Transmission Power Measurements for Wireless Sensor Nodes and their Relationship to the Battery Level

In this work we focus on the new generation EYESIFXv2 [1] wireless sensor nodes by carrying out experimental measurements on power related quantities. In particular, our aim is to characterize the relationship between the level of the battery and the transmission power radiated by the node. The present results point out the non linear and non trivial effects due to the output potentiometer which can be used to tune the transmission power. It shall be observed that a thorough study of how battery and/or potentiometer settings translate to actual transmitted power levels is crucial to e.g. design correct power control algorithms, which can effectively operate under any operational condition of the wireless sensor device

On the Nature of MeV-blazars

Broad-band spectra of the FSRQ (flat-spectrum-radio quasars) detected in the high energy gamma-ray band imply that there may be two types of such objects: those with steep gamma-ray spectra, hereafter called MeV-blazars, and those with flat gamma-ray spectra, GeV-blazars. We demonstrate that this difference can be explained in the context of the ERC (external-radiation-Compton) model using the same electron injection function. A satisfactory unification is reachable, provided that: (a) spectra of GeV-blazars are produced by internal shocks formed at the distances where cooling of relativistic electrons in a jet is dominated by Comptonization of broad emission lines, whereas spectra of MeV-blazars are produced at the distances where cooling of relativistic electrons is dominated by Comptonization of near-IR radiation from hot dust; (b) electrons are accelerated via a two step process and their injection function takes the form of a double power-law, with the break corresponding to the threshold energy for the diffusive shock acceleration. Direct predictions of our model are that, on average, variability time scales of the MeV-blazars should be longer than variability time scales of the GeV-blazars, and that both types of the blazar phenomenon can appear in the same object.Comment: Accepted for publication in the Astrophysical Journa

Measuring Interviewer Characteristics Pertinent to Social Surveys: A Conceptual Framework

Interviewer effects are found across all types of interviewer-mediated surveys crossing disciplines and countries. While studies describing interviewer effects are manifold, identifying characteristics explaining these effects has proven difficult due to a lack of data on the interviewers. This paper proposes a conceptual framework of interviewer characteristics for explaining interviewer effects and its operationalization in an interviewer questionnaire. The framework encompasses four dimensions of interviewer characteristics: interviewer attitudes, interviewers’ own behaviour, interviewers’ experience with measurements, and interviewers’ expectations. Our analyses of the data collected from interviewers working on the fourth wave of SHARE Germany show that the above measures distinguish well between interviewers

Modeling group-specific interviewer effects on survey participation using separate coding for random slopes in multilevel models

Despite its importance in terms of survey participation, the literature is sparse on how face-to-face interviewers differentially affect specific groups of sample units. In this paper, we demonstrate how an alternative parametrization of the random components in multilevel models, so-called separate coding, delivers valuable insights into differential interviewer effects for specific groups of sample members. At the example of a face-to-face recruitment interview for a probability-based online panel, we detect small interviewer effects regarding survey participation for non-Internet households, whereas we find sizable interviewer effects for Internet households. Based on the proposed variance decomposition, we derive practical guidance for survey practitioners to address such differential interviewer effects

Trap-limited electron transport in disordered semiconducting polymers

The electron transport in diodes of poly(dialkoxy-p-phenylene vinylene) (PPV) derivatives is strongly reduced as compared to the hole transport. A recent reexamination [M. M. Mandoc , Phys. Rev. B 73, 155205 (2006)] revealed that the room-temperature electron current shows the fingerprints of trap-limited transport with a distribution of traps in energy. Here, we report on the measured temperature dependence of the electron current in these PPV derivatives. This dependence is weak and seems to be in contradiction with existing trap-limited models. We demonstrate that the presence of a Gaussian density of states (DOS) for the mobile carriers, being characteristic for disordered semiconductors, reduces the temperature dependence of the trap-limited charge transport. The reduction is governed by the width of the Gaussian DOS and originates from the equilibrium concentrations of the mobile and trapped carriers

Model selection in High-Dimensions: A Quadratic-risk based approach

In this article we propose a general class of risk measures which can be used for data based evaluation of parametric models. The loss function is defined as generalized quadratic distance between the true density and the proposed model. These distances are characterized by a simple quadratic form structure that is adaptable through the choice of a nonnegative definite kernel and a bandwidth parameter. Using asymptotic results for the quadratic distances we build a quick-to-compute approximation for the risk function. Its derivation is analogous to the Akaike Information Criterion (AIC), but unlike AIC, the quadratic risk is a global comparison tool. The method does not require resampling, a great advantage when point estimators are expensive to compute. The method is illustrated using the problem of selecting the number of components in a mixture model, where it is shown that, by using an appropriate kernel, the method is computationally straightforward in arbitrarily high data dimensions. In this same context it is shown that the method has some clear advantages over AIC and BIC.Comment: Updated with reviewer suggestion

Modelling Group-Specific Interviewer Effects on Nonresponse Using Separate Coding for Random Slopes in Multilevel Models

