Changes in the muscle of three Indian major carps during frozen storage

Chunks of Labeo rohita, Cirrhinus mrigala and Catla catla wrapped in polythene film were stored at -8 to -10°C in the freezer cabinet of the refrigerator. It was found that L. rohita and C. mrigala were acceptable up to 33 days and C. catch up to 35 days. Total volatile base nitrogen, free fatty acids and degree of sponginess of the samples showed increasing trend during frozen storage.

Relationship between water, lipid and protein in the muscle, liver and gonad in a freshwater fish Puntius filamentosus (Val.)

Details are given of a study investigating the relationship between water, lipid, and protein in Puntius filamentosus. Percentage compositions in the muscle, liver and gonad of fish specimens from Lake Vellayani in India are given, showing the fluctuations which occur during maturation.

A method to preserve fish muscle pieces and mince from sciaenids

Fish muscle pieces and mince from sciaenids can be preserved for 72 and 48 h respectively at ambient temperature (34°C ± 4.5) in media containing 8% NaCl, 0.2% sodium benzoate and 0.5% potassium sorbate. Incorporation of 0.1% sodium bisulphite in this media slightly improved the texture and flavour of minced fish.

Functional significance of stiffness in adaptation of multijoint arm movements to stable and unstable dynamics.

This study compared the mechanisms of adaptation to stable and unstable dynamics from the perspective of changes in joint mechanics. Subjects were instructed to make point to point movements in force fields generated by a robotic manipulandum which interacted with the arm in either a stable or an unstable manner. After subjects adjusted to the initial disturbing effects of the force fields they were able to produce normal straight movements to the target. In the case of the stable interaction, subjects modified the joint torques in order to appropriately compensate for the force field. No change in joint torque or endpoint force was required or observed in the case of the unstable interaction. After adaptation, the endpoint stiffness of the arm was measured by applying displacements to the hand in eight different directions midway through the movements. This was compared to the stiffness measured similarly during movements in a null force field. After adaptation, the endpoint stiffness under both the stable and unstable dynamics was modified relative to the null field. Adaptation to unstable dynamics was achieved by selective modification of endpoint stiffness in the direction of the instability. To investigate whether the change in endpoint stiffness could be accounted for by change in joint torque or endpoint force, we estimated the change in stiffness on each trial based on the change in joint torque relative to the null field. For stable dynamics the change in endpoint stiffness was accurately predicted. However, for unstable dynamics the change in endpoint stiffness could not be reproduced. In fact, the predicted endpoint stiffness was similar to that in the null force field. Thus, the change in endpoint stiffness seen after adaptation to stable dynamics was directly related to changes in net joint torque necessary to compensate for the dynamics in contrast to adaptation to unstable dynamics, where a selective change in endpoint stiffness occurred without any modification of net joint torque.

Different mechanisms involved in adaptation to stable and unstable dynamics.

Recently, we demonstrated that humans can learn to make accurate movements in an unstable environment by controlling magnitude, shape, and orientation of the endpoint impedance. Although previous studies of human motor learning suggest that the brain acquires an inverse dynamics model of the novel environment, it is not known whether this control mechanism is operative in unstable environments. We compared learning of multijoint arm movements in a "velocity-dependent force field" (VF), which interacted with the arm in a stable manner, and learning in a "divergent force field" (DF), where the interaction was unstable. The characteristics of error evolution were markedly different in the 2 fields. The direction of trajectory error in the DF alternated to the left and right during the early stage of learning; that is, signed error was inconsistent from movement to movement and could not have guided learning of an inverse dynamics model. This contrasted sharply with trajectory error in the VF, which was initially biased and decayed in a manner that was consistent with rapid feedback error learning. EMG recorded before and after learning in the DF and VF are also consistent with different learning and control mechanisms for adapting to stable and unstable dynamics, that is, inverse dynamics model formation and impedance control. We also investigated adaptation to a rotated DF to examine the interplay between inverse dynamics model formation and impedance control. Our results suggest that an inverse dynamics model can function in parallel with an impedance controller to compensate for consistent perturbing force in unstable environments.

Adaptation to stable and unstable dynamics achieved by combined impedance control and inverse dynamics model.

