3-D Vision and Figure-Ground Separation by Visual Cortex

A neural network theory of :3-D vision, called FACADE Theory, is described. The theory proposes a solution of the classical figure-ground problem for biological vision. It does so by suggesting how boundary representations and surface representations are formed within a Boundary Contour System (BCS) and a Feature Contour System (FCS). The BCS and FCS interact reciprocally to form 3-D boundary and surface representations that arc mutually consistent. Their interactions generate 3-D percepts wherein occluding and occluded object completed, and grouped. The theory clarifies how preattentive processes of 3-D perception and figure-ground separation interact reciprocally with attentive processes of spatial localization, object recognition, and visual search. A new theory of stereopsis is proposed that predicts how cells sensitive to multiple spatial frequencies, disparities, and orientations are combined by context-sensitive filtering, competition, and cooperation to form coherent BCS boundary segmentations. Several factors contribute to figure-ground pop-out, including: boundary contrast between spatially contiguous boundaries, whether due to scenic differences in luminance, color, spatial frequency, or disparity; partially ordered interactions from larger spatial scales and disparities to smaller scales and disparities; and surface filling-in restricted to regions surrounded by a connected boundary. Phenomena such as 3-D pop-out from a 2-D picture, DaVinci stereopsis, a 3-D neon color spreading, completion of partially occluded objects, and figure-ground reversals are analysed. The BCS and FCS sub-systems model aspects of how the two parvocellular cortical processing streams that join the Lateral Geniculate Nucleus to prestriate cortical area V4 interact to generate a multiplexed representation of Form-And-Color-And-Depth, or FACADE, within area V4. Area V4 is suggested to support figure-ground separation and to interact. with cortical mechanisms of spatial attention, attentive objcect learning, and visual search. Adaptive Resonance Theory (ART) mechanisms model aspects of how prestriate visual cortex interacts reciprocally with a visual object recognition system in inferotemporal cortex (IT) for purposes of attentive object learning and categorization. Object attention mechanisms of the What cortical processing stream through IT cortex are distinguished from spatial attention mechanisms of the Where cortical processing stream through parietal cortex. Parvocellular BCS and FCS signals interact with the model What stream. Parvocellular FCS and magnocellular Motion BCS signals interact with the model Where stream. Reciprocal interactions between these visual, What, and Where mechanisms arc used to discuss data about visual search and saccadic eye movements, including fast search of conjunctive targets, search of 3-D surfaces, selective search of like-colored targets, attentive tracking of multi-element groupings, and recursive search of simultaneously presented targets.Air Force Office of Scientific Research (90-0175, F49620-92-J-0499); ARPA (90-0083, N00014-92-J-4015); Office of Naval Research (N00014-91-J-4100

The detection and representation of foreground vs. background objects

In order to navigate through the environment, recognize objects, and interact physically with object surfaces, we need to recover the 3-D layout of a visual scene from the 2-D images that are projected onto the eyes. A primary cue used by the human visual system to perceive the depths of surfaces in the scene is stereo disparity (Marr & Poggio, 1979; Howard & Rogers, 2002; Brown, Burschka, & Hager, 2003; Harris & Wilcox, 2009). Stereo disparity arises from the difference in perspective provided by the two eyes. As a result of this difference, objects can appear at slightly different positions in the left and right images. The human visual system is able to detect this disparity in position and use it to infer depth (Figure 1). For tasks such as the recognition and manipulation of objects in the scene, it is important to segment the image into regions that belong to distinct objects. A strong cue to the presence of an object boundary is a large change in depth between two adjacent image regions. Stereo processing enables the detection of these boundaries and computation of the relative depth between surfaces meeting at boundaries in the image

Study on the Method of Constructing a Statistical Shape Model and Its Application to the Segmentation of Internal Organs in Medical Images

