GATOR: Requirements capturing of telephony features

We are developing a natural language-based, requirements gathering system called GATOR (for the GATherer Of Requirements). GATOR assists in the development of more accurate and complete specifications of new telephony features. GATOR interacts with a feature designer who describes a new feature, set of features, or capability to be implemented. The system aids this individual in the specification process by asking for clarifications when potential ambiguities are present, by identifying potential conflicts with other existing features, and by presenting its understanding of the feature to the designer. Through user interaction with a model of the existing telephony feature set, GATOR constructs a formal representation of the new, 'to be implemented' feature. Ultimately GATOR will produce a requirements document and will maintain an internal representation of this feature to aid in future design and specification. This paper consists of three sections that describe (1) the structure of GATOR, (2) POND, GATOR's internal knowledge representation language, and (3) current research issues

Holistic evaluation of management policies: What are the consequences of modified gear use on Georges Bank?

Georges Bank haddock is a recently recovered fish stock in the New England groundfish fishery. Due to federal constraints under the Magnuson-Steven Act, however, this stock cannot be optimally exploited due to the bycatch of other critical species in the New England groundfishery such as cod and yellowtail flounder which are overfished. The Ruhle trawl and Separator trawl are examples of recent advances in gear technology that have been shown to significantly increase haddock to bycatch ratios. This study models the groundfish fishery through a mixed stock yield model which incorporates technological interactions. We also develop a socio-economic model that quantifies the amount of employment and producer surplus associated with three trawl types. Our results explore policy situations regarding the use of the new trawls. By bridging the biological and socio-economic models, we are able to view the fishery as a system that more accurately represents stakeholder views. Our model shows that each trawl, when used exclusively, produces different optimum strategies and therefore an optimum management strategy would most likely include a combination of trawl types. Our results also support the logic of using modified trawls for haddock fishing trips in which bycatch is strictly regulated as the Ruhle trawl is able to maintain 80% of catches caught by a conventional trawl while reducing bycatch up to over 60%. This paper is a first step towards an aid for policy makers to examine fishery gear trade-offs and the resulting biological and socio-economic consequences of different management actions within the constraints of the Magnuson-Stevens Act

A bio-economic analysis of harvest control rules for the Northeast Arctic cod fishery

Harvest control rules (HCRs) have been implemented for many fisheries worldwide. However, in most instances, those HCRs are not based on the explicit feedbacks between stock properties and economic considerations. This paper develops a bio-economic model that evaluates the HCR adopted in 2004 by the Joint Norwegian-Russian Fishery Commission to manage the world's largest cod stock, Northeast Arctic cod (NEA). The model considered here is biologically and economically detailed, and is the firt to compare the performance of the stock's current HCR with that of alternative HCRs derived with optimality criteria. In particular, HCRs are optimized for economic objectives including fleet profit, economic welfare, and total yield and the emerging properties are analyzed. The performance of these optimal HCRs was compared with the currently used HCR. This paper show that the current HCR does in fact comes very close to maximizing profits. Furthermore, the results reveal that the HCR that maximizes profits is the most precautionary one among the considered HCRs. Finally, the HCR that maximizes yield leads to un-precautionary low levels of biomass. In these ways, the implementation of the HCR for NEA cod can be viewed as a success story that may provide valuable lessons for other fishries

Statistical Origin of Quantum Mechanics

The one particle quantum mechanics is considered in the frame of a N-body classical kinetics in the phase space. Within this framework, the scenario of a subquantum structure for the quantum particle, emerges naturally, providing an ontological support to the orthodox quantum mechanics. This approach to quantum mechanics, constitutes a deductive and direct method which, in a self-consistent scheme of a classical kinetics, allows us: i) to obtain the probabilistic nature of the quantum description and to interpret the wave function $\psi$ according to the Copenhagen school; ii) to derive the quantum potential and then the Schr\"odinger equation; iii) to calculate the values of the physical observables as mean values of the associated quantum operators; iv) to obtain the Heisenberg uncertainty principle.Comment: Accepted for publication in Physica

Significant Digits: Responsible use of quantitative information

We live in an age when good policies are assumed to be evidence-based. And that evidential base is assumed to be at its best when expressed in numbers. The digital information may be derived from quantitative data organised in statistics, or from qualitative data organised in indicators. Either way, evidence in digital form provides the accepted foundation of policy arguments over a very broad range of issues. In the policy realm there are frequent debates over particular policy issues and their associated evidence. But only rarely is the nature of the evidence called into question. Such a faith in numbers can be dangerous. Policies in economic and financial policy, based on numbers whose significance was less than assumed, recently turned out to be quite disastrously wrong. Other examples can easily be cited. The decades-long period of blaming dietary fats for heart disease, rather than sugar, is a notable recent case. We are concerned here with the systemic problem: whether we are regularly placing too much of an evidentiary burden on quantitative sciences whose strength and maturity are inherently inadequate. The harm that has been done to those sciences, as well as to the policy process, should be recognised. Only in that way can future errors be avoided.JRC.DDG.01-Econometrics and applied statistic

Does Blood Flow Restriction Applied Post High-Load Exercise Augment Skeletal Muscle Growth Following Eight Weeks of Training?

