Lichen secondary metabolites in Umbilicaria antarctica evaluated by acetone rinsing ( Short Communication )

Study of the extracts from an Antarctic lichen Umbilicaria antarctica was done using a spectrophotometric approach. Secondary compounds were extracted by acetone rinsing from dried thalli of U. antarctica. The extracts were dried out, and diluted in ethanol. Then, spectral absorbance of the extracts were measured within the wavelength of 190-700 nm. The spectra of the secondary compounds obtained by acetone rinsing (EAR – re-diluted (ethanol) extract gained during acetone rinsing) were compared with those from untreated thalli (control) and ethanol extract from the thalli of U. antarctica that passed acetone rinsing (ART). Spectral absorbance curves of the extracts gained by acetone rinsing were attributed to different prevailing secondary metabolites: usnic acid, lecanoric acid (U. antarctica). Spectral absorption curves of control thalli exbibited similar shape as ART spectral curves, however, the absorbance in the range of 230-310 nm reached higher values in control than in ART. Spectral absorbance curves from ART showed that a part of secondary metabolites still remained in the thalli. Photosynthetic pigments (carotenoids and chlorophylls) remained uneffected by acetone rinsing

Extracranial Herpetic Paresis

Segmental zoster paresis (SZP) is a rare complication of varicella zoster infection that occurs due to the spread of the infection from the posterior horn of spinal cord to the anterior horn and the motor nerve root. As recognizing segmental zoster paresis is important in the differential diagnosis of muscle weakness of other origin, information about demographic (gender and age), clinical presentation, diagnosis, treatment, and course about published patients with SZP was extracted from PubMed database. SZP is classified into several categories: paresis of upper extremity, lower limb involvement, diaphragmatic involvement, and abdomen involvement. Published experiences have shown that clinical course and electromyoneurography of paretic muscle are the most important in the diagnosis; physical therapy is the most common therapy in these patients and their prognosis is generally good except diaphragmatic paresis, where there is no significant recovery in most number of patients

Deep reinforcement learning from human preferences

For sophisticated reinforcement learning (RL) systems to interact usefully with real-world environments, we need to communicate complex goals to these systems. In this work, we explore goals defined in terms of (non-expert) human preferences between pairs of trajectory segments. We show that this approach can effectively solve complex RL tasks without access to the reward function, including Atari games and simulated robot locomotion, while providing feedback on less than one percent of our agent's interactions with the environment. This reduces the cost of human oversight far enough that it can be practically applied to state-of-the-art RL systems. To demonstrate the flexibility of our approach, we show that we can successfully train complex novel behaviors with about an hour of human time. These behaviors and environments are considerably more complex than any that have been previously learned from human feedback

Oscillations on the star Procyon

Stars are sphere of hot gas whose interiors transmit acoustic waves very efficiently. Geologists learn about the interior structure of Earth by monitoring how seismic waves propagate through it and, in a similar way, the interior of a star can be probed using the periodic motions on the surface that arise from such waves. Matthews et al. claim that the star Procyon does not have acoustic surface oscillations of the strength predicted. However, we show here, using ground-based spectroscopy, that Procyon is oscillating, albeit with an amplitude that is only slightly greater than the noise level observed by Matthews et al. using spaced-based photometry

BIOFEEDBACK AND NEUROFEEDBACK APPLICATION IN THE TREATMENT OF MIGRAINE

Introduction: Biofeedback is a non-invasive method of measurement of physiological functions. Precise instruments measure the slightest changes of different body functions-which are then in a clear and understandable manner shown in the form of feedback. Person gets an insight into what is going on inside the body and thus learns to change the patterns of behavior to improve health and performance. Any changes that are wanted are rewarded, which leads to learning of the new patterns of behavior. Neurofeedback is a type of biofeedback which uses electrical activity in the brain. Certain disorders are associated with specific patterns of brain activity, and through neurofeedback it is possible to reduce or even remove symptoms of some disorders. In the treatment of migraine different biofeedback methods- such as breathing, training of vasoconstriction/vasodilatation and neurofeedback, may be applied. Methods: This paper will describe the successful treatment of 25 years old girl who suffered for many years from painful migraine. She had in total25 treatments during which listed biofeedback methods were used. The first part of the treatment was neurofeedback training on the central sensorimotor area, followed by respiration training and at the end by biofeedback training of vasoconstriction/vasodilatation. Results and Conclusion: The final result of the treatment was significant reduce in the frequency of migraine attacks and the pain reduction. Further study, have to be done with more patients and with placebo group to scientifically prove the effectiveness of he method

Designing a Profit-Maximizing Product Line for Heterogeneous Market

Designing product line is important marketing decision that affects the firm\u27s overall performances and profitability. This is particularly important due to the fact that the contemporary markets are characterized by sophisticated and diverse preferences of consumers as well as strong competition. Therefore, to meet market demand, firms prefer to offer a product line instead of a single product. In order to decide both on the number and position of products in its product line, the company should understand the way in which consumers value and choose products. For that purpose, a multi-attribute research technique known as conjoint analysis can be used. At the same time, the company should take into account product and pricing strategy of competitors and the possible competitors’ reactions on its own strategy. For modelling market competition, the concept of the Nash equilibrium appears as an appropriate tool. This paper proposes a model for designing a competitive profit-maximizing product line for a heterogeneous market. Preferences were modelled by a model of partial utilities associated with the corresponding attribute levels, while the logit model is used to transform respondents’ preferences into a potential market share. The problem of optimizing the product line was formulated as a nonlinear binary programming model. Proposed model was tested on the previously published conjoint data set, thus confirming its efficiency and applicability

A New Approach to Evaluation of University Teaching Considering Heterogeneity of Students’ Preferences

AbstractStudents’ evaluations of teaching are increasingly used by universities to evaluate teaching performance. However, these evaluations are controversial mainly due to fact that students value various aspects of excellent teaching differently. Therefore, in this paper we propose a new approach to student evaluation of university teaching based on data from conjoint analysis. Conjoint analysis is a multivariate technique used to analyze the structure of individuals’ preference. In particular, our approach accounts for different importance students attach to various aspects of teaching. Moreover, it accounts explicitly for heterogeneity arising from student preferences, and incorporates it to form comprehensive teaching evaluation score. We have conducted survey and confirmed applicability and efficiency of the proposed approach