Unequal Time Research Articles

Statistical microeconomics and commodity prices: theory and empirical results.

A review is made of the statistical generalization of microeconomics by Baaquie (Baaquie 2013 Phys. A 392, 4400-4416. (doi:10.1016/j.physa.2013.05.008)), where the market price of every traded commodity, at each instant of time, is considered to be an independent random variable. The dynamics of commodity market prices is given by the unequal time correlation function and is modelled by the Feynman path integral based on an action functional. The correlation functions of the model are defined using the path integral. The existence of the action functional for commodity prices that was postulated to exist in Baaquie (Baaquie 2013 Phys. A 392, 4400-4416. (doi:10.1016/j.physa.2013.05.008)) has been empirically ascertained in Baaquie et al. (Baaquie et al. 2015 Phys. A 428, 19-37. (doi:10.1016/j.physa.2015.02.030)). The model's action functionals for different commodities has been empirically determined and calibrated using the unequal time correlation functions of the market commodity prices using a perturbation expansion (Baaquie et al. 2015 Phys. A 428, 19-37. (doi:10.1016/j.physa.2015.02.030)). Nine commodities drawn from the energy, metal and grain sectors are empirically studied and their auto-correlation for up to 300 days is described by the model to an accuracy of R(2)>0.90-using only six parameters.

The Time Grind: Unequal Time: Gender, Class and Family in Employment Schedules

The Time Grind: <i>Unequal Time: Gender, Class and Family in Employment Schedules</i>

Frequency-Domain Simulation of Electromagnetic Transients Using Variable Sampling Time-Step

This letter presents the extension of a previously proposed frequency-domain (FD) approach for the analysis of electromagnetic transients (EMTs), primarily due to a set of discrete switching events, in an electric power network. The method is based on dividing the analysis time window into a set of subwindows with equal or unequal time lengths and solving each in the FD. The sampling time step is also independently selected for each subwindow. The extended method, formerly proposed for a single transmission line, can readily use the concept of network equivalents, achieving efficient EMT solutions of large systems, and can simultaneously accommodate slow and fast dynamics.

Unequal Time: Gender, Class, and Family in Employment Schedules. By Dan Clawson and Naomi Gerstel. New York: Russell Sage, 2014. Pp. xvi+324. $35.00 (paper).

<i>Unequal Time: Gender, Class, and Family in Employment Schedules</i>. By Dan Clawson and Naomi Gerstel. New York: Russell Sage, 2014. Pp. xvi+324. $35.00 (paper).

Online Doppler Effect Elimination Based on Unequal Time Interval Sampling for Wayside Acoustic Bearing Fault Detecting System.

The railway occupies a fairly important position in transportation due to its high speed and strong transportation capability. As a consequence, it is a key issue to guarantee continuous running and transportation safety of trains. Meanwhile, time consumption of the diagnosis procedure is of extreme importance for the detecting system. However, most of the current adopted techniques in the wayside acoustic defective bearing detector system (ADBD) are offline strategies, which means that the signal is analyzed after the sampling process. This would result in unavoidable time latency. Besides, the acquired acoustic signal would be corrupted by the Doppler effect because of high relative speed between the train and the data acquisition system (DAS). Thus, it is difficult to effectively diagnose the bearing defects immediately. In this paper, a new strategy called online Doppler effect elimination (ODEE) is proposed to remove the Doppler distortion online by the introduced unequal interval sampling scheme. The steps of proposed strategy are as follows: The essential parameters are acquired in advance. Then, the introduced unequal time interval sampling strategy is used to restore the Doppler distortion signal, and the amplitude of the signal is demodulated as well. Thus, the restored Doppler-free signal is obtained online. The proposed ODEE method has been employed in simulation analysis. Ultimately, the ODEE method is implemented in the embedded system for fault diagnosis of the train bearing. The results are in good accordance with the bearing defects, which verifies the good performance of the proposed strategy.

Clawson, D., &amp; Gerstel, N. (2014). Unequal Time: Gender, Class, and Family in Employment Schedules

Clawson, D., &amp; Gerstel, N. (2014). <i>Unequal Time: Gender, Class, and Family in Employment Schedules</i>

Contribution of domain wall networks to the CMB power spectrum

We use three domain wall simulations from the radiation era to the late-time dark energy domination era based on the PRS algorithm to calculate the energy–momentum tensor components of domain wall networks in an expanding universe. Unequal time correlators in the radiation, matter and cosmological constant epochs are calculated using the scaling regime of each of the simulations. The CMB power spectrum of a network of domain walls is determined. The first ever quantitative constraint for the domain wall surface tension is obtained using a Markov chain Monte Carlo method; an energy scale of domain walls of 0.93 MeV, which is close but below the Zel'dovich bound, is determined.

