The health and nutritional status of multiethnic perimenopausal women

An integrated, dual-phase study design assessed the health and nutritional status and practices of African-American (A-A), Caribbean (A-C), and white non-Hispanic (W-A) women during perimenopause (40–55 years). During Phase I, four focus groups (n = 37) of male and female participants discussed the health and social implications of perimenopause. A conceptual framework for the main study (Phase II) was developed from the focus groups' findings, in concert with the main study's specific aims and objectives. ^ The main study, a cross-sectional survey, quantitatively assessed the health and nutritional status of a convenience sample of 109 women (25 A-A, 31 A-C and 53 W-A), who met specific eligibility criteria. Using seven instruments, sociodemographic, dietary, medical, reproductive health, health practice and anthropometric data were collected. ^ The groups were of comparable age, education, and socioeconomic status (SES). Despite these similarities, statistically significant interethnic nutritional status differences were found. Significantly more total energy and energy from fat were consumed by A-A than W-A and A-C women. Also, significantly more A-A and A-C than W-A women were overweight or obese with android-type weight patterning. ^ Overall, iron and calcium Recommended Dietary Allowances (RDA's) were not met by 35% and 68% of participants, respectively. Iron deficiency anemia was reported by 29% of participants while 33% reported heavier menstrual bleeding. Coupled with suboptimal iron intakes, this is likely to present a serious public health problem. Similarly, increased bone demineralization characteristic of perimenopause, coupled with suboptimal calcium intakes could precipitate another public health problem, osteoporosis. ^ Participants had different expectations about the role of medical care during perimenopause. Significantly more white (57%) than black (38% [A-A and AC]) women sought medical attention for symptoms. Whereas Hormone Replacement Therapy (HRT) was prescribed for 25% of them, only 13% were compliant at enrollment. ^ The trends and statistically significant findings of this study have huge public health policy implications. It is imperative that appropriate policies are formulated to ensure that America's ethnically diverse perimenopausal women have ready access to culturally appropriate care. This would optimize their health outcomes, and enhance their quality of life and productive capacities at this critical juncture of their lives. ^

A framework for transforming, analyzing, and realizing software designs in unified modeling language

Unified Modeling Language (UML) is the most comprehensive and widely accepted object-oriented modeling language due to its multi-paradigm modeling capabilities and easy to use graphical notations, with strong international organizational support and industrial production quality tool support. However, there is a lack of precise definition of the semantics of individual UML notations as well as the relationships among multiple UML models, which often introduces incomplete and inconsistent problems for software designs in UML, especially for complex systems. Furthermore, there is a lack of methodologies to ensure a correct implementation from a given UML design. The purpose of this investigation is to verify and validate software designs in UML, and to provide dependability assurance for the realization of a UML design.^ In my research, an approach is proposed to transform UML diagrams into a semantic domain, which is a formal component-based framework. The framework I proposed consists of components and interactions through message passing, which are modeled by two-layer algebraic high-level nets and transformation rules respectively. In the transformation approach, class diagrams, state machine diagrams and activity diagrams are transformed into component models, and transformation rules are extracted from interaction diagrams. By applying transformation rules to component models, a (sub)system model of one or more scenarios can be constructed. Various techniques such as model checking, Petri net analysis techniques can be adopted to check if UML designs are complete or consistent. A new component called property parser was developed and merged into the tool SAM Parser, which realize (sub)system models automatically. The property parser generates and weaves runtime monitoring code into system implementations automatically for dependability assurance. The framework in the investigation is creative and flexible since it not only can be explored to verify and validate UML designs, but also provides an approach to build models for various scenarios. As a result of my research, several kinds of previous ignored behavioral inconsistencies can be detected.^

