Hydraulic and Hydrologic Model Calibration and Validation for an Earthquake-prone Three-Waters Network

This paper summarises the three-waters network (water, wastewater, storm water) model calibration and validation work undertaken in Christchurch after the devastating 2010–2011 earthquakes. The paper outlines some unusual and unique challenges during model calibration due to continual earthquakes in the region and the post-earthquake rebuild work. In case of water supply network model, the validation peak summer date was chosen carefully so that earthquake-related damage and associated rebuild works would have minimal impact on the captured data. The wastewater network was damaged significantly due to the earthquakes. Wastewater flow data were influenced by earthquake damage and post-earthquake major construction activities. Christchurch’s storm water network faced a number of changes – changes in topography, ground levels, river channels and liquefaction – due to the earthquakes. Ongoing model maintenance and updating was a big challenge during model calibration, and an effective collaboration among various teams – GIS, construction contractors, network operations and survey – was important for data collection, data interpretation, model calibration and validation work

Farmers’ Perception and Adoption of Agroforestry Practices in Faridpur District of Bangladesh

This study mainly focused on exploring perception of farmers' towards agroforestry practices and identifying the demographic factors influencing agroforestry adoption in Faridpur district. Field survey was conducted during November-December, 2016 using semi-structured questionnaire. Multi-stage random sampling was used to select upazillas, unions and villages. Snowball purposive sampling was applied to select 84 respondents in total for the questionnaire survey. Chi-square was used to test variables at 5% level of significance. Homestead agroforestry was found to be the most common agroforestry practice (39.28%), followed by fruit-based agroforestry (21.42%), woodlot plantation (13.09%) and so on. Agroforestry was perceived to increase farm productivity by 82.14% of the respondents, 73.8% opined that agroforestry increase household income, while 30.95% perceived it as a means to food security. On the contrary, 34.52% opined that agroforestry practices decrease cash crops production, 17.85% of the respondents stated agroforestry as a difficult practice. Chi-square test showed no significant association between the adoption of agroforestry practices and respondent's age (P > 0.05) or income range (P > 0.05) of the respondents. On the other hand, there is a positive significant association between the adoption of agroforestry practices and educational level (p< 0.05) as well as the farm size (p< 0.05) of the respondents. The study suggests raising awareness regarding the benefits of agroforestry practices as well as providing technical assistance

Connecting protein and mRNA burst distributions for stochastic models of gene expression

The intrinsic stochasticity of gene expression can lead to large variability in protein levels for genetically identical cells. Such variability in protein levels can arise from infrequent synthesis of mRNAs which in turn give rise to bursts of protein expression. Protein expression occurring in bursts has indeed been observed experimentally and recent studies have also found evidence for transcriptional bursting, i.e. production of mRNAs in bursts. Given that there are distinct experimental techniques for quantifying the noise at different stages of gene expression, it is of interest to derive analytical results connecting experimental observations at different levels. In this work, we consider stochastic models of gene expression for which mRNA and protein production occurs in independent bursts. For such models, we derive analytical expressions connecting protein and mRNA burst distributions which show how the functional form of the mRNA burst distribution can be inferred from the protein burst distribution. Additionally, if gene expression is repressed such that observed protein bursts arise only from single mRNAs, we show how observations of protein burst distributions (repressed and unrepressed) can be used to completely determine the mRNA burst distribution. Assuming independent contributions from individual bursts, we derive analytical expressions connecting means and variances for burst and steady-state protein distributions. Finally, we validate our general analytical results by considering a specific reaction scheme involving regulation of protein bursts by small RNAs. For a range of parameters, we derive analytical expressions for regulated protein distributions that are validated using stochastic simulations. The analytical results obtained in this work can thus serve as useful inputs for a broad range of studies focusing on stochasticity in gene expression

The Loudest Event Statistic: General Formulation, Properties and Applications

The use of the loudest observed event to generate statistical statements about rate and strength has become standard in searches for gravitational waves from compact binaries and pulsars. The Bayesian formulation of the method is generalized in this paper to allow for uncertainties both in the background estimate and in the properties of the population being constrained. The method is also extended to allow rate interval construction. Finally, it is shown how to combine the results from multiple experiments and a comparison is drawn between the upper limit obtained in a single search and the upper limit obtained by combining the results of two experiments each of half the original duration. To illustrate this, we look at an example case, motivated by the search for gravitational waves from binary inspiral.Comment: 11 pages, 8 figure

Detecting transient gravitational waves in non-Gaussian noise with partially redundant analysis methods

There is a broad class of astrophysical sources that produce detectable, transient, gravitational waves. Some searches for transient gravitational waves are tailored to known features of these sources. Other searches make few assumptions about the sources. Typically events are observable with multiple search techniques. This work describes how to combine the results of searches that are not independent, treating each search as a classifier for a given event. This will be shown to improve the overall sensitivity to gravitational-wave events while directly addressing the problem of consistent interpretation of multiple trials.Comment: 11 pages, 5 figure

