As some companies in the paper industry struggle to shift from commodity grades to value added products, technical challenges and opportunities have grown tremendously. These new products require more stringent manufacturing specifications and improved performance relative to those of lignocellulosic fibers currently being produced. Hence, topochemical and mechanical modifications of pulp fibers have moved to the forefront of many corporate strategies. Researchers are beginning to develop new tools to help better understand the fundamental mechanisms of fiber modifications and how to most efficiently apply them. Two novel approaches are presented. First, a new method to observe single fiber crossings is developed. It was found that refining reduces the stepheight in the fiber crossing for both hardwood and softwood kraft pulps by increasing the tendency of the fibers to collapse, deform, and assume a lens like shape. The effect of pulp type, bleaching, drying, wet pressing, and fiber charge were also investigated. Graphs of stepheight versus freespan were linear through the origin suggesting that the freespan (flexibility) of the crossing fiber is largely unimportant to the formation of fiber crossings. Quite surprisingly, the ratio of stepheight to freespan remained relatively constant no matter the treatment. Only bleaching and the addition of surface charge via CMC had any independent impact on freespan. The data do not fit bending or shear mechanisms that have been developed in the literature suggesting that another mechanism may be responsible for the deformation behavior of single fiber crossings. Also, a method employing fluorescence microscopy and fluorescence resonance energy transfer is used to image the areas of a fiber-fiber interface while they were bonded. Analysis of the FRET signal from fiber crossings indicate that wet pressing increased the FRET occurring between the two dyed fiber surfaces. The results are consistent with the increased amount of interdiffusion expected with higher levels of wet pressing. Two novel techniques are used to investigate fundamental aspects of fiber deformation behavior and fiber-fiber bond formation. As these methods are further refined and utilized they will provide new avenues for researchers to explore and expand the property space of fibers and paper sheets.

<p>Myasthenia gravis (MG) is an autoimmune neuromuscular disorder that causes fluctuating muscle weakness. MG may be divided into an ocular form and a generalized form based on the involved muscles. Treatment differs between these different MG forms. The majority (80%) of patients with generalized MG are seropositive for antibodies against the acetylcholine receptor (AChR-Ab). Recently a new antibody was detected against muscle specific tyrosine kinase (MuSK) in about 40% of patients who are AChR-Ab seronegative. A few patients with MuSK-Abs have muscular atrophies, as well as electrophysiological myopathy.</p><p>In this thesis we have characterized MuSK-Ab seropositive [MuSK(+)] patients using clinical parameters, including health-related quality of life (hrQoL), neurophysiology and muscle morphology, and compared them to patients with and without AChR-Abs. The question concerned which factors contribute to their muscle weakness. Additionally, we wanted to determine if single-fiber electromyography (SFEMG) in a limb muscle has any predictive value for generalization of ocular MG. </p><p>Our results suggest that MuSK(+) patients more often have a myopathic electromyography pattern, although this pattern is found also in other immunological subtypes of MG. The myopathic pattern may be associated with the frequently found mitochondrial abnormalities. However, disturbed neuromuscular transmission is the primary cause of muscle weakness in the majority of MuSK(+) patients, as well as in AChR-Ab seropositive patients. The disease-specific hrQoL MG questionnaire was successfully validated into Swedish and these scores correlated with disturbed neuromuscular transmission in a proximal arm muscle. Abnormal SFEMG findings occur also in muscles outside of the facial area in ocular MG, although this is not predictive of subsequent generalization. </p><p>MuSK (+) patients have little or no beneficial effect of acetylcholine esterase inhibitors (AChEI). On the contrary AChEI may produce profound adverse effects. We present the hypothesis that this effect of AChEI is due to abnormal receptor morphology in MuSK(+) patients.</p>