Knowledge assisted data management and retrieval in multimedia database systems

With the proliferation of multimedia data and ever-growing requests for multimedia applications, there is an increasing need for efficient and effective indexing, storage and retrieval of multimedia data, such as graphics, images, animation, video, audio and text. Due to the special characteristics of the multimedia data, the Multimedia Database management Systems (MMDBMSs) have emerged and attracted great research attention in recent years. Though much research effort has been devoted to this area, it is still far from maturity and there exist many open issues. In this dissertation, with the focus of addressing three of the essential challenges in developing the MMDBMS, namely, semantic gap, perception subjectivity and data organization, a systematic and integrated framework is proposed with video database and image database serving as the testbed. In particular, the framework addresses these challenges separately yet coherently from three main aspects of a MMDBMS: multimedia data representation, indexing and retrieval. In terms of multimedia data representation, the key to address the semantic gap issue is to intelligently and automatically model the mid-level representation and/or semi-semantic descriptors besides the extraction of the low-level media features. The data organization challenge is mainly addressed by the aspect of media indexing where various levels of indexing are required to support the diverse query requirements. In particular, the focus of this study is to facilitate the high-level video indexing by proposing a multimodal event mining framework associated with temporal knowledge discovery approaches. With respect to the perception subjectivity issue, advanced techniques are proposed to support users' interaction and to effectively model users' perception from the feedback at both the image-level and object-level.

Estimation and prediction of average vehicle occupancies using traffic accident records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver’s age, and driver’s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Life cycle of Deccan trap magma chambers: A crystal scale elemental and strontium isotopic investigation

The Deccan Trap basalts are the remnants of a massive series of lava flows that erupted at the K/T boundary and covered 1-2 million km2 of west-central India. This eruptive event is of global interest because of its possible link to the major mass extinction event, and there is much debate about the duration of this massive volcanic event. In contrast to isotopic or paleomagnetic dating methods, I explore an alternative approach to determine the lifecycle of the magma chambers that supplied the lavas, and extend the concept to obtain a tighter constraint on Deccan’s duration. My method relies on extracting time information from elemental and isotopic diffusion across zone boundaries in individual crystals. I determined elemental and Sr-isotopic variations across abnormally large (2-5 cm) plagioclase crystals from the Thalghat and Kashele “Giant Plagioclase Basalts” from the lowermost Jawhar and Igatpuri Formations respectively in the thickest Western Ghats section near Mumbai. I also obtained bulk rock major, trace and rare earth element chemistry of each lava flow from the two formations. Thalghat flows contain only 12% zoned crystals, with 87 Sr/86Sr ratios of 0.7096 in the core and 0.7106 in the rim, separated by a sharp boundary. In contrast, all Kashele crystals have a wider range of 87Sr/86Sr values, with multiple zones. Geochemical modeling of the data suggests that the two types of crystals grew in distinct magmatic environments. Modeling intracrystalline diffusive equilibration between the core and rim of Thalghat crystals led me to obtain a crystal growth rate of 2.03x10-10 cm/s and a residence time of 780 years for the crystals in the magma chamber(s). Employing some assumptions based on field and geochronologic evidence, I extrapolated this residence time to the entire Western Ghats and obtained an estimate of 25,000–35,000 years for the duration of Western Ghats volcanism. This gave an eruptive rate of 30–40 km3/yr, which is much higher than any presently erupting volcano. This result will remain speculative until a similarly detailed analytical-modeling study is performed for the rest of the Western Ghats formations.

Improving resource management in virtualized data centers using application performance models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity.^ We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. ^ This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.^

