Computational research making use of molecular dynamics (MD) simulations has begun to expand the paradigm of structural biology to include dynamics as the mediator between structure and function. This work aims to expand the utility of MD simulations by developing Principal Component Analysis (PCA) techniques to extract the biologically relevant information in these increasingly complex data sets. Gramicidin is a simple protein with a very clear functional role and a long history of experimental, theoretical and computational study, making it an ideal candidate for detailed quantitative study and the development of new analysis techniques. First we quantify the convergence of our PCA results to underwrite the scope and validity of three 64 ns simulations of gA and two covalently linked analogs (SS and RR) solvated in a glycerol mono-oleate (GMO) membrane. Next we introduce a number of statistical measures for identifying regions of anharmonicity on the free energy landscape and highlight the utility of PCA in identifying functional modes of motion at both long and short wavelengths. We then introduce a simple ansatz for extracting physically meaningful modes of collective dynamics from the results of PCA, through a weighted superposition of eigenvectors. Applied to the gA, SS and RR backbone, this analysis results in a small number of collective modes which relate structural differences among the three analogs to dynamic properties with functional interpretations. Finally, we apply elements of our analysis to the GMO membrane, yielding two simple modes of motion from a large number of noisy and complex eigenvectors. Our results demonstrate that PCA can be used to isolate covariant motions on a number of different length and time scales, and highlight the need for an adequate structural and dynamical account of many more PCs than have been conventionally examined in the analysis of protein motion.

Computational research making use of molecular dynamics (MD) simulations has begun to expand the paradigm of structural biology to include dynamics as the mediator between structure and function. This work aims to expand the utility of MD simulations by developing Principal Component Analysis (PCA) techniques to extract the biologically relevant information in these increasingly complex data sets. Gramicidin is a simple protein with a very clear functional role and a long history of experimental, theoretical and computational study, making it an ideal candidate for detailed quantitative study and the development of new analysis techniques. First we quantify the convergence of our PCA results to underwrite the scope and validity of three 64 ns simulations of gA and two covalently linked analogs (SS and RR) solvated in a glycerol mono-oleate (GMO) membrane. Next we introduce a number of statistical measures for identifying regions of anharmonicity on the free energy landscape and highlight the utility of PCA in identifying functional modes of motion at both long and short wavelengths. We then introduce a simple ansatz for extracting physically meaningful modes of collective dynamics from the results of PCA, through a weighted superposition of eigenvectors. Applied to the gA, SS and RR backbone, this analysis results in a small number of collective modes which relate structural differences among the three analogs to dynamic properties with functional interpretations. Finally, we apply elements of our analysis to the GMO membrane, yielding two simple modes of motion from a large number of noisy and complex eigenvectors. Our results demonstrate that PCA can be used to isolate covariant motions on a number of different length and time scales, and highlight the need for an adequate structural and dynamical account of many more PCs than have been conventionally examined in the analysis of protein motion.

Parkinson’s disease is a clinical syndrome manifesting with slowness and instability. As it is a progressive disease with varying symptoms, repeated assessments are necessary to determine the outcome of treatment changes in the patient. In the recent past, a computer-based method was developed to rate impairment in spiral drawings. The downside of this method is that it cannot separate the bradykinetic and dyskinetic spiral drawings. This work intends to construct the computer method which can overcome this weakness by using the Hilbert-Huang Transform (HHT) of tangential velocity. The work is done under supervised learning, so a target class is used which is acquired from a neurologist using a web interface. After reducing the dimension of HHT features by using PCA, classification is performed. C4.5 classifier is used to perform the classification. Results of the classification are close to random guessing which shows that the computer method is unsuccessful in assessing the cause of drawing impairment in spirals when evaluated against human ratings. One promising reason is that there is no difference between the two classes of spiral drawings. Displaying patients self ratings along with the spirals in the web application is another possible reason for this, as the neurologist may have relied too much on this in his own ratings.

The Strategies of the firms in Patent are not only about the future, but also forming the barrier for competitor. For the sake, we should develop the patent strategies and technological position.This study goes to the discussion of technological position by the patent multivariate analysis, and suggest the patent strategy by the difference within and between the groups which were clustered from IC design companies. This study selects twenty gobal IC design companies,which are always on the top25 of the industry.In case1 ,we wonder figure out the technological postion and the path of technology shift.In case2,we can recognize the technological position as industrial position. In case 1, we got four clusters by cluster analysis.Cluster 1 is called SpecialistII,and cluster2 is called Strong Generalist, and cluster 3 is called Specialist I,and cluster 4 is called Weak Generalist. For further observation, the firms with technology shift will shift from cluster 1 to cluster 2 in the same direction.Others still maintain the same strategies in their clusters. In case 2 , we also got four clusters by the analysis. Cluster 1 is called Weak Generalist ,and cluster 2 is called Strong Generalist, and cluster 3 is called Specialist I,and cluster 4 is called Specialist III.As financial results , we got homogeneity within a cluster except cluster 4. Performance between clusters, we made and observed the line chart of trend in the selected financial ratio and we used the median of samples within a cluster. In case 2,it seems heterogeneous in ROA and Price-to-book ratio in the chart.In case1,it is also heterogeneous in ROA and price-to-book ratio.It¡¦s significant and positively correlated in R&D productivity(GrossMargin-to-R&D ratio) between others by the correlation coefficient matrix.It seems to be the proxy to the other financial ratio.

