Endoscopic Anatomy of the Pterygopalatine Fossa and the Transpterygoid Approach: Development of a Surgical Instruction Model

Introduction: The pterygopalatine fossa (PPF) is a narrow space located between the posterior wall of the antrum and the pterygoid plates. Surgical access to the PPF is difficult because of its protected position and its complex neurovascular anatomy. Endonasal approaches using rod lens endoscopes, however, provide better visualization of this area and are associated with less morbidity than external approaches. Our aim was to develop a simple anatomical model using cadaveric specimens injected with intravascular colored silicone to demonstrate the endoscopic anatomy of the PPF. This model could be used for surgical instruction of the transpterygoid approach. Methods: We dissected six PPF in three cadaveric specimens prepared with intravascular injection of colored material using two different injection techniques. An endoscopic endonasal approach, including a wide nasoantral window and removal of the posterior antrum wall, provided access to the PPF. Results: We produced our best anatomical model injecting colored silicone via the common carotid artery. We found that, using an endoscopic approach, a retrograde dissection of the sphenopalatine artery helped to identify the internal maxillary artery (IMA) and its branches. Neural structures were identified deeper to the vascular elements. Notable anatomical landmarks for the endoscopic surgeon are the vidian nerve and its canal that leads to the petrous portion of the internal carotid artery (ICA), and the foramen rotundum, and V2 that leads to Meckel`s cave in the middle cranial fossa. These two nerves, vidian and V2, are separated by a pyramidal shaped bone and its apex marks the ICA. Conclusion: Our anatomical model provides the means to learn the endoscopic anatomy of the PPF and may be used for the simulation of surgical techniques. An endoscopic endonasal approach provides adequate exposure to all anatomical structures within the PPF. These structures may be used as landmarks to identify and control deeper neurovascular structures. The significance is that an anatomical model facilitates learning the surgical anatomy and the acquisition of surgical skills. A dissection superficial to the vascular structures preserves the neural elements. These nerves and their bony foramina, such as the vidian nerve and V2, are critical anatomical landmarks to identify and control the ICA at the skull base.

Behavioral Types for Embedded Software - A Survey

At present, there is a variety of formalisms for modeling and analyzing the communication behavior of components. Due to a tremendous increase in size and complexity of embedded systems accompanied by shorter time to market cycles and cost reduction, so called behavioral type systems become more and more important. This chapter presents an overview and a taxonomy of behavioral types. The intentions of this taxonomy are to provide a guidance for software engineers and to form the basis for future research.

Oral Hygiene Indirect Instruction and Periodic Reinforcements: Effects on Index Plaque in Schoolchildren

The aim of this study was to evaluate the effectiveness of the indirect instruction and the influence of the periodic reinforcement on the plaque index in schoolchildren. Forty schoolchildren aged from 7 to 9 years old were selected from a public school. After determining the initial O`Leary Plaque Index all schoolchildren were submitted to a program for oral hygiene through indirect instruction - ""The Smiling Robot"". The schoolchildren were divided into 2 groups: with and without motivation reinforcement. The index plaque exam was performed in both groups after 30, 60 and 90 days of the educational program. Comparing the groups, the plaque index decreasing could be observed in the group with reinforcement with statistically significant difference. For the group with reinforcement, statistically significant difference among the evaluations was found. For the group without reinforcement, significant decrease in the plaque index was found after 30 days when compared to the first, third and fourth evaluations. The indirect instruction with ""The Smiling Robot ""promoted a positive initial impact on the decrease of plaque index in the schoolchildren. The periodic reinforcements showed snore suitable results and significant reduction of the plaque index in the course of the evaluations.

Learning the dynamics of embedded clauses

Recent work by Siegelmann has shown that the computational power of recurrent neural networks matches that of Turing Machines. One important implication is that complex language classes (infinite languages with embedded clauses) can be represented in neural networks. Proofs are based on a fractal encoding of states to simulate the memory and operations of stacks. In the present work, it is shown that similar stack-like dynamics can be learned in recurrent neural networks from simple sequence prediction tasks. Two main types of network solutions are found and described qualitatively as dynamical systems: damped oscillation and entangled spiraling around fixed points. The potential and limitations of each solution type are established in terms of generalization on two different context-free languages. Both solution types constitute novel stack implementations - generally in line with Siegelmann's theoretical work - which supply insights into how embedded structures of languages can be handled in analog hardware.

