868 resultados para High technology industries.
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The design of a high-density neural recording system targeting epilepsy monitoring is presented. Circuit challenges and techniques are discussed to optimize the amplifier topology and the included OTA. A new platform supporting active recording devices targeting wireless and high-resolution focus localization in epilepsy diagnosis is also proposed. The post-layout simulation results of an amplifier dedicated to this application are presented. The amplifier is designed in a UMC 0.18µm CMOS technology, has an NEF of 2.19 and occupies a silicon area of 0.038 mm(2), while consuming 5.8 µW from a 1.8-V supply.
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Many industrial solids processes require the production of disperse particles. In industries such as food, personal care, and pharmaceuticals, particle formation is widely used to produce solid products or to separate substances in intermediate process steps. The most important characteristics known to impact the effectiveness of a solid product are purity, size, internal structure, and morphology. These characteristics are essential to maintain optimal operation of subsequent process steps and for obtaining the desired high quality product. This thesis aims to aid in the advancement of particle production technology by (1) investigating the use of a vibrating orifice aerosol generator (VOAG) for collecting data to predict particle attributes including morphology, size, and internal structure as a function of processing parameters such as solvent, solution concentration, air flow rate, and initial droplet size, as well as to (2) determine the extent to which uniform droplet evaporation can be a tool to achieve novel particle morphologies, controlled sizes, or internal structures (crystallinity and crystal form). Experimental results for succinic acid, L-serine, and L-glutamic acid suggest that particles of controlled characteristics can indeed be produced by this method. Analysis by scanning electron microscopy (SEM), nanoindentation, and X-ray diffraction (XRD) shows that various sizes, internal structures, and morphologies can be obtained using the VOAG. Furthermore, unique morphologies and unexpected internal structures were able to be achieved for succinic acid, providing an added benefit to particle formation by this method.
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The Chicago Classification of esophageal motility was developed to facilitate the interpretation of clinical high resolution esophageal pressure topography (EPT) studies, concurrent with the widespread adoption of this technology into clinical practice. The Chicago Classification has been an evolutionary process, molded first by published evidence pertinent to the clinical interpretation of high resolution manometry (HRM) studies and secondarily by group experience when suitable evidence is lacking.
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With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of "signature" protein profiles specific to each pathologic state (e.g., normal vs. cancer) or differential profiles between experimental conditions (e.g., treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data analytic strategy for discovering protein biomarkers based on such high-dimensional mass-spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data analytic strategy takes properties of the SELDI mass-spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After these pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary predictors and construct a summary classifier. We empirically evaluate sensitivity and specificity of the resulting summary classifiers with a test dataset that is independent from the training dataset used to construct the summary classifiers. The proposed method performed nearly perfectly in distinguishing cancer and benign hyperplasia from normal. In the classification of cancer vs. benign hyperplasia, however, an appreciable proportion of the benign specimens were classified incorrectly as cancer. We discuss practical issues associated with our proposed approach to the analysis of SELDI output and its application in cancer biomarker discovery.
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Introduction: The Health Technology Assessment report on effectiveness, cost-effectiveness and appropriateness of homeopathy was compiled on behalf of the Swiss Federal Office for Public Health (BAG) within the framework of the 'Program of Evaluation of Complementary Medicine (PEK)'. Materials and Methods: Databases accessible by Internet were systematically searched, complemented by manual search and contacts with experts, and evaluated according to internal and external validity criteria. Results: Many high-quality investigations of pre-clinical basic research proved homeopathic high-potencies inducing regulative and specific changes in cells or living organisms. 20 of 22 systematic reviews detected at least a trend in favor of homeopathy. In our estimation 5 studies yielded results indicating clear evidence for homeopathic therapy. The evaluation of 29 studies in the domain 'Upper Respiratory Tract Infections/Allergic Reactions' showed a positive overall result in favor of homeopathy. 6 out of 7 controlled studies were at least equivalent to conventional medical interventions. 8 out of 16 placebocontrolled studies were significant in favor of homeopathy. Swiss regulations grant a high degree of safety due to product and training requirements for homeopathic physicians. Applied properly, classical homeopathy has few side-effects and the use of high-potencies is free of toxic effects. A general health-economic statement about homeopathy cannot be made from the available data. Conclusion: Taking internal and external validity criteria into account, effectiveness of homeopathy can be supported by clinical evidence and professional and adequate application be regarded as safe. Reliable statements of cost-effectiveness are not available at the moment. External and model validity will have to be taken more strongly into consideration in future studies.