Diffference between mouth and esophageal occlusion pressure during CO2 rebreathing in chronic obstructive pulmonary disease.

During CO2 rebreathing, we measured the pressures generated at the mouth and in the esophagus during the first 0.1 sec of inspiratory effort against a closed airway in 6 normal subjects and 6 patients with chronic obstructive lung disease. Normal subjects showed similar reponses to CO2 in terms of both mouth pressure and esophageal pressure. Patients' responses at the mouth to CO2 were decreased compared to those of normal subjects, but the responses in the esophagus were not significantly different. The patients demonstrated a greater response of occlusion pressure measured in the esophagus than at the mouth. In patients with altered mechanical properties of the lung, the change in mouth occlusion pressure might be influenced by problems of equalization of pressure within the airways due to unequal time constants, by problems of regional differences in pressure gradients over the pleural surface, or both. Esophageal pressure during airway occlusion 100 msec after the onset of inspiration may be better measure of respiratory drive than mouth pressure in patients with intrinsic increase of airway resistance.

MSCA: a spectral comparison algorithm between time series to identify protein-protein interactions.

BackgroundThe interactions between pathogen proteins and their hosts allow pathogens to manipulate host cellular mechanisms to their advantage. The identification of host proteins that are targeted by virulent pathogen proteins is crucial to increase our understanding of infection mechanisms and to propose new therapeutics that target pathogens. Understanding the virulence mechanisms of pathogens requires a detailed molecular description of the proteins involved, but acquiring this knowledge is time consuming and prohibitively expensive. Therefore, we develop a statistical method based on hypothesis testing to compare the time series obtained from conversion of the physicochemical characteristics of the amino acids that form the primary structure of proteins and thus to propose potential functional relation between proteins. We called this algorithm the multiple spectral comparison algorithm (MSCA); the MSCA was inspired by the BLASTP tool and was implemented in R code. The algorithm compares and relates multiple time series according to their spectral similarities, and the biological relation between them could be interpreted as either a similar function or protein-protein interaction (PPI).ResultsA simulation study showed that the MSCA works satisfactorily well when we compare unequal time series generated from ARMA processes because its power was close to 1. The MSCA presented a 70% average accuracy of detecting protein interactions using a threshold of 0.7 for our spectral measure, indicating that this algorithm could predict novel PPIs and pathogen-host interactions (PHIs) with acceptable confidence. The MSCA also was validated by its identification of well-known interactions of the human proteins MAGI1, SCRIB and JAK1, as well as interactions of the virulence proteins ROP16, ROP18, ROP17 and ROP5. We verified the spectral similarities for human intraspecific PPIs and PHIs that were previously demonstrated experimentally by other authors. We suggest that human GBP (GTPase group induced by interferon) and the CREB transcription factor family could be human substrates for the complex of ROP18, ROP17 and ROP5.ConclusionsUsing multiple-hypothesis testing between the spectral densities of a set of unequal time series, we developed an algorithm that is able to identify the similarities or interactions between a set of proteins.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0599-8) contains supplementary material, which is available to authorized users.

Re-Evaluating Sexual Violence Prevention Through Bystander Education: A Latent Growth Curve Approach.

Recently, there has been a call for more advanced analytic techniques in violence against women research, particularly in community interventions that use longitudinal designs. The current study re-evaluates experimental evaluation data from a sexual violence bystander intervention program. Using an exploratory latent growth curve approach, we were able to model the longitudinal growth trajectories of individual participants over the course of the entire study. Although the results largely confirm the original evaluation findings, the latent growth curve approach better fits the demands of "messy" data (e.g., missing data, varying number of time points per participant, and unequal time spacing within and between participants) that are frequently obtained during a community-based intervention. The benefits of modern statistical techniques to practitioners and researchers in the field of sexual violence prevention, and violence against women more generally, are further discussed.

CMB power spectrum of Nambu-Goto cosmic strings

We improve predictions of the cosmic microwave background (CMB) power spectrum induced by cosmic strings by using source terms obtained from Nambu-Goto network simulations in an expanding universe. We use three high-resolution cosmic string simulations that cover the entire period from recombination until late-time $\Lambda$ domination to calculate unequal time correlators (UETCs) for scalar, vector and tensor components of the cosmic-string energy-momentum tensor. We calculate the CMB angular power spectrum from strings in two ways. First, to aid comparison with previous work, we fit our simulated UETCs to those obtained from different parameter combinations from the unconnected segment model and then calculate the CMB power spectra using these parameters to represent the string network. Second and more accurately, we decompose the UETCs into their corresponding eigenvalues and eigenvectors and input them directly into an Einstein-Boltzmann solver to calculate the power spectrum for each of the three simulation time periods. We combine the three simulations together, using each of them in its relevant redshift range and we obtain overall power spectra in temperature and polarisation channels. Finally, we use the power spectra obtained with the latest Planck and BICEP2 likelihoods to obtain constraints on the cosmic string tension.

