Evolution of statistical analysis in empirical software engineering research: Current state and steps forward

Software engineering research is evolving and papers are increasingly based on empirical data from a multitude of sources, using statistical tests to determine if and to what degree empirical evidence supports their hypotheses. To investigate the practices and trends of statistical analysis in empirical software engineering (ESE), this paper presents a review of a large pool of papers from top-ranked software engineering journals. First, we manually reviewed 161 papers and in the second phase of our method, we conducted a more extensive semi-automatic classification of papers spanning the years 2001--2015 and 5,196 papers. Results from both review steps was used to: i) identify and analyze the predominant practices in ESE (e.g., using t-test or ANOVA), as well as relevant trends in usage of specific statistical methods (e.g., nonparametric tests and effect size measures) and, ii) develop a conceptual model for a statistical analysis workflow with suggestions on how to apply different statistical methods as well as guidelines to avoid pitfalls. Lastly, we confirm existing claims that current ESE practices lack a standard to report practical significance of results. We illustrate how practical significance can be discussed in terms of both the statistical analysis and in the practitioner's context.Comment: journal submission, 34 pages, 8 figure

Ecological Functions And Values Of Fringing Salt Marshes Susceptible To Oil Spills In Casco Bay, Maine

Casco Bay is the largest oil port in Maine and northern New England, handling over 20 million tons of crude oil and oil products annually. The susceptibility of the Bay’s estuarine habitats, especially its fringing salt marshes, to potential spill events was the impetus for this study. Although much has been learned to date about the effects of oil spills on estuarine habitats around the world, there is a real need for site-specific knowledge of the structures and functions of local habitats so that resource managers can be prepared in the event of a spill. Our study focused specifically on the value of Casco Bay’s fringing salt marshes to shellfish and finfish production, to vegetation production and diversity, and as buffers against sea level rise and coastal erosion. The work we have accomplished has been the first study of the fringing salt marshes of Casco Bay that has explored the biotic communities (fish, invertebrates and plants) of these marshes in conjunction with the physical properties of these sites. Knowledge of these local fringing salt marsh habitats will be invaluable in improving the effectiveness of oil spill cleanup operations, accurate assessment of natural resource damages caused by spills, and the restoration of impacted sites. In addition, the data acquired in this study provide an initial set of benchmarks upon which to build a program to assess long-term change in Casco Bay tidal marsh habitats

A Structural Classification of Australian Vegetation Using ICESat/GLAS, ALOS PALSAR and Landsat Sensor Data

Australia has historically used structural descriptors of height and cover to characterize, differentiate, and map the distribution of woody vegetation across the continent but no national satellite-based structural classification has been available. In this study, we present a new 30-m spatial resolution reference map of Australian forest and woodland structure (height and cover), with this generated by integrating Landsat Thematic Mapper (TM) and Enhanced TM, Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (PALSAR) and Ice, Cloud, and land Elevation (ICESat),and Geoscience Laser Altimeter System (GLAS) data. ALOS PALSAR and Landsat-derived Foliage Projective Cover (FPC) were used to segment and classify the Australian landscape. Then, from intersecting ICESat waveform data, vertical foliage profiles and height metrics (e.g., 95% percentile height, mean height and the height to maximum vegetation density) were extracted for each of the classes generated. Within each class, and for selected areas, the variability in ICESat profiles was found to be similar with differences between segments of the same class attributed largely to clearance or disturbance events. ICESat metrics and profiles were then assigned to all remaining segments across Australia with the same class allocation. Validation against airborne LiDAR for a range of forest structural types indicated a high degree of correspondence in estimated height measures. On this basis, a map of vegetation height was generated at a national level and was combined with estimates of cover to produce a revised structural classification based on the scheme of the Australian National Vegetation Information System (NVIS). The benefits of integrating the three datasets for segmenting and classifying the landscape and retrieving biophysical attributes was highlighted with this leading the way for future mapping using ALOS-2 PALSAR-2, Landsat/Sentinel-2, Global Ecosystem Dynamics Investigation (GEDI), and ICESat-2 LiDAR data. The ability to map across large areas provides considerable benefits for quantifying carbon dynamics and informing on biodiversity metrics

Effect of Electrically Mediated Intratumor and Intramuscular Delivery of a Plasmid Encoding IFN α on Visible B16 Mouse Melanomas

Interferon α may be used as a single agent therapy for metastatic malignant melanoma or as an adjuvant to chemotherapy. Delivery of interferon α by gene therapy offers an alternative to recombinant protein therapy. Electrically mediated delivery enhances plasmid expression in a number of tissues, for instance skin, liver, muscle and tumors including melanomas. Here we compare the effect of delivery of a plasmid encoding mouse interferon α on growth of visible B16 mouse melanomas following electrically mediated delivery to muscle or directly to the tumor. Intratumoral delivery of interferon α plasmid not only slows melanoma growth, but induces complete, long term, regression. This effect was not observed after intramuscular delivery

Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy

Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients worldwide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on - and may directly propagate along - underlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention

HI intensity mapping with FAST

We discuss the detectability of large-scale HI intensity fluctuations using the FAST telescope. We present forecasts for the accuracy of measuring the Baryonic Acoustic Oscillations and constraining the properties of dark energy. The FAST $19$-beam L-band receivers ($1.05$--$1.45$ GHz) can provide constraints on the matter power spectrum and dark energy equation of state parameters ($w_{0},w_{a}$) that are comparable to the BINGO and CHIME experiments. For one year of integration time we find that the optimal survey area is $6000\,{\rm deg}^2$. However, observing with larger frequency coverage at higher redshift ($0.95$--$1.35$ GHz) improves the projected errorbars on the HI power spectrum by more than $2~\sigma$ confidence level. The combined constraints from FAST, CHIME, BINGO and Planck CMB observations can provide reliable, stringent constraints on the dark energy equation of state.Comment: 7 pages, 3 figures, submitted to "Frontiers in Radio Astronomy and FAST Early Sciences Symposium 2015" conference proceedin

