Investigating The Effects Of Tactile Stress On A Military Touniquet Application Task

In combat, soldiers encounter stress from multiple sources including loss of sleep, extremely high levels of physical and psychological discomfort, extended periods of increased vigilance, and intense danger. Therefore, it is imperative to train such personnel on how to cope with these stressors. One way to do this is to include stressors in different forms of training to acclimate soldiers to the subsequent stress of combat. Due to their advantages, tactile trainers are being investigated increasingly for the use of training Army medics in this context. The present work examines how vibrating tactile sensors, or tactors, can be used as surrogate sources of stress on an operator performing a simulated medical task. This work also examines how this optimal configuration interacts with other types of stress, such as noise and time pressure. The outcome findings support the hypotheses that configurations placed on sensitive body areas are more stressful than those placed on more benign body locations in terms of worse task performance on a tourniquet application task. In terms of application times, the same trends persist in terms of proper application, subjective stress and subjective workload, as well as a secondary monitoring task, in terms of response times, accuracy, and time estimation. Additionally, findings supported hypotheses that the stress responses experienced order tactile stress alone is compounded when other types of stress are employed, both on the primary and secondary tasks. These results have implications for training, such that if stressors are employed in training, performance decrements might be lessened during actual task performance; they can be generalized to not only combat medics, but other military specialties and civilian jobs that incur vibration, auditory stress, and time pressure while engaged in performance

THE RATIONALE BEHIND WEAKLY TIED NETWORKING OF THE BANGLADESHI DIASPORA IN MALAYSIA

This paper is an exploration of the survival strategies of the Bangladeshi Diaspora in Malaysia. To cope with the realities, Bangladeshi migrants develop different forms of survival strategies. As a result intra and inter-ethnic strong and weak ties are formed in the receiving country. Empirical analysis depicts that respondents with weak ties have higher income mobility than those with strong ties. It also demonstrates that the Bangladeshi migrants of the study areas do not restrict themselves only to their close social networks; rather they develop distant networks for higher social mobility. Or in other words, though the ideal socio-cultural model emphasizes community cohesion (something that can be conceptualized as an example of a tightly structured social system), the actual behavior of the Bangladeshi migrants indicates a loosely or disintegrated social system. Migrant's embeddedness in the ongoing social relations and power structures regulates the nature and strength of these ties

Quality of Life in Macular Degeneration Between Photodynamic Therapy and Pegaptanib Treatment Groups

The purpose of this study was to examine quality of life (QOL) in age-related macular degeneration (AMD), particularly across photodynamic therapy (PDT) and pegaptanib sodium injection treatment groups. Patients with AMD were either mailed or were administered in person a modified version of the Visual Function Questionnaire (VFQ-25). Subgroup analysis of the VFQ-25 was performed per NEI prescribed algorithms and additional analyses regarding questions on treatment side effects were also performed. A two-tailed student t-test and mean were calculated for each treatment group and correlations between visual acuity and subgroup outcomes were calculated. Correlations between the subgroup and treatment-related subgroup outcomes were also calculated to determine which QOL deficits might occur together. Multiple linear regression models were used to estimate the association between the overall QOL score and scaled visual acuity, age, gender, and treatment history. 30 patients were interviewed in person and an additional 41 patients returned the questionnaire by mail. Of these, 37 had been treated with PDT (ten had also received intravitreal triamcinolone acetate (IVTA) injections); 16 had been treated with pegaptanib; seven had been treated with both pegaptanib and PDT (two had also received IVTA); and 25 had not been treated with any of these treatments. The mean age was 79 years. Patients lowest subgroup scores were in perception of general vision (43.2) and in driving (50.8). The ocular pain subgroup yielded a mean score of 82.9 for the PDT group and 87.5 for the pegaptanib group (p = 0.59). The average vision worsening score for the first two weeks following treatment was 87.5 for the PDT group and 77.8 for the pegaptanib group (p = 0.29). The average mental health score for concerns related to treatments was 78.2 for the PDT group and 73.6 for the pegaptanib group (p = 0.61), while the average independence score related to treatment appointments was 86.1 for the PDT group and 87.5 for the pegaptanib group (p = 0.92). Strong positive correlations (\u3e 0.45) were seen between general health and ocular pain; between treatment-related mental health and both overall QOL score and treatment-related vision worsening; and between numerous measures of visual function. The best predictor of overall QOL score was the near activities score. Age was moderately or weakly negatively correlated with multiple measures. Stepwise multiple linear regression analysis demonstrated that the square of SVA provided the most explanatory power for the overall QOL score, implying a non-linear relationship between visual acuity and QOL. None of the treatment modalities added explanatory power to the model when added to the square of SVA. In conclusion, QOL, stress regarding treatment, and ocular pain did not differ between PDT and pegaptanib treatment groups. Decreasing visual acuity was associated most strongly with decreases in ability to perform near and distance activities, overall QOL, driving, and independence. Scales denoting worry and frustration about treatment did not demonstrate a strong relationship to visual function, implying patient concern about treatment across the visual acuity spectrum. A nonlinear relationship was seen between QOL and visual acuity

