Auriculo-condylar syndrome: mapping of a first locus and evidence for genetic heterogeneity

Auriculo-condylar syndrome (ACS), an autosomal dominant disorder of first and second pharyngeal arches, is characterized by malformed ears (`question mark ears`), prominent cheeks, microstomia, abnormal temporomandibular joint, and mandibular condyle hypoplasia. Penetrance seems to be complete, but there is high inter-and intra-familial phenotypic variation, with no evidence of genetic heterogeneity. We herein describe a new multigeneration family with 11 affected individuals (F1), in whom we confirm intra-familial clinical variability. Facial asymmetry, a clinical feature not highlighted in other ACS reports, was highly prevalent among the patients reported here. The gene responsible for ACS is still unknown and its identification will certainly contribute to the understanding of human craniofacial development. No chromosomal rearrangements have been associated with ACS, thus mapping and positional cloning is the best approach to identify this disease gene. To map the ACS gene, we conducted linkage analysis in two large ACS families, F1 and F2 (F2; reported elsewhere). Through segregation analysis, we first excluded three known loci associated with disorders of first and second pharyngeal arches (Treacher Collins syndrome, oculo-auriculo-vertebral spectrum, and Townes-Brocks syndrome). Next, we performed a wide genome search and we observed evidence of linkage to 1p21.1-q23.3 in F2 (LOD max 3.01 at theta = 0). Interestingly, this locus was not linked to the phenotype segregating in F1. Therefore, our results led to the mapping of a first locus of ACS (ACS1) and also showed evidence for genetic heterogeneity, suggesting that there are at least two loci responsible for this phenotype.

Semantic mapping using mobile robots

Robotic mapping is the process of automatically constructing an environment representation using mobile robots. We address the problem of semantic mapping, which consists of using mobile robots to create maps that represent not only metric occupancy but also other properties of the environment. Specifically, we develop techniques to build maps that represent activity and navigability of the environment. Our approach to semantic mapping is to combine machine learning techniques with standard mapping algorithms. Supervised learning methods are used to automatically associate properties of space to the desired classification patterns. We present two methods, the first based on hidden Markov models and the second on support vector machines. Both approaches have been tested and experimentally validated in two problem domains: terrain mapping and activity-based mapping.

Structural aspects of the fermion-boson mapping in two-dimensional gauge and anomalous gauge theories with massive fermions

Using a synthesis of the functional integral and operator approaches we discuss the fermion-buson mapping and the role played by the Bose field algebra in the Hilbert space of two-dimensional gauge and anomalous gauge field theories with massive fermions. In QED, with quartic self-interaction among massive fermions, the use of an auxiliary vector field introduces a redundant Bose field algebra that should not be considered as an element of the intrinsic algebraic structure defining the model. In anomalous chiral QED, with massive fermions the effect of the chiral anomaly leads to the appearance in the mass operator of a spurious Bose field combination. This phase factor carries no fermion selection rule and the expected absence of Theta-vacuum in the anomalous model is displayed from the operator solution. Even in the anomalous model with massive Fermi fields, the introduction of the Wess-Zumino field replicates the theory, changing neither its algebraic content nor its physical content. (C) 2002 Elsevier B.V. (USA).

Classification and characterization of places for mapping of environment using hierarchical neural network and omnivision

Mobile robots need autonomy to fulfill their tasks. Such autonomy is related whith their capacity to explorer and to recognize their navigation environments. In this context, the present work considers techniques for the classification and extraction of features from images, using artificial neural networks. This images are used in the mapping and localization system of LACE (Automation and Evolutive Computing Laboratory) mobile robot. In this direction, the robot uses a sensorial system composed by ultrasound sensors and a catadioptric vision system equipped with a camera and a conical mirror. The mapping system is composed of three modules; two of them will be presented in this paper: the classifier and the characterizer modules. Results of these modules simulations are presented in this paper.