In image processing, segmentation is one of the critical tasks for diagnostic analysis and image interpretation. In the following thesis, we describe the investigation of three problems related to the segmentation algorithms for medical images: Active shape model algorithm, 3-dimensional (3-D) statistical shape model building and organic segmentation experiments. For the development of Active shape models, the constraints of statistical model reduced this algorithm to be difficult for various biological shapes. To overcome the coupling of parameters in the original algorithm, in this thesis, the genetic algorithm is introduced to relax the shape limitation. How to construct a robust and effective 3-D point model is still a key step in statistical shape models. Generally the shape information is obtained from manually segmented voxel data. In this thesis, a two-step procedure for generating these models was designed. After transformed the voxel data to triangular polygonal data, in the first step, attitudes of these interesting objects are aligned according their surface features. We propose to reflect the surface orientations by means of their Gauss maps. As well the Gauss maps are mapped to a complex plane using stereographic projection approach. The experiment was run to align a set of left lung models. The second step is identifying the positions of landmarks on polygonal surfaces. This is solved by surface parameterization method. We proposed two simplex methods to correspond the landmarks. A semi-automatic method attempts to “copy” the phasic positions of pre-placed landmarks to all the surfaces, which have been mapped to the same parameterization domain. Another automatic corresponding method attempts to place the landmarks equidistantly. Finally, the goodness experiments were performed to measure the difference to manually corresponded results. And we also compared the affection to correspondence when using different surface mapping methods. The third part of this thesis is applying the segmentation algorithms to solve clinical problems. We did not stick to the model-based methods but choose the suitable one or their complex according to the objects. In the experiment of lung regions segmentation which includes pulmonary nodules, we propose a complementary region growing method to deal with the unpredictable variation of image densities of lesion regions. In the experiments of liver regions, instead of using region growing method in 3-D style, we turn into a slice-by-slice style in order to reduce the overflows. The image intensity of cardiac regions is distinguishable from lung regions in CT image. But as to the adjacent zone of heart and liver boundary are generally blurry. We utilized a shape model guided method to refine the segmentation results.3-D segmentation techniques have been applied widely not only in medical imaging fields, but also in machine vision, computer graphic. At the last part of this thesis, we resume some interesting topics such as 3-D visualization for medical interpretation, human face recognition and object grasping robot etc.九州工業大学博士学位論文 学位記番号:工博甲第353号　学位授与年月日:平成25年9月27日Chapter 1: Introduction|Chapter 2: Framework of Medical Image Segmentation|Chapter 3: 2-D Organic Regions Using Active Shape Model and Genetic Algorithm|Chapter 4: Alignment of 3-D Models|Chapter 5: Corespondence of 3-D Models|Chapter 6:Experiments of Organic Segmentation|Chapter 7: Visualization Technology and Its Applications|Chapter 8: Conclusions and Future Works九州工業大学平成25年

Contrasting Visual Working Memory for Verbal and Non-Verbal Material with Multivariate Analysis of fMRI

We performed a Delayed-Item-Recognition task to investigate the neural substrates of non-verbal visual working memory with event-related fMRI ('Shape task'). 25 young subjects (mean age: 24.0 years; STD=3.8 years) were instructed to study a list of either 1, 2 or 3 unnamable nonsense line drawings for 3s ('stimulus phase' or STIM). Subsequently, the screen went blank for 7s ('retention phase' or RET), and then displayed a probe stimulus for 3s in which subjects indicated with a differential button press whether the probe was contained in the studied shape-array or not ('probe phase' or PROBE). Ordinal Trend Canonical Variates Analysis (Habeck et al., 2005a) was performed to identify spatial covariance patterns that showed a monotonic increase in expression with memory load during all task phases. Reliable load-related patterns were identified in the stimulus and retention phase (p<0.01), while no significant pattern could be discerned during the probe phase. Spatial covariance patterns that were obtained from an earlier version of this task (Habeck et al., 2005b) using 1, 3, or 6 letters ('Letter task') were also prospectively applied to their corresponding task phases in the current non-verbal task version. Interestingly, subject expression of covariance patterns from both verbal and non-verbal retention phases correlated positively in the non-verbal task for all memory loads (p<0.0001). Both patterns also involved similar frontoparietal brain regions that were increasing in activity with memory load, and mediofrontal and temporal regions that were decreasing. Mean subject expression of both patterns across memory load during retention also correlated positively with recognition accuracy (d(L)) in the Shape task (p<0.005). These findings point to similarities in the neural substrates of verbal and non-verbal rehearsal processes. Encoding processes, on the other hand, are critically dependent on the to-be-remembered material, and seem to necessitate material-specific neural substrates