Ensemble Stream Model for Data-Cleaning in Sensor Networks

Ensemble Stream Modeling and Data-cleaning are sensor information processing systems have different training and testing methods by which their goals are cross-validated. This research examines a mechanism, which seeks to extract novel patterns by generating ensembles from data. The main goal of label-less stream processing is to process the sensed events to eliminate the noises that are uncorrelated, and choose the most likely model without over fitting thus obtaining higher model confidence. Higher quality streams can be realized by combining many short streams into an ensemble which has the desired quality. The framework for the investigation is an existing data mining tool. First, to accommodate feature extraction such as a bush or natural forest-fire event we make an assumption of the burnt area (BA*), sensed ground truth as our target variable obtained from logs. Even though this is an obvious model choice the results are disappointing. The reasons for this are two: One, the histogram of fire activity is highly skewed. Two, the measured sensor parameters are highly correlated. Since using non descriptive features does not yield good results, we resort to temporal features. By doing so we carefully eliminate the averaging effects; the resulting histogram is more satisfactory and conceptual knowledge is learned from sensor streams. Second is the process of feature induction by cross-validating attributes with single or multi-target variables to minimize training error. We use F-measure score, which combines precision and accuracy to determine the false alarm rate of fire events. The multi-target data-cleaning trees use information purity of the target leaf-nodes to learn higher order features. A sensitive variance measure such as ƒ-test is performed during each node's split to select the best attribute. Ensemble stream model approach proved to improve when using complicated features with a simpler tree classifier. The ensemble framework for data-cleaning and the enhancements to quantify quality of fitness (30% spatial, 10% temporal, and 90% mobility reduction) of sensor led to the formation of streams for sensor-enabled applications. Which further motivates the novelty of stream quality labeling and its importance in solving vast amounts of real-time mobile streams generated today.

“Namastey London”: Bollywood Movies and Their Impact on how Indians Perceive European Destinations

The aim of this study is to analyze the perception of European destinations through the eyes of Indian Bollywood film viewers to determine how perception is influenced by what is viewed in films. Researchers surveyed Indian consumers and collected 670 usable surveys. European destinations were divided into top five and bottom five destinations for Indian tourists, and data was then compared to world tourism statistics. Results indicate differences in destination preference among Bollywood viewers and worldwide tourist trends. Findings indicate that prominently featuring a landscape within Bollywood films can significantly impact Indians’ perception on the destinations’ image. European countries frequently portrayed in films have higher marks on multiple perception categories than those not featured in blockbuster Bollywood films.

Advanced methodologies in dynamic traffic assignment modeling of managed lanes

Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. ^ Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. ^ Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. ^ With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.^

Positive Effects of Peer Modeling and Positive Reinforcement on Healthy Food Intake in Elementary School Children

The current study aims to discover the effects of “Food Dudes” peer modeling videos and positive reinforcement on vegetable consumption using a delayed multiple baseline design across subjects. Results suggest peer modeling and positive reinforcement as effective means to increase vegetable intake.

Experimental and Analytical Methodologies for Predicting Peak Loads on Building Envelopes and Roofing Systems

The performance of building envelopes and roofing systems significantly depends on accurate knowledge of wind loads and the response of envelope components under realistic wind conditions. Wind tunnel testing is a well-established practice to determine wind loads on structures. For small structures much larger model scales are needed than for large structures, to maintain modeling accuracy and minimize Reynolds number effects. In these circumstances the ability to obtain a large enough turbulence integral scale is usually compromised by the limited dimensions of the wind tunnel meaning that it is not possible to simulate the low frequency end of the turbulence spectrum. Such flows are called flows with Partial Turbulence Simulation. In this dissertation, the test procedure and scaling requirements for tests in partial turbulence simulation are discussed. A theoretical method is proposed for including the effects of low-frequency turbulences in the post-test analysis. In this theory the turbulence spectrum is divided into two distinct statistical processes, one at high frequencies which can be simulated in the wind tunnel, and one at low frequencies which can be treated in a quasi-steady manner. The joint probability of load resulting from the two processes is derived from which full-scale equivalent peak pressure coefficients can be obtained. The efficacy of the method is proved by comparing predicted data derived from tests on large-scale models of the Silsoe Cube and Texas-Tech University buildings in Wall of Wind facility at Florida International University with the available full-scale data. For multi-layer building envelopes such as rain-screen walls, roof pavers, and vented energy efficient walls not only peak wind loads but also their spatial gradients are important. Wind permeable roof claddings like roof pavers are not well dealt with in many existing building codes and standards. Large-scale experiments were carried out to investigate the wind loading on concrete pavers including wind blow-off tests and pressure measurements. Simplified guidelines were developed for design of loose-laid roof pavers against wind uplift. The guidelines are formatted so that use can be made of the existing information in codes and standards such as ASCE 7-10 on pressure coefficients on components and cladding.

