How the neural representations of different sensory modalities transition from one to another is an unexplored issue of cortical organization. The present experiments addressed this problem by examining auditory projections to the lateral suprasylvian visual area (LSS) of the cat using neuroanatomical tract tracing methods. Injections of tracer (Biotinylated Dextran Amine, BDA) were made into defined areas of the cat auditory cortex. Following transport and tissue processing, a light microscope with a digitizing stage was used to visualize and plot labeled auditory projections to the LSS. The results showed that all auditory cortices tested demonstrated projections to a restricted portion of the LSS. While these projections were concentrated on the outer lip of the lateral bank of the LSS, some scattered auditory projections were found along the entire depth of the lateral bank. These data indicate that, at least in the LSS, projections from different sensory modalities do not form abrupt borders but exhibit areas of overlap. These overlapped projections may provide the anatomical basis for multisensory properties of neurons within transition areas between representations of different sensory modalities.

The aim of the paper is to introduce an optic microscope as well as microscopic photography producing. It further engages in sharpening issues and attaining a sharp image with extremely robust depth acuteness assuming using a series of images with different acuteness levels. The goal is to create a suitable algorithm to increase depth acuteness, to perform a visual processing of the series of images and to get one final image with high depth acuteness.

Inhalation of respirable coal mine dust (RCMD) can lead to chronic lung diseases, including coal worker’s pneumoconiosis (CWP) and more severe forms such as progressive massive fibrosis. After the Federal Coal Mine Health and Safety Act was passed in 1969, limits on exposure to respirable dust were set, and the prevalence of CWP abruptly decreased. However, during the last two decades, a resurgence of the disease has been reported. Many authors have argued that the increasing numbers might be related to mining practices, including the extraction of thinner coal seams, characteristics of the mineral deposits, and more powerful cutting machines. Dust particles in coal mines are usually associated with three main sources: Coal particles are produced when the coal seam is being actively extracted. Silica and silicates are generated while cutting the rock strata surrounding the coal or during roof-bolting activities. Finally, rock dust application is the primary source of highly pure carbonates. Timely information about dust composition would allow the identification of potential dust sources and pursue efforts to control dust exposure efficiently. However, this information needs to be provided promptly since dust levels are dynamically changing through the shift. Currently, monitoring technologies such as the continuous personal dust monitor allow real-time measurements, but they are limited to total dust concentration and provide no information about dust composition. More recently, the National Institute for Occupational Safety and Health (NIOSH) has been developing an end-of-shift silica monitor. Still, technologies that offer information on dust composition in a semi-continuous manner are needed. In this work, a new monitoring concept is explored that has the potential to provide near real time data on RCMD constituents. The possible use of a portable optical microscopy (OM) combined with image processing techniques is explored as the basis for a novel RCDM monitoring device. The use of OM in different fields and the rapid development of automated image analysis reveals a clear opportunity that has not been yet exploited for mine dust monitoring applications. This thesis research consisted of two primary studies. The first was an analysis of lab-generated respirable dust samples containing the main mineralogical classes in RCMD (i.e., coal, silica, kaolinite as a proxy for silicate minerals, and a real rock dust product). Samples were imaged using a polarizing microscope and analyzed using an image processing routine to identify and classify particles based on optical characteristics. Specifically, birefringence of particles was exploited to separate coal particles form mineral particles. This is an exciting result since even such a basic fractionation of RCMD would be valuable to track changing conditions at the mine production face and enable rapid decision making. The second study was conducted to explore subclassification of the mineral fraction. A model was built to explore multiple particle features, including particle size, shape, color, texture, and optical properties. However, a simple stepwise method that uses birefringence for separating coal particles first and then classifying silica particles proved most effective. One particular challenge to the silica classification was determined to be the particle loading density. Future work to further enhance the output of the algorithm and next steps were depicted. This thesis research demonstrated that OM and image processing can be used to separate mineral and coal fractions. Subclassification of silica and other minerals using optical properties such as birefringence of particles alone was successful, but showed less accuracy. A robust sampling method that accounts for particle loading density and a more complex model with additional differentiating features might enhance the results. This approach should be considered as a potential candidate for the development of new RCMD monitoring technologies. This tool could enable better tracking of dust conditions and thus better decision-making regarding ventilation, dust controls, and operator position to reduce exposure hazards. / M.S. / Inhalation of fine particles in underground coal environments can lead to chronic lung diseases, such as coal worker’s pneumoconiosis or progressive massive fibrosis (PMF), which is the most severe form of disease. During the last two decades, the rates of reported cases of PMF in underground coal miners have more than doubled. Many authors have suggested different reasons to explain this trend, including the extraction of thinner coal deposits, mining techniques, changes in mineral content, and the use of high-powered cutting equipment. However, detailed information of specific dust constituents and monitoring the variability of dust concentrations during work shifts are needed to determine possible dust sources and comprehend the more recent changing disease patterns. A dust-monitoring system that provides accurate and timely data on specific respirable coal mine dust (RCMD) constituents would enable the deployment of effective control strategies to mitigate exposure to respirable hazards. Optical microscopy (OM) has been used for a long time to analyze and identify dust particles. More recent advances in portable microscopy have allowed the microscope analysis to be implemented in the field. On the other hand, automated image processing techniques are rapidly progressing and powerful imaging hardware has become a reality in handy small devices. OM and image processing technologies offer a path for near real-time applications that have not been explored for RCMD monitoring yet. In this work, a novel monitoring concept is explored using OM and image processing to classify RCMD particles. Images from dust samples captured with a polarizing microscope were used to build a classification model based on optical properties. The method herein described showed outstanding accuracy for separating coal and mineral fractions. Additionally, the Identification of silica particles in the mineral fraction was investigated and has proved more challenging. A particular finding suggests that particle loading density in the images plays an important role in classification accuracy.

The demountable splicing of optical fibres uses different types of connectors which ensures accurate position of connected fibres. If the optical fibres are aligned in free space, a view from two perpendicular viewing directions is necessary for a maximum aligning accuracy. The method of direct monitoring of optical fibres provides this possibility however, it is necessary to use two imaging systems. This problem can be solved by a special microscope, which is designed in this thesis. The microscope can visualize the alignment of optical fibres from two mutually perpendicular directions by moving the objective lens and inclined mirror. The diploma thesis also describes the procedure of designing an optical simulation of the connection of optical fibres. Based on it, the microscope is designed, adjusted and tested with various optical fibres.

Existence of larval dorsoabdominal scent glands (DAGs) together with occurence of adult metathoracic scent glands is one of the important autapomorphic characters of taxon Heteroptera within taxon Insecta. DAGs can persist until adults in some species of this taxon. The persistence of DAGs were proved also in members of infraorder Pentatomomorpha. Targets of this thesis are: collect the knowledge about persistent adult DAGs in selected representative members of important families of taxon Pentatomomorpha; study and compare the condition of the DAGs in the oldest larval instars and adults; clarify the significance of existence the openings of conducting ductules of proper glandular units in reservoir intima of DAGs in study of the persistence of these glands. For study were used stereomicroscope, light and scanning electron microscope. Key words: Pentatomomorpha, Heteroptera, dorsoabdominal scent glands, openings of conducting ductules of glandular units, larvae of 5th instar, persistence in adults, persistence patterns, light microscope, scanning electron microscope