Unequal time: gender, class, and family in employment schedules

Unequal time: gender, class, and family in employment schedules

The bispectrum of matter perturbations from cosmic strings

We present the first calculation of the bispectrum of the matter perturbations induced by cosmic strings. The calculation is performed in two different ways: the first uses the unequal time correlators (UETCs) of the string network - computed using a Gaussian model previously employed for cosmic string power spectra. The second approach uses the wake model, where string density perturbations are concentrated in sheet-like structures whose surface density grows with time. The qualitative and quantitative agreement of the two gives confidence to the results. An essential ingredient in the UETC approach is the inclusion of compensation factors in the integration with the Green's function of the matter and radiation fluids, and we show that these compensation factors must be included in the wake model also. We also present a comparison of the UETCs computed in the Gaussian model, and those computed in the unconnected segment model (USM) used by the standard cosmic string perturbation package CMBACT. We compare numerical estimates for the bispectrum of cosmic strings to those produced by perturbations from an inflationary era, and discover that, despite the intrinsically non-Gaussian nature of string-induced perturbations, the matter bispectrum is unlikely to produce competitive constraints on a population of cosmic strings.

Book Review: Unequal Time: Gender, Class, and Family in Employment Schedules

Book Review: Unequal Time: Gender, Class, and Family in Employment Schedules

Empirical microeconomics action functionals

A statistical generalization of microeconomics has been made in Baaquie (2013), where the market price of every traded commodity, at each instant of time, is considered to be an independent random variable. The dynamics of commodity market prices is modeled by an action functional–and the focus of this paper is to empirically determine the action functionals for different commodities. The correlation functions of the model are defined using a Feynman path integral. The model is calibrated using the unequal time correlation of the market commodity prices as well as their cubic and quartic moments using a perturbation expansion. The consistency of the perturbation expansion is verified by a numerical evaluation of the path integral. Nine commodities drawn from the energy, metal and grain sectors are studied and their market behavior is described by the model to an accuracy of over 90% using only six parameters. The paper empirically establishes the existence of the action functional for commodity prices that was postulated to exist in Baaquie (2013).

Estimating survival of rock lobsters from long-term tagging programmes: how survey number and interval influence estimates

Abstract A long-term tagging dataset on southern rock lobster (Jasus edwardsii) conducted at the Crayfish Point Scientific Reserve near Hobart, Tasmania, Australia, was used to determine how survey number and survey duration affected the precision of survival estimates of male and female lobsters to ensure sustainable exploitation of the population. Tagging surveys were undertaken twice yearly during 2000–2003 with unequal time-intervals between surveys and then once a year with equal time-intervals during 2004–2012 during the January–February period. The most parsimonious Cormack–Jolly–Seber model for estimating survival of lobsters was dependent on (i) timing of the tagging and recapture surveys, (ii) time between consecutive recapture surveys, and (iii) gender. The number of surveys required to provide a precise survival probability varied with gender and time between recapture surveys. For surveys where there was unequal time between recapture surveys, seven and five surveys were required for female and male lobsters, respectively, whereas only five surveys were required when annual surveys were undertaken. Thus, lobster tagging projects using annual surveys should ideally extend to at least 5 years, which is beyond the 3-year project duration common in marine science.

Chaotic randomness of mutually coupled vertical-cavity surface-emitting laser by optical injection

In this paper, a randomness-enhanced chaotic system model of mutually coupled vertical-cavity surface-emitting lasers (VCSELs) is established by adding anothor injected VCSEL with variable polarizer optical feedback (VPOF). The randomness of chaotic signals is evaluated quantitatively by an information-theory-based quantifier, the permutation entropy (PE). The influences of VPOF-VCSEL rotating polarizer degree, feedback strength, injection strength, mutual coupling strength, path time delay and frequency detuning about injected VCSEL and coupled VCSELs on chaotic signal permutation entropy are numerically studied. It is shown that the chaotic signal permutation entropy of mutually coupled VCSEL system driven by the third VCSEL is much higher than the mutual system with no-driving VCSEL. That is to say, the randomness of coupled system chaotic signal can be enhanced by optical injection. When the rotating polarizer degree is approximately 45 degrees and the injection strength is saturated at a constant level, the system PE can be increased by coupled strength, which is set to be higher than feedback strength. In addition, unequal delay time between both coupled time and feedback time, and higher detuning frequency between driving VCSEL and coupled VCSELs can contribute to randomness-enhanced chaotic signals.

