Principles of Gravitational-Wave Detection with Pulsar Timing Arrays

Pulsar timing uses the highly stable pulsar spin period to investigate many astrophysical topics. In particular, pulsar timing arrays make use of a set of extremely well-timed pulsars and their time correlations as a challenging detector of gravitational waves. It turns out that pulsar timing arrays are particularly sensitive to ultra-low-frequency gravitational waves, which makes them complementary to other gravitational-wave detectors. Here, we summarize the basics, focusing especially on supermassive black-hole binaries and cosmic strings, which have the potential to form a stochastic gravitational-wave background in the pulsar timing array detection band, and the scientific goals on this challenging topic. We also briefly outline the recent interesting results of the main pulsar timing array collaborations, which have found strong evidence of a common-spectrum process compatible with a stochastic gravitational-wave background and mention some new perspectives that are particularly interesting in view of the forthcoming radio observatories such as the Five hundred-meter Aperture Spherical Telescope, the MeerKAT telescope, and the Square Kilometer Array.

Identification of the cosmogenic $$^{11}$$C background in large volumes of liquid scintillators with Borexino

Cosmogenic radio-nuclei are an important source of background for low-energy neutrino experiments. In Borexino, cosmogenic $$^{11}$$ 11 C decays outnumber solar pep and CNO neutrino events by about ten to one. In order to extract the flux of these two neutrino species, a highly efficient identification of this background is mandatory. We present here the details of the most consolidated strategy, used throughout Borexino solar neutrino measurements. It hinges upon finding the space-time correlations between $$^{11}$$ 11 C decays, the preceding parent muons and the accompanying neutrons. This article describes the working principles and evaluates the performance of this Three-Fold Coincidence (TFC) technique in its two current implementations: a hard-cut and a likelihood-based approach. Both show stable performances throughout Borexino Phases II (2012–2016) and III (2016–2020) data sets, with a $$^{11}$$ 11 C tagging efficiency of $$\sim 90$$ ∼ 90 % and $$\sim $$ ∼ 63–66 % of the exposure surviving the tagging. We present also a novel technique that targets specifically $$^{11}$$ 11 C produced in high-multiplicity during major spallation events. Such $$^{11}$$ 11 C appear as a burst of events, whose space-time correlation can be exploited. Burst identification can be combined with the TFC to obtain about the same tagging efficiency of $$\sim 90\%$$ ∼ 90 % but with a higher fraction of the exposure surviving, in the range of $$\sim $$ ∼ 66–68 %.

Merging of Horizontally and Vertically Separated Small-Scale Buoyant Flames

The purpose of this study was to investigate the merging behavior of small-scale buoyant flames that might be representative of flames from a leaf in a shrub. Zirconia felt pads soaked in n-heptane were suspended on thin rods and spaced both horizontally and vertically. Time-dependent video images from flames from two-pad and three-pad configurations were analyzed to determine merging probability, combined flame characteristics (height, area, and width), and changes in burn time. Correlations of these combined flame characteristics were developed based on horizontal and vertical spacing between the pads. Merging probability correlated with an exponential function that was quadratic in horizontal and/or vertical spacing. Flame heights corrected for vertical inter-pad spacing showed a maximum increase of 50% over single flame heights, and were correlated with an exponential decay function. Flame areas increased by a maximum of 34%, but on average were relatively constant. Corrected flame widths for the merged flames increased by as much as 55% in some configurations, but decreased by up to 73% in other configurations. Burn times for upper pads decreased when there was no horizontal spacing. The limited flame growth observed in these non-overlapping configurations in the horizontal dimension imply that overlapping configurations seem to be necessary for significant flame growth.

Metal Complex Formation and Anticancer Activity of Cu(I) and Cu(II) Complexes with Metformin

Metformin has been used for decades in millions of type 2 diabetes mellitus patients. In this time, correlations between metformin use and the occurrence of other disorders have been noted, as well as unpredictable metformin side effects. Diabetes is a significant cancer risk factor, but unexpectedly, metformin-treated diabetic patients have lower cancer incidence. Here, we show that metformin forms stable complexes with copper (II) ions. Both copper(I)/metformin and copper(II)/metformin complexes form adducts with glutathione, the main intracellular antioxidative peptide, found at high levels in cancer cells. Metformin reduces cell number and viability in SW1222 and K562 cells, as well as in K562-200 multidrug-resistant cells. Notably, the antiproliferative effect of metformin is enhanced in the presence of copper ions.

