Use of homeo drug for curing ulcerative syndrome in fishes

Fungal infection was observed in Catla catla and Labeo rohita cultured in two private fish farms. The later stage of the infection resulted in ulcerations followed by haemorrhage on the dorsal surface of the body. Initially, usual treatments of copper sulphate, potassium permanganate and common salt solution were tried, but no improvement was observed. Then repeated intramuscular injections of homeopathic drug Heaper Sulpher and Arnica spray were given with encouraging results. Infection reported in another farm was also successfully controlled using a similar treatment.

Incidence of epizootic ulcerative syndrome (EUS) in freshwater fishes in the endemic area of Punjab, Pakistan

Incidence of Epizootic Ulcerative Syndrome (EUS) has been recorded for the first time in freshwater fishes in the endemic area of Punjab, Pakistan. Survey of private fish farms, hatchery and natural water bodies was conducted in a radius of 14 Km from around river Ravi near Lahore (Punjab Province) Pakistan. Out Of 1628 fishes belonging to 18 genera, 517 fishes of 10 genera were found affected with EUS. The incidence of EUS in culturable fishes was higher in Cirrhina mrigala (15.4%) moderate in Catla cat/a (13.3%) and lower in Labeo rohita (5.0%). Exotic fish, Chinese carp Ctenoparyngodon idella and Hypophthalmicthys molitrix were not affected with EUS. In non-culturable fishes the incidence of EUS was highest in Channa punctatus (72.8%) moderate in by C. straitus (65.45%) and comparatively lower Puntius ticto (43.7%). A slow growing temperature sensitive Saprolegnia spp. was isolated from all of EUS infected fish species. Aeromonas spp. and Pseudomonas spp. were isolated from the diseased fishes. Ectoparasites viz. Lernaea, Argulus and Triclwdina spp. were also isolated from the skin and gills of infected fish species. The disease was more severe in water having low alkalinity (70 mg/1), hardness (75 mg/1) and low temperature of 10-12 °C.

Rapid detection of white spot syndrome virus (WSSV) of Penaeus monodon by latex agglutination test using monoclonal antibodies

Latex beads were sensitized with monoclonal antibodies (MAb) rose against VP28 of WSSV. The optimum concentration of MAb required to sensitize the latex beads was 125 µg/ml. The sensitized latex beads were used to detect WSSV from PCR-positive stomach tissue homogenates obtained from infected shrimp. Stomach tissue homogenates from WSSV-infected shrimp agglutinated the sensitized latex beads within 10 minutes, while uninfected samples did not produce any agglutination, although non-specific agglutinations were observed in some samples. The analytical sensitivity, analytical specificity, diagnostic sensitivity and diagnostic specificity of the (LAT) agglutination test were assessed. The analytical sensitivity of the test was 40 ng of purified WSSV (2 µg/ml). The sensitized latex beads did not agglutinate with normal shrimp tissue or MBV-infected tissue homogenate. The test has a diagnostic sensitivity of 70 and 45%, respectively, compared to single-step and nested PCR. The diagnostic specificity of the test was 82%. This test is a simple and rapid on-farm test which can be used to corroborate clinical signs for the detection of WSSV in grow-out ponds.

Rapid joint speaker and noise compensation for robust speech recognition

For speech recognition, mismatches between training and testing for speaker and noise are normally handled separately. The work presented in this paper aims at jointly applying speaker adaptation and model-based noise compensation by embedding speaker adaptation as part of the noise mismatch function. The proposed method gives a faster and more optimum adaptation compared to compensating for these two factors separately. It is also more consistent with respect to the basic assumptions of speaker and noise adaptation. Experimental results show significant and consistent gains from the proposed method. © 2011 IEEE.

Joint modelling of voicing label and continuous F0 for HMM based speech synthesis

Fundamental frequency, or F0 is critical for high quality speech synthesis in HMM based speech synthesis. Traditionally, F0 values are considered to depend on a binary voicing decision such that they are continuous in voiced regions and undefined in unvoiced regions. Multi-space distribution HMM (MSDHMM) has been used for modelling the discontinuous F0. Recently, a continuous F0 modelling framework has been proposed and shown to be effective, where continuous F0 observations are assumed to always exist and voicing labels are explicitly modelled by an independent stream. In this paper, a refined continuous F0 modelling approach is proposed. Here, F0 values are assumed to be dependent on voicing labels and both are jointly modelled in a single stream. Due to the enforced dependency, the new method can effectively reduce the voicing classification error. Subjective listening tests also demonstrate that the new approach can yield significant improvements on the naturalness of the synthesised speech. A dynamic random unvoiced F0 generation method is also investigated. Experiments show that it has significant effect on the quality of synthesised speech. © 2011 IEEE.

Polymorphisms in the C-type lectin genes cluster in chromosome 19 and predisposition to severe acute respiratory syndrome coronavirus (SARS-CoV) infection

Background: Polymorphisms of CLEC4M have been associated with predisposition for infection by the severe acute respiratory syndrome coronavirus (SARS-CoV). DC-SIGNR, a C-type lectin encoded by CLEC4M, is a receptor for the virus. A variable number tandem

Short- and long-term changes in joint co-contraction associated with motor learning as revealed from surface EMG.

In the field of motor control, two hypotheses have been controversial: whether the brain acquires internal models that generate accurate motor commands, or whether the brain avoids this by using the viscoelasticity of musculoskeletal system. Recent observations on relatively low stiffness during trained movements support the existence of internal models. However, no study has revealed the decrease in viscoelasticity associated with learning that would imply improvement of internal models as well as synergy between the two hypothetical mechanisms. Previously observed decreases in electromyogram (EMG) might have other explanations, such as trajectory modifications that reduce joint torques. To circumvent such complications, we required strict trajectory control and examined only successful trials having identical trajectory and torque profiles. Subjects were asked to perform a hand movement in unison with a target moving along a specified and unusual trajectory, with shoulder and elbow in the horizontal plane at the shoulder level. To evaluate joint viscoelasticity during the learning of this movement, we proposed an index of muscle co-contraction around the joint (IMCJ). The IMCJ was defined as the summation of the absolute values of antagonistic muscle torques around the joint and computed from the linear relation between surface EMG and joint torque. The IMCJ during isometric contraction, as well as during movements, was confirmed to correlate well with joint stiffness estimated using the conventional method, i.e., applying mechanical perturbations. Accordingly, the IMCJ during the learning of the movement was computed for each joint of each trial using estimated EMG-torque relationship. At the same time, the performance error for each trial was specified as the root mean square of the distance between the target and hand at each time step over the entire trajectory. The time-series data of IMCJ and performance error were decomposed into long-term components that showed decreases in IMCJ in accordance with learning with little change in the trajectory and short-term interactions between the IMCJ and performance error. A cross-correlation analysis and impulse responses both suggested that higher IMCJs follow poor performances, and lower IMCJs follow good performances within a few successive trials. Our results support the hypothesis that viscoelasticity contributes more when internal models are inaccurate, while internal models contribute more after the completion of learning. It is demonstrated that the CNS regulates viscoelasticity on a short- and long-term basis depending on performance error and finally acquires smooth and accurate movements while maintaining stability during the entire learning process.