Estimation and Prediction of Average Vehicle Occupancies using Traffic Accident Records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver¡¯s age, and driver¡¯s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Fuzzy Modeling and Control Based Virtual Machine Resource Management

Virtual machines (VMs) are powerful platforms for building agile datacenters and emerging cloud systems. However, resource management for a VM-based system is still a challenging task. First, the complexity of application workloads as well as the interference among competing workloads makes it difficult to understand their VMs’ resource demands for meeting their Quality of Service (QoS) targets; Second, the dynamics in the applications and system makes it also difficult to maintain the desired QoS target while the environment changes; Third, the transparency of virtualization presents a hurdle for guest-layer application and host-layer VM scheduler to cooperate and improve application QoS and system efficiency. This dissertation proposes to address the above challenges through fuzzy modeling and control theory based VM resource management. First, a fuzzy-logic-based nonlinear modeling approach is proposed to accurately capture a VM’s complex demands of multiple types of resources automatically online based on the observed workload and resource usages. Second, to enable fast adaption for resource management, the fuzzy modeling approach is integrated with a predictive-control-based controller to form a new Fuzzy Modeling Predictive Control (FMPC) approach which can quickly track the applications’ QoS targets and optimize the resource allocations under dynamic changes in the system. Finally, to address the limitations of black-box-based resource management solutions, a cross-layer optimization approach is proposed to enable cooperation between a VM’s host and guest layers and further improve the application QoS and resource usage efficiency. The above proposed approaches are prototyped and evaluated on a Xen-based virtualized system and evaluated with representative benchmarks including TPC-H, RUBiS, and TerraFly. The results demonstrate that the fuzzy-modeling-based approach improves the accuracy in resource prediction by up to 31.4% compared to conventional regression approaches. The FMPC approach substantially outperforms the traditional linear-model-based predictive control approach in meeting application QoS targets for an oversubscribed system. It is able to manage dynamic VM resource allocations and migrations for over 100 concurrent VMs across multiple hosts with good efficiency. Finally, the cross-layer optimization approach further improves the performance of a virtualized application by up to 40% when the resources are contended by dynamic workloads.

Expressão geofísica-estrutural do lineamento transbrasiliano na porção central da Bacia do Parnaíba (Maranhão-Piauí)

The objective of this study was to characterize the structural-geophysical expression of the Transbrasiliano Lineament (TBL) in the east-central portion of the Parnaíba Basin. The TBL corresponds to a major Neoproterozoic NE-trending shear zone related to the Brasiliano orogenic cycle, with dextral strike-slip kinematics, underlying (but also laterally exposed in the NE and SW basin edges) the sedimentary section of the Parnaíba Basin. In this study, the interpretation of gravity and magnetic anomaly maps is consistent with the TBL kinematics, the signature of the geophysical anomalies corresponding to the high (plastic behaviour) and subsequent declining temperature (ductile to brittle behaviour) stages during Brasiliano and late Brasiliano times. The pattern of residual gravity anomalies is compatible with an S-C dextral pair shaping the geological bodies of an heterogeneous basement, such as slices of gneisses and granulites (positive anomalies), granitic and low-medium grade metasedimentary rocks (negative anomalies). Such anomalies curvilinear trends, ranging from NNE (interpreted as S surfaces) to NE (C surfaces), correspond to flattening surfaces (S), while the NE rectilinear trend must represent a C band. The narrower magnetic anomalies also display NNE to NE (S surfaces) trends and should correspond to similar (although narrower and more discontinuous) sources in the equivalent anomaly patterns. Pre-Silurian pull-apart style grabens may contribute to the NE negative gravimetric anomalies, although this interpretation demands control by seismic data analysis. On the other hand, the curvilinear anomalies associated to contractional trends are incompatible with their interpretation as pre-Silurian graben, in both maps. In the (reduced to the pole) magnetic anomalies map, most of these are again associated to low-temperature shear zones (C planes) and faults, juxtaposing distinct blocks in terms of magnetic properties, or eventually filled with basic bodies. It is also possible that some isolated magnetic anomalies correspond to igneous bodies of late-Brasiliano or Mesozoic age. The basement late discontinuities pattern can be interpreted in analogy to the Riedel fractures model, with steep dipping surfaces and a sub-horizontal movement section. This study also explored 2D gravity modeling controlled by the interpretation of a dip seismic line as regards to the Transbrasiliano Lineament. The rock section equivalent to the Jaibaras Group occupying a graben structure (as identified in the seismic line) corresponds to a discrete negative anomaly superimposed to a gravimetric high, once again indicating a stronger influence of older crystalline basement rocks as gravimetric sources, mainly reflecting the heterogeneities and anisotropies generated at high temperature conditions and their subsequent cooling along the TBL, during the Brasiliano cycle.