Analysis of floristic composition and structure as an aid to monitoring protected areas of dense rain forest in southeastern Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Clarifications on breakpoints in HSAX and BTAX by comparative mapping of F9, HPRT, and XIST in cattle

The coagulation factor IX gene (179), the hypoxanthine phosphoribosyl transferase 1 gene (HPRT1), and the X-inactive specific transcript gene (XIST) were physically assigned in cattle to analyze chromosomal breakpoints on BTAX recently identified by radiation hybrid (RH) mapping experiments. Whereas the FISH assignment of XIST indicates a similar location on the q-arm of the human and cattle X chromosomes, the locus of HPRT1 supported the assumption of a chromosome rearrangement between the distal half of the q-arm of HSAX and the p-arm of BTAX identified by RH mapping. F9 previously located on the Cl-arm of BTAX was assigned to the p-arm of BTAX using RH mapping and FISH. The suggested new position of F9 close to HPRT I supports the homology between HSAXq and BTAXp. The F9 locus corresponds with the gene order found in the homologous human chromosome segment. XIST was assigned on BTAXq23, HPRT1 and F9 were mapped to BTAXp22, and the verification of the location of F9 in a 5000 rad cattle-hamster whole genome radiation hybrid panel linked the gene to markers URB10 and HPRT1. Copyright (C) 2003 S. Karger AG, Basel.

Environment mapping for mobile robots navigation using hierarchical neural network and omnivision

Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.

Improving a process in a brazilian automotive plant applying process mapping, Design of Experiments and Discrete Events Simulation

The objective of this article is to apply the Design of Experiments technique along with the Discrete Events Simulation technique in an automotive process. The benefits of the design of experiments in simulation include the possibility to improve the performance in the simulation process, avoiding trial and error to seek solutions. The methodology of the conjoint use of Design of Experiments and Computer Simulation is presented to assess the effects of the variables and its interactions involved in the process. In this paper, the efficacy of the use of process mapping and design of experiments on the phases of conception and analysis are confirmed.

The status of millennium development goals: monitoring and reporting in selected Caribbean countries

In spite of various initiatives, Caribbean countries continue to have difficulties in addressing demands of monitoring and measuring progress towards the fulfilment of the Millennium Development Goals (MDGs) and other Internationally Agreed upon Development Goals (IADGs)1. To address this gap, the Economic Commission for Latin America and the Caribbean (ECLAC) has received funding for a technical assistance project, Strengthening the capacity of National Statistical Offices (NSOs) in the Caribbean Small Island Developing States to fulfil the Millennium Development Goals and other Internationally Agreed Development Goals (IADGs). The main imperative of the project is to support the strengthening of national institutional capabilities for generating reliable data to meet these monitoring and reporting requirements. The project seeks to build on past and current initiatives directed towards broadening and improving statistics and indicators through the use of already available knowledge, experience and expertise at the national and regional level. In an effort to avoid duplication of present or repetition of past activities in this field, ECLAC considered it important to conduct a thorough assessment of the status and structure of MDG and IADG monitoring and reporting at the national and regional levels as well as to provide an overview of initiatives undertaken by other regional development partners and intergovernmental bodies in the subregion. This paper is composed as follows: The first chapter of the document will present an overview of the statistical infrastructure at the national level, followed by a summary of the results of a survey administered to Caribbean NSOs that gathered information on the status of and mechanisms in place in MDG and IADG monitoring and reporting at the national level. Then, an attempt will be made to provide a briefing on activities carried out by intergovernmental bodies and development partners in the region. The fourth section presents a brief summary of data sources for secondary data and introduces concepts for metadata collection and reporting. It further discusses major challenges with poverty measurements and monitoring in the subregion. The paper ends with a summary and recommendations for the way forward.

Physical mapping of 18S rDNA and heterochromatin in species of family Lygaeidae (Hemiptera: Heteroptera)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Ecological and toxicological responses in a multistressor scenario: are monitoring programs showing the stressors or just showing stress? A case study in Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genetic Variability of Beauveria bassiana and a DNA Marker for Environmental Monitoring of a Highly Virulent Isolate Against Cosmopolites sordidus

