MODEL OF CROATIAN SEA PASSENGER PORTS MANAGEMENT RATIONALIZATION

Predmet istraživanja u ovome znanstvenom radu je razvitak pomorskoputničkih luka u Republici Hrvatskoj do 2012. godine. Za definiranje svojstava i determinanti pomorskoputničkih luka koristilo se modelom na bazi matrice rasta. Analiza i vrednovanje pojedinih elemenata modela i dobivene izravne stope rasta imale su za cilj znanstveno formulirati rezultate istraživanja, prema najvažnijim teorijskim zakonitostima razvitka pomorskoputničkih luka u Republici Hrvatskoj. Autori su se u znanstvenom istraživanju i prezentiranju rezultata istraživanja ovog rada služili kombinaciju znanstvenih metoda kao što su: metoda analize i sinteze, metoda konkretizacije, komparativna metoda i metoda modeliranja (matrica rasta). Glavna znanstvena hipoteza dokazana je izravnim stopama rasta odabranih elemenata modela a ona glasi: Znanstveno utemeljenim spoznajama o funkcioniranju i poslovanju sustava pomorskoputničkih luka moguće je predložiti model, mjere i aktivnosti za racionalno upravljanje tim lukama kako bi se osigurao rast i razvoj sustava pomorskoputničkih luka.This paper analyses the sustainable development of sea passenger ports in the Republic of Croatia until 2012. A model of growth was used in order to define the main characteristics and determinants of sea passenger ports. The purpose of the paper was to present a scientifically-based formulation of sustainable development analysis of sea passenger ports in Croatia, based on the evaluation and analysis of relevant elements and resulting direct rates. The authors in their scientific research and presentation used a various combination of scientific methods like: analysis and syntheses method, concretization method, comparative method and modeling method (growth matrix). The main scientific hypothesis is: By using scientifically based acknowledgments about functioning and management of sea passenger port system it is possible to suggest a model, measurements and activities for the rational management of sea passenger ports in Croatia in order to secure their growth and development. This scientific hypothesis was confirmed by the direct rates of growth of the model elements

DNA methylation analysis of selected loci in WT, <i>ros1</i>, <i>rdm16ros1</i> and <i>nrpd1ros1</i>.

<p>(<b>A–C</b>) DNA methylation levels of three loci. Upper panel, DNA methylation snapshot in IGV browser from whole-genome bisulfite sequencing data; Lower panel, individually bisulfite sequencing results. (<b>A</b>) At5g42940 promoter, (<b>B</b>) At5g35730 promoter, (<b>C</b>) At1g26400 promoter.</p

Morphological and physiological defects in <i>rdm16ros1</i> compared to <i>ros1</i> mutant.

<p>(<b>A–C</b>) Morphological comparison of <i>rdm16ros1</i> with <i>ros1</i> with respect to plant stature (<b>A</b>), leaves (<b>B</b>) and siliques (<b>C</b>). (<b>D–F</b>) WT and <i>ros1</i>, <i>rdm16ros1</i> seed germination under control condition (<b>D</b>), 75 mM NaCl (<b>E</b>) and 0.5 µM ABA (<b>F</b>). (<b>G–H</b>) Seeds were germinated on a half-strength MS plate for 6 d and then the seedlings were exposed to different concentrations of NaCl (<b>G</b>) and ABA (<b>H</b>) for 7 d. Data are means ± SD (n = 15).</p

Average CHH methylation levels in transposable elements (TEs) (A) and genes (B).

<p>TEs and genes were divided into 5 groups based on their size for detailed comparison of the DNA methylation levels among WT, <i>ros1</i>, <i>rdm16ros1</i> and <i>nrpd1ros1</i>.</p

The <i>rdm16</i> mutation reduced the levels of Pol V transcripts.

<p>(<b>A–E</b>) Five Pol V-dependent loci showed decreased Pol V transcript levels in <i>rdm16ros1</i> compared to WT and <i>ros1</i> controls. (<b>A</b>) RD29A promoter, (<b>B</b>) IGN5, (<b>C</b>) IGN28, (<b>D</b>) IGN30, (<b>E</b>) IGN32.</p

ChIP analysis of RDM16 on Pol V targeted loci.

<p>(<b>A</b>) ChIP analysis of RDM16-3xFlag transgenic lines using anti-Flag antibody. (<b>B</b>) ChIP analysis of RDM16-3xHA transgenic lines using anti-HA antibody.</p

Analysis of DMRs identified in <i>rdm16ros1</i>.

<p>(<b>A</b>) Category of hypomethylated or hypermethylated loci in <i>rdm16ros1</i>, <i>nrpd1ros1</i> or WT in comparison with <i>ros1</i>. (<b>B</b>) Distance distribution of intergenic DMRs relative to gene start codon. (<b>C–D</b>) Overlap of differentially methylated loci between <i>rdm16ros1</i> and <i>nrpd1ros1</i> (<b>C</b>), and between <i>rdm16ros1</i> and <i>ros1</i> (<b>D</b>). Boxplots represent methylation levels of each class of differentially methylated loci.</p

Mutation of <i>RDM16</i> partially releases the transcriptional silencing of <i>RD29A-LUC</i> transgene and endogenous <i>RD29A</i> in <i>ros1</i> mutant background.

<p>(<b>A</b>) Luminescence imaging of <i>RD29A-LUC</i> expression in WT, <i>ros1</i> and <i>rdm16ros1</i>. (<b>B–C</b>) Real-time RT-PCR analysis of the expression of <i>RD29A-LUC</i> (<b>B</b>) and endogenous <i>RD29A</i> (<b>C</b>) in WT, <i>ros1</i> and <i>rdm16ros1</i> exposed to NaCl, abscisic acid (ABA) and cold (4°C) stresses. (<b>D</b>) Expression analysis of <i>ROS1</i> in WT, <i>ros1</i>, <i>rdm16ros1</i>, <i>nrpd1ros1</i> and <i>nrpe1ros1</i>.</p

Cytosine DNA methylation analysis of transgenic and endogenous loci in WT, <i>ros1</i>, <i>rdm16ros1</i>, <i>nrpd1ros1</i> and <i>nrpe1ros1</i> through bisulfite sequencing.

<p>DNA methylation analysis of transgenic <i>RD29A</i> promoter (<b>A</b>), endogenous <i>RD29A</i> promoter (<b>B</b>), At4g18650 promoter (<b>C</b>) and AtSN1 (<b>D</b>).</p