Optimal workloop energetics of muscle-actuated systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.Includes bibliographical references (p. 117-122).Skeletal muscles are the primary actuators that power, stabilize and control locomotive and functional motor tasks in biological systems. It is well known that coordinated action and co-activation of multiple muscles give rise to desirable effects such as enhanced postural and dynamic stability. In this thesis, we study the role of muscle co-activation from an energetics perspective: Are there situations in which antagonist co-activation leads to enhanced power generation, and if so, what is the underlying mechanism? The mechanical energetics of muscles are traditionally characterized in terms of workloop measures where muscles are activated against oscillating, zero-admittance motion sources. We extend these measures to more natural, "mid-range" admittance loads, actuated by multiple muscles. Specifically, we set up the problem of a second-order mechanical system driven by a pair of antagonist muscles. This is the simplest problem where the influences of load dynamics and muscle co-activation on the output energetics may be investigated. To enable experimentation, a muscle testing apparatus capable of real-time servo emulation of the load is developed and utilized for identification and workloop measurements.(cont.) Using this apparatus, an experimentally identified model predicting muscle contractile force is proposed. Experimental data shows that with a simple Weiner structure, the model accounts for 74% (sigma = 5.6%) of the variance in muscle force, that force dependence on contraction velocity is minimal, and that a bilinear approximation of the output nonlinearity is warranted. Based on this model we investigate what electrical stimulation input gives rise to maximal power transfer for a particular load. This question is cast in an optimal control framework. Necessary conditions for optimality are derived and methods for computing solutions are presented. Solutions demonstrate that the optimal stimulation frequencies must include the effects of muscle impedances, and that optimal co-activation levels are indeed modulated to enable a pair of muscles to produce more work synergistically rather than individually. Pilot experimental data supporting these notions is presented. Finally, we interpret these results in the context of the familiar engineering notion of impedance matching. These results shed new light on the role of antagonist co-activation from an energetics perspective.by Walled A. Farahat.Ph.D

Sphenopalatine ganglion block for treatment of post dural puncture headache: Review article

Background: Post-Dural puncture headache (PDPH) is a consequence of spinal and epidural anesthesia. The gold standard for its treatment is epidural blood patch. Sphenopalatine ganglion block (SPGB) has been proposed as a non-invasive intervention with minimal adverse effect. Objective: The aim of this study was to assess the efficacy of sphenopalatine ganglion block for treatment of post-dural puncture headache. Methods: The databases were searched for articles published in English in 3 data bases [PubMed – Google scholar and Egyptian bank of knowledge] and Boolean operators had been used such as [Sphenopalatine ganglion block and post dural puncture headache] and in reviewed articles. Conclusion: SPGB is an effective initial modality for managing severe headache in patients with PDPH

Effect of different pretreatments on egyptian sugar-cane bagasse saccharification and bioethanol production

AbstractSugar-cane processing generates large amount of bagasse. Disposal of bagasse is critical for both agricultural profitability and environmental protection. Sugar-cane bagasse is a renewable resource that can be used to produce ethanol.In this study, twelve microbial isolates, five bacteria, four yeasts and three filamentous fungi were isolated from sugar-cane bagasse. Bacterial and yeast isolates were selected for their ability to utilize different sugars and cellulose. Chipped and ground bagasse was subjected to different pretreatment methods; physically through steam treatment by autoclaving at 121°C and 1.5bar for 20min and/or different doses of gamma γ irradiation (50 and 70Mrad). Autoclaved pretreated bagasse was further biologically treated through the solid state fermentation process by different fungal isolates; F-66, F-94 and F-98 producing maximum total reducing sugars of 18.4., 26.1 and 20.4g/L, respectively.Separate biological hydrolysis and fermentation (SHF) process for bagasse was done by the two selected fungal isolates; Trichoderma viride F-94 and Aspergillus terreus F-98 and the two yeast isolates identified as Candida tropicalis Y-26 and Saccharomyces cerevisiae Y-39. SHF processes by F-94 and Y-26 produced 226kg of ethanol/ton bagasse while that of F-98 and Y-39 produced 185kg of ethanol/ton bagasse

Development of the Arabic Voice Pathology Database and Its Evaluation by Using Speech Features and Machine Learning Algorithms

A voice disorder database is an essential element in doing research on automatic voice disorder detection and classification. Ethnicity affects the voice characteristics of a person, and so it is necessary to develop a database by collecting the voice samples of the targeted ethnic group. This will enhance the chances of arriving at a global solution for the accurate and reliable diagnosis of voice disorders by understanding the characteristics of a local group. Motivated by such idea, an Arabic voice pathology database (AVPD) is designed and developed in this study by recording three vowels, running speech, and isolated words. For each recorded samples, the perceptual severity is also provided which is a unique aspect of the AVPD. During the development of the AVPD, the shortcomings of different voice disorder databases were identified so that they could be avoided in the AVPD. In addition, the AVPD is evaluated by using six different types of speech features and four types of machine learning algorithms. The results of detection and classification of voice disorders obtained with the sustained vowel and the running speech are also compared with the results of an English-language disorder database, the Massachusetts Eye and Ear Infirmary (MEEI) database