Nanomaterials Embedded Nitrogen-Doped Graphene for Advanced Energy Storage and Conversion

A facile synthesis of nitrogen-doped graphene with high atomic percentage of Nitrogen (9.2 at%) including high ratio of pyridinic N and graphitic N has been reported via thermal annealing of graphene oxide with uric acid. The resultant material shows efficient electrochemical properties for capacitances and bifunctional electrocatalysis of oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). In spite of its remarkable electrochemical properties, the major limitation of the two-dimensional graphene like materials for device fabrication or commercial applications is the restacking nature of the layers. Designing a three-dimensional nanostructure via inserting metal nanoparticles or one-dimensional carbonaceous nanomaterials inside the graphene layers can prevent the restacking of the layers and hence enhance the electrochemical properties of the composites by providing higher electroactive surface area for electrolyte permeation, charge storage as well as active sites for electrocatalysis. To enhance the electrocatalytical activity of the synthesized nitrogen-doped graphene, a hybrid of nickel embedded nitrogen-doped graphene is developed. The composite shows superior noble-metal-free quadrafunctional electrocatalysis of oxygen reduction reaction (ORR), oxygen evolution reaction (OER), hydrogen evolution reaction (HER) and hydrogen peroxide oxidation reaction (HPOR) compared to commercial electrocatalysts of Pt/C and Ru/C. Alternatively, the insertion of carbon nanotubes inside the graphene layers and fabricating a lamellar three-dimensional nanostructure exhibit excellent supercapacitor behavior as fabricated as solid-state supercapacitor and high-rate capable anode for Li-ion battery as well as metal-free bifunctional electrocatalysis of ORR and OER. In addition, the decoration of copper nanoparticles in the three-dimensional nanostructured nitrogen-doped graphene/carbon nanotube composite further improves the conductivity and electrochemical properties via interconnecting network of copper nanoparticles and carbon nanotubes with the graphene layers and have been evaluated for high performance metal-ion battery applications. The resultant composites show promising electrochemical performances for developing as electrode materials for next generation energy storage and conversion devices like solid-state supercapacitor, metal-ion battery, metal-air battery and rechargeable fuel cells

The pattern of perineuronal net elements in the mediodorsal thalamus

Perineuronal nets (PNNs) decrease neuroplasticity, increase stability of neural systems, and are key to ending the neurodevelopmental critical period. PNNs are found throughout the brain, including the mediodorsal (MD) thalamus, a key region in cortico-thalamo-cortical communication with the prefrontal cortex (PFC). I examined the structure and location of PNN elements relative to axons in the MD thalamus from post-mortem human brain tissue in three normal individuals. Using electron microscopy and two-dimensional analysis, my results showed that about a third of axons have a consistent distribution of the PNN element brevican. A vital component of PNNs, the chondroitin sulfate proteoglycan (CSPG) brevican was found within the cytoplasm, within the myelin, and outside the myelin along the length of axons. Three-dimensional analyses and axon reconstructions showed that the quantity of brevican varied periodically along axons in a wave-like manner. These findings suggest a model for the arrangement of brevican in a weaving pattern through myelin, cytoplasm, and external surface of axons. This model of PNN elements has various functional implications, including influence on the growth and function of axons, ion homeostasis along the axon, and the ability of neurons to produce and transmit action potentials. These structures likely have a significant impact on the function of MD. The combined influence of PNNs and connections of the MD thalamus with the PFC may play powerful roles in various cognitive disorders, including schizophrenia

Dimensionality reduction and classification of time embedded EEG signals

Department Head: L. Darrell Whitley.2007 Summer.Includes bibliographical references (pages 49-51).Electroencephalogram (EEG) is the measurement of the electrical activity of the brain measured by placing electrodes on the scalp. These EEG signals give the micro-voltage difference between different parts of the brain in a non-invasive manner. The brain activity measured in this way is being currently analyzed for a possible diagnosis of physiological and psychiatric diseases. These signals have also found a way into cognitive research. At Colorado State University we are trying to investigate the use of EEG as computer input. In this particular research our goal is to classify two mental tasks. A subject is asked to think about a mental task and the EEG signals are measured using six electrodes on his scalp. In order to differentiate between two different tasks, the EEG signals produced by each task need to be classified. We hypothesize that a bottleneck neural network would help us to classify EEG data much better than classification techniques like Linear Discriminant Analysis(LDA), Quadratic Discriminant Analysis (QDA), and Support Vector Machines. A five layer bottleneck neural network is trained using a fast convergence algorithm (variation of Levenberg-Marquardt algorithm) and Scaled Conjugate Gradient (SCG). Classification is compared between a neural network, LDA, QDA and SVM for both raw EEG data as well as bottleneck layer output. Results indicate that QDA and SVM do better classification of raw EEG data without a bottleneck network. QDA and SVM always achieved higher classification accuracy than the neural network with a bottleneck layer in all our experiments. Neural network was able to achieve its best classification accuracy of 92% of test samples correctly classified, whereas QDA achieved 100% accuracy in classifying the test data