The application of blood flow restriction during low load exercise has consistently been shown to augment muscle hypertrophy which has been attributed to metabolic accumulation. It remains unknown, however, whether metabolites can augment muscle growth independent of further mechanical tension, specifically when maintained post high-load training. Thirteen untrained individuals performed 24 training sessions. The control arm performed one set of elbow flexion (70% 1RM) exercise to volitional fatigue, while the experimental arm performed the same protocol immediately folloby 3 min of blood flow restriction (70% arterial occlusion). Both conditions completed the same volume (3687 vs. 3638 kg) of exercise. There was an interaction (p=0.031) demonstrating an attenuation of muscle growth at the 60% site in the experimental [pre: 3.1 (0.6), post: 3.1 (0.7) cm] vs. control [pre: 3.1 (0.7), post 3.3 (0.7) cm] condition. Muscle growth at the 50% site did not differ between the experimental [pre: 2.9 (0.6), post 2.9 (0.6) cm] and control [pre: 2.8 (0.7), post: 2.9 (0.6) cm] condition (p=0.31) nor did it differ at the 70% site [experimental pre: 3.3 (0.60), post 3.5 (0.7) cm; control pre: 3.4 (0.7), post 3.6 (0.7) cm]. Although there were no differences at the group level, there were attenuations at the individual level. The number of measured sites displaying growth at or outside the error of the measurement was greater in the control (21) vs. experimental (10) condition. The application of blood flow restriction post high-load exercise did not augment, but appeared to attenuate muscle growth at the group and individual level. With regard to one-repetition maximum strength, increases were observed in both the control [pre: 13.5 (3.8), post: 16.3 (4.5) kg] and experimental [pre: 13.7 (4.1), post: 16.3 (4.6) kg] conditions with no differences between conditions. No changes were observed for isometric or isokinetic strength for either the control or experimental conditions. These results unveil the possibilities that 1) metabolites do not have anabolic properties per se, and may be detrimental for muscle hypertrophy; 2) immediate post-exercise blood flow is important for muscle hypertrophy; and/or 3) metabolites have anabolic properties but this was masked by the restriction of blood flow

Do Individual Responses to Resistance Exercise Exist to an Extent That Can be Detected Beyond That of Measurement Error/Random Biological Variability?

Millions of dollars are spent analyzing inter-individual differences in response to resistance exercise, but the lack of a non-exercise control group means they may simply be examining random error. The purpose of this study was to determine whether there are inter-individual differences in response to two distinct resistance exercise protocols. Participants (n=151) were randomly assigned to one of 3 groups as follows: (1) a traditional exercise group performing 4 sets to failure with a load that could be lifted 8-12 times; (2) a one-repetition maximum (1RM) training group performing a 1RM test each visit; and (3) a non-exercise control group. Both exercise groups performed 18 sessions of elbow flexion exercise over 6 weeks. Both 1RM training (2.3kg) and traditional training (2.4kg) increased 1RM strength to a similar extent. Only the 1RM group increased untrained arm 1RM strength (1.5kg) which was greater than both other groups (p\u3c0.05). The traditional exercise group also increased ultrasound measured muscle size at all sites (all\u3e0.22cm), each of which were greater than both the control and 1RM group (p\u3c0.05). The 1RM group did not increase muscle mass (p\u3e0.05). Across both training groups, the only individual responses were found in the change in 1RM strength of the trained arm in the traditional training group (Levene’s test p\u3c0.05) in which 10 individuals (25%) were classified as responding differently from the mean. The variability in the response to other outcomes did not exceed that of the control group indicating it could not be detected above random error. Other commonly used approaches of classifying differential responders such as clustering analyses, standard deviations above and below the mean, and upper/lower percentiles would produce different results but are not appropriate. These findings demonstrate the importance oftaking into consideration the magnitude of random error when classifying individual responders, and provide possible rationale as to why numerous analyses fail to find/replicate what genes may be responsible for producing more favorable exercise outcomes