A Statistical Model for Predicting Neutropenic Fever

BackgroundFebrile neutropenia (FN) is a common occurrence associated with chemotherapy regimens used in patients (pts) with acute myelogenous leukemia (AML). Febrile neutropenia is presently defined as a single temperature of ≥38.3°C (101°F) or a temperature of ≥38.0°C (100.4°F) for >1 hour in a patient with an absolute neutrophil count < 500/mm3. Due to the potential for life threatening infections, fever in a patient with neutropenia is considered an oncologic emergency. Initiating appropriate antibiotic therapy as soon as possible in these patients leads to better outcomes. However, to our knowledge, there is no evidence that supports the current definition of neutropenic fever.AimTo identify a temperature pattern that is predictive of the subsequent development of febrile neutropenia in neutropenic pts with AMLMethodsAfter obtaining IRB approval we retrospectively obtained demographic and temperature data from hospitalized patients with AML undergoing induction therapy who were admitted to our institution between 12/8/2012 and 12/7/2013. Temperature data was recorded at intervals per physician order and nursing discretion during admission. We identified fever as a single temperature ≥38.3°C (101°F) or consecutive temperatures recorded 1 hour apart ≥38.06°C (100.5°F).Data was processed using SAS data programming to create and summarize this pilot temperature series data. Data for 68 patients containing 137 fever events was divided into 203 segments: a series was considered to end at the time of fever (or end of data) and a new series for the same patient began 24 hours after a preceding fever. Plots were created showing temperature over time leading up to fever (end of series).Our data consists of unequal interval time series data and does not lend itself to the usual methods of statistical ROC analysis. An ROC-like analysis to estimate sensitivity and specificity of a maximum temperature that predicts for a subsequent episode of FN was performed. Temperature data was subset into 7 time intervals: a pre-fever interval spanning 4 to 28 hours preceding fever or series end, and 6 non-fever intervals, each 24 hours long and spanning the period from 48 to 192 hours before fever or series end, for a total of 854 data windows. Statistics on each patient series within each interval were used as variables in predicting fever onset in logistic regression analysis. The variables included were maximum temperature within 24 hours, minimum temperature within 24 hours, average of positive increases between subsequent measurements, and largest 24 hour increase.Statistical analysis consisted of a generalized linear model with logit link (logistic regression) predicting fever at least 4 hours before onset, and used generalized estimating equations to adjust for correlated temperature measures within patient.ResultsOf the 68 patients identified, 47% were male, 53% were female with a mean age of 56.3 ± 15.1 years.Our fever curve plots suggest that there is an increase in average temperature at least 24 hours before the onset of fever in those patients that will go on to develop a fever by current definition (Figure 1).A prediction score including, maximum temperature within 24 hours, minimum temperature within 24 hours, average of positive increases between subsequent measurements, and largest 24 hour increase was able to predict 86.1% of oncoming FN events 4 to 28 hours before onset and reject 67.4% of non-FN events. This rule has a negative predictive value of 96.2% and a positive predictive value of 33.7%.DiscussionOur analysis demonstrates the feasibility of using temperature series data for early prediction of FN. A more comprehensive analysis is planned and is expected to result in higher sensitivities. If subsequent analysis proves to be significant this data may be used to develop future prospective clinical studies to evaluate new fever criteria and may alter our current definition and management of pts with FN. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Relating Latent Change Score and Continuous Time Models

The primary goal of this article is to demonstrate the close relationship between 2 classes of dynamic models in psychological research: latent change score models and continuous time models. The secondary goal is to point out some differences. We begin with a brief review of both approaches, before demonstrating how the 2 methods are mathematically and conceptually related. It will be shown that most commonly used latent change score models are related to continuous time models by the difference equation approximation to the differential equation. One way in which the 2 approaches differ is the treatment of time. Whereas there are theoretical and practical restrictions regarding observation time points and intervals in latent change score models, no such limitations exist in continuous time models. We illustrate our arguments with three simulated data sets using a univariate and bivariate model with equal and unequal time intervals. As a by-product of this comparison, we discuss the use of phantom and definition variables to account for varying time intervals in latent change score models. We end with a reanalysis of the Bradway–McArdle longitudinal study on intellectual abilities (used before by McArdle & Hamagami, 2004) by means of the proportional change score model and the dual change score model in discrete and continuous time.

Sample Size Estimation for Negative Binomial Regression Comparing Rates of Recurrent Events with Unequal Follow-Up Time

A sample size formula is derived for negative binomial regression for the analysis of recurrent events, in which subjects can have unequal follow-up time. We obtain sharp lower and upper bounds on the required size, which is easy to compute. The upper bound is generally only slightly larger than the required size, and hence can be used to approximate the sample size. The lower and upper size bounds can be decomposed into two terms. The first term relies on the mean number of events in each group, and the second term depends on two factors that measure, respectively, the extent of between-subject variability in event rates, and follow-up time. Simulation studies are conducted to assess the performance of the proposed method. An application of our formulae to a multiple sclerosis trial is provided.