Design and Hydraulics of a Combined Storm Overflow Structure

Storm overflow structures in combined sewers are used to separate sewage from storm water. For subcritical approach flow, sideweirs are currently used; however, they often behave hydraulically poor. This study was conducted to explore a combined storm overflow structure able to improve the hydraulic performance of sewer sideweirs. Such a structure consists of a low-crested sideweir and a bottom opening just downstream from the sideweir end. First, the hydraulic design procedure is described, and then, based on laboratory experiments and by using the governing flow equations, the main hydraulic features are highlighted. The results indicate that the proposed device has advantageous characteristics in terms of hydraulic efficiency, reliability, and maintenance.     

Shields’ Entrainment Criterion in Bridge Hydraulics

Two related problems of sediment hydraulics are addressed: (1) Inception of sediment transport for nearly uniform flow of both uniform and nonuniform sediment beds for two different sediment densities and grain sizes ranging from sand to gravel, and (2) generalized inception conditions if elements are inserted in a plane sediment bed. The Shields’ criterion is formulated with basic quantities involving gravity, viscosity, and densities of the two-phase flow. The results of the analysis relate to the viscous, the transition, and the fully turbulent regimes. The transition regime is verified with extended laboratory experiments. Then, these conditions are used as a basis for formulating a general stability criterion for loose bed hydraulics, and compared to detailed experiments involving pier and square elements located either at the channel side or at its axis. In addition, a generalized densimetric particle Froude number is introduced that accounts for both uniform sediments and mixtures. The engineering application of the present results is straightforward, given that basic parameters of hydraulics, sediment, and fluid are involved.     

Caffeine self-administration in humans: 1. Efficacy of cola vehicle

Eight exclusive cola drinkers in Experiment 1 (mean caffeine intake = 157 +/- 74 mg/day) and 16 drinkers of both cola and coffee in Experiment 2 (mean caffeine intake = 579 +/- 201 mg/day) underwent 6 independent, double-blind weekly trials. Each trial began with a randomized cross-over sampling period of 1 day of access to noncaffeinated cola and 1 day of access to caffeinated (33 mg/8 oz) cola. During the subsequent 1- or 2-day test period, participants had unlimited concurrent access to the 2 colas. Reliable caffeine self-administration occurred in 2 of 8 participants in Experiment 1 and in 4 of 16 participants in Experiment 2. Self-reported drowsiness, fatigue, and headache were higher when participants received only placebo colas in Experiment 2, but not Experiment 1. Caffeine self-administration via cola occurs both among people whose primary source of caffeine is cola and among those whose primary source of caffeine is coffee.     

Individual differences in humans responding under a cocaine discrimination procedure: Discriminators versus nondiscriminators.

Twenty-six cocaine-abusing volunteers were trained to discriminate cocaine (80 mg/70 kg, p.o.) from placebo. On the basis of a discrimination acquisition criterion (i.e., >80% drug-appropriate responding for 4 consecutive sessions within 8–10 sessions), 18 participants were classified as discriminators (Ds) and 8 as nondiscriminators (NDs). Relative to Ds, NDs reported a greater amount of cocaine use per time. During the training phase, NDs showed significantly lower ratings than Ds on a stimulant ratings scale, regardless of the training drug condition. During the test-of-acquisition phase, cocaine-induced increases in scores on ratings of drug strength, anxious-nervous and cocaine high, as well as on a euphoria ratings scale, were significantly greater in Ds than NDs, relative to placebo. These results suggest that drug use history, general arousal level, and drug sensitivity may be important variables influencing the acquisition of cocaine versus placebo discrimination in cocaine abusers. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A systematic survey of caffeine intake in Vermont.

