Search results for "Biase"
showing 10 items of 67 documents
Measurement of damping and temperature: Precision bounds in Gaussian dissipative channels
2011
We present a comprehensive analysis of the performance of different classes of Gaussian states in the estimation of Gaussian phase-insensitive dissipative channels. In particular, we investigate the optimal estimation of the damping constant and reservoir temperature. We show that, for two-mode squeezed vacuum probe states, the quantum-limited accuracy of both parameters can be achieved simultaneously. Moreover, we show that for both parameters two-mode squeezed vacuum states are more efficient than either coherent, thermal or single-mode squeezed states. This suggests that at high energy regimes two-mode squeezed vacuum states are optimal within the Gaussian setup. This optimality result i…
Microscopic biasing of discrete-time quantum trajectories
2021
We develop a microscopic theory for biasing the quantum trajectories of an open quantum system, which renders rare trajectories typical. To this end we consider a discrete-time quantum dynamics, where the open system collides sequentially with qubit probes which are then measured. A theoretical framework is built in terms of thermodynamic functionals in order to characterize its quantum trajectories (each embodied by a sequence of measurement outcomes). We show that the desired biasing is achieved by suitably modifying the Kraus operators describing the discrete open dynamics. From a microscopical viewpoint and for short collision times, this corresponds to adding extra collisions which enf…
Statistical Analysis of a Method to Predict Drug–Polymer Miscibility
2015
In this study, a method proposed to predict drug-polymer miscibility from differential scanning calorimetry measurements was subjected to statistical analysis. The method is relatively fast and inexpensive and has gained popularity as a result of the increasing interest in the formulation of drugs as amorphous solid dispersions. However, it does not include a standard statistical assessment of the experimental uncertainty by means of a confidence interval. In addition, it applies a routine mathematical operation known as "transformation to linearity," which previously has been shown to be subject to a substantial bias. The statistical analysis performed in this present study revealed that t…
New Results in Generalized Minimum Variance Control of Computer Networks
2014
In this paper new results in adaptive (generalized) minimum variance control of packet switching computer networks are presented. New solutions, corresponding to the new inverses of the nonsquare polynomial matrices, can be used for design of robust control of multivariable systems with different number of inputs and outputs. Application of polynomial matrix inverses with arbitrary degrees of freedom creates the possibilities to optimal control of computer networks in terms of usage their maximal bandwidth. Simulation examples made in Matlab environment show big potential of presented approach. DOI: http://dx.doi.org/10.5755/j01.itc.43.3.6268
Propagation of precipitation measurement biases into the hydraulic modelling of urban drainage systems – A case study of the Parco D’Orleans sub-urba…
2020
Aim of this study is to evaluate the impact of Precipitation Measurement Biases (PMBs) of tippingbucket rain gauges onto the hydraulic modelling of urban drainage networks. As a case study, the monitored experimental suburban catchment of Parco d’Orleans located in the University Campus of Palermo, Italy and managed since 1987 by the Department of Engineering of the University of Palermo is considered. . Two tipping-bucket rain gauges provide a good spatial coverage of the catchment area and an acoustic level gauge is installed at the outlet of the drainage network for flow mesaurements. Contemporary high temporal resolution rainfall and runoff data series are available between 1993 to 1998…
The Role of Low Complexity Regions in Protein Interaction Modes: An Illustration in Huntingtin
2021
Low complexity regions (LCRs) are very frequent in protein sequences, generally having a lower propensity to form structured domains and tending to be much less evolutionarily conserved than globular domains. Their higher abundance in eukaryotes and in species with more cellular types agrees with a growing number of reports on their function in protein interactions regulated by post-translational modifications. LCRs facilitate the increase of regulatory and network complexity required with the emergence of organisms with more complex tissue distribution and development. Although the low conservation and structural flexibility of LCRs complicate their study, evolutionary studies of proteins …
The Conservation of Low Complexity Regions in Bacterial Proteins Depends on the Pathogenicity of the Strain and Subcellular Location of the Protein
2021
Low complexity regions (LCRs) in proteins are characterized by amino acid frequencies that differ from the average. These regions evolve faster and tend to be less conserved between homologs than globular domains. They are not common in bacteria, as compared to their prevalence in eukaryotes. Studying their conservation could help provide hypotheses about their function. To obtain the appropriate evolutionary focus for this rapidly evolving feature, here we study the conservation of LCRs in bacterial strains and compare their high variability to the closeness of the strains. For this, we selected 20 taxonomically diverse bacterial species and obtained the completely sequenced proteomes of t…
Understanding Prediction Limits Through Unbiased Branches
2006
The majority of currently available branch predictors base their prediction accuracy on the previous k branch outcomes. Such predictors sustain high prediction accuracy but they do not consider the impact of unbiased branches which are difficult-to-predict. In this paper, we quantify and evaluate the impact of unbiased branches and show that any gain in prediction accuracy is proportional to the frequency of unbiased branches. By using the SPECcpu2000 integer benchmarks we show that there are a significant proportion of unbiased branches which severely impact on prediction accuracy (averaging between 6% and 24% depending on the prediction context used).
Propagation of precipitation measurement biases into the hydraulic modelling of urban drainage systems: a case study
2021
Precipitation is the primary source of freshwater, while it can have great socio-economical impacts associated with extreme weather events such as floods and droughts. Good quality hydro-meteorological data is an essential condition not only for climate analysis but also for warning systems, hydraulic structures design, risk assessment, etc. In fact, precipitation is one of the most intensively used variables in hydrological modelling and its measurement accuracy is of foremost importance (Peterson et al., 1998). Accurate and timely knowledge of precipitation characteristics at urban and natural basins scales is essential for understanding how different catchment hydrological systems operat…
Perché le teorie liberali moderate non devono temere la behavioral economics o la heuristics and biases psychology
2021
In this article I will explain the content of soime cognitive bias and the content of liberal theories. I will argument that people commit less cognitive errors than Conly and others think. Secondly, some behaviours that Conly and others think are cognitive bias are not. Finally, it is clear in the studies of Kahneman and Tversky that the majority of cognitive bias are not incorrigibles (in the correct sense of this word)