Dynamic alterations in the amplitude of low-frequency fluctuation in patients with cerebral small vessel disease

Background and purposePrevious studies have focused on the changes of dynamic and static functional connections in cerebral small vessel disease (CSVD). However, the dynamic characteristics of local brain activity are poorly understood. The purpose of this study was to investigate the dynamic cerebral activity changes in patients with CSVD using the dynamic amplitude of low-frequency fluctuation (d-ALFF).MethodsA total of 104 CSVD patients with cognitive impairment (CSVD-CI, n = 52) or normal cognition (CSVD-NC, n = 52) and 63 matched healthy controls (HCs) were included in this study. Every participant underwent magnetic resonance imaging scans and a battery of neuropsychological examinations. The dynamics of spontaneous brain activity were assessed using dynamic changes in the amplitude of low-frequency fluctuation (ALFF) with the sliding-window method. We used voxel-wise one-way analysis of variance (ANOVA) to compare dynamic ALFF variability among the three groups. Post-hoc t-tests were used to evaluate differences between each group pair. Finally, the brain regions with d-ALFF values with differences between CSVD subgroups were taken as regions of interest (ROI), and the d-ALFF values corresponding to the ROI were extracted for partial correlation analysis with memory.Results(1) There was no significant difference in age (p = 0.120), sex (p = 0.673) and education (p = 0.067) among CSVD-CI, CSVD-NC and HC groups, but there were significant differences Prevalence of hypertension and diabetes mellitus among the three groups (p &lt; 10−3). There were significant differences in scores of several neuropsychological scales among the three groups (p &lt; 10−3). (2) ANOVA and post-hoc t-test showed that there were dynamic abnormalities of spontaneous activity in several brain regions in three groups, mainly located in bilateral parahippocampal gyrus and bilateral hippocampus, bilateral insular and frontal lobes, and the static activity abnormalities in bilateral parahippocampal gyrus and bilateral hippocampal regions were observed at the same time, suggesting that bilateral parahippocampal gyrus and bilateral hippocampus may be the key brain regions for cognitive impairment caused by CSVD. (3) The correlation showed that d-ALFF in the bilateral insular was slightly correlated with the Mini-Mental State Examination (MMSE) score and disease progression rate. The d-ALFF value of the left postcentral gyrus was negatively correlated with the Clock Drawing Test (CDT) score (r = −0.416, p = 0.004), and the d-ALFF value of the right postcentral gyrus was negatively correlated with the Rey’s Auditory Verbal Learning Test (RAVLT) word recognition (r = −0.320, p = 0.028).ConclusionThere is a wide range of dynamic abnormalities of spontaneous brain activity in patients with CSVD, in which the abnormalities of this activity in specific brain regions are related to memory and execution or emotion