To enhance response among underrepresented groups and hence, to increase response rates and to decrease potential nonresponse bias survey practitioners often use interviewers in population surveys (Heerwegh, 2009). While interviewers tend to increase overall response rates in surveys (see Heerwegh, 2009), research on the determinants of nonresponse have also identified human interviewers as one reason for variations in response rates (see for examples Couper & Groves, 1992; Durrant, Groves, Staetsky, & Steele, 2010; Durrant & Steele, 2009; Hox & de Leeuw, 2002; Loosveldt & Beullens, 2014; West & Blom, 2016). In addition, research on interviewer effects indicates that interviewers introduce nonresponse bias, if interviewers systematically differ in their success in obtaining response from specific respondent groups (see West, Kreuter, & Jaenichen, 2013; West & Olson, 2010). Therefore, interviewers might be a source of selective nonresponse in surveys. Interviewers might also differentially contribute to selective nonresponse in surveys and hence, potential nonresponse bias, when interviewer effects are correlated with characteristics of the approached sample units (for an example see Loosveldt & Beullens, 2014). Multilevel models including dummies in the random part of the model to distinguish between respondent groups are commonly used to investigate whether interviewer effects on nonresponse differ across specific respondent groups (see Loosveldt & Beullens, 2014). When dummy coding, which is also referred to as contrast coding (Jones, 2013), are included as random components in multilevel models for interviewers effects, the obtained variance estimates indicate to what extent the contrast between respondent groups varies across interviewers. Yet, such parameterization does not directly yield insight on the size of interviewer effects for specific respondent groups. Surveys with large imbalances among respondent groups gain from an investigation of the variation of interviewer effect sizes on nonresponse, as one gains insights on whether the interviewer effect size is the same for specific respondent groups. The importance of the interviewer effect size for specific groups of respondents lies in its prediction of the effectiveness of interviewer-related fieldwork strategies (for examples on liking, matching, or prioritizing respondents with interviewers see Durrant et al., 2010; Peytchev, Riley, Rosen, Murphy, & Lindblad, 2010; Pickery & Loosveldt, 2002, 2004) and thus, a effective mitigation of potential nonresponse bias. Consequently, understanding group-specific interviewer effect sizes can aide the efficiency of respondent recruitment, because we then understand why some interviewer-related fieldwork strategies have great impact on some respondent group’s participation while other strategies have little effect. To obtain information on differences in interviewer effect size, we propose to use an alternative coding strategy, so-called separate coding in multilevel models with random slopes (for examples see Jones, 2013; Verbeke & Molenberghs, 2000, ch. 12.1). In case of separate coding, every variable represents a direct estimate of the interviewer effects for specific respondent groups (rather than the contrast with a reference category). Investigating nonresponse during the recruitment of a probability-based online panel separately for persons with and without prior internet access (data used from the German Internet Panel, see Blom et al., 2017), we detect that the size of the interviewer effect differs between the two respondent groups. While we discover no interviewer effects on nonresponse for persons without internet access (offliners), we find sizable interviewer effects for persons with internet access (onliners). In addition, we identify interviewer characteristics that explain this group-specific nonresponse. Our results demonstrate that the implementation of interviewer-related fieldwork strategies might help to increase response rates among onliners, as for onliners the interviewer effect size was relatively large compared to the interviewer effect size for offliners

Fokker-Planck equation with variable diffusion coefficient in the Stratonovich approach

We consider the Langevin equation with multiplicative noise term which depends on time and space. The corresponding Fokker-Planck equation in Stratonovich approach is investigated. Its formal solution is obtained for an arbitrary multiplicative noise term given by $g(x,t)=D(x)T(t)$, and the behaviors of probability distributions, for some specific functions of $D(x)$% , are analyzed. In particular, for $D(x)\sim | x| ^{-\theta /2}$, the physical solutions for the probability distribution in the Ito, Stratonovich and postpoint discretization approaches can be obtained and analyzed.Comment: 6 pages in LATEX cod

Does the Blazar Gamma-Ray Spectrum Harden with Increasing Flux? Analysis of 9 Years of EGRET Data

The Energetic Gamma-Ray Experiment Telescope (EGRET) on the Compton Gamma-Ray Observatory (CGRO) discovered gamma-ray emission from more than 67 blazars during its 9 yr lifetime. We conducted an exhaustive search of the EGRET archives and selected all the blazars that were observed multiple times and were bright enough to enable a spectral analysis using standard power-law models. The sample consists of 18 flat-spectrum radio quasars(FSRQs), 6 low-frequency peaked BL Lac objects (LBLs) and 2 high-frequency peaked BL Lac objects (HBLs). We do not detect any clear pattern in the variation of spectral index with flux. Some of the blazars do not show any statistical evidence for spectral variability. The spectrum hardens with increasing flux in a few cases. There is also evidence for a flux-hardness anticorrelation at low fluxes in five blazars. The well-observed blazars (3C 279, 3C 273, PKS 0528+134, PKS 1622-297 PKS 0208-512) do not show any overall trend in the long-term spectral dependence on flux, but the sample shows a mixture of hard and soft states. We observed a previously unreported spectral hysteresis at weekly timescales in all three FSRQs for which data from flares lasting for ~(3-4) weeks were available. All three sources show a counterclockwise rotation, despite the widely different flux profiles. We analyze the observed spectral behavior in the context of various inverse Compton mechanisms believed to be responsible for emission in the EGRET energy range. Our analysis uses the EGRET skymaps that were regenerated to include the changes in performance during the mission