Detailed data were collected on lifetime caffeine intake from 202 Vermont residents using a random-digit dial telephone survey. The sample appeared representative and test–retest reliability of caffeine intake was high (r?=?.95). Almost all participants (96%) had ever used and most (83%) presently used one or more caffeinated beverages weekly. The average caffeine intake was 186 mg/day. Many caffeine users (61%) used caffeinated beverages other than coffee. Current caffeine intake was a poor measure of lifetime intake. For example, among ever-users of caffeine, 41% had stopped at least 1 type of caffeinated beverage and 14% had stopped caffeine altogether. Cessation was mostly due to health concerns and unpleasant side effects. It was concluded that simply asking about "usual" coffee use is a poor and biased estimate of lifetime caffeine use. Thus, prior findings that caffeine is not associated with medical or behavioral disorders may represent false-negative results. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Labeling source code with information retrieval methods: an empirical study

To support program comprehension, software artifacts can be labeled—for example within software visualization tools—with a set of representative words, hereby referred to as labels. Such labels can be obtained using various approaches, including Information Retrieval (IR) methods or other simple heuristics. They provide a bird-eye’s view of the source code, allowing developers to look over software components fast and make more informed decisions on which parts of the source code they need to analyze in detail. However, few empirical studies have been conducted to verify whether the extracted labels make sense to software developers. This paper investigates (i) to what extent various IR techniques and other simple heuristics overlap with (and differ from) labeling performed by humans; (ii) what kinds of source code terms do humans use when labeling software artifacts; and (iii) what factors—in particular what characteristics of the artifacts to be labeled—influence the performance of automatic labeling techniques. We conducted two experiments in which we asked a group of students (38 in total) to label 20 classes from two Java software systems, JHotDraw and eXVantage. Then, we analyzed to what extent the words identified with an automated technique—including Vector Space Models, Latent Semantic Indexing (LSI), latent Dirichlet allocation (LDA), as well as customized heuristics extracting words from specific source code elements—overlap with those identified by humans. Results indicate that, in most cases, simpler automatic labeling techniques—based on the use of words extracted from class and method names as well as from class comments—better reflect human-based labeling. Indeed, clustering-based approaches (LSI and LDA) are more worthwhile to be used for source code artifacts having a high verbosity, as well as for artifacts requiring more effort to be manually labeled. The obtained results help to define guidelines on how to build effective automatic labeling techniques, and provide some insights on the actual usefulness of automatic labeling techniques during program comprehension tasks.     

Identifying Extract Class refactoring opportunities using structural and semantic cohesion measures

Approaches for improving class cohesion identify refactoring opportunities using metrics that capture structural relationships between the methods of a class, e.g., attribute references. Semantic metrics, e.g., C3 metric, have also been proposed to measure class cohesion, as they seem to complement structural metrics. However, until now semantic relationships between methods have not been used to identify refactoring opportunities. In this paper we propose an Extract Class refactoring method based on graph theory that exploits structural and semantic relationships between methods. The empirical evaluation of the proposed approach highlighted the benefits provided by the combination of semantic and structural measures and the potential usefulness of the proposed method as a feature for software development environments.     

Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation

Drift analysis is a powerful tool used to bound the optimization time of evolutionary algorithms (EAs). Various previous works apply a drift theorem going back to Hajek in order to show exponential lower bounds on the optimization time of EAs. However, this drift theorem is tedious to read and to apply since it requires two bounds on the moment-generating (exponential) function of the drift. A recent work identifies a specialization of this drift theorem that is much easier to apply. Nevertheless, it is not as simple and not as general as possible. The present paper picks up Hajek’s line of thought to prove a drift theorem that is very easy to use in evolutionary computation. Only two conditions have to be verified, one of which holds for virtually all EAs with standard mutation. The other condition is a bound on what is really relevant, the drift. Applications show how previous analyses involving the complicated theorem can be redone in a much simpler and clearer way. In some cases even improved results may be achieved. Therefore, the simplified theorem is also a didactical contribution to the runtime analysis of EAs.     

Assessing IR-based traceability recovery tools through controlled experiments

We report the results of a controlled experiment and a replication performed with different subjects, in which we assessed the usefulness of an Information Retrieval-based traceability recovery tool during the traceability link identification process. The main result achieved in the two experiments is that the use of a traceability recovery tool significantly reduces the time spent by the software engineer with respect to manual tracing. Replication with different subjects allowed us to investigate if subjects’ experience and ability play any role in the traceability link identification process. In particular, we made some observations concerning the retrieval accuracy achieved by the software engineers with and without the tool support and with different levels of experience and ability.