Analysis of coronary angiography related psychophysiological responses

<p>Abstract</p> <p>Background</p> <p>Coronary angiography is an important tool in diagnosis of cardiovascular diseases. However, it is the administration is relatively stressful and emotionally traumatic for the subjects. The aim of this study is to evaluate psychophysiological responses induced by the coronary angiography instead of subjective methods such as a questionnaire. We have also evaluated the influence of the tranquilizer on the psychophysiological responses.</p> <p>Methods</p> <p>Electrocardiography (ECG), Blood Volume Pulse (BVP), and Galvanic Skin Response (GSR) of 34 patients who underwent coronary angiography operation were recorded. Recordings were done at three phases: "1 hour before," "during," and "1 hour after" the coronary angiography test. Total of 5 features obtained from the physiological signals were compared across these three phases. Sixteen of the patients were administered 5 mg of a tranquilizer (Diazepam) before the operation and remaining 18 were not.</p> <p>Results</p> <p>Our results indicate that there is a strong correlation between features (LF/HF, Bk, DN1/DN2, skin conductance level and seg_mean) in terms of reflecting psychophysiological responses. However only DN1/DN2 feature has statistically significant differences between angiography phases (for diazepam: p = 0.0201, for non_diazepam p = 0.0224). We also note that there are statistically significant differences between the diazepam and non-diazepam groups for seg_mean features in "before", "during" and "after" phases (p = 0.0156, 0.0282, and 0.0443, respectively).</p> <p>Conclusions</p> <p>The most intense sympathetic activity is observed in the "during" angiography phase for both of the groups. The obtained features can be used in some clinical studies where generation of the customized/individual diagnoses styles and quantitative evaluation of psychophysiological responses is necessary.</p

MARITIME ACCIDENT ANALYSIS AT TURKISH COASTAL WATERS IN 2004-2008 INCLUDING SHIPS ON INTERNATIONAL VOYAGE

Denizyolu ile taşımacılık şüphesiz riskli bir aktivitedir ve gemi operasyonlarınınkarmaşık olmasından dolayı yıllardır kaçınılmaz bir şekilde deniz kazaları meydanagelmektedir. Deniz kazaları riskinin olması yaşamsal, ekonomik ve çevresel risklerin deolması demektir. Bu nedenle, deniz kazaları riskinin en aza indirilmesi ve seyir emniyetiadına gerekli önlemlerin alınması için meydana gelen deniz kazalarının analizleri ve buanalizlerin değerlendirilmesi büyük önem arz etmektedir. Bu çalışmada, kıyılarımızdauluslararası sefer yapan gemilerin karıştığı kazaların, kaza inceleme raporları analizedilerek, kazalara neden olan faktörlerin belirlenmesi ve bu faktörler arasındaki ilişkilerindeğerlendirilmesi amaçlanmıştır. Shipping is undoubtedly a risky activity and maritime accidents at sea occurinevitably for many years due to ship operations are complex. Being of maritime accidentsrisk means being of vital risks, economical risks and environmental risks. So, maritimeaccidents analyses and evaluations of these analyses' results are more important forminimizing the maritime accident risks and taking necessary measures for safety ofnavigation. In this study, it is aimed to determination of factors caused to maritimeaccidents and evaluation of relations between these factors by analysing data on maritimeaccident investigation reports belong to ships which are on international voyages in ourcoastal waters

Use of Meixner functions in estimation of Volterra kernels of nonlinear systems with delay