The banana weevil Cosmopolites sordidus (Germar) is one of a number of pests that attack banana crops. The use of the entomopathogenic fungus Beauveria bassiana as a biological control agent for this pest may contribute towards reducing the application of chemical insecticides on banana crops. In this study, the genetic variability of a collection of Brazilian isolates of B. bassiana was evaluated. Samples were obtained from various geographic regions of Brazil, and from different hosts of the Curculionidae family. Based on the DNA fingerprints generated by RAPD and AFLP, we found that 92 and 88 % of the loci were polymorphic, respectively. The B. bassiana isolates were attributed to two genotypic clusters based on the RAPD data, and to three genotypic clusters, when analyzed with AFLP. The nucleotide sequences of nuclear ribosomal DNA intergenic spacers confirmed that all isolates are in fact B. bassiana. Analysis of molecular variance showed that variability among the isolates was not correlated with geographic origin or hosts. A RAPD-specific marker for isolate CG 1024, which is highly virulent to C. sordidus, was cloned and sequenced. Based on the sequences obtained, specific PCR primers BbasCG1024F (5'-TGC GGC TGA GGA GGA CT-3') and BbasCG1024R (5'-TGC GGC TGA GTG TAG AAC-3') were designed for detecting and monitoring this isolate in the field.

Yield mapping, soil fertility and tree gaps in an orange orchard

The current high competition on Citrus industry demands from growers new management technologies for superior efficiency and sustainability. In this context, precision agriculture (PA) has developed techniques based on yield mapping and management systems that recognize field spatial variability, which contribute to increase profitability of commercial crops. Because spatial variability is often not perceived the orange orchards are still managed as uniform and adoption of PA technology on citrus farms is low. Thus, the objective of the present study was to characterize the spatial variability of three factors: fruit yield, soil fertility and occurrence of plant gaps caused by either citrus blight or huanglongbing (HLB) in a commercial Valencia orchard in Brotas, São Paulo State, Brazil. Data from volume, geographic coordinates and representative area of the bags used on harvest were recorded to generate yield points that were then interpolated to produce the yield map. Soil chemical characteristics were studied by analyzing samples collected along planting rows and inter-rows in 24 points distributed in the field. A map of density of tree gaps was produced by georeferencing individual gaps and later by counting the number of gaps within 500 m² cells. Data were submitted to statistical and geostatistical analyses. A t test was used to compare means of soil chemical characteristics between sampling regions. High variation on yield and density of tree gaps was observed from the maps. It was also demonstrated overlapping regions of high density of plant absence and low fruit yield. Soil fertility varied depending on the sampling region in the orchard. The spatial variability found on yield, soil fertility and on disease occurrence demonstrated the importance to adopt site specific nutrient management and disease control as tools to guarantee efficiency of fruit production.

The use of remote sensing imagery for monitoring recovery in the aftermath of a natural disaster: the Hurricane Katrina Case

Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.

Slope stability analysis by multi-temporal DEMs and 3D modelling: The 2002 and 2007 Stromboli landslide events

Natural hazard related to the volcanic activity represents a potential risk factor, particularly in the vicinity of human settlements. Besides to the risk related to the explosive and effusive activity, the instability of volcanic edifices may develop into large landslides often catastrophically destructive, as shown by the collapse of the northern flank of Mount St. Helens in 1980. A combined approach was applied to analyse slope failures that occurred at Stromboli volcano. SdF slope stability was evaluated by using high-resolution multi-temporal DTMMs and performing limit equilibrium stability analyses. High-resolution topographical data collected with remote sensing techniques and three-dimensional slope stability analysis play a key role in understanding instability mechanism and the related risks. Analyses carried out on the 2002–2003 and 2007 Stromboli eruptions, starting from high-resolution data acquired through airborne remote sensing surveys, permitted the estimation of the lava volumes emplaced on the SdF slope and contributed to the investigation of the link between magma emission and slope instabilities. Limit Equilibrium analyses were performed on the 2001 and 2007 3D models, in order to simulate the slope behavior before 2002-2003 landslide event and after the 2007 eruption. Stability analyses were conducted to understand the mechanisms that controlled the slope deformations which occurred shortly after the 2007 eruption onset, involving the upper part of slope. Limit equilibrium analyses applied to both cases yielded results which are congruent with observations and monitoring data. The results presented in this work undoubtedly indicate that hazard assessment for the island of Stromboli should take into account the fact that a new magma intrusion could lead to further destabilisation of the slope, which may be more significant than the one recently observed because it will affect an already disarranged deposit and fractured and loosened crater area. The two-pronged approach based on the analysis of 3D multi-temporal mapping datasets and on the application of LE methods contributed to better understanding volcano flank behaviour and to be prepared to undertake actions aimed at risk mitigation.