Using latent features for short-term person re-identification with RGB-D cameras

This paper presents a system for people re-identification in uncontrolled scenarios using RGB-depth cameras. Compared to conventional RGB cameras, the use of depth information greatly simplifies the tasks of segmentation and tracking. In a previous work, we proposed a similar architecture where people were characterized using color-based descriptors that we named bodyprints. In this work, we propose the use of latent feature models to extract more relevant information from the bodyprint descriptors by reducing their dimensionality. Latent features can also cope with missing data in case of occlusions. Different probabilistic latent feature models, such as probabilistic principal component analysis and factor analysis, are compared in the paper. The main difference between the models is how the observation noise is handled in each case. Re-identification experiments have been conducted in a real store where people behaved naturally. The results show that the use of the latent features significantly improves the re-identification rates compared to state-of-the-art works.The work presented in this paper has been funded by the Spanish Ministry of Science and Technology under the CICYT contract TEVISMART, TEC2009-09146.Oliver Moll, J.; Albiol Colomer, A.; Albiol Colomer, AJ.; Mossi García, JM. (2016). Using latent features for short-term person re-identification with RGB-D cameras. Pattern Analysis and Applications. 19(2):549-561. https://doi.org/10.1007/s10044-015-0489-8S549561192http://kinectforwindows.org/http://www.gpiv.upv.es/videoresearch/personindexing.htmlAlbiol A, Albiol A, Oliver J, Mossi JM (2012) Who is who at different cameras. Matching people using depth cameras. Comput Vis IET 6(5):378–387Bak S, Corvee E, Bremond F, Thonnat M (2010) Person re-identification using haar-based and dcd-based signature. 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Fire detection, fuel model estimation and fire propagation estimation/visualization for the protection of Cultural Heritage

FIRESENSE (Fire Detection and Management through a Multi-Sensor Network for the Protection of Cultural Heritage Areas from the Risk of Fire and Extreme Weather Conditions) is a project co-funded by EU FP7 Environment that aims to develop a multi-sensor early warning system to remotely monitor areas of archaeological and cultural interest from the risk of fire and extreme weather conditions. It will combine different sensing technologies, i.e. wireless networks of temperature/humidity sensors, optical and infrared cameras, as well as local weather stations. Pilot deployments will be made in five cultural heritage sites in Greece, Turkey, Italy and Tunisia. Another goal is the estimation of the propagation direction and speed in order to help forest fire management. FIRESENSE will provide real-time information about the evolution of fire using wireless sensor network data and estimate the propagation of the fire based on the fuel model of the area and other important parameters such as wind speed, slope, and aspect of the ground surface. The fire propagation data are visualized on a user-friendly 3D-GIS environment. Some of the supported features are: a) Display of sensor locations and regions of interest in the cultural sites b) Interactive selection of some parameters (e.g. ignition point, humidity parameters) c) Automatic acquisition of weather data from onsite or nearby weather stations d) 2-D or 3-D visualization of fire propagation estimation output (ignition time and flame length). Commercial satellite images have reached a fairly high spatial resolution which allows more powerful textural analyses and more detailed description of soil surface. This improves the capacity to recognize and classify land uses, the amount and typology of vegetation and other potential sources of fuel for wildfires. It also reduced substantially the time and costs for updating vegetation and fuel distribution. Ground truth is also required especially for developing and testing of new image analysis algorithms. Measurements of the main fuel component are required and are usually destructive and costly, sometimes even unacceptable, especially if biodiversity or soil are threatened or in protected sites. Therefore, a sampling technique has been developed for single or groups of plants. Sub-volumes, which are characterized by the same type of fuel component and vegetation mix, are sampled over small known volumes. Volumetric mass densities are transformed into biomass and fuel components as mass per unit of surface. Very-High-resolution satellite images (QuickBird) are ortho-rectified with a detailed DTM of the study area and analyzed: recognition of lines of water flux convergence, pathways, usually unrecorded on official maps, vegetation patchiness, connectivity lines for fire to spread more easily, and connectivity lines for water fluxes during rainstorms will be among the results. Another approach that we use for vegetation classification is multi-band SVM classification approach. Each band characterizes/emphasizes a particular type of information such as textural, spatial, local and spectral information. The combination of these features improves significantly the accuracy of the results. We are currently investigating the registration between the ortho-rectified images and a ground truth map from the covered area in order to validate and improve the classification results. It is expected that the characterization of these areas and the accumulation of temporal series of vegetation/fuel distribution will serve not just for fire prevention and management but also for soil conservation and soil erosion control

β-arrestin2와 CXCR7의 C-말단 인산화 펩타이드 복합체 구조 규명을 통한 β-arrestin2의 활성 기작 연구 및 장내 병원성 세 균인 Campylobacter jejuni의 나선형 세포 모양을 결정하는 Pgp3 단백질의 구조 및 기능 연구