A Wireless EEG Acquisition Platform based on Embedded Systems

This paper proposes a wireless EEG acquisition platform based on Open Multimedia Architecture Platform (OMAP) embedded system. A high-impedance active dry electrode was tested for improving the scalp- electrode interface. It was used the sigma-delta ADS1298 analog-to-digital converter, and developed a “kernelspace” character driver to manage the communications between the converter unit and the OMAP’s ARM core. The acquired EEG signal data is processed by a “userspace” application, which accesses the driver’s memory, saves the data to a SD-card and transmits them through a wireless TCP/IP-socket to a PC. The electrodes were tested through the alpha wave replacement phenomenon. The experimental results presented the expected alpha rhythm (8-13 Hz) reactiveness to the eyes opening task. The driver spends about 725 μs to acquire and store the data samples. The application takes about 244 μs to get the data from the driver and 1.4 ms to save it in the SD-card. A WiFi throughput of 12.8Mbps was measured which results in a transmission time of 5 ms for 512 kb of data. The embedded system consumes about 200 mAh when wireless off and 400 mAh when it is on. The system exhibits a reliable performance to record EEG signals and transmit them wirelessly. Besides the microcontroller-based architectures, the proposed platform demonstrates that powerful ARM processors running embedded operating systems can be programmed with real-time constrains at the kernel level in order to control hardware, while maintaining their parallel processing abilities in high level software applications.

Peer Instruction method in introductory math courses

Learning is not a spectator’s sport. Students do not learn much by just sitting in class listening their teachers, memorizing pre-packaged assignments and spitting out answers. The teaching-learning process has been a constant target of studies, particularly in Higher Education, in consequence of the annual increase of new students. The concern with maintaining a desired quality level in the training of these students, conjugated with the will to widen the access to all of those who finish Secondary School Education, has triggered a greater intervention from the education specialists, in partnership with the teachers of all Higher Education areas, in the analysis of this problem. Considering the particular case of Engineering, it has been witnessed a rising concern with the active learning strategies and forms of assessment. Research has demonstrated that students learn more if they are actively engaged with the material they are studying. In this presentation we describe, present and discuss the techniques and the results of Peer Instruction method in an introductory Calculus courses of an Engineering Bach

Reconfigurable SiC Embedded Photonic Structures with Self Optical Bias Control

Multilayered heterostructures based on embedded a-Si:H and a-SiC:H p-i-n filters are analyzed from differential voltage design perspective using short- and long-pass filters. The transfer functions characteristics are presented. A numerical simulation is presented to explain the filtering properties of the photonic devices. Several monochromatic pulsed lights, separately (input channels) or in a polychromatic mixture (multiplexed signal) at different bit rates, illuminated the device. Steady-state optical bias is superimposed from the front and the back side. Results show that depending on the wavelength of the external background and impinging side, the device acts either as a short- or a long-pass band filter or as a band-stop filter. Particular attention is given to the amplification coefficient weights, which allow to take into account the wavelength background effects when a band or frequency needs to be filtered or the gate switch, in which optical active filter gates are used to select and filter input signals to specific output ports in wavelength division multiplexing (WDM) communication systems. This nonlinearity provides the possibility for selective removal or addition of wavelengths. A truth table of an encoder that performs 8-to-1 MUX function exemplifies the optoelectronic conversion.

Scalable Unified Transform Architecture for Advanced Video Coding Embedded Systems

A novel high throughput and scalable unified architecture for the computation of the transform operations in video codecs for advanced standards is presented in this paper. This structure can be used as a hardware accelerator in modern embedded systems to efficiently compute all the two-dimensional 4 x 4 and 2 x 2 transforms of the H.264/AVC standard. Moreover, its highly flexible design and hardware efficiency allows it to be easily scaled in terms of performance and hardware cost to meet the specific requirements of any given video coding application. Experimental results obtained using a Xilinx Virtex-5 FPGA demonstrated the superior performance and hardware efficiency levels provided by the proposed structure, which presents a throughput per unit of area relatively higher than other similar recently published designs targeting the H.264/AVC standard. Such results also showed that, when integrated in a multi-core embedded system, this architecture provides speedup factors of about 120x concerning pure software implementations of the transform algorithms, therefore allowing the computation, in real-time, of all the above mentioned transforms for Ultra High Definition Video (UHDV) sequences (4,320 x 7,680 @ 30 fps).

A biosignal embedded system for physiological computing

Thesis submitted in the fulfilment of the requirements for the Degree of Master in Electronic and Telecomunications Engineering

Embedded platform for ECG biometric recognition

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Embedded System for ECG Biometrics

Comunication in Internationa Conference with Peer Review First International Congress on Cardiovasular Technologies - CARDIOTECHNIX, Vilamoura, Portugal, 2013

Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.