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In most microarray technologies, a number of critical steps are required to convert raw intensity measurements into the data relied upon by data analysts, biologists and clinicians. These data manipulations, referred to as preprocessing, can influence the quality of the ultimate measurements. In the last few years, the high-throughput measurement of gene expression is the most popular application of microarray technology. For this application, various groups have demonstrated that the use of modern statistical methodology can substantially improve accuracy and precision of gene expression measurements, relative to ad-hoc procedures introduced by designers and manufacturers of the technology. Currently, other applications of microarrays are becoming more and more popular. In this paper we describe a preprocessing methodology for a technology designed for the identification of DNA sequence variants in specific genes or regions of the human genome that are associated with phenotypes of interest such as disease. In particular we describe methodology useful for preprocessing Affymetrix SNP chips and obtaining genotype calls with the preprocessed data. We demonstrate how our procedure improves existing approaches using data from three relatively large studies including one in which large number independent calls are available. Software implementing these ideas are avialble from the Bioconductor oligo package.
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The purpose of this project was to investigate the effect of using of data collection technology on student attitudes towards science instruction. The study was conducted over the course of two years at Madison High School in Adrian, Michigan, primarily in college preparatory physics classes, but also in one college preparatory chemistry class and one environmental science class. A preliminary study was conducted at a Lenawee County Intermediate Schools student summer environmental science day camp. The data collection technology used was a combination of Texas Instruments TI-84 Silver Plus graphing calculators and Vernier LabPro data collection sleds with various probeware attachments, including motion sensors, pH probes and accelerometers. Students were given written procedures for most laboratory activities and were provided with data tables and analysis questions to answer about the activities. The first year of the study included a pretest and posttest measuring student attitudes towards the class they were enrolled in. Pre-test and post-test data were analyzed to determine effect size, which was found to be very small (Coe, 2002). The second year of the study focused only on a physics class and used Keller’s ARCS model for measuring student motivation based on the four aspects of motivation: Attention, Relevance, Confidence and Satisfaction (Keller, 2010). According to this model, it was found that there were two distinct groups in the class, one of which was motivated to learn and the other that was not. The data suggest that the use of data collection technology in science classes should be started early in a student’s career, possibly in early middle school or late elementary. This would build familiarity with the equipment and allow for greater exploration by the student as they progress through high school and into upper level science courses.
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This work presents an innovative integration of sensing and nano-scaled fluidic actuation in the combination of pH sensitive optical dye immobilization with the electro-osmotic phenomena in polar solvents like water for flow-through pH measurements. These flow-through measurements are performed in a flow-through sensing device (FTSD) configuration that is designed and fabricated at MTU. A relatively novel and interesting material, through-wafer mesoporous silica substrates with pore diameters of 20 -200 nm and pore depths of 500 µm are fabricated and implemented for electro-osmotic pumping and flow-through fluorescence sensing for the first time. Performance characteristics of macroporous silicon (> 500 µm) implemented for electro-osmotic pumping include, a very large flow effciency of 19.8 µLmin-1V-1 cm-2 and maximum pressure effciency of 86.6 Pa/V in comparison to mesoporous silica membranes with 2.8 µLmin-1V-1cm-2 flow effciency and a 92 Pa/V pressure effciency. The electrical current (I) of the EOP system for 60 V applied voltage utilizing macroporous silicon membranes is 1.02 x 10-6A with a power consumption of 61.74 x 10-6 watts. Optical measurements on mesoporous silica are performed spectroscopically from 300 nm to 1000 nm using ellipsometry, which includes, angularly resolved transmission and angularly resolved reflection measurements that extend into the infrared regime. Refractive index (n) values for oxidized and un-oxidized mesoporous silicon sample at 1000 nm are found to be 1.36 and 1.66. Fluorescence results and characterization confirm the successful pH measurement from ratiometric techniques. The sensitivity measured for fluorescein in buffer solution is 0.51 a.u./pH compared to sensitivity of ~ 0.2 a.u./pH in the case of fluorescein in porous silica template. Porous silica membranes are efficient templates for immobilization of optical dyes and represent a promising method to increase sensitivity for small variations in chemical properties. The FTSD represents a device topology suitable for application to long term monitoring of lakes and reservoirs. Unique and important contributions from this work include fabrication of a through-wafer mesoporous silica membrane that has been thoroughly characterized optically using ellipsometry. Mesoporous silica membranes are tested as a porous media in an electro-osmotic pump for generating high pressure capacities due to the nanometer pore sizes of the porous media. Further, dye immobilized mesoporous silica membranes along with macroporous silicon substrates are implemented for continuous pH measurements using fluorescence changes in a flow-through sensing device configuration. This novel integration and demonstration is completely based on silicon and implemented for the first time and can lead to miniaturized flow-through sensing systems based on MEMS technologies.