학위논문 (박사) -- 서울대학교 대학원 : 자연과학대학 화학부, 2020. 8. 이형호.The dissertation focuses on gaining a molecular level of understanding of how ligand recognition affects the alteration of protein structure and function. The dissertation is divided into two research chapters. Chapter 1 discusses one of the important cell-signaling regulating proteins, β-arrestin 2 (βarr2) to obtain the molecular level of understanding for the G-protein coupled receptor (GPCR) recognition. Chapter 2 discusses one of the cell-shape determining (Csd) proteins called peptidoglycan peptidase 3 (Pgp3) from Campylobacter jejuni. The molecular level of studies for the peptidoglycan recognition of Pgp3 protein can perhaps provide us with an insight into the mechanism for host infection of the pathogen. In Chapter 1, the structural and biophysical studies on the active conformation of βarr2 will be discussed. βarrs critically regulate signaling and trafficking of GPCRs, and there are two isoforms of βarrs: βarr1 and βarr2. GPCRs are the largest family of receptors on cell membranes and comprise an important class of drug targets. To turn off G-protein-mediated GPCR signaling, GPCR kinases phosphorylate the C-terminal tail and/or intracellular loops of GPCRs, which leads to arrestin binding. To date, the high-resolution structure of active βarr1 in complex with a phosphopeptide derived from GPCR has been revealed, but that of βarr2 remains elusive. To understand the recognition of the phosphorylated carboxyl-terminus tail of GPCR by the βarr2 protein, we determined a crystal structure of Rattus norvegicus βarr2 in complex with a phosphopeptide (C7pp) derived from CXCR7, a class A GPCR. The crystal structure of C7pp-bound βarr2 reveals key differences from the previously determined active conformation of βarr1. One of the key differences is that C7pp-bound βarr2 shows a relatively small inter-domain rotation. To prove the active conformation of βarr2, we used hydrogen/deuterium exchange mass spectrometry (HDX-MS) and synthetic-antibody-based conformational sensors. In Chapter 2, the structural and functional studies on the Pgp3 protein from C. jejuni will be discussed. The helical cell shape of C. jejuni is important for bacterial colonization during the infection of human intestines, which is believed to be due to the specific type of crosslinking of peptidoglycan. Via the remodeling of peptidoglycan by Csd proteins, the C. jejuni has sustained its adeptness at colonization and pathogenesis. To understand how Csd proteins recognize peptidoglycan, we solved eight X-ray crystal structures of Pgp3 including two complex structures bound with peptidoglycan derivative substrates. In addition, functional characterization of Pgp3 by the turnover chemistry revealed that it contains both D,D-endopeptidase and D,Dcarboxypeptidase activities. Catalysis is accompanied by large conformational changes upon peptidoglycan binding, whereby a loop regulates access to the active site. Furthermore, prior hydrolysis of the cross-linked peptide stem, which stems from the saccharide backbone of the peptidoglycan on one side, is a pre-requisite for its recognition and turnover by Pgp3. These analyses reveal the noncanonical nature of the transformations at the core of the events that define the morphological shape for C. jejuni as an intestinal pathogen.본 논문은 리간드 인식이 단백질 구조 및 기능의 변화에 어떻게 영향을 미치는지에 대한 분자 수준의 이해를 얻는 데 중점을 둔다. 본 논문은 두 개의 장으로 나뉜다. 제1장에서는 G-단백질 결합 수용체 (GPCR) 인식에 대한 분자 수준의 이해를 얻기 위해 중요한 세포 신호 조절 단백질인 β-arrestin (βarr)을 설명한다. 제2장에서는 C. jejuni의 세포 모양 결정 (Csd) 단백질 중 하나인 펩티도글리칸 분해효소 3 (Pgp3)에 대해 논의한다. Pgp3 단백질의 펩티도글리칸 인식에 대한 분자 수준의 연구는 병원체의 숙주 감염 메커니즘에 대한 통찰력을 갖게 할 것이다. 