Learning Max-CSPs via Active Constraint Acquisition

Constraint acquisition can assist non-expert users to model their problems as constraint networks. In active constraint acquisition, this is achieved through an interaction between the learner, who posts examples, and the user who classifies them as solutions or not. Although there has been recent progress in active constraint acquisition, the focus has only been on learning satisfaction problems with hard constraints. In this paper, we deal with the problem of learning soft constraints in optimization problems via active constraint acquisition, specifically in the context of the Max-CSP. Towards this, we first introduce a new type of queries in the context of constraint acquisition, namely partial preference queries, and then we present a novel algorithm for learning soft constraints in Max-CSPs, using such queries. We also give some experimental results

What’s on the (publication fee) menu, who pays the bill and what should be the venue?

We address the cost of access to knowledge and its ethical implications in ‘true’, ‘pseudo’ and ‘hybrid’ OA journals

Age at maturity of Mediterranean marine fishes

In this review we collected data on the age at maturity (tm) and maximum reported age (tmax) for 235 stocks of Mediterranean marine fishes, belonging to 82 species, 37 families, 12 orders and 2 classes (Actinopterygii and Elasmobranchii). Among Actinopterygii (mean tm ± SD = 2.20 ± 1.43 y, n = 215), tm ranged from 0.3 y, for the common goby Pomatoschistus microps, to 12 y, for dusky grouper Epinephelus marginatus, while among Elasmobranchii (mean tm ± SD = 5.94 ± 2.47 y, n = 20), tm ranged between 2.7 y, for brown ray Raja miraletus, and 12 y for picked dogfish Squalus acanthias. Overall, the tmax ranged between 1 y, for transparent goby Aphia minuta, and 70 y, for wreckfish Polyprion americanus. The mean tmax of Actinopterygii (tmax ± SD = 10.14 ± 9.42 y) was lower than that of Elasmobranchii (tmax ± SD = 14.05 ± 8.47 y). The tm exhibited a strong positive linear relation with tmax for both Actinopterygii (logtm = 0.58 ´ logtmax – 0.25, r2 = 0.51, P < 0.001) and Elasmobranchii (logtm = 0.67 ´ logtmax – 0.006, r2 = 0.51, P = 0.007). The mean tm/tmax did not differ significantly with sex within Actinopterygii (ANOVA: F = 0.27, P = 0.60, n = 90; females: mean ± SD = 0.276 ± 0.143; males: mean ± SD = 0.265 ± 0.138) and Elasmobranchii (ANOVA: F = 1.44, P = 0.25, n = 10; females: mean ± SD = 0.499 ± 0.166; males: mean ± SD = 0.418 ± 0.133). Finally, the dimensionless ratio tm/tmax was significantly lower (ANOVA: F = 31.04, P < 0.001) for Actinopterygii (mean ± SD = 0.270 ± 0.135, n = 180) than for Elasmobranchii, (mean ± SD = 0.458 ± 0.152, n = 20), when stocks with combined sexes were excluded from the analysis

Learning Class Regularized Features for Action Recognition

Training Deep Convolutional Neural Networks (CNNs) is based on the notion of using multiple kernels and non-linearities in their subsequent activations to extract useful features. The kernels are used as general feature extractors without specific correspondence to the target class. As a result, the extracted features do not correspond to specific classes. Subtle differences between similar classes are modeled in the same way as large differences between dissimilar classes. To overcome the class-agnostic use of kernels in CNNs, we introduce a novel method named Class Regularization that performs class-based regularization of layer activations. We demonstrate that this not only improves feature search during training, but also allows an explicit assignment of features per class during each stage of the feature extraction process. We show that using Class Regularization blocks in state-of-the-art CNN architectures for action recognition leads to systematic improvement gains of 1.8%, 1.2% and 1.4% on the Kinetics, UCF-101 and HMDB-51 datasets, respectively

Editorial note on weight–length relations of fishes

Weight-length relations of fishes are useful for estimation of biomass from length observations, e.g., in fisheries or conservation research. Here we provide some guidance to authors of such papers, in order to facilitate the publication and review process

Editorial note on reproductive biology of fishes

Fish reproductive biology (onset and duration of spawning, sex ratio, maturity stages, length and age at maturity, and fecundity) is important in fisheries research, stock assessment, and management. In this editorial note, we provide some criteria and recommendations on issues of fish reproductive biology, which may be useful in research planning, data analysis and presentation, as well as in manuscript preparation

Reduced vertical displacement of the center of mass is not accompanied by reduced oxygen uptake during walking