This study compared adaptation in novel force fields where trajectories were initially either stable or unstable to elucidate the processes of learning novel skills and adapting to new environments. Subjects learned to move in a null force field (NF), which was unexpectedly changed either to a velocity-dependent force field (VF), which resulted in perturbed but stable hand trajectories, or a position-dependent divergent force field (DF), which resulted in unstable trajectories. With practice, subjects learned to compensate for the perturbations produced by both force fields. Adaptation was characterized by an initial increase in the activation of all muscles followed by a gradual reduction. The time course of the increase in activation was correlated with a reduction in hand-path error for the DF but not for the VF. Adaptation to the VF could have been achieved solely by formation of an inverse dynamics model and adaptation to the DF solely by impedance control. However, indices of learning, such as hand-path error, joint torque, and electromyographic activation and deactivation suggest that the CNS combined these processes during adaptation to both force fields. Our results suggest that during the early phase of learning there is an increase in endpoint stiffness that serves to reduce hand-path error and provides additional stability, regardless of whether the dynamics are stable or unstable. We suggest that the motor control system utilizes an inverse dynamics model to learn the mean dynamics and an impedance controller to assist in the formation of the inverse dynamics model and to generate needed stability.

How is somatosensory information used to adapt to changes in the mechanical environment?

Recent studies examining adaptation to unexpected changes in the mechanical environment highlight the use of position error in the adaptation process. However, force information is also available. In this chapter, we examine adaptation processes in three separate studies where the mechanical environment was changed intermittently. We compare the expected consequences of using position error and force information in the changes to motor commands following a change in the mechanical environment. In general, our results support the use of position error over force information and are consistent with current computational models of motor learning. However, in situations where the change in the mechanical environment eliminates position error the central nervous system does not necessarily respond as would be predicted by these models. We suggest that it is necessary to take into account the statistics of prior experience to account for our observations. Another deficiency in these models is the absence of a mechanism for modulating limb mechanical impedance during adaptation. We propose a relatively simple computational model based on reflex responses to perturbations which is capable of accounting for iterative changes in temporal patterns of muscle co-activation.

How are internal models of unstable tasks formed?

The results of recent studies suggest that humans can form internal models that they use in a feedforward manner to compensate for both stable and unstable dynamics. To examine how internal models are formed, we performed adaptation experiments in novel dynamics, and measured the endpoint force, trajectory and EMG during learning. Analysis of reflex feedback and change of feedforward commands between consecutive trials suggested a unified model of motor learning, which can coherently unify the learning processes observed in stable and unstable dynamics and reproduce available data on motor learning. To our knowledge, this algorithm, based on the concurrent minimization of (reflex) feedback and muscle activation, is also the first nonlinear adaptive controller able to stabilize unstable dynamics.

Comparison of physicochemical properties of muscle proteins in cultured and wild prawns (Penaeus (Fenneropenaeus) orientalis Kishinouye, 1918)

Protein physicochemical properties in cultured and wild prawns (Penaeus (F.) orientalis Kishinouye, 1918) were studied and compared. Protein fractions were separated into water-soluble, salt-soluble, alkali-soluble, and stroma. The results showed that salt- and alkali-soluble proteins were slightly higher in wild prawns and water-soluble proteins were higher in cultured prawns. There were only slight differences in Ca super(2+)-ATPase, MG super(2+)-ATPase, and ATP sensitivities. The textural values of wild prawns were significantly higher than the cultured ones.

The study of biological characteristics and heavy metal determination of Cd, Pb, Fe, V, Ni in the muscle, liver and gonad tissues of kingfish Scomberomorus commerson in the coastal waters of the Hormozagan Province (Persian Gulf)