Voids as a Precision Probe of Dark Energy

A signature of the dark energy equation of state may be observed in the shape of voids. We estimate the constraints on cosmological parameters that would be determined from the ellipticity distribution of voids from future spectroscopic surveys already planned for the study of large scale structure. The constraints stem from the sensitivity of the distribution of ellipticity to the cosmological parameters through the variance of fluctuations of the density field smoothed at some length scale. This length scale can be chosen to be of the order of the comoving radii of voids at very early times when the fluctuations are Gaussian distributed. We use Fisher estimates to show that the constraints from void ellipticities are promising. Combining these constraints with other traditional methods results in the improvement of the Dark Energy Task Force Figure of Merit on the dark energy parameters by an order of hundred for future experiments. The estimates of these future constraints depend on a number of systematic issues which require further study using simulations. We outline these issues and study the impact of certain observational and theoretical systematics on the forecasted constraints on dark energy parameters.Comment: Submitted to PRD, 22 pages 9 figure

Improving the LSST dithering pattern and cadence for dark energy studies

The Large Synoptic Survey Telescope (LSST) will explore the entire southern sky over 10 years starting in 2022 with unprecedented depth and time sampling in six filters, $ugrizy$. Artificial power on the scale of the 3.5 deg LSST field-of-view will contaminate measurements of baryonic acoustic oscillations (BAO), which fall at the same angular scale at redshift $z \sim 1$. Using the HEALPix framework, we demonstrate the impact of an "un-dithered" survey, in which $17\%$ of each LSST field-of-view is overlapped by neighboring observations, generating a honeycomb pattern of strongly varying survey depth and significant artificial power on BAO angular scales. We find that adopting large dithers (i.e., telescope pointing offsets) of amplitude close to the LSST field-of-view radius reduces artificial structure in the galaxy distribution by a factor of $\sim$10. We propose an observing strategy utilizing large dithers within the main survey and minimal dithers for the LSST Deep Drilling Fields. We show that applying various magnitude cutoffs can further increase survey uniformity. We find that a magnitude cut of $r < 27.3$ removes significant spurious power from the angular power spectrum with a minimal reduction in the total number of observed galaxies over the ten-year LSST run. We also determine the effectiveness of the observing strategy for Type Ia SNe and predict that the main survey will contribute $\sim$100,000 Type Ia SNe. We propose a concentrated survey where LSST observes one-third of its main survey area each year, increasing the number of main survey Type Ia SNe by a factor of $\sim$1.5, while still enabling the successful pursuit of other science drivers.Comment: 9 pages, 6 figures, published in SPIE proceedings; corrected typo in equation

Likelihood-ratio ranking of gravitational-wave candidates in a non-Gaussian background

We describe a general approach to detection of transient gravitational-wave signals in the presence of non-Gaussian background noise. We prove that under quite general conditions, the ratio of the likelihood of observed data to contain a signal to the likelihood of it being a noise fluctuation provides optimal ranking for the candidate events found in an experiment. The likelihood-ratio ranking allows us to combine different kinds of data into a single analysis. We apply the general framework to the problem of unifying the results of independent experiments and the problem of accounting for non-Gaussian artifacts in the searches for gravitational waves from compact binary coalescence in LIGO data. We show analytically and confirm through simulations that in both cases the likelihood ratio statistic results in an improved analysis.Comment: 10 pages, 6 figure

Presto-Color: A Photometric Survey Cadence for Explosive Physics and Fast Transients

We identify minimal observing cadence requirements that enable photometric astronomical surveys to detect and recognize fast and explosive transients and fast transient features. Observations in two different filters within a short time window (e.g., g-and-i, or r-and-z, within 1.5 hr) are desirable for this purpose. Such an observing strategy delivers both the color and light curve evolution of transients on the same night. This allows the identification and initial characterization of fast transient—or fast features of longer timescale transients—such as rapidly declining supernovae, kilonovae, and the signatures of SN ejecta interacting with binary companion stars or circumstellar material. Some of these extragalactic transients are intrinsically rare and generally all hard to find, thus upcoming surveys like the Large Synoptic Survey Telescope (LSST) could dramatically improve our understanding of their origin and properties. We colloquially refer to such a strategy implementation for the LSST as the Presto-Color strategy (rapid-color). This cadence's minimal requirements allow for overall optimization of a survey for other science goals

Presto-Color: A Photometric Survey Cadence for Explosive Physics and Fast Transients

We identify minimal observing cadence requirements that enable photometric astronomical surveys to detect and recognize fast and explosive transients and fast transient features. Observations in two different filters within a short time window (e.g., g-and-i, or r-and-z, within 1.5 hr) are desirable for this purpose. Such an observing strategy delivers both the color and light curve evolution of transients on the same night. This allows the identification and initial characterization of fast transient—or fast features of longer timescale transients—such as rapidly declining supernovae, kilonovae, and the signatures of SN ejecta interacting with binary companion stars or circumstellar material. Some of these extragalactic transients are intrinsically rare and generally all hard to find, thus upcoming surveys like the Large Synoptic Survey Telescope (LSST) could dramatically improve our understanding of their origin and properties. We colloquially refer to such a strategy implementation for the LSST as the Presto-Color strategy (rapid-color). This cadence's minimal requirements allow for overall optimization of a survey for other science goals