제1장에서는 βarr2의 구조적 및 생물 물리학적 연구에 대해 다룬다. βarr은 GPCR의 신호 전달 및 이동을 조절하는데 중요하며, βarr은 βarr1과 βarr2 이렇게 두 가지 동위체가 존재한다. GPCR은 세포막 수용체 중에서 가장 큰 패밀리를 가진 수용체이며, 약물 표적에 주요 단백질이다. G-단백질 매개 GPCR 신호 전달을 끄기 위해서, GPCR 인산화 효소는 GPCR의 C-말단 꼬리 및/또는 세포 내 존재하는 루프를 인산화 시켜, βarr와의 결합을 초래한다. 현재까지, GPCR의 C-말단 꼬리로부터 유래된 인산화 펩타이드와 활성형 (activated) βarr1의 고해상도 복합체 구조가 밝혀졌지만, βarr2와의 복합체 구조는 밝혀져 있지 않았다. βarr2 단백질에 의한 GPCR의 인산화 된 카복실-말단의 인식을 분자적으로 이해하기 위해, class A GPCR인 CXCR7 수용체의 C-말단에서 유래된 인산화 펩타이드 (C7pp)와 βarr2 단백질의 복합체 결정 구조를 규명하였다. C7pp와 결합된 βarr2의 구조는 기존에 밝혀진 βarr1 활성형 구조와 주요한 차이점을 보인다. 주요 차이점 중 하나는 C7pp와 결합된 βarr2의 구조가 비교적 작은 도메인 (N-도메인과 C-도메인) 간 회전을 나타낸다는 것이다. 또한, 본 연구에서 규명한 βarr2의 CXCR7 인산화 펩타이드 복합체 구조가 활성형임을 확인하기 위하여 수소/중수소 교환 질량 분석법 (HDX-MS) 및 합성 항체 기반 입체 구조 센서를 사용하였다. 제2장에서는 C. jejuni의 Pgp3 단백질에 대한 구조적 및 기능적 연구가 논의된다. C. jejuni의 나선형 세포 모양은 사람의 장 내 감염을 위해 박테리아 군집형성에 중요하며, 나선형 세포 모양은 펩티도글리칸의 특정 유형의 가교 결합으로 인한 것으로 여겨진다. Csd 단백질에 의한 C. jejuni의 펩티도글리칸 리모델링을 통해, C. jejuni는 박테리아 군집화 및 발병 기전에 적합하도록 세포의 모양을 유지하게 된다. Csd 단백질이 펩티도글리칸을 인식하는 방법을 이해하기 위해, 서로 다른 2가지의 펩티도글리칸 유도체 기질이 결합된 서로 다른 복합체 구조 2개를 포함하여 총 8개의 Pgp3 단백질의 X-선 결정 구조를 규명하였다. 또한, Pgp3 단백질은 펩티도글리칸 세포벽에 대해 D,D-endopeptidase와 D,D-carboxypeptidase 활성이 있음을 밝혔다. Pgp3의 촉매 작용은 펩티도글리칸에 결합할 때 큰 구조적 변화를 동반하는 것으로 나타났는데, 특히 Pgp3의 루프가 기질이 활성 부위에 접근하는데 조절함을 밝혔다. 또한, 한쪽의 펩티도글리칸의 당류 골격으로부터의 가교 된 펩티드 줄기의 가수 분해는 Pgp3에 의한 펩티도글리칸의 인식 및 촉매 작용을 위한 전제 조건임을 유추할 수 있었다. 이러한 분석은 사람의 장내 병원체인 C. jejuni의 병원성을 정의하는 핵심이 세포 모양 형태라는 점에서 비전형적 특성을 나타낸다는 것을 말한다.Chapter1 1.1 Introduction 1 1.1.1 Background of GPCR and β-arrestin signaling 1 1.1.2 Structural studies of β-arrestin 5 1.1.3 Background of CXCR7 8 1.2 Materials and Methods 11 1.2.1 Expression and purification of recombinant rat β-arrestin21-356 and β-arrestin21-410 11 1.2.2 Expression and purification of human CXCR71-362 15 1.2.3 Fluorescence detection SEC (FSEC) 15 1.2.4 Western blot 16 1.2.5 Isothermal titration calorimetry (ITC) 18 1.2.6 Crystallization and data collection 18 1.2.7 Structure determination and refinement 18 1.2.8 Hydrogen deuterium exchange mass spectrometry 22 1.3 Results 24 1.3.1 Generation and characterization of CXCR7 phosphopeptides 24 1.3.2 Mapping of phosphorylation sites on CXCR7 24 1.3.3 HDX-MS profiles of β-arrestin2 with or without co-incubation of C7pp 27 1.3.4 Crystal structure of rat β-arrestin21-356 in complex with CXCR7 phosphopeptide 29 1.3.5 Smaller inter-domain rotation of CXCR7-β-arrestin2 compared to V2Rpp-β-arrestin1 35 1.3.6 Distinct conformational changes of the loop regions in the C7pp-β-arrestin2 structure 42 1.3.7 Distinct binding modes of CXCR7 compared to other Rp-tails 45 1.3.8 Interaction of C7pp phosphopeptide with β-arrestin2 49 1.4 Discussions 56 1.5 References 57 Chapter2 65 2.1 Introduction 66 2.1.1 Biological role of cell-shape-determining proteins 66 2.1.2 Cell-shape-determining proteins from C. jejuni 66 2.2 Materials and Methods 70 2.2.1 Reaction of Pgp3 with synthetic peptidoglycans detected by liquid-chromatography mass spectrometry 70 2.2.2 Reaction of Pgp3 with sacculus 70 2.2.3 Protein expression and purification 70 2.2.4 Crystallization and data collection 75 2.2.5 Structure determination and refinement 77 2.2.6 Size-exclusion multi-angle light scattering 81 2.2.7 Computational modeling 81 2.3 Results 84 2.3.1 Pgp3 has D,D-carboxy- and D,D-endopeptidase activities 84 2.3.2 Crystal structure of Pgp3 with open and closed conformation 89 2.3.3 Domain architecture and structural comparisons 92 2.3.4 Crystal structure of H247A and H216A variants Pgp3 98 2.3.5 Crystal structures of Pgp3 in complex with substrates 103 2.3.6 Confirmation of oligomeric state of Pgp3 107 2.3.7 Structural insights into endolytic and exolytic reaction 109 2.3.8 The catalytic mechanism 111 2.3.9 Computational modeling of Pgp3 with a peptidoglycan 113 2.4 Discussions 118 2.5 References 119 국문 초록 124Docto