Volterra series representation of nonlinear systems is a mathematical analysis tool that has been successfully applied in many areas of biological sciences, especially in the area of modeling of hemodynamic response. In this study, we explored the possibility of using discrete time Meixner basis functions (MBFs) in estimating Volterra kernels of nonlinear systems. The problem of estimation of Volterra kernels can be formulated as a multiple regression problem and solved using least squares estimation. By expanding system kernels with some suitable basis functions, it is possible to reduce the number of parameters to be estimated and obtain better kernel estimates. Thus far, Laguerre basis functions have been widely used in this framework. However, research in signal processing indicates that when the kernels have a slow initial onset or delay, Meixner functions, which can be made to have a slow start, are more suitable in terms of providing a more accurate approximation to the kernels. We, therefore, compared the performance of Meixner functions, in kernel estimation, to that of Laguerre functions in some test cases that we constructed and in a real experimental case where we studied photoreceptor responses of photoreceptor cells of adult fruitflies (Drosophila melanogaster). Our results indicate that when there is a slow initial onset or delay, MBF expansion provides better kernel estimates

The Impact of Global Economic Crisis on Human Resources Strategies in Maritime Industry

Human resource is one of the leading determinants in maritime transport industry and both the industry and the individual shipping companies consider human resources strategies as an important area of research. The global financial and economic crisis that has been affecting international trade and shipping in a very dramatic way since the fourth quarter of 2008 forces researchers to examine the short and long term trends in maritime careers generally and particularly in seagoing professions. This study aims to research the developments in human resources strategies during the global financial and economic crisis. A survey was applied to the human resources managers in shipping companies in Turkey in order to define their human resources strategies. Through this research it is aimed to evaluate the human resources strategies in the field of resourcing, recruiting, selection and retention, compensation, performance management, training and development

Cooperative learning and teamwork effectiveness: impacts of education period on cadets

Abstract Maritime industry is a multinational industry where participants of several languages and cultures operate in a global teamwork environment. Seafarers&apos; operating procedures are totally based on a teamwork infrastructure and climate. By the introduction of Safety Management Systems, shore-based human resources are also included in the wider system of the maritime teamwork of the company where information and communication technologies have accelerated this integration. Goals and tasks for the team, team composition, team-player styles, phases of team development, communication and interpersonal skills, decision making, leadership, and evaluation of team performance are the key elements in developing the structure of the teamwork based systems. Training and development is the main instrument in preparing the human resources for the teamwork climate of modern organizations. Education methodologies that support the characteristics, which encourage teamwork and cooperation, are widely applied in maritime education. Cooperative learning and problem-based learning are among those approaches. This study analyzes the effects of cooperative learning dimensions among the cadets in a maritime higher education institute with regard to teamwork effectiveness. An empirical study has been realized to measure the effects of cooperative learning dimensions on 1) individual performance in groups, 2) effective team members. To comment on the impacts of the education period on these dimensions, the study aims to realize a comparative analysis among the cadets of a senior clas s, before and after a simulator based bridge team management course

Nonpreserved amniotic membrane transplantation for bilateral toxic keratopathy caused by topical anesthetic abuse: a case report

<p>Abstract</p> <p>Introduction</p> <p>Corneal damage associated with abuse of topical anesthetics is a rare clinic entity. Topical anesthetic abuse is one of the causes of ring keratitis. Ring keratitis is easily overlooked because it can mimic acanthamoeba keratitis or other infectious keratitis. The outcome is often poor, leading to persistent epithelial defects, corneal scarring, and perforations.</p> <p>Case presentation</p> <p>We report the clinical presentation, diagnosis, and treatment of a 65-year-old Caucasian man, who worked as a health care worker, with bilateral toxic keratopathy caused by topical anesthetic abuse. Nonpreserved amniotic membrane transplantation was performed for both eyes of the patient.</p> <p>Conclusion</p> <p>It is important to identify and treat patients who abuse topical anesthetics before permanent vision loss ensues. Nonpreserved amniotic membrane transplantation may be useful in relieving pain and improving corneal surface in anesthetic agent abusers.</p

Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction

&lt;b&gt;Background&lt;/b&gt; The widely used k top scoring pair (k-TSP) algorithm is a simple yet powerful parameter-free classifier. It owes its success in many cancer microarray datasets to an effective feature selection algorithm that is based on relative expression ordering of gene pairs. However, its general robustness does not extend to some difficult datasets, such as those involving cancer outcome prediction, which may be due to the relatively simple voting scheme used by the classifier. We believe that the performance can be enhanced by separating its effective feature selection component and combining it with a powerful classifier such as the support vector machine (SVM). More generally the top scoring pairs generated by the k-TSP ranking algorithm can be used as a dimensionally reduced subspace for other machine learning classifiers.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Results&lt;/b&gt; We developed an approach integrating the k-TSP ranking algorithm (TSP) with other machine learning methods, allowing combination of the computationally efficient, multivariate feature ranking of k-TSP with multivariate classifiers such as SVM. We evaluated this hybrid scheme (k-TSP+SVM) in a range of simulated datasets with known data structures. As compared with other feature selection methods, such as a univariate method similar to Fisher's discriminant criterion (Fisher), or a recursive feature elimination embedded in SVM (RFE), TSP is increasingly more effective than the other two methods as the informative genes become progressively more correlated, which is demonstrated both in terms of the classification performance and the ability to recover true informative genes. We also applied this hybrid scheme to four cancer prognosis datasets, in which k-TSP+SVM outperforms k-TSP classifier in all datasets, and achieves either comparable or superior performance to that using SVM alone. In concurrence with what is observed in simulation, TSP appears to be a better feature selector than Fisher and RFE in some of the cancer datasets.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusions&lt;/b&gt; The k-TSP ranking algorithm can be used as a computationally efficient, multivariate filter method for feature selection in machine learning. SVM in combination with k-TSP ranking algorithm outperforms k-TSP and SVM alone in simulated datasets and in some cancer prognosis datasets. Simulation studies suggest that as a feature selector, it is better tuned to certain data characteristics, i.e. correlations among informative genes, which is potentially interesting as an alternative feature ranking method in pathway analysis

Covert Waking Brain Activity Reveals Instantaneous Sleep Depth

The neural correlates of the wake-sleep continuum remain incompletely understood, limiting the development of adaptive drug delivery systems for promoting sleep maintenance. The most useful measure for resolving early positions along this continuum is the alpha oscillation, an 8–13 Hz electroencephalographic rhythm prominent over posterior scalp locations. The brain activation signature of wakefulness, alpha expression discloses immediate levels of alertness and dissipates in concert with fading awareness as sleep begins. This brain activity pattern, however, is largely ignored once sleep begins. Here we show that the intensity of spectral power in the alpha band actually continues to disclose instantaneous responsiveness to noise—a measure of sleep depth—throughout a night of sleep. By systematically challenging sleep with realistic and varied acoustic disruption, we found that sleepers exhibited markedly greater sensitivity to sounds during moments of elevated alpha expression. This result demonstrates that alpha power is not a binary marker of the transition between sleep and wakefulness, but carries rich information about immediate sleep stability. Further, it shows that an empirical and ecologically relevant form of sleep depth is revealed in real-time by EEG spectral content in the alpha band, a measure that affords prediction on the order of minutes. This signal, which transcends the boundaries of classical sleep stages, could potentially be used for real-time feedback to novel, adaptive drug delivery systems for inducing sleep

Fly Photoreceptors Encode Phase Congruency

More than five decades ago it was postulated that sensory neurons detect and selectively enhance behaviourally relevant features of natural signals. Although we now know that sensory neurons are tuned to efficiently encode natural stimuli, until now it was not clear what statistical features of the stimuli they encode and how. Here we reverse-engineer the neural code of Drosophila photoreceptors and show for the first time that photoreceptors exploit nonlinear dynamics to selectively enhance and encode phase-related features of temporal stimuli, such as local phase congruency, which are invariant to changes in illumination and contrast. We demonstrate that to mitigate for the inherent sensitivity to noise of the local phase congruency measure, the nonlinear coding mechanisms of the fly photoreceptors are tuned to suppress random phase signals, which explains why photoreceptor responses to naturalistic stimuli are significantly different from their responses to white noise stimuli