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Traditionally, asphalt mixtures were produced at high temperatures (between 150°C to 180°C) and therefore often referred to as Hot Mix Asphalt (HMA). Recently, a new technology named Warm Mix Asphalt (WMA) was developed in Europe that allows HMA to be produced at a lower temperature. Over years of research efforts, a few WMA technologies were introduced including the foaming method using Aspha-min® and Advera® WMA; organic additives such as Sasobit® and Asphaltan B®; and chemical packages such as Evotherm® and Cecabase RT®. Benefits were found when lower temperatures were used to produce asphalt mixtures, especially when it comes to environmental and energy savings. Even though WMA has shown promising results in energy savings and emission reduction, however, only limited studies and laboratory tests have been conducted to date. The objectives of this project are to 1) develop a mix design framework for WMA by evaluating its mechanical properties; 2) evaluate performance of WMA containing high percentages of recycled asphalt material; and 3) evaluate the moisture sensitivity in WMA. The test results show that most of the WMA has higher fatigue life and TSR which indicated WMA has better fatigue cracking and moisture damage resistant; however, the rutting potential of most of the WMA tested were higher than the control HMA. A recommended WMA mix design framework was developed as well. The WMA design framework was presented in this study to provide contractors, and government agencies successfully design WMA. Mixtures containing high RAP and RAS were studied as well and the overall results show that WMA technology allows the mixture containing high RAP content and RAS to be produced at lower temperature (up to 35°C lower) without significantly affect the performance of asphalt mixture in terms of rutting, fatigue and moisture susceptibility. Lastly, the study also found that by introducing the hydrated lime in the WMA, all mixtures modified by the hydrated lime passed the minimum requirement of 0.80. This indicated that, the moisture susceptibility of the WMA can be improved by adding the hydrated lime.
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High concentrations of fluoride naturally occurring in the ground water in the Arusha region of Tanzania cause dental, skeletal and non-skeletal fluorosis in up to 90% of the region’s population [1]. Symptoms of this incurable but completely preventable disease include brittle, discolored teeth, malformed bones and stiff and swollen joints. The consumption of high fluoride water has also been proven to cause headaches and insomnia [2] and adversely affect the development of children’s intelligence [3, 4]. Despite the fact that this array of symptoms may significantly impact a society’s development and the citizens’ ability to perform work and enjoy a reasonable quality of life, little is offered in the Arusha region in the form of solutions for the poor, those hardest hit by the problem. Multiple defluoridation technologies do exist, yet none are successfully reaching the Tanzanian public. This report takes a closer look at the efforts of one local organization, the Defluoridation Technology Project (DTP), to address the region’s fluorosis problem through the production and dissemination of bone char defluoridation filters, an appropriate technology solution that is proven to work. The goal of this research is to improve the sustainability of DTP’s operations and help them reach a wider range of clients so that they may reduce the occurrence of fluorosis more effectively. This was done first through laboratory testing of current products. Results of this testing show a wide range in uptake capacity across batches of bone char emphasizing the need to modify kiln design in order to produce a more consistent and high quality product. The issue of filter dissemination was addressed through the development of a multi-level, customerfunded business model promoting the availability of filters to Tanzanians of all socioeconomic levels. Central to this model is the recommendation to focus on community managed, institutional sized filters in order to make fluoride free water available to lower income clients and to increase Tanzanian involvement at the management level.
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PURPOSE: To assess the literature on accuracy and clinical performance of computer technology applications in surgical implant dentistry. MATERIALS AND METHODS: Electronic and manual literature searches were conducted to collect information about (1) the accuracy and (2) clinical performance of computer-assisted implant systems. Meta-regression analysis was performed for summarizing the accuracy studies. Failure/complication rates were analyzed using random-effects Poisson regression models to obtain summary estimates of 12-month proportions. RESULTS: Twenty-nine different image guidance systems were included. From 2,827 articles, 13 clinical and 19 accuracy studies were included in this systematic review. The meta-analysis of the accuracy (19 clinical and preclinical studies) revealed a total mean error of 0.74 mm (maximum of 4.5 mm) at the entry point in the bone and 0.85 mm at the apex (maximum of 7.1 mm). For the 5 included clinical studies (total of 506 implants) using computer-assisted implant dentistry, the mean failure rate was 3.36% (0% to 8.45%) after an observation period of at least 12 months. In 4.6% of the treated cases, intraoperative complications were reported; these included limited interocclusal distances to perform guided implant placement, limited primary implant stability, or need for additional grafting procedures. CONCLUSION: Differing levels and quantity of evidence were available for computer-assisted implant placement, revealing high implant survival rates after only 12 months of observation in different indications and a reasonable level of accuracy. However, future long-term clinical data are necessary to identify clinical indications and to justify additional radiation doses, effort, and costs associated with computer-assisted implant surgery.