Expressão geofísica-estrutural do lineamento transbrasiliano na porção central da Bacia do Parnaíba (Maranhão-Piauí)

The objective of this study was to characterize the structural-geophysical expression of the Transbrasiliano Lineament (TBL) in the east-central portion of the Parnaíba Basin. The TBL corresponds to a major Neoproterozoic NE-trending shear zone related to the Brasiliano orogenic cycle, with dextral strike-slip kinematics, underlying (but also laterally exposed in the NE and SW basin edges) the sedimentary section of the Parnaíba Basin. In this study, the interpretation of gravity and magnetic anomaly maps is consistent with the TBL kinematics, the signature of the geophysical anomalies corresponding to the high (plastic behaviour) and subsequent declining temperature (ductile to brittle behaviour) stages during Brasiliano and late Brasiliano times. The pattern of residual gravity anomalies is compatible with an S-C dextral pair shaping the geological bodies of an heterogeneous basement, such as slices of gneisses and granulites (positive anomalies), granitic and low-medium grade metasedimentary rocks (negative anomalies). Such anomalies curvilinear trends, ranging from NNE (interpreted as S surfaces) to NE (C surfaces), correspond to flattening surfaces (S), while the NE rectilinear trend must represent a C band. The narrower magnetic anomalies also display NNE to NE (S surfaces) trends and should correspond to similar (although narrower and more discontinuous) sources in the equivalent anomaly patterns. Pre-Silurian pull-apart style grabens may contribute to the NE negative gravimetric anomalies, although this interpretation demands control by seismic data analysis. On the other hand, the curvilinear anomalies associated to contractional trends are incompatible with their interpretation as pre-Silurian graben, in both maps. In the (reduced to the pole) magnetic anomalies map, most of these are again associated to low-temperature shear zones (C planes) and faults, juxtaposing distinct blocks in terms of magnetic properties, or eventually filled with basic bodies. It is also possible that some isolated magnetic anomalies correspond to igneous bodies of late-Brasiliano or Mesozoic age. The basement late discontinuities pattern can be interpreted in analogy to the Riedel fractures model, with steep dipping surfaces and a sub-horizontal movement section. This study also explored 2D gravity modeling controlled by the interpretation of a dip seismic line as regards to the Transbrasiliano Lineament. The rock section equivalent to the Jaibaras Group occupying a graben structure (as identified in the seismic line) corresponds to a discrete negative anomaly superimposed to a gravimetric high, once again indicating a stronger influence of older crystalline basement rocks as gravimetric sources, mainly reflecting the heterogeneities and anisotropies generated at high temperature conditions and their subsequent cooling along the TBL, during the Brasiliano cycle.