Myasthenia gravis (MG) is an autoimmune neuromuscular disorder that causes fluctuating muscle weakness. MG may be divided into an ocular form and a generalized form based on the involved muscles. Treatment differs between these different MG forms. The majority (80%) of patients with generalized MG are seropositive for antibodies against the acetylcholine receptor (AChR-Ab). Recently a new antibody was detected against muscle specific tyrosine kinase (MuSK) in about 40% of patients who are AChR-Ab seronegative. A few patients with MuSK-Abs have muscular atrophies, as well as electrophysiological myopathy. In this thesis we have characterized MuSK-Ab seropositive [MuSK(+)] patients using clinical parameters, including health-related quality of life (hrQoL), neurophysiology and muscle morphology, and compared them to patients with and without AChR-Abs. The question concerned which factors contribute to their muscle weakness. Additionally, we wanted to determine if single-fiber electromyography (SFEMG) in a limb muscle has any predictive value for generalization of ocular MG. Our results suggest that MuSK(+) patients more often have a myopathic electromyography pattern, although this pattern is found also in other immunological subtypes of MG. The myopathic pattern may be associated with the frequently found mitochondrial abnormalities. However, disturbed neuromuscular transmission is the primary cause of muscle weakness in the majority of MuSK(+) patients, as well as in AChR-Ab seropositive patients. The disease-specific hrQoL MG questionnaire was successfully validated into Swedish and these scores correlated with disturbed neuromuscular transmission in a proximal arm muscle. Abnormal SFEMG findings occur also in muscles outside of the facial area in ocular MG, although this is not predictive of subsequent generalization. MuSK (+) patients have little or no beneficial effect of acetylcholine esterase inhibitors (AChEI). On the contrary AChEI may produce profound adverse effects. We present the hypothesis that this effect of AChEI is due to abnormal receptor morphology in MuSK(+) patients.

MetPreg, a composite developed by Touchstone Research Laboratories (Tridelphia, WV), is an aluminum metal matrix composite reinforced by continuous NextelTM 610 alumina fibers. The question is, after processing, are the NextelTM fibers affected in any way that their strengthening contribution to the composite is reduced? From experimentation and statistical analysis, a strength distribution of pre-processed NextelTM 610 fibers is formed and an empirical correlation is developed relating strength to the observed flaw size on the failed single fibers. This correlation is then independently applied to flaw size information gathered from fibers on the fracture surface of MetPreg samples to develop a separate strength distribution of post-processed NextelTM 610 fibers. The pre- and post-processed distributions are compared to one another to determine the effect, if any, that composite processing has on the strength of NextelTM 610 fibers. The results indicate that the in-situ strength distribution of fibers was increased by composite processing. / Master of Science

The quantitative analysis of decomposed electromyographic (EMG) signals reveals information for diagnosing and characterizing neuromuscular disorders. Neuromuscular jitter is an important measure that reflects the stability of the operation of a neuromuscular junction. It is conventionally measured using single fiber electromyographic (SFEMG) techniques. SFEMG techniques require substantial physician dexterity and subject cooperation. Furthermore, SFEMG needles are expensive, and their re-use increases the risk of possible transmission of infectious agents. Using disposable concentric needle (CN) electrodes and automating the measurment of neuromuscular jitter would greatly facilitate the study of neuromuscular disorders. An improved automated jitter measurment system based on the decomposition of CN detected EMG signals is developed and evaluated in this thesis. Neuromuscular jitter is defined as the variability of time intervals between two muscle fiber potentials (MFPs). Given the candidate motor unit potentials (MUPs) of a decomposed EMG signal, which is represented by a motor unit potential train (MUPT), the automated jitter measurement system designed in this thesis can be summarized as a three-step procedure: 1) identify isolated motor unit potentials in a MUPT, 2) detect the significant MFPs of each isolated MUP, 3) track significant MFPs generated by the same muscle fiber across all isolated MUPs, select typical MFP pairs, and calculate jitter. In Step one, a minimal spanning tree-based 2-phase clustering algorithm was developed for identifying isolated MUPs in a train. For the second step, a pattern recognition system was designed to classify detected MFP peaks. At last, the neuromuscular jitter is calculated based on the tracked and selected MFP pairs in the third step. These three steps were simulated and evaluated using synthetic EMG signals independently, and the whole system is preliminary implemented and evaluated using a small simulated data base. Compared to previous work in this area, the algorithms in this thesis showed better performance and great robustness across a variety of EMG signals, so that they can be applied widely to similar scenarios. The whole system developed in this thesis can be implemented in a large EMG signal decomposition system and validated using real data.

