adult dogs of different breeds were recruited and divided in 3 groups of 8 subjects each. A group was fed with a control diet (D0), whilst the others were supplemented with 1 (D1) or 3 (D3) mg/kg live weight of grape proanthocyanidins. Samples of feces were collected at the beginning and after 14 and 28 days for microbiota, short chain fatty acid, and lactic acid analysis. Serotonin and cortisol were measured in saliva, collected at the beginning of the study and after 28 days. A significantly higher abundance (p < 0.01) of Enterococcus and Adlercreutzia were observed in D0, whilst Escherichia and Eubacterium were higher in D1. Fusobacterium and Phascolarctobacterium were higher (p < 0.01) in D3. Salivary serotonin increased (p < 0.01) at T28 for D1 and D3 groups but cortisol did not vary. Proanthocyanidins administration influenced the fecal microbiota and neuroendocrine response of dogs, but a high variability of taxa was observed, suggesting a uniqueness and stability of fecal microbiota related to the individual