Abstract The six determinants of gait proposed that the goal of gait is to minimize vertical displacement of the body’s center of mass (CoM) with the objective to optimize energy expenditure. On the contrary, recent investigations suggest that reduced vertical displacement leads to an increase in energy expenditure. However, these investigations had the included subjects deliberately changing their gait, which could bias the endpoint measures. The present study investigated the effect of reduced vertical displacement of the CoM on oxygen uptake and walking economy without imposing altered gait patterns. This was accomplished by having subjects walk on a curved treadmill and on a flat treadmill. Vertical displacement of the CoM (sacrum marker displacement), oxygen uptake, walking economy, stride characteristics and lower limb joint angles were measured. There were significant differences in stride characteristics and phase dependent differences in lower limb movement pattern between the two conditions which in size were comparable to the changes observed between different speeds. The vertical displacement of the CoM was significantly reduced on the curved treadmill. This was accompanied by an increase in oxygen uptake and walking economy. These results support recent assertions that the six determinants of gait do not serve to improve walking economy

Trammel net catch species composition, catch rates and metiers in southern European waters: A multivariate approach

We identified and quantified the effect of season, depth, and inner and outer panel mesh size on the trammel net catch species composition and catch rates in four southern European areas (Northeast Atlantic: Basque Country, Spain; Algarve, Portugal; Gulf of Cadiz, Spain; Mediterranean: Cyclades, Greece), all of which are characterised by important trammel net fisheries. In each area, we conducted, in 1999-2000, seasonal, experimental fishing trials at various depths with trammel nets of six different inner/outer panel mesh combinations (i.e., two large outer panel meshes and three small inner panel meshes). Overall, our study covered some of the most commonly used inner panel mesh sizes, ranging from 40 to 140 mm (stretched). We analysed the species composition and catch rates of the different inner/outer panel combinations with regression, multivariate analysis (cluster analysis and multidimensional scaling) and other 'community' techniques (number of species, dominance curves). All our analyses indicated that the outer panel mesh sizes used in the present study did not significantly affect the catch characteristics in terms of number of species, catch rates and species composition. Multivariate analyses and seasonal dominance plots indicated that in Basque, Algarve and Cyclades waters, where sampling covered wide depth ranges, both season and depth strongly affected catch species compositions. For the Gulf of Cadiz, where sampling was restricted to depths 10-30 m, season was the only factor affecting catch species composition and thus group formation. In contrast, the inner panel mesh size did not generally affect multidimensional group formation in all areas but affected the dominance of the species caught in the Algarve and the Gulf of Cadiz. Multivariate analyses also revealed 11 different metiers (i.e., season-depth-species-inner panel mesh size combinations) in the four areas. This clearly indicated the existence of trammel net 'hot spots', which represent essential habitats (e.g., spawning, nursery or wintering grounds) of the life history of the targeted and associated species. The number of specimens caught declined significantly with inner panel mesh size in all areas. We attributed this to the exponential decline in abundance with size, both within- and between-species. In contrast, the number of species caught in each area was not related to the inner mesh size. This was unexpected and might be a consequence of the wide size-selective range of trammel nets. (c) 2006 Elsevier B.V All rights reserved

Biomechanics (Chapter 9)

Biomechanics is a discipline. A discipline deals with understanding, predicting, and explaining phenomena within a content domain, and biomechanics is the study of the human body in motion. Kinesiology, the parent discipline of biomechanics, is a science that investigates movement. Biomechanical research in human development focuses on evaluating essential movement patterns across the human life span. Biomechanical analysis is specifically important in quantifying the developmental motor skills and movement patterns such as walking, kicking, jumping, throwing, and catching. Biomechanical research also involves studying the movement patterns of injured and disabled people. Forensic biomechanists are invited to analyze evidence, clarify some of the most important issues, and facilitate the decisions of the jury. Motion recording devices use optical lenses to capture body motion and provide permanent recorded images of movement that can be evaluated with more precision than perception with the naked eye alone

A Bayesian population model to estimate changes in the stock size in data poor cases using Mediterranean bogue (Boops boops) and picarel (Spicara smaris) as an example

The paper presents an effort to build a biologically realistic, age structured Bayesian model for the stock assessment of data poor fisheries where only aggregated catch data is available. The model is built using prior information from other areas and ecologically or taxonomically similar species. The modeling approach is tested with data poor fisheries on the Cyclades islands in Greek archipelago. The two most important species in the area are selected: bogue (Boops boops) and picarel (Spicara smaris). Both are hermaphroditic. The only data available is the total catch from 1950 to 2010. Information was gathered about natural mortality, recruitment, growth, body size, fecundity, and sex ratio. There were significant problems in finding reliable prior information and a uniform prior was used for fishing mortality. The models at their present stage are not used to give management advice. The biological characteristics of the species in that area should be further studied. However, the posteriors of biological parameters reflect the best available knowledge on these species and they could be used in future studies or in simpler biomass dynamics models as priors