Standard Statistical Transformations (Logarithm and Logit) are Uniquely Determined by the Corresponding Symmetries

Abstract Logarithm and logit transformations are well-established in statistics: logarithm transforms an allpositive quantity into a quantity that can take arbitrary real value, and logit does the same for a random variables whose values are limited to the interval (0, 1). In this paper, we analyze possible symmetries of such transformations, and we also show that, in effect, these two transformations are the only ones which are invariant with respect to the corresponding symmetries

Hydroxyurea-induced hyperpigmentation with iron deposition

Hydroxyurea is a chemotherapeutic agent that is used in the treatment of various hematological diseases including chronic myelogenous leukemia, polycythemia vera, and sickle cell anemia. Hydroxyurea is also used to treat psoriasis. Drug-induced hyperpigmentation is a known cutaneous side effect of hydroxyurea along with xerosis, dermal ulcers, and dermatomyositis-like eruptions. Hyperpigmentation has been observed in the oral mucosa, nails, and in a generalized or a diffuse pattern. The mechanism of hyperpigmentation related to hydroxyurea is believed to be correlated with increased melanin. Classically, clinical types of diffuse hyperpigmentation owing to iron deposition in the dermis have been associated with minocycline and not with hydroxyurea. We report a novel case in which hydroxyurea hyperpigmentation is associated with iron deposition

Towards The Use of Aesthetics in Decision Making: Kolmogorov Complexity Formalizes Birkhoff's Idea

Decision making is traditionally based on utilitarian criteria such as cost, efficiency, time, etc. These criteria are reasonably easy to formalize; hence, for such criteria, we can select the best decision by solving the corresponding well-defined optimization problem. In many engineering projects, however, e.g., in designing cars, building, airplanes, etc., an important additional criterion which needs to be satisfied is that the designed object should be good looking. This additional criterion is difficult to formalize and, because of that, it is rarely taken into consideration in formal decision making. In the 1930s, the famous mathematician G. D. Birkhoff has proposed a formula that described beauty in terms of "order" and "complexity". In the simplest cases, he formalized these notions and showed that his formula is indeed working. However, since there was no general notion of complexity, he was unable to formalize his idea in the general case. In this paper, we show that the exi..

Upcoming topical TRPV1 anti-pruritic compounds

Transient receptor potential vanilloid type 1 (TRPV1) is found on sensory neurons, keratinocytes, sebocytes, and dendritic cells. Activated TRPV1 channels are believed to help propagate the itch sensation. Therefore, there has been great interest in targeting TRPV1 to treat pruritus. Since oral formulations aimed at TRPV1 have led to adverse effects such as hyperthermia, there has been emphasis on developing novel topical agents. Several companies are investigating topical TRPV1 anti-pruritic compounds and the initial data has been very promising. These drugs have the potential to be important treatment options for the management of itch. This paper reviews topical products in current development for pruritus that target TRPV1 channels

TOWARDS OPTIMAL FEW-PARAMETRIC REPRESENTATION OF SPATIAL VARIATION: GEOMETRIC APPROACH AND ENVIRONMENTAL APPLICATIONS

Abstract. In this paper, we use geometric approach to show that under reasonable assumption, the spatial variability of a field f(x), i.e., the expected value F (z) def = E[(f(x + z) − f(x)) 2], has the form α n ∑ n∑ F (z) = gij · zi · zj. We explain how to find gij and α from ∣i=1 j=1 ∣ the observations, and how to optimally place sensors in view of this spatial variability. Need to describe spatial variability. To understand climate trends, we need to describe not only the values of temperature, humidity, wind speed and direction at a single location, we also need to kno

Upcoming topical TRPV1 anti-pruritic compounds

Transient receptor potential vanilloid type 1 (TRPV1) is found on sensory neurons, keratinocytes, sebocytes, and dendritic cells. Activated TRPV1 channels are believed to help propagate the itch sensation. Therefore, there has been great interest in targeting TRPV1 to treat pruritus. Since oral formulations aimed at TRPV1 have led to adverse effects such as hyperthermia, there has been emphasis on developing novel topical agents. Several companies are investigating topical TRPV1 anti-pruritic compounds and the initial data has been very promising. These drugs have the potential to be important treatment options for the management of itch. This paper reviews topical products in current development for pruritus that target TRPV1 channels

Fixed Future and Uncertain Past: Theorems Explain Why It Is Often More Difficult to Reconstruct the Past Than to Predict the Future

At first glance. it may seem that reconstructing the past is, in general, easier than predicting the future, because the past has already occurred and it has already left its traces, while the future is still yet to come, and so no traces of the future are available. However, in many real life situations, including problems from geophysics and celestial mechanics, reconstructing the past is much more computationally difficult than predicting the future. In this paper, we give an explanation of this difficulty. This explanation is given both on a formal level (as a theorem) and on the informal level (as a more intuitive explanation)

Estimating sample mean under interval uncertainty and constraint on sample varience

Traditionally, practitioners start a statistical analysis of a given sample x1, … , xn by computing the sample mean E and the sample variance V. The sample values xi usually come from measurements. Measurements are never absolutely accurate and often, the only information that we have about the corresponding measurement errors are the upper bounds Δi on these errors. In such situations, after obtaining the measurement result , the only information that we have about the actual (unknown) value xi of the ith quantity is that xi belongs to the interval . Different values xi from the corresponding intervals lead, in general, to different values of the sample mean and sample variance. It is therefore desirable to find the range of possible values of these characteristics when xi ∈ xi. Often, we know that the values xi cannot differ too much from each other, i.e., we know the upper bound V0 on the sample variance V : V ⩽ V0. It is therefore desirable to find the range of E under this constraint. This is the main problem that we solve in this paper