Multiple Sclerosis (MS) is the most common demyelinating disease affecting the central nervous system. Over 80% of MS patients are in the relapsing remitting stage. Symptoms range from fever, fatigue, emotional distress, tingling, numbness, optic neuritis, spasticity, muscle weakness, impaired coordination, to other abnormal neurological problems. Expression of symptoms is known as a relapse or exacerbation. The cause of relapses is unknown, but multiple factors seem to play a significant role. Possible factors that may influence MS onset and relapse consist of a genetic association, viruses, disruption of the blood-brain barrier, and stress. Stress has shown to have negative implications and may stimulate relapses. Thus, this study examined a possible stress intervention that most people already had available to them, companion animals. Companion animals have been shown to lower blood pressure, decrease heart rate, provide social support, and reduce stress. The main hypothesis was to evaluate whether or not pet ownership and/or attachment influenced the perceived stress level and number of negative life events experienced by MS patients in the relapsing remitting stage. Participants were given a questionnaire that consisted of 7 surveys. The questionnaire accessed quality of life, disease severity, number of negative life events, perceived stress level, level of depression, social support, and pet ownership and attachment level. Our sample population consisted of MS patients seen at the University of Texas Southwestern Neurology clinic from February 23rd to May 21st, 2004. One hundred and forty seven relapsing remitting MS patients were included in the study. Multiple linear regression was used to compare the relationship of stress and number of negative life events to pet ownership and attachment. Results revealed that pet ownership and attachment levels did not affect the stress level and number of negative life events of MS patients. No confounders were identified. Interaction terms with disease severity as the dependent variable, pet ownership and perceived stress level or negative life events as the independent variables were not significant. The type of pet owned did not influence the attachment level of the MS patient. In conclusion, the results of this study did not support the hypothesis.

Modern seismic imaging tools for oil and gas exploration and production (E&P) assume that seismic data contain responses only of waves that bounce (e.g., reflect, diffract) only once at each interface in the subsurface. This type of response is called a primary. Unfortunately, actual seismic data also contain responses of waves that bounce at several interfaces in the subsurface. This type of response is called a multiple. In general, multiples in seismic data fall into two categories: (1) events that bounce at least once at the free surface in addition to any other bounce in the sub- surface and (2) events that do not bounce at the free surface but instead inside the subsurface, at two or more interfaces. The first category has the greater amount of energy; therefore most of the research and development efforts in E&P have so far focused on attenuating this category of multiples accurately. At present, more knowledge of the subsurface is expected from seismic imaging. To avoid any misinterpretation of these details, there is a growing need in the E&P industry to also attenuate the second category of multiples, known as internal multiples. In this work I describe a new method of attenuation of internal multiples. The method consists of predicting the internal multiples and then subtracting them from the data. The prediction of internal multiples from seismic data is made possible by the discovery of a new type of seismic scattering event known as a virtual event. Seismic virtual events constitute a calculational device, which is becoming an important part of seismic data processing. Virtual events combine forward and back- ward wave propagation in such a way that their convolution with real events allows us to predict internal multiples. In addition to showing how virtual events can be constructed from real seismic events, I also show that virtual events obey physical laws, despite their counterintuitive wavepath. I have illustrated the findings in this thesis with synthetic examples. In particu- lar, I have shown the effectiveness of my internal-multiple-attenuation method for a 1D data set, which includes several primaries and internal multiple interferences.

Stressful life events have been associated with the onset and/or exacerbation of multiple sclerosis (MS). To investigate the effects of stress on the pathogenesis of MS, we employed restraint stress (RST) in the Theiler’s virus-induced demyelination (TVID) model, an animal model for human MS. Intracerebral inoculation of susceptible strain of mice with Theiler’s murine encephalomyelitis virus (TMEV) results in a biphasic disease – an acute encephalomyelitis and chronic demyelination. The establishment of persistent viral infection is critical in inducing immune-mediated demyelination during the chronic disease. The exposure of mice to RST prior to viral infection produced a stress response as evidenced by elevated circulating corticosterone (CORT). To further study the effect of stress on the immune response to TMEV infection and demyelination, we first examined the cytokine and chemokine response during the acute TMEV infection. We demonstrated that RST down-regulated the virus-induced expression of chemokines, Ltn, IP-10, RANTES, and pro-inflammatory cytokines, TNF, IFN and LT in both the brain and spleen during early infection. Histologically, a decreased pattern of inflammation was observed in the brain of restrained mice as compared to non-restrained mice. The increased viral titer was noted in the CNS of restrained mice and was correlated with the decreased production of pro-inflammatory cytokine, suggesting an impaired immune response by RST. Secondly, the duration of stress on the late demyelination was investigated. Repeated and chronically stressed SJL/J mice developed an early onset of clinical signs and a delayed onset was observed in acutely stressed mice. Both acute and chronic RST suppressed the antibody response to TMEV and stressed displayed a higher incidence of demyelination than non-restrained mice. Axonal loss was also noted in chronic stressed mice. Additionally, RST caused an increased systemic viral infection in extraneural organs during the acute infection and cardiotropic TMEV was isolated from the heart of stressed mice. Taken together, stress resulted in profound immunsuppression during acute infection, which may consequently increase the incidence of demyelination. The present study may be generalized in human MS which is potentially triggered by viral infection.