Il settore dell'olivicoltura da tavola in Italia: situazione e prospettive

The Italian table olive industry is almost completely located in the southern regions: Sicily and Apulia together account for about 2/3 of the entire national production. ‘Nocellara del Belice’,‘Nocellara etnea’, ‘Bella di Cerignola’ and ‘Ascolana tenera’ are the leading cultivars together with a large number of other local traditional varieties, often utilised for a double purpose (table olives and oil production). Although Italy is nowadays largely dependent (for about 60%) onto import from other Countries (mainly Spain, Greece and Morocco) the domestic production has been declining in the last thirty years and currently accounts for about 3-4% of the total world production against a value of about 10% of the period 1980/85. Nevertheless, some interesting examples of specialized production concentrations are still represented by the producing areas of the ‘Nocellara del Belice’, ‘Bella di Cerignola’ (syn. ‘Bella della Daunia’) and ‘Ascolana tenera’ which recently received the DOP (protected designation of origin) recognition. In this paper, besides the overall review of the Italian varietal platform and a brief description of the main cultivars, the advantages and the opportunities offered by the application of specialized cultural techniques are discussed, with special emphasis on the positive role of a more appropriate and wide diffusion of irrigation (including RDI) and chemical fruit thinning. Potential of other cultural techniques such as fertilization, pruning and pest and disease control are also reviewed with reference to the possible role in fruit quality enhancement together with the needs for further development of the entire table olive industry and the R&D involved