The quantitative analysis of decomposed electromyographic (EMG) signals reveals information for diagnosing and characterizing neuromuscular disorders. Neuromuscular jitter is an important measure that reflects the stability of the operation of a neuromuscular junction. It is conventionally measured using single fiber electromyographic (SFEMG) techniques. SFEMG techniques require substantial physician dexterity and subject cooperation. Furthermore, SFEMG needles are expensive, and their re-use increases the risk of possible transmission of infectious agents. Using disposable concentric needle (CN) electrodes and automating the measurment of neuromuscular jitter would greatly facilitate the study of neuromuscular disorders. An improved automated jitter measurment system based on the decomposition of CN detected EMG signals is developed and evaluated in this thesis. Neuromuscular jitter is defined as the variability of time intervals between two muscle fiber potentials (MFPs). Given the candidate motor unit potentials (MUPs) of a decomposed EMG signal, which is represented by a motor unit potential train (MUPT), the automated jitter measurement system designed in this thesis can be summarized as a three-step procedure: 1) identify isolated motor unit potentials in a MUPT, 2) detect the significant MFPs of each isolated MUP, 3) track significant MFPs generated by the same muscle fiber across all isolated MUPs, select typical MFP pairs, and calculate jitter. In Step one, a minimal spanning tree-based 2-phase clustering algorithm was developed for identifying isolated MUPs in a train. For the second step, a pattern recognition system was designed to classify detected MFP peaks. At last, the neuromuscular jitter is calculated based on the tracked and selected MFP pairs in the third step. These three steps were simulated and evaluated using synthetic EMG signals independently, and the whole system is preliminary implemented and evaluated using a small simulated data base. Compared to previous work in this area, the algorithms in this thesis showed better performance and great robustness across a variety of EMG signals, so that they can be applied widely to similar scenarios. The whole system developed in this thesis can be implemented in a large EMG signal decomposition system and validated using real data.

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Contexte: La réponse synchrone des fibres auditives, évaluée à partir de l'onde I des potentiels d'action évoqués auditifs (PEA), ou à partir du potentiel d'action composite (PAC) du nerf auditif, est l'élément clé du dépistage des neuropathies auditives. De récentes études ont toutefois montré que le seuil et l'amplitude de cette réponse pouvaient être absolument normaux malgré une perte importante de fibres du nerf auditif. Dans ce travail de thèse, nous proposons une nouvelle méthode d'exploration fonctionnelle, potentiellement applicable à l'homme, rendant mieux compte du nombre et de l'intégrité des fibres du nerf auditif. Cette méthode a été évaluée à l'aide d'un modèle pharmacologique de neuropathie physiologiquement pertinent.Matériel et méthodes: Chez des gerbilles, une perte sélective de fibres auditives a été induite par application d'une faible concentration d'ouabaïne dans la niche de la fenêtre ronde de la cochlée. Cette neuropathie a ensuite été caractérisée par des comptages de synapses (immunohistochimie/imagerie confocale 3D) et l'enregistrement de l'activité unitaire de fibres du nerf auditif. Les PAC et l'activité soutenue du nerf ont été enregistrés 6 jours après l'application d'ouabaïne, à l'aide d'une électrode de recueil disposée dans la niche de la fenêtre ronde. Résultats: L'application d'ouabaïne induit une perte spécifique des fibres à basse activité spontanée (AS<0,5 potentiel d'action/sec) comme observé au cours du vieillissement et après une surexposition sonore. La disparition de cette population de fibres est indétectable à l'aide du PAC car leur réponse unitaire est à la fois retardée et désynchronisée. Par contre, l'amplitude de la réponse soutenue du nerf se révèle être un bien meilleur indicateur de la perte des fibres à basse activité spontanée. Pour aller plus loin, nous avons mis au point une méthode qui permet d'observer l'activité synchrone et soutenue du nerf auditif dans une même réponse. Cette approche rend compte des trois mécanismes de fusion vésiculaire (libération rapide, lente et soutenue) de la première synapse auditive.Conclusion: L'analyse de la réponse soutenue du nerf auditif est une approche fiable pour déterminer le nombre et le phénotype fonctionnel des fibres qui composent le nerf auditif. Cette méthode, applicable à l'homme, devrait améliorer le dépistage des neuropathies, avec une meilleure différenciation des atteintes d'origine synaptique et/ou neuronale.Mots clés: Cochlée, nerf auditif, potentiel d'action composite, activité soutenue du nerf auditif, enregistrement unitaires, ouabaïne, neuropathie / Background: The synchronous activation of the auditory nerve fibers (ANFs), is commonly studied through the compound action potential (CAP), or the auditory brainstem responses (ABR), to probe deafness in experimental and clinical settings. Recent studies have shown that substantial ANF loss can coexist with normal hearing threshold, and even unchanged CAP amplitude, making the detection of auditory neuropathies difficult. In this study, we took advantage of the round window neural noise (RWNN) to probe ANF loss in a physiologically-relevant model of neuropathy.Material and methods: ANF loss was induced by the application of ouabain onto the round window niche. CAP and RWNN of the gerbil's cochlea were recorded through an electrode placed onto the round window niche, 6 days after the ouabain application. Afferent synapse counts and single-unit recordings were carried-out to determine the degree and the nature of ANF loss, respectively. Results: Application of a low ouabain-dose into the gerbil RW niche elicits a specific degeneration of low spontaneous rate (SR) fibers, as shown by single-unit recordings. Simultaneous recordings (CAP/single-unit) demonstrate that low-SR fibers have a weak contribution to the CAP amplitude because of their delayed and broad first spike latency distribution. However, the RWNN amplitude decreases with the degree of synaptic loss. The RWNN method is therefore more sensitive than CAP to detect low-SR fiber loss, most probably because it reflects the sustained discharge rate of ANFs. Based on these data, we proposed a far-field method (Peri-stimulus time response-PSTR) to assess the fast, slow, and sustain vesicular release at the first auditory synapse.Conclusion: The round window neural noise is a faithful proxy to probe the degree and the SR-based nature of fiber loss. This method could be translated into the clinic to probe hidden hearing loss and orient the practitioner toward synaptopathy and/or neuropathy.Key words: Cochlea, auditory nerve, compound action potential, round window neural noise, single fiber recording, ouabain-induced neuropathy