ABSTRACT The relationships between high ozone events and synoptic weather patterns were investigated based on the meteorological and air-quality data at four monitoring stations in Kaohsiung city during 1997 to 2004 in this study. The PCA (principal component analysis) and correlation studies show that ozone concentration exhibit positive correlations with the ambient temperature and sunshine duration, while negative correlation with the cloud cover. The frequency of high ozone events was highest under the weather patterns of northeast seasonal wind (B1 type), high-pressure system with recirculation (B3 type), high-pressure system with offshore type (B2 type), and in the warm core of approaching front (B4 type), most frequently in autumn, winter, and spring, and least frequently in summer. The above four weather patterns are primarily dominated by the high-pressure system from Mainland China, with relatively cold and dry weather and little rain in Taiwan. Since the high-pressure center is usually located north or northeast of Taiwan during autumn, winter, and spring such that the leeside areas of Central Mountain Ranges in the western coast of Taiwan are prone to high pollution events, particularly when the wind speed is low (< 4m/s) and duration of sunshine is long (> 5.5 hr). Or sometimes the meso-scale wind system, for example, the sea-land breeze or the combined flow caused by the detouring flow from the Henchun Peninsula and northeast wind tends to raise the pollutant concentrations. Keywords¡GHigh ozone event, Synoptic weather pattern, Principal component analysis.

In recent years, a central focus of the field of early intervention/early childhood special education has been to investigate ways to effectively support young children with challenging behavior and their families (Center for Evidence-Based Practice: Young Children with Challenging Behavior, 2003; DEC, 1999). Positive behavior support (PBS) is one of the most promising evidence-based practices for young children with challenging behavior and their families. The central purposes of PBS are to both help people develop and engage in socially desirable behaviors and to help minimize patterns of socially stigmatizing responding (Koegel, Koegel, and Dunlap, 1996). Research documenting the utility and applicability of PBS with preschool-aged populations remain scarce, particularly within natural environments (e.g., Blair, Umbreit, and Eck, 2000; Duda, Dunlap, Fox, Clarke, and Lentini, 2004; Moes and Frea, 2000). Several gaps in the research remain, including studies incorporating natural intervention agents, natural settings, and studies measuring technical aspects of behavior change (e.g., maintenance). Though studies of maintenance may be difficult to execute, they may provide researchers with a greater understanding of which factors in the change process are most critical to successful implementation, as well as to enhance the goodness of fit between specific plan components and the ecology in which implementation occurs (Albin, Lucyshyn, Horner, and Flannery, 1996). The purpose of this research study was to first assess the relationship of support plan components to behavior change, and then systematically fade the functional components, reducing the plan to naturalistic strategies that may be easy for the family to use over time. Results indicated each of the three child participants consistently maintained low levels of challenging behavior and high levels of engagement within each routine, despite the fact that clear functional relationships among individual intervention components were not attained. Procedural fidelity data indicated that intervention components were both implemented by the mother on a consistent basis and were easily adapted into natural family routines over time.

In this research paper have been examined the ability of artificial neuron network, to project multidimensional data into smaller measurement expanse, by using the idea of main components. Described the usage of artificial neuron network and educational algorithm for specific features extraction and multidimensional data projection. Analyzed classical research methods of main components, and program KOMPONENTĖ has been designed to accomplish this particular work. Also there have been analyzed the possibilities of artificial neuron network to project the multidimensional data into the straight and plane. There have been designed programs TIESĖ, OJA and SANGER for this research paper. There have been accomplished and presented the results of this research. The results, obtained using classical main components method, were compared with results, obtained by neuron network realizabled main components. Additional conclusions maid about multidimensional data visualization problems, using the Y.H.Oja ir T.D.Sanger regulations and dependance of these regulations from parameter of educational precision, and parameter of significance of educational rate. Software operated in this research paper: Free Pascal IDE for WIN32 and Microsoft Excel 2003.