An Investigation of Multidimensional Voice Program Parameters in Three Different Databases for Voice Pathology Detection and Classification

Background and Objective Automatic voice-pathology detection and classification systems may help clinicians to detect the existence of any voice pathologies and the type of pathology from which patients suffer in the early stages. The main aim of this paper is to investigate Multidimensional Voice Program (MDVP) parameters to automatically detect and classify the voice pathologies in multiple databases, and then to find out which parameters performed well in these two processes. Materials and Methods Samples of the sustained vowel /a/ of normal and pathological voices were extracted from three different databases, which have three voice pathologies in common. The selected databases in this study represent three distinct languages: (1) the Arabic voice pathology database; (2) the Massachusetts Eye and Ear Infirmary database (English database); and (3) the Saarbruecken Voice Database (German database). A computerized speech lab program was used to extract MDVP parameters as features, and an acoustical analysis was performed. The Fisher discrimination ratio was applied to rank the parameters. A t test was performed to highlight any significant differences in the means of the normal and pathological samples. Results The experimental results demonstrate a clear difference in the performance of the MDVP parameters using these databases. The highly ranked parameters also differed from one database to another. The best accuracies were obtained by using the three highest ranked MDVP parameters arranged according to the Fisher discrimination ratio: these accuracies were 99.68%, 88.21%, and 72.53% for the Saarbruecken Voice Database, the Massachusetts Eye and Ear Infirmary database, and the Arabic voice pathology database, respectively

Intra- and Inter-database Study for Arabic, English, and German Databases:Do Conventional Speech Features Detect Voice Pathology?

A large population around the world has voice complications. Various approaches for subjective and objective evaluations have been suggested in the literature. The subjective approach strongly depends on the experience and area of expertise of a clinician, and human error cannot be neglected. On the other hand, the objective or automatic approach is noninvasive. Automatic developed systems can provide complementary information that may be helpful for a clinician in the early screening of a voice disorder. At the same time, automatic systems can be deployed in remote areas where a general practitioner can use them and may refer the patient to a specialist to avoid complications that may be life threatening. Many automatic systems for disorder detection have been developed by applying different types of conventional speech features such as the linear prediction coefficients, linear prediction cepstral coefficients, and Mel-frequency cepstral coefficients (MFCCs). This study aims to ascertain whether conventional speech features detect voice pathology reliably, and whether they can be correlated with voice quality. To investigate this, an automatic detection system based on MFCC was developed, and three different voice disorder databases were used in this study. The experimental results suggest that the accuracy of the MFCC-based system varies from database to database. The detection rate for the intra-database ranges from 72% to 95%, and that for the inter-database is from 47% to 82%. The results conclude that conventional speech features are not correlated with voice, and hence are not reliable in pathology detection

Genotoxic and Anatomical Deteriorations Associated with Potentially Toxic Elements Accumulation in Water Hyacinth Grown in Drainage Water Resources

Potentially toxic elements (PTEs)-induced genotoxicity on aquatic plants is still an open question. Herein, a single clone from a population of water hyacinth covering a large distribution area of Nile River (freshwater) was transplanted in two drainage water resources to explore the hazardous effect of PTEs on molecular, biochemical and anatomical characters of plants compared to those grown in freshwater. Inductivity Coupled Plasma (ICP) analysis indicated that PTEs concentrations in water resources were relatively low in most cases. However, the high tendency of water hyacinth to bio-accumulate and bio-magnify PTEs maximized their concentrations in plant samples (roots in particular). A Random Amplified Polymorphic DNA (RAPD) assay showed the genotoxic effects of PTEs on plants grown in drainage water. PTEs accumulation caused substantial alterations in DNA profiles including the presence or absence of certain bands and even the appearance of new bands. Plants grown in drainage water exhibited several mutations on the electrophoretic profiles and banding pattern of total protein, especially proteins isolated from roots. Several anatomical deteriorations were observed on PTEs-stressed plants including reductions in the thickness of epidermis, cortex and endodermis as well as vascular cylinder diameter. The research findings of this investigation may provide some new insights regarding molecular, biochemical and anatomical responses of water hyacinth grown in drainage water resources.</jats:p

Effect of Novel Quercetin Titanium Dioxide-Decorated Multi-Walled Carbon Nanotubes Nanocomposite on Bacillus subtilis Biofilm Development

The present work was targeted to design a surface against cell seeding and adhering of bacteria, Bacillus subtilis. A multi-walled carbon nanotube/titanium dioxide nano-power was produced via simple mixing of carbon nanotube and titanium dioxide nanoparticles during the sol-gel process followed by heat treatment. Successfully, quercetin was immobilized on the nanocomposite via physical adsorption to form a quercetin/multi-walled carbon nanotube/titanium dioxide nanocomposite. The adhesion of bacteria on the coated-slides was verified after 24 h using confocal laser-scanning microscopy. Results indicated that the quercetin/multi-walled carbon nanotube/titanium dioxide nanocomposite had more negativity and higher recovery by glass surfaces than its counterpart. Moreover, coating surfaces with the quercetin-modified nanocomposite lowered both hydrophilicity and surface-attached bacteria compared to surfaces coated with the multi-walled carbon nanotubes/titanium dioxide nanocomposite