The role of Comprehension in Requirements and Implications for Use Case Descriptions

Within requirements engineering it is generally accepted that in writing specifications (or indeed any requirements phase document), one attempts to produce an artefact which will be simple to comprehend for the user. That is, whether the document is intended for customers to validate requirements, or engineers to understand what the design must deliver, comprehension is an important goal for the author. Indeed, advice on producing ‘readable’ or ‘understandable’ documents is often included in courses on requirements engineering. However, few researchers, particularly within the software engineering domain, have attempted either to define or to understand the nature of comprehension and it’s implications for guidance on the production of quality requirements. Therefore, this paper examines thoroughly the nature of textual comprehension, drawing heavily from research in discourse process, and suggests some implications for requirements (and other) software documentation. In essence, we find that the guidance on writing requirements, often prevalent within software engineering, may be based upon assumptions which are an oversimplification of the nature of comprehension. Hence, the paper examines guidelines which have been proposed, in this case for use case descriptions, and the extent to which they agree with discourse process theory; before suggesting refinements to the guidelines which attempt to utilise lessons learned from our richer understanding of the underlying discourse process theory. For example, we suggest subtly different sets of writing guidelines for the different tasks of requirements, specification and design

Evaporation and scattering of momentum- and velocity-dependent dark matter in the Sun

Dark matter with momentum- or velocity-dependent interactions with nuclei has shown significant promise for explaining the so-called Solar Abundance Problem, a longstanding discrepancy between solar spectroscopy and helioseismology. The best-fit models are all rather light, typically with masses in the range of 3–5 GeV. This is exactly the mass range where dark matter evaporation from the Sun can be important, but to date no detailed calculation of the evaporation of such models has been performed. Here we carry out this calculation, for the first time including arbitrary velocity- and momentum-dependent interactions, thermal effects, and a completely general treatment valid from the optically thin limit all the way through to the optically thick regime. We find that depending on the dark matter mass, interaction strength and type, the mass below which evaporation is relevant can vary from 1 to 4 GeV. This has the effect of weakening some of the better-fitting solutions to the Solar Abundance Problem, but also improving a number of others. As a by-product, we also provide an improved derivation of the capture rate that takes into account thermal and optical depth effects, allowing the standard result to be smoothly matched to the well-known saturation limit

Learning Gradient Fields for Shape Generation

In this work, we propose a novel technique to generate shapes from point cloud data. A point cloud can be viewed as samples from a distribution of 3D points whose density is concentrated near the surface of the shape. Point cloud generation thus amounts to moving randomly sampled points to high-density areas. We generate point clouds by performing stochastic gradient ascent on an unnormalized probability density, thereby moving sampled points toward the high-likelihood regions. Our model directly predicts the gradient of the log density field and can be trained with a simple objective adapted from score-based generative models. We show that our method can reach state-of-the-art performance for point cloud auto-encoding and generation, while also allowing for extraction of a high-quality implicit surface. Code is available at https://github.com/RuojinCai/ShapeGF.Comment: Published in ECCV 2020 (Spotlight); Project page: https://www.cs.cornell.edu/~ruojin/ShapeGF

A novel long non-coding natural antisense RNA is a negative regulator of Nos1 gene expression

Long non-coding natural antisense transcripts (NATs) are widespread in eukaryotic species. Although recent studies indicate that long NATs are engaged in the regulation of gene expression, the precise functional roles of the vast majority of them are unknown. Here we report that a long NAT (Mm-antiNos1 RNA) complementary to mRNA encoding the neuronal isoform of nitric oxide synthase (Nos1) is expressed in the mouse brain and is transcribed from the non-template strand of the Nos1 locus. Nos1 produces nitric oxide (NO), a major signaling molecule in the CNS implicated in many important functions including neuronal differentiation and memory formation. We show that the newly discovered NAT negatively regulates Nos1 gene expression. Moreover, our quantitative studies of the temporal expression profiles of Mm-antiNos1 RNA in the mouse brain during embryonic development and postnatal life indicate that it may be involved in the regulation of NO-dependent neurogenesis

Quantitative analysis of the epithelial lining architecture in radicular cysts and odontogenic keratocysts

BACKGROUND: This paper describes a quantitative analysis of the cyst lining architecture in radicular cysts (of inflammatory aetiology) and odontogenic keratocysts (thought to be developmental or neoplastic) including its 2 counterparts: solitary and associated with the Basal Cell Naevus Syndrome (BCNS). METHODS: Epithelial linings from 150 images (from 9 radicular cysts, 13 solitary keratocysts and 8 BCNS keratocysts) were segmented into theoretical cells using a semi-automated partition based on the intensity of the haematoxylin stain which defined exclusive areas relative to each detected nucleus. Various morphometrical parameters were extracted from these "cells" and epithelial layer membership was computed using a systematic clustering routine. RESULTS: Statistically significant differences were observed across the 3 cyst types both at the morphological and architectural levels of the lining. Case-wise discrimination between radicular cysts and keratocyst was highly accurate (with an error of just 3.3%). However, the odontogenic keratocyst subtypes could not be reliably separated into the original classes, achieving discrimination rates slightly above random allocations (60%). CONCLUSION: The methodology presented is able to provide new measures of epithelial architecture and may help to characterise and compare tissue spatial organisation as well as provide useful procedures for automating certain aspects of histopathological diagnosis