Healthy aging is associated with an increased incidence of injuries such as low back pain and falling. Age-related changes in trunk neuromuscular activation patterns could potentially explain uncontrolled trunk motion, a risk factor for these injuries. The purpose of this study was two-fold: i) to establish if trunk neuromuscular activation patterns differ between older and younger adults, and ii) to identify if increased cognitive load can alter the activation patterns used by older adults. Participants performed a controlled dynamic transfer task known to challenge trunk musculature by continuously changing the external moment experienced by the spine. In this thesis, the transfer task was altered by increasing the external moment and cognitive load to address purpose i) and ii) respectively. Three dimensional trunk and pelvis motion and surface electromyograms for 24 trunk muscle sites were collected in two experiments. In the first experiment 26 younger adults, and 17 older adults, performed the transfer task at two physical task intensities. In a second experiment, eight of these older adults performed the dynamic transfer task while performing a simultaneous cognitive dual-task. An analysis of amplitude and temporal characteristics of EMG waveforms, using principal component analysis, showed that older adults had altered trunk neuromuscular activation patterns compared to younger adults. In particular, after accounting for physical task intensity, older adults have increased antagonist co-activation, less temporal variation to changing external moments, and changes in the synergistic relationships between trunk muscle sites. Increasing the cognitive load had no influence on the trunk neuromuscular activation patterns used by healthy active older adults. However, as cognitive performance was not measured in the dual-task it cannot be excluded that i) the cognitive task did not represent enough challenge to result in competition of cortical resources, or ii) the cognitive resources necessary for the successful completion of the transfer task were prioritized in older adults.

The objectives of the present body of work were 1) to evaluate the Personal Lift-Assist Device (PLAD) in terms of its effect on lifting technique, interjoint coordination, and whether sex modulates these effects and 2) to explore the use of principal component analysis (PCA) as a method to investigate lifting waveforms. Thirty participants (15M, 15F) completed a freestyle, symmetrical lifting protocol during which three-dimensional kinematics of the ankle, knee, hip, and lumbar and thoracic spine were collected using a two-camera Optotrak 3020 system. There were four testing conditions: a) with and b) without wearing the PLAD; and c) 0% load and d) 10% of maximum back strength load. All data were evaluated using PCA. In the first analysis, the relationship between the PLAD and lifting technique under a loaded condition was explored. Results showed that 8 PCs were significantly different between the PLAD/No PLAD conditions yet there were no significant effects of sex on any of the PCs. It was concluded that wearing the PLAD encourages a lifting technique that is reflective of a squat lift, independent of sex. In the second analysis, the PLAD’s effect on interjoint coordination patterns under both loaded and unloaded conditions was examined using the relative phase angle (RPA). It was found that there were no significant differences between device, sex, or load conditions on any of the PCs retained in the model. A novel approach to enhance interpretability of PCs was developed during this study. Finally, when the PLAD was not worn, male and female differences were further investigated under loaded and unloaded conditions. It was determined that when the load is individualized to personal strength characteristics, sex differences in lifting technique are negligible. This is a contradictory finding from previous research. Overall, the major contributions of this research are: support for the use of the PLAD in industry; the recommendation that load be selected based on individual strength characteristics for lifting research experimental design; the use of PCA as a method to effectively evaluate lifting waveforms; and the development of a novel approach to aid in the interpretation of principal components. / Thesis (Master, Kinesiology & Health Studies) -- Queen's University, 2010-08-18 09:35:19.142

The objectives of the present study were: 1) to determine if there is a sex-based difference in lifting technique across increasing load conditions; and, 2) to examine the use of body size-adjusted tasks and back strength-adjusted loads in the analysis of lifting technique. Eleven male and 14 female participants (n=25) with no previous history of low back pain participated in the study. Participants completed freestyle, symmetric lifts of a box with handles from the floor to table height for five trials under three load conditions (10%, 20%, and 30% of their individual maximum isometric back strength). Joint kinematic data for the ankle, knee, hip, and lumbar and thoracic spine were collected using a two-camera Optotrak 3020 system (NDI, Waterloo, ON). Joint angles were calculated using a three-dimensional Euler rotation sequence and PCA was applied to assess differences in lifting technique across the entire waveform. A repeated measures ANOVA with a mixed design revealed no significant effect of sex for any of the PCs. This was contrary to previous research that used discrete points on the lifting curve to analyze sex-based differences but agreed with more recent research using more complex analysis techniques. There was a significant effect of load on lifting technique for six PCs of the lower limb (p<0.005). However, there was no significant difference in lifting technique for the thoracic and lumbar spine. It was concluded that, when load is standardized to individual back strength characteristics, males and females adopted a similar lifting technique. In addition, as load increases participants used more of a semi-squat or squat lifting technique. / Thesis (Master, Kinesiology & Health Studies) -- Queen's University, 2012-10-03 21:10:11.889