The Relative Weight (Wr) Condition Index as a Predictor of Growth, Prey Abundance and Environmental Conditions

We evaluated the relative weight (Wr) condition index for assessment of growth, prey availability and environmental conditions in fish populations. Standard weight (Ws) equations for pumpkinseed (Lepomis gibbosus) and golden shiner (Notemigonus crysoleucas) from 302 pumpkinseed and 285 golden shiner populations, with well over 10,000 fish of each species, were developed with regression-line-percentile (RLP) technique. The proposed Ws equation in metric units for pumpkinseed is log10Ws = -5.179 + 3.237 log10TL, and for golden shiner is log10Ws = -5.593 + 3.302 log10TL. The English-unit versions of these equations were also developed. Evaluation of relationships of Wr with fish growth and other ecological variables were made from ten southern Quebec lakes in 1987 and 1988, with over 2,000 fish of each species. Size-specific growth and size-specific Wr were calculated using stock and quality length of each species. Lake, year, season, and length affected Wr, but not sex of fish. No significant relationships were found between Wr and growth among lakes or among individual fish. Significant correlations were found between Wr and prey availability and chlorophyll a, but not fish biomass, macrophyte biomass, and temperature. Our results suggest that Wr can reflect prey availability of fish populations better than other physiological or ecological conditions of fish. We recommend that Wr be used cautiously as an assessment tool in freshwater fishes

The Relative Weight (Wr) Condition Index as a Predictor of Growth, Prey Abundance and Environmental Conditions

We evaluated the relative weight (Wr) condition index for assessment of growth, prey availability and environmental conditions in fish populations. Standard weight (Ws) equations for pumpkinseed (Lepomis gibbosus) and golden shiner (Notemigonus crysoleucas) from 302 pumpkinseed and 285 golden shiner populations, with well over 10,000 fish of each species, were developed with regression-line-percentile (RLP) technique. The proposed Ws equation in metric units for pumpkinseed is log10Ws = -5.179 + 3.237 log10TL, and for golden shiner is log10Ws = -5.593 + 3.302 log10TL. The English-unit versions of these equations were also developed. Evaluation of relationships of Wr with fish growth and other ecological variables were made from ten southern Quebec lakes in 1987 and 1988, with over 2,000 fish of each species. Size-specific growth and size-specific Wr were calculated using stock and quality length of each species. Lake, year, season, and length affected Wr, but not sex of fish. No significant relationships were found between Wr and growth among lakes or among individual fish. Significant correlations were found between Wr and prey availability and chlorophyll a, but not fish biomass, macrophyte biomass, and temperature. Our results suggest that Wr can reflect prey availability of fish populations better than other physiological or ecological conditions of fish. We recommend that Wr be used cautiously as an assessment tool in freshwater fishes

Assessment of diet and consumption dynamics of the adult piscivorous fish community in Spirit Lake, Iowa

We explored differences among four well-known indices (%W, %O, %N, and %IRI), plus a modified %IRI (%MIRI), examined diet and consumption dynamics of black crappie (Pomoxis nigromaculatus), largemouth bass (Micropterus salmoides), northern pike (Esox lucius ), smallmouth bass (Micropterus dolomieui), walleye (Stizostedion vitreum), and yellow perch (Perca flavescens ) in Spirit Lake, Iowa, in 1995--1997. %W and %MIRI emphasizes importance of large prey taxa, even when relatively rare in diets, whereas %O and %N emphasize small prey common in diets. %IRI yielded intermediate results. Using %IRI, we found that the most important prey taxa overall were yellow perch, Decapoda, and Amphipoda. Largemouth bass, northern pike, and walleye fed intensively on yellow perch. Smallmouth bass preyed heavily on both yellow perch and decapods. Black crappie and yellow perch largely relied on macroinvertebrates. Yellow perch, logperch (Percina caprodes), walleye, and bluegill (Lepomis macrochirus) were the four most predominant prey fish species over the course of the study. Using bioenergetics models, we found that walleye dominated both the total consumption and consumption of fish in 1995--1997, due to their high abundance and piscivory. We believe that annual intensive walleye stocking in Spirit Lake results in higher consumptive demand on forage fishes and walleye cannibalism compared to other systems in North America. As an important prey as well as dominant predator, yellow perch could influences walleye well-being and compete walleye for food in Spirit Lake, playing a complex role in the trophic dynamics of the fish community. Using data from our study and previous studies, we developed regression models to help fisheries managers to obtain quick approximations of annual population consumption

Morphology and properties of thermal/cooling-gel bi-phasic systems based on hydroxypropyl methylcellulose and hydroxypropyl starch

The miscibility between two gels with largely different gelation behaviors is an interesting topic both scientifically and practically. This paper reports a novel bi-phasic system based on two natural polymers, hydroxypropyl methylcellulose (HPMC) which has a thermal gelation behavior, and hydroxypropyl starch (HPS) which has a cooling gelation property. While both biopolymers have the same glucose unit grafted with propylene oxide, and are compatible to a certain degree, they were observed immiscible because of their different gelation behaviors. The immiscibility of these two compatible polymers could result in special structures leading to different blend film properties. Regarding this, the morphology, thermal transition, mechanical properties and oxygen barrier property could be well tailored by the ratio of two biopolymers and the environmental conditions. The knowledge obtained from this work could be useful for understanding other similar systems with desirable structure and properties

High-Pressure torsion-Induced Grain Growth in Electrodeposited Nanocrystalline Ni

Deformation-induced grain growth has been reported in nanocrystalline (nc) materials under indentation and severe cyclic loading, but not under any other deformation mode. This raises an issue on critical conditions for grain growth in nc materials. This study investigates deformation-induced grain growth in electrodeposited nc Ni during high-pressure torsion (HPT). Our results indicate that high stress and severe plastic deformation are required for inducing grain growth, and the upper limit of grain size is determined by the deformation mode and parameters. Also, texture evolution suggests that grain-boundary-mediated mechanisms played a significant role in accommodating HPT strain

Integrating audio and visual modalities for multimodal personality trait recognition via hybrid deep learning

Recently, personality trait recognition, which aims to identify people’s first impression behavior data and analyze people’s psychological characteristics, has been an interesting and active topic in psychology, affective neuroscience and artificial intelligence. To effectively take advantage of spatio-temporal cues in audio-visual modalities, this paper proposes a new method of multimodal personality trait recognition integrating audio-visual modalities based on a hybrid deep learning framework, which is comprised of convolutional neural networks (CNN), bi-directional long short-term memory network (Bi-LSTM), and the Transformer network. In particular, a pre-trained deep audio CNN model is used to learn high-level segment-level audio features. A pre-trained deep face CNN model is leveraged to separately learn high-level frame-level global scene features and local face features from each frame in dynamic video sequences. Then, these extracted deep audio-visual features are fed into a Bi-LSTM and a Transformer network to individually capture long-term temporal dependency, thereby producing the final global audio and visual features for downstream tasks. Finally, a linear regression method is employed to conduct the single audio-based and visual-based personality trait recognition tasks, followed by a decision-level fusion strategy used for producing the final Big-Five personality scores and interview scores. Experimental results on the public ChaLearn First Impression-V2 personality dataset show the effectiveness of our method, outperforming other used methods