Quantum phase transition in a single-molecule quantum dot

Quantum criticality is the intriguing possibility offered by the laws of quantum mechanics when the wave function of a many-particle physical system is forced to evolve continuously between two distinct, competing ground states. This phenomenon, often related to a zero-temperature magnetic phase transition, can be observed in several strongly correlated materials such as heavy fermion compounds or possibly high-temperature superconductors, and is believed to govern many of their fascinating, yet still unexplained properties. In contrast to these bulk materials with very complex electronic structure, artificial nanoscale devices could offer a new and simpler vista to the comprehension of quantum phase transitions. This long-sought possibility is demonstrated by our work in a fullerene molecular junction, where gate voltage induces a crossing of singlet and triplet spin states at zero magnetic field. Electronic tunneling from metallic contacts into the $\rm{C_{60}}$ quantum dot provides here the necessary many-body correlations to observe a true quantum critical behavior.Comment: 8 pages, 5 figure

Effect of electromagnetic dipole dark matter on energy transport in the solar interior

In recent years, a revised set of solar abundances has led to a discrepancy in the sound-speed profile between helioseismology and theoretical solar models. Conventional solutions require additional mechanisms for energy transport within the Sun. Vincent et al. have recently suggested that dark matter with a momentum or velocity dependent cross section could provide a solution. In this work, we consider three models of dark matter with such cross sections and their effect on the stellar structure. In particular, the three models incorporate dark matter particles interacting through an electromagnetic dipole moment: an electric dipole, a magnetic dipole or an anapole. Each model is implemented in the DarkStec stellar evolution program, which incorporates the effects of dark matter capture and heat transport within the solar interior. We show that dark matter with an anapole moment of ~ 1 GeV−2 or magnetic dipole moment of ~ 10−3μp can improve the sound-speed profile, small frequency separations and convective zone radius with respect to the Standard Solar Model. However, the required dipole moments are strongly excluded by direct detection experiments

The role of nutrient loading and eutrophication in estuarine ecology.

Eutrophication is a process that can be defined as an increase in the rate of supply of organic matter (OM) to an ecosystem. We provide a general overview of the major features driving estuarine eutrophication and outline some of the consequences of that process. The main chemical constituent of OM is carbon (C), and therefore rates of eutrophication are expressed in units of C per area per unit time. OM occurs in both particulate and dissolved forms. Allochthonous OM originates outside the estuary, whereas autochthonous OM is generated within the system, mostly by primary producers or by benthic regeneration of OM. The supply rates of limiting nutrients regulate phytoplankton productivity that contributes to inputs of autochthonous OM. The trophic status of an estuary is often based on eutrophication rates and can be categorized as oligotrophic (<100 g C m(-2) y(-1), mesotrophic (100-300 g C m(-2) y(-1), eutrophic (300-500 g C m(-2) y(-1), or hypertrophic (>500 g C m(-2) y(-1). Ecosystem responses to eutrophication depend on both export rates (flushing, microbially mediated losses through respiration, and denitrification) and recycling/regeneration rates within the estuary. The mitigation of the effects of eutrophication involves the regulation of inorganic nutrient (primarily N and P) inputs into receiving waters. Appropriately scaled and parameterized nutrient and hydrologic controls are the only realistic options for controlling phytoplankton blooms, algal toxicity, and other symptoms of eutrophication in estuarine ecosystems

Bayesian mapping of pulmonary tuberculosis in Antananarivo, Madagascar

<p>Abstract</p> <p>Background</p> <p>Tuberculosis (TB), an infectious disease caused by the <it>Mycobacterium tuberculosis </it>is endemic in Madagascar. The capital, Antananarivo is the most seriously affected area. TB had a non-random spatial distribution in this setting, with clustering in the poorer areas. The aim of this study was to explore this pattern further by a Bayesian approach, and to measure the associations between the spatial variation of TB risk and national control program indicators for all neighbourhoods.</p> <p>Methods</p> <p>Combination of a Bayesian approach and a generalized linear mixed model (GLMM) was developed to produce smooth risk maps of TB and to model relationships between TB new cases and national TB control program indicators. The TB new cases were collected from records of the 16 Tuberculosis Diagnostic and Treatment Centres (DTC) of the city from 2004 to 2006. And five TB indicators were considered in the analysis: number of cases undergoing retreatment, number of patients with treatment failure and those suffering relapse after the completion of treatment, number of households with more than one case, number of patients lost to follow-up, and proximity to a DTC.</p> <p>Results</p> <p>In Antananarivo, 43.23% of the neighbourhoods had a standardized incidence ratio (SIR) above 1, of which 19.28% with a TB risk significantly higher than the average. Identified high TB risk areas were clustered and the distribution of TB was found to be associated mainly with the number of patients lost to follow-up (SIR: 1.10, CI 95%: 1.02-1.19) and the number of households with more than one case (SIR: 1.13, CI 95%: 1.03-1.24).</p> <p>Conclusion</p> <p>The spatial pattern of TB in Antananarivo and the contribution of national control program indicators to this pattern highlight the importance of the data recorded in the TB registry and the use of spatial approaches for assessing the epidemiological situation for TB. Including these variables into the model increases the reproducibility, as these data are already available for individual DTCs. These findings may also be useful for guiding decisions related to disease control strategies.</p