Measuring the Numerical Viscosity in Simulations of Protoplanetary Disks in Cartesian Grids -- The Viscously Spreading Ring Revisited

Hydrodynamical simulations solve the governing equations on a discrete grid of space and time. This discretization causes numerical diffusion similar to a physical viscous diffusion, whose magnitude is often unknown or poorly constrained. With the current trend of simulating accretion disks with no or very low prescribed physical viscosity, it becomes essential to understand and quantify this inherent numerical diffusion, in the form of a numerical viscosity. We study the behavior of the viscous spreading ring and the spiral instability that develops in it. We then use this setup to quantify the numerical viscosity in Cartesian grids and study its properties. We simulate the viscous spreading ring and the related instability on a two-dimensional polar grid using PLUTO as well as FARGO, and ensure convergence of our results with a resolution study. We then repeat our models on a Cartesian grid and measure the numerical viscosity by comparing results to the known analytical solution, using PLUTO and Athena++. We find that the numerical viscosity in a Cartesian grid scales with resolution as approximately $\nu_{num}\propto\Delta x^2$ and is equivalent to an effective $\alpha\sim10^{-4}$ for a common numerical setup. We also show that the spiral instability manifests as a single leading spiral throughout the whole domain on polar grids. This is contrary to previous results and indicates that sufficient resolution is necessary in order to correctly resolve the instability. Our results are relevant in the context of models where the origin should be included in the computational domain, or when polar grids cannot be used. Examples of such cases include models of disk accretion onto a central binary and inherently Cartesian codes

Differential Modulation of Thresholds for Intracranial Self-Stimulation by mGlu5 Positive and Negative Allosteric Modulators: Implications for Effects on Drug Self-Administration

Pharmacological manipulation of the type 5 metabotropic glutamate (mGlu5) receptor alters various addiction related behaviors such as drug self-administration and the extinction and reinstatement of drug-seeking behavior. However, the effects of pharmacological modulation of mGlu5 receptors on brain reward function have not been widely investigated. We examined the effects of acute administration of positive and negative allosteric modulators (PAMs and NAMs, respectively) on brain reward function by assessing thresholds for intracranial self-stimulation (ICSS). In addition, when acute effects were observed, we examined changes in ICSS thresholds following repeated administration. Male Sprague-Dawley rats were implanted with bipolar electrodes into the medial forebrain bundle and trained to respond for ICSS, followed by assessment of effects of mGlu5 ligands on ICSS thresholds using a discrete trials current–intensity threshold determination procedure. Acute administration of the selective mGlu5 NAMs MTEP (0, 0.3, 1, or 3 mg/kg) and fenobam (0, 3, 10, or 30 mg/kg) dose-dependently increased ICSS thresholds (∼70% at the highest dose tested), suggesting a deficit in brain reward function. Acute administration of the mGlu5 PAMs CDPPB (0, 10, 30, and 60 mg/kg) or ADX47273 (0, 10, 30, and 60 mg/kg) was without effect at any dose tested. When administered once daily for five consecutive days, the development of tolerance to the ability of threshold-elevating doses of MTEP and fenobam to increase ICSS thresholds was observed. We conclude that mGlu5 PAMs and NAMs differentially affect brain reward function, and that tolerance to the ability of mGlu5 NAMs to reduce brain reward function develops with repeated administration. These brain reward deficits should be taken into consideration when interpreting acute effects of mGlu5 NAMs on drug self-administration, and repeated administration of these ligands may be an effective method to reduce these deficits

REMAP:An online remote sensing application for land cover classification and monitoring

Recent assessments of progress towards global conservation targets have revealed a paucity of indicators suitable for assessing the changing state of ecosystems. Moreover, land managers and planners are often unable to gain timely access to the maps they need to support their routine decision-making. This deficiency is partly due to a lack of suitable data on ecosystem change, driven mostly by the considerable technical expertise needed to develop ecosystem maps from remote sensing data. We have developed a free and open-access online remote sensing and environmental modelling application, the Remote Ecosystem Monitoring and Assessment Pipeline (Remap; https://remap-app.org), that enables volunteers, managers and scientists with little or no experience in remote sensing to generate classifications (maps) of land cover and land use change over time. Remap utilizes the geospatial data storage and analysis capacity of Google Earth Engine and requires only spatially resolved training data that define map classes of interest (e.g. ecosystem types). The training data, which can be uploaded or annotated interactively within Remap, are used in a random forest classification of up to 13 publicly available predictor datasets to assign all pixels in a focal region to map classes. Predictor datasets available in Remap represent topographic (e.g. slope, elevation), spectral (archival Landsat image composites) and climatic variables (precipitation, temperature) that are relevant to the distribution of ecosystems and land cover classes. The ability of Remap to develop and export high-quality classified maps in a very short (<10 min) time frame represents a considerable advance towards globally accessible and free application of remote sensing technology. By enabling access to data and simplifying remote sensing classifications, Remap can catalyse the monitoring of land use and change to support environmental conservation, including developing inventories of biodiversity, identifying hotspots of ecosystem diversity, ecosystem-based spatial conservation planning, mapping ecosystem loss at local scales and supporting environmental education initiatives