Are Hand Preference and Sexual Orientation Possible Predicting Factors for Finasteride Adverse Effects in Male Androgenic Alopecia?

Sexual side effects of finasteride seem to be redoubtable, being encountered not only during therapy but also after treatment cessation. Consequently, any possible clinical/paraclinical elements that might predict these adverse effects would be useful in the selection of a therapeutic strategy for male androgenic alopecia. Previous published studies show that some compounds that interfere with sexual hormones can decrease sexual activation and response, according to hand preference (as reported for finasteride and tamoxifen) and according to sexual orientation (as noted for bicalutamide). Our preliminary published data and the arguments presented here suggest that these two individual parameters might be used by dermatologists in the therapeutic approach of male androgenic alopecia, so as to alert specific subsets of men, prior to treatment, of the potential increased risk for developing adverse effects to finasteride

Dilemmas of Rawlsian Opportunity

John Rawls's repeated assertions that the basic structure of society creates profound and inevitable differences in life prospects for people born in different starting places seems to contradict his assertions that, under fair equality of opportunity, a person's life prospects would not be affected by class of origin for those similarly endowed and motivated. This seeming contradiction seems to be resolved by Rawls's apparent belief that class of origin inevitably affects motivation. This reconciliation leaves us with a very weak conception of "fair equality of opportunity." Should Rawls have advocated something stronger? Within the constraints of his theory of justice nothing stronger seems possible. Still, his theory harbors highly implausible sociological assumptions. A more plausible sociology requires us to reject distributive justice in favor of contributive justice

Fingerprinting-Based Positioning in Distributed Massive MIMO Systems

Location awareness in wireless networks may enable many applications such as emergency services, autonomous driving and geographic routing. Although there are many available positioning techniques, none of them is adapted to work with massive multiple-in-multiple-out (MIMO) systems, which represent a leading 5G technology candidate. In this paper, we discuss possible solutions for positioning of mobile stations using a vector of signals at the base station, equipped with many antennas distributed over deployment area. Our main proposal is to use fingerprinting techniques based on a vector of received signal strengths. This kind of methods are able to work in highly-cluttered multipath environments, and require just one base station, in contrast to standard range-based and angle-based techniques. We also provide a solution for fingerprinting-based positioning based on Gaussian process regression, and discuss main applications and challenges.Comment: Proc. of IEEE 82nd Vehicular Technology Conference (VTC2015-Fall

Semilogarithmic Nonuniform Vector Quantization of Two-Dimensional Laplacean Source for Small Variance Dynamics

In this paper high dynamic range nonuniform two-dimensional vector quantization model for Laplacean source was provided. Semilogarithmic A-law compression characteristic was used as radial scalar compression characteristic of two-dimensional vector quantization. Optimal number value of concentric quantization domains (amplitude levels) is expressed in the function of parameter A. Exact distortion analysis with obtained closed form expressions is provided. It has been shown that proposed model provides high SQNR values in wide range of variances, and overachieves quality obtained by scalar A-law quantization at same bit rate, so it can be used in various switching and adaptation implementations for realization of high quality signal compression

Knowledge-based entrepreneurship in Central and Eastern Europe: myth and reality

This paper summarises results of a survey of 304 knowledge based firms in six central and east European (CEE) countries. Knowledge-based entrepreneurs in CEE are not ‘gazelles’ (i.e., fast growing new technology based firms which have the potential to reshape the industrial landscape). They consist of distinct types of companies, of which new technology based firms (NTBFs) are only one. The key factor in KBE firms’ growth is most often firm specific capabilities which do not always involve R&D. Based on factor analysis we develop several taxonomies of KBEs which all point to a specific nature of knowledge based entrepreneurship in CEE. The networks of KBEs are broader and more frequently involve innovation system actors, including professional networks. For different types of KBEs different networks are important

Belief Consensus Algorithms for Fast Distributed Target Tracking in Wireless Sensor Networks

In distributed target tracking for wireless sensor networks, agreement on the target state can be achieved by the construction and maintenance of a communication path, in order to exchange information regarding local likelihood functions. Such an approach lacks robustness to failures and is not easily applicable to ad-hoc networks. To address this, several methods have been proposed that allow agreement on the global likelihood through fully distributed belief consensus (BC) algorithms, operating on local likelihoods in distributed particle filtering (DPF). However, a unified comparison of the convergence speed and communication cost has not been performed. In this paper, we provide such a comparison and propose a novel BC algorithm based on belief propagation (BP). According to our study, DPF based on metropolis belief consensus (MBC) is the fastest in loopy graphs, while DPF based on BP consensus is the fastest in tree graphs. Moreover, we found that BC-based DPF methods have lower communication overhead than data flooding when the network is sufficiently sparse

Target Tracking in Confined Environments with Uncertain Sensor Positions

To ensure safety in confined environments such as mines or subway tunnels, a (wireless) sensor network can be deployed to monitor various environmental conditions. One of its most important applications is to track personnel, mobile equipment and vehicles. However, the state-of-the-art algorithms assume that the positions of the sensors are perfectly known, which is not necessarily true due to imprecise placement and/or dropping of sensors. Therefore, we propose an automatic approach for simultaneous refinement of sensors' positions and target tracking. We divide the considered area in a finite number of cells, define dynamic and measurement models, and apply a discrete variant of belief propagation which can efficiently solve this high-dimensional problem, and handle all non-Gaussian uncertainties expected in this kind of environments. Finally, we use ray-tracing simulation to generate an artificial mine-like environment and generate synthetic measurement data. According to our extensive simulation study, the proposed approach performs significantly better than standard Bayesian target tracking and localization algorithms, and provides robustness against outliers.Comment: IEEE Transactions on Vehicular Technology, 201

What role for knowledge-intensive business services (KIBS) in de-industrialised regions?

This paper seeks to provide insights into the structural role that Knowledge Intensive Business Services (KIBS) SMEs play in de-industrialised regions in the UK. The paper aims to establish what contribution KIBS make to their regional economies in terms of exports to other regions in the UK as well as abroad but also to what extent do they depend on the intermediate demand in their respective regions. The paper draws evidence from a survey of KIBS SMEs in the North East and the West Midlands conducted during the most recent recession. The results exhibit a degree of wider generalizability to other regions, which may be characterised by deindustrialisation. Results from the West Midlands and the North East survey show that although KIBS play an important role in the local economic base of de-industrialised regions they are not as important as their elite, tradable counterparts in global cities such as London. However, KIBS SMEs in the North East and West Midlands provide important support to their regional clients, many of which are in the declining manufacturing and public service sectors. A vast majority are also trading outside their respective regions