Pete Riegel, a well-known sport expert, proposed the formula of race time prediction in 1977. This article discusses whether it is also suitable for Taiwan marathoners. We compiled two hundred and four effective datum by questionary. Some variables possible to affect the running result are added in this work, namely: sex, age, the year of run, height, weight, the race number of marathon, the quantity and the frequency of practices each week. Next, we use multiple regression and sliced inverse regression to increase the accuracy of the running time prediction. The best model, found here has eighty percentage's player with predictive error within fifteen minuates, which is better than the original model by Riegel(1977) with only having sixty-two percentages.

Wireless sensor networks typically consist of a significant number of low-cost sensor nodes which can collaborate among each other to execute a wide range of applications, such as environmental and health monitoring, intrusion detection, etc. Basically, sensor nodes are mainly battery-powered and have a limited amount of energy to spend, thereby they are not likely to be recharged or replenished after being deployed in an inaccessible sensed environment. As a result, in the past decade, power saving has become a critical issue for the design of a media access control (MAC) protocol in wireless sensor networks. By incorporating power-saving mechanism into MAC, we expect to maximize the lifetime of a sensor network. Intuitively, a large amount of research tends to make use of the TDMA protocol because it has inherently more favorable characteristics when compared to the CSMA protocol, that is, sensor nodes only need to wake up to transmit or receive data at its allocated time slots, and other time slots they can go into sleep mode. By doing so, it can reduce power consumption. However, in this master thesis, we found that there exists a rather acute problem, called the Multiple-Cluster Collision (MCC) problem, in the TDMA cluster-based protocol that will degrade the system performance drastically. Therefore, in this thesis, we propose the approach, called Multiple Cluster Collision Problem (MCCP), to perfectly eliminate the MCC problem by sensor nodes. Finally, we will compare our approach with SRSA, proposed by Tao WU et al., to show that the performance of our approach outperforms SRSA in terms of collision reduction, throughput and so on.

Large integer factoring problem is a difficult computing problem. The security of many public-key cryptograohy system depend on the large interger factoring problem. Dr. Guan implement ¡uThe Multiple Polynomail Quadratic Sieve Algorithm¡v and name the program ¡uGQS¡v. The program successfully factor RSA-130 interger in 2004. It can reduce the time of sieving that the MPQS algorithm retain the smooth number with one or two prime. But finally the size of factor basis is large. We use some of the prime retained by the MPQS algorithm to match with the smooth number and reduce the size of factor basis. And then we can reduce the time of factoring. In this paper, we implement our idea in a AIX server and the result of this paper can be a suggestion of the improvement of MPQS.

Various approaches have been proposed for finding the longest common subsequence (LCS) of two sequences. The time complexities of these algorithms are usually $O(n^2)$ in the worst case, where $n$ is the length of input sequences. However, these algorithms would become infeasible when the input length, $n$, is very long. Recently, the $k$-LCS $(k ≥ 2)$ problem has become more attractive. Some algorithms have been proposed for solving the problem, but the execution time required for solving the $k$-LCS problem is still too long to be practical. In this thesis, we propose a genetic algorithm for solving the $k$-LCS problem with time complexity $O(Gpk(n + |P_j|))$, which $G$ is the number of generations, $p$ is the number of template patterns, $k$ is the number of input sequences, $n$ and $|P_j|$ are the length of input sequences and the length of template patterns, respectively. As our experimental results show, when $k$ is 20 and $n$ is 1000, the performance ratio ($|CS|/|LCS|$) of our algorithm is greater than 0.8, where $|CS|$ denotes the length of the solution we find, and $|LCS|$ represents the length of the real (optimal) LCS. Comparing the performance ratios with Expansion Algorithm and BNMAS Algorithm, our algorithm is much better than them when the number of input sequences varies from 2 to 20 and the length of the input sequences varies from 100 to 2000.

In many multimedia applications, a little error in the output results is allowable. Therefore, this thesis presents an iterative floating-point multiplier with multiple precision to reduce the energy consumption of floating-point multiplication operations. The multiplier can provide the users with three kinds of modes. The distinction among the three modes is the accepted output error and the achievable energy saving through reducing the length of mantissa in the multiplication operation. In addition, to reduce the area of multiple precision floating-point multiplier we use the iterative structure to implement the mantissa multiplier in a floating point multiplier. Moreover the C++ language is adopted to evaluate the product error between each mode and the IEEE754 single precision multiplier. When the multimedia applications request high precision, the multiple precision floating-point multiplier will iteratively execute the 4-2 compression tree three times and the product error is around 10e-5%. The second-mode with the middle accuracy will iteratively execute the 4-2 compression tree two times and the product error is around 10e-3%. The third mode with the lowest accuracy will execute the 4-2 compression tree once and the product error is around 1%, it requires less execution cycle number. When compared with the tree-stage IEEE754 single-precision multiplier, the proposed iterative floating-point multiplier can save 42.54% area. For IDCT application, it can save 37.78% energy under 1% error constraint, For YUV to RGB application, it can save 31.36% energy under 1.1% error constraint. The experimental results demonstrate that the proposed multiple precision iterative floating-point multiplier can significantly reduce the energy consumption of multimedia applications that allow a little output distortion

Reproduction de : Thèse de doctorat : Sciences et ingénierie des ressources procédés produits environnement. Discipline de la vie; Toxicologie de l'environnement : Metz : 2003. / Titre provenant de l'écran-titre. Notes bibliographiques.

Thèse de doctorat : Sciences physiques et de l'ingénieur. Mécanique et ingénierie : Bordeaux 1 : 2009. / Titre provenant de l'écran-titre.