Biological studies and heavy metal (Ni, v, Fe, Pb,Cd) determination in liver, gonad and muscle of Scomberomorus commerson were carried out from Oct 2006 to Sept 2007 in Hormozgan coastal waters. 599 Samples were gutted for reproduction and nutrition studies, fork length and weight were measured to nearest cm and g respectively. Meanwhile 40 samples were also investigated for heavy metal studies. All specimens were collected from two major landing sites (Bandar Lengeh & Bandar Abbas). Minimums & maximum fork length & weight were 29, 128 cm & 235 and 15350 g respectively.Isometric growth was shown according to our study and b was estimated 2.9 (overall), 2.91(male) & 2.89 (female). The average relative gut length was 0.52± 0.007 and it was determined that S. commerson is a carnivorous. More than 99 percent of gut content was different teleost fishes. Gastro somatic index had two peaks in Nov & Jan (before spawning) and with a decreased trend in July, the spawning period. Occurrence of empty stomach was estimated % 65.77. Maximum amount of condition factor was in Dec. Spawning season was started from June. The average of Absolute & relative fecundity (to weight unit) was 1217149±179315 and 178.2±15.58 respectively. Lm50% was estimated 75 cm for females. Sex ratio was 0.97: 1 (male: female). Chi- Square test showed no significant difference (p>0.05). Maximum amount of hepatosomatic index was estimated in March.Metal concentrations were determined using either Flame Atomic Absorption Spectroscopy (for Fe) or Graphite Furnace Atomic Absorption Spectroscopy (for Pb,Cd,Ni and V). The mean concentration (μg/g dry weight)of Pb,Cd,Ni,V and Fe in the liver were 0.0309, 0.0268, 0.0672, 0.0077, 2.5159 in the gonad 0.0440 ,0.0295, 0.1096, 0.0000, 1.4449 and in the muscle 0.0244, 0.0324, 0.0656, 0.0128, 1.6138 respectively. The maximum metal concentrations were below the maximum permissible limits for human consumption recommended by the USEPA, WHO and the UK. The results of Kendall's Tau-b correlation coefficient were as follows: The Liver tissue: There were significant positive linear relationships between accumulation of V, Fe, and Pb with Fork length, Pb and Fe with weight, GSI with Pb, Cd, V and 109 Fe, and a negative linear relationships between HSI with accumulation of V and Fe, Fork length, weight and GSI. The Gonad tissue: There were significant positive linear relationships between GSI with accumulation of Pb, Cd, Fe, Fork length and weight, a negative linear relationship between HSI with Fork length, weight and GSI. The Muscle tissue: There were significant positive linear relationships between accumulations of V, Fe with Fork length and weight factors and as well as GSI with Cd, V, Fe, Pb, Fork length and weight,a negative linear relationship between HSI with Fork length, weight, Cd, Fe and GSI. The results of Mann-Whitney U tests (P≤0.05) show that there were significant differences between summer and autumn from heavy metal contents in the studied tissues point of view. The only exceptions were for Ni in the liver, gonads and muscle and as well as there were significant differences between male and female from heavy metal contents in the studied tissues. The only exceptions were for Pb in muscle, Ni in liver, gonad and muscle, V in muscle, and Cd and Fe in gonads.

Identification and determination of muscle's fatty acids and amino acids in Cobia and Indian squid

The present study aims to find the effect of freezing Time on the quality of Cobia (Rastrelliger kanagurta) and Indian Squid in commercial scale during freezing and subsequent frozen storage (−18◦C). Total time for freezing was significantly different (P<0.05) between the Cobia and Indian squid samples. The difference in the freezing time could be attributed to the varied quality of the 2 samples. Upon freezing, the moisture content decreased in Indian Squide samples compared to Cobia freezer where protein content decreased in both the samples. Upon freezing and during frozen storage, lipid oxidation products (peroxide value, and free fatty acid value) and volatile bases (total volatile base nitrogen) showed an increasing trend in both the samples with values slightly higher in Indian squid samples compared to cobia frozen samples. The total plate counts showed a significantly (P<0.05) decreasing trend in both the samples. K value did not show any significant (P<0.05) difference between the samples whereas the histamine formation was significantly (P<0.05) increased in Indian squid frozen samples compared to cobia samples. The taste and overall acceptability was significantly different (P<0.05) in cobia samples compared to Indian squid frozen samples on 5th month. Both samples were in acceptable condition up to 5 month but the Cobia frozen samples quality was slightly better than the air blast frozen samples.

Unsupervised intra-lingual and cross-lingual speaker adaptation for HMM-based speech synthesis using two-pass decision tree construction

Hidden Markov model (HMM)-based speech synthesis systems possess several advantages over concatenative synthesis systems. One such advantage is the relative ease with which HMM-based systems are adapted to speakers not present in the training dataset. Speaker adaptation methods used in the field of HMM-based automatic speech recognition (ASR) are adopted for this task. In the case of unsupervised speaker adaptation, previous work has used a supplementary set of acoustic models to estimate the transcription of the adaptation data. This paper first presents an approach to the unsupervised speaker adaptation task for HMM-based speech synthesis models which avoids the need for such supplementary acoustic models. This is achieved by defining a mapping between HMM-based synthesis models and ASR-style models, via a two-pass decision tree construction process. Second, it is shown that this mapping also enables unsupervised adaptation of HMM-based speech synthesis models without the need to perform linguistic analysis of the estimated transcription of the adaptation data. Third, this paper demonstrates how this technique lends itself to the task of unsupervised cross-lingual adaptation of HMM-based speech synthesis models, and explains the advantages of such an approach. Finally, listener evaluations reveal that the proposed unsupervised adaptation methods deliver performance approaching that of supervised adaptation.