Correlations of power output fluctuations in an offshore wind farm using high-resolution SCADA data

Space–time correlations of power output fluctuations of wind turbine pairs provide information on the flow conditions within a wind farm and the interactions of wind turbines. Such information can play an essential role in controlling wind turbines and short-term load or power forecasting. However, the challenges of analysing correlations of power output fluctuations in a wind farm are the highly varying flow conditions. Here, we present an approach to investigate space–time correlations of power output fluctuations of streamwise-aligned wind turbine pairs based on high-resolution supervisory control and data acquisition (SCADA) data. The proposed approach overcomes the challenge of spatially variable and temporally variable flow conditions within the wind farm. We analyse the influences of the different statistics of the power output of wind turbines on the correlations of power output fluctuations based on 8 months of measurements from an offshore wind farm with 80 wind turbines. First, we assess the effect of the wind direction on the correlations of power output fluctuations of wind turbine pairs. We show that the correlations are highest for the streamwise-aligned wind turbine pairs and decrease when the mean wind direction changes its angle to be more perpendicular to the pair. Further, we show that the correlations for streamwise-aligned wind turbine pairs depend on the location of the wind turbines within the wind farm and on their inflow conditions (free stream or wake). Our primary result is that the standard deviations of the power output fluctuations and the normalised power difference of the wind turbines in a pair can characterise the correlations of power output fluctuations of streamwise-aligned wind turbine pairs. Further, we show that clustering can be used to identify different correlation curves. For this, we employ the data-driven k-means clustering algorithm to cluster the standard deviations of the power output fluctuations of the wind turbines and the normalised power difference of the wind turbines in a pair. Thereby, wind turbine pairs with similar power output fluctuation correlations are clustered independently from their location. With this, we account for the highly variable flow conditions inside a wind farm, which unpredictably influence the correlations.

Predicting Deconversion: Concurrent and Cross-time Correlations in Three Samples

This chapter presents results about one of the questions that our research has focused from the beginning: religious change and deconversion. While in the Deconversion Study (2001-2005) we could use only cross-sectional data to estimate characteristics of deconverts in the U.S.A. and Germany, the analyses reported in this chapter are based on repeated surveys in three waves that allow the identification of concurrent and cross-time correlations—thus, open perspectives on the prediction of deconversion. Results indicate that, with difference between the three waves however, deconversion concurrently may correlate positively with openness to experience and negatively with consciousness, it may correlate also with mysticism and show concurrent correlations with truth of texts and teachings and self-rated religiosity. Cross-time correlations indicated as (negative) predictors of deconversion: self-rated religiosity, extraversion, agreeableness, environmental mastery, positive relations with others, purpose in life, self-acceptance, interpretive mysticism, and truth of texts and teachings. We conclude that low scores on variables for religiosity and religious cognition, but also personality and well-being variable that call for emotional compensation are predictors of deconversion.

Mixing time in yield stress fluids

Yield stress fluids are commonly encountered in the pharmaceutical, wastewater and bioprocess industries. On agitation of these fluids with an impeller, a zone of significant motion (cavern) is formed surrounded by stagnant regions. These inhomogeneous conditions are undesirable from a product quality standpoint. Therefore, to evolve a mixing system design that would eliminate these problems, experimental measurements of mixing time were obtained and combined with power consumption to provide a measure of mixing system efficiency. The effect of different parameters such as fluid rheology, impeller rotational speed, impeller type and impeller clearance on the mixing times was also investigated. In addition, using CFD, numerical mixing times were calculated and a comparison of the numerical and experimental mixing times were conducted to investigate the capability of the CFD tool to correctly predict the homogenization process in mixing tanks. In general, it was observed that the power characteristics of the different agitators were well reproduced by the computational package. In addition, CFD was able to correctly predict the effect of impeller rotational speed and fluid yield stress on the mixing times. However, the effect of impeller clearance on the mixing time was not correctly predicted by the CFD package when compared with experimental results obtained in this work as well as those obtained by other researchers. A comparison of the impellers used in this study (Pitched Blade Turbine (PBT), marine propeller and Lightnin A320) using the mixing time correlations available in the literature to fit the experimental data revealed that the PBT was superior to the other impellers in mixing yield stress fluids. In addition, the validated CFD model was used to measure the dimensions of the cavern formed around the impeller and it showed good agreement with the Elson's cavern model.