<p dir="ltr">The vagus nerve (VN) is the tenth cranial nerve that mediates most of the parasympathetic functions of the autonomic nervous system. The axons of the human VN comprise a mix of unmyelinated and myelinated axons, where ~80% of the axons are unmyelinated C fibers (Havton et al., 2021). Understanding that most VN axons are unmyelinated, there is a need to map the pathways of these axons to and from organs to understand their function(s) and whether C fiber morphology or signaling characteristics yield insights into their functions. Developing a machine learning model that detects and predicts the morphology of VN single fiber action potentials based on select fiber characteristics, e.g., diameter, myelination, and position within the VN, allows us to more readily categorize the nerve fibers with respect to their function(s). Additionally, the features of this machine learning model could help inform peripheral neuromodulation devices that aim to restore, replace, or augment one or more specific functions of the VN that have been lost due to injury, disease, or developmental abnormalities.</p><p dir="ltr">We designed and trained four types of Multi-layer Perceptron Artificial Deep Neural Networks (MLP-ANN) with 10,000 rat abdominal vagal C-fibers simulated via the peripheral neural interface model ViNERS. We analyze the accuracy of each MLP-ANN’s SFAP predictions by conducting normalized cross-correlation and morphology analyses with the ViNERS C-fiber SFAP counterparts. Our results showed that our best MLP predicted over 94% of the C-fiber SFAPs with strong normalized cross-correlation coefficients of 0.7 through 1 with the ViNERS SFAPs. Overall, this novel tool can use a C-fiber’s biophysical characteristics (i.e., fiber diameter size, fiber position on the x/y axis, etc.) to predict C-fiber SFAP morphology.</p>

Clean air is a global health concern. Each year more than seven million people across the globe perish from breathing poor quality air. Development of high efficiency particulate air (HEPA) filters demonstrate an effort to mitigate dangerous aerosol hazards at the point of production. The nuclear power industry installs HEPA filters as a final line of containment of hazardous particles. Advancement air filtration technology is paramount to achieving global clean air. An exploration of analytical, experimental, computational, and machine learning models is presented in this dissertation to advance the science of air filtration technology. This dissertation studies, develops, and analyzes alternative air filtration materials and methods of analysis that optimize filtration efficiency and reduce resistance to air flow. Alternative nonwoven filter materials are considered for use in HEPA filtration. A detailed review of natural and synthetic fibers is presented to compare mechanical, thermal, and chemical properties of fibers to desirable characteristics for air filtration media. An experimental effort is undertaken to produce and evaluate new nanofibrous air filtration materials through electrospinning. Electrospun and stabilized nanofibrous media are visually analyzed through optical imaging and tested for filtration efficiency and air flow resistance. The single fiber efficiency (SFE) analytical model is applied to air filtration media for the prediction of filtration efficiency and air flow resistance. Digital twin replicas of nonwoven nanofibrous media are created using computer scripting and commercial digital geometry software. Digital twin filters are visually compared to melt-blown and electrospun filters. Scanning electron microscopy images are evaluated using a machine learning model. A convolutional neural network is presented as a method to analyze complex geometry. Digital replication of air filtration media enables coordination among experimental, analytical, machine learning, and computational air filtration models. The value of using synthetic data to train and evaluate computational and machine learning models is demonstrated through prediction of air filtration performance, and comparison to analytical results. This dissertation concludes with discussion on potential opportunities and future work needed in the continued effort to advance clean air technologies for the mitigation of a global health and safety challenge.