30 research outputs found

    Sperm quality analysis in XX, XY and YY males of the Nile tilapia (Oreochromis niloticus).

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    peer reviewedIn Nile tilapia (Oreochromis niloticus), individuals with atypical sexual genotype are commonly used in farming (use of YY males to produce all-male offsprings), but they also constitute major tools to study sex determinism mechanisms. In other species, sexual genotype and sex reversal procedures affect different aspects of biology such as growth, behaviour and reproductive success. The aim of this study was to assess the influence of sexual genotype on sperm quality in Nile tilapia. Milt characteristics were compared in XX (sex-reversed), XY and YY males in terms of gonadosomatic index, sperm count, sperm motility and duration of sperm motility. Sperm motility was measured by computer-assisted sperm analysis (CASA) quantifying several parameters: total motility, progressive motility, curvilinear velocity, straight line velocity, average path velocity and linearity. None of the sperm trait measured differed significantly between the three genotypes. Mean values of gonadosomatic index, sperm concentration and sperm motility duration of XX, XY and YY males respectively ranged from 0.92 to 1.33 %, from 1.69 to 2.22 × 10(9) cells mL-1 and from 18’04’’ to 27’32’’. Mean values of total motility and curvilinear velocity 1 min after sperm activation respectively ranged from 53 to 58 % and from 71 to 76 µm s-1 for the three genotypes. After 3 min of activity, all the sperm motility and velocity parameters dropped by half and continued to slowly decrease thereafter. Seven min after activation, only 9 to 13 % of spermatozoa were still progressive. Our results prove that neither sexual genotype nor hormonal sex reversal treatments affect sperm quality in male Nile tilapias with atypical sexual genotype

    Predictive current control of an active harmonic filter

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    Voltage and current harmonics can have various deleterious effects on the entire power system, from residential households to power utilities. The onus to correct these harmonic problems lies dually with the end user and the power utilities. Active Harmonic Filters are one solution that can ensure the supply of clean power, to end users in a distributed system. Research into active harmonic filters has become an area of growing interest in the recent years. This is due to the increased use of non-linear loads, coupled with greater demand for electricity in general. This paper outlines the development of simulations and low voltage modeling of a pure active harmonic filter. The filter is composed of a three phase inverter direct-connected in shunt with the load and a microcontroller used to implement the control strategy. The control algorithm and filtering are performed in the dq rotating reference frame. This implementation attempts to improve the control scheme proposed by Akagi et. al for “Pure Active Harmonic Filters.” The output stages of the control scheme are replaced with a predictive current controller with space vector modulation. Simulation and experimental results are provided to support the findings of this paper

    Aphaenogaster obsidiana

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    Aphaenogaster obsidiana (Mayr, 1861) Atta obsidiana Mayr, 1861: 67. MATERIAL EXAMINED. — Turkey • 50☿; Rize, İkizdere, Rüzgarlı Vill.; 40°45’17”N, 40°33’15”E; 2100 m; 13.VIII.2000; K. Kiran leg.; EMTU 00/0084 • 2 ♂, 50 ☿; same collection data as for preceding; K. Kiran leg.; EMTU 00/0086 • 1 ♂, 50 ☿; Trabzon, Uzungöl Lake; 40°38’33”N, 40°16’21”E; 1800 m; 17.VIII.2000; K. Kiran leg.; EMTU 00/0170a • 50 ☿; same collection data as for preceding; K. Kiran leg.; EMTU 00/0172. DISTRIBUTION IN TURKEY. — Artvin.Published as part of Kiran, Kadri & Karaman, Celal, 2020, Additions to the Ant Fauna of Turkey (Hymenoptera, Formicidae), pp. 285-329 in Zoosystema 42 (18) on page 304, DOI: 10.5252/zoosystema2020v42a18, http://zenodo.org/record/392226

    Perceived Threat and Corroboration: Key Factors That Improve a Predictive Model of Trust in Internet-based Health Information and Advice

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    Background: How do people decide which sites to use when seeking health advice online? We can assume, from related work in e-commerce, that general design factors known to affect trust in the site are important, but in this paper we also address the impact of factors specific to the health domain. Objective: The current study aimed to (1) assess the factorial structure of a general measure of Web trust, (2) model how the resultant factors predicted trust in, and readiness to act on, the advice found on health-related websites, and (3) test whether adding variables from social cognition models to capture elements of the response to threatening, online health-risk information enhanced the prediction of these outcomes. Methods: Participants were asked to recall a site they had used to search for health-related information and to think of that site when answering an online questionnaire. The questionnaire consisted of a general Web trust questionnaire plus items assessing appraisals of the site, including threat appraisals, information checking, and corroboration. It was promoted on the hungersite.com website. The URL was distributed via Yahoo and local print media. We assessed the factorial structure of the measures using principal components analysis and modeled how well they predicted the outcome measures using structural equation modeling (SEM) with EQS software. Results: We report an analysis of the responses of participants who searched for health advice for themselves (N = 561). Analysis of the general Web trust questionnaire revealed 4 factors: information quality, personalization, impartiality, and credible design. In the final SEM model, information quality and impartiality were direct predictors of trust. However, variables specific to eHealth (perceived threat, coping, and corroboration) added substantially to the ability of the model to predict variance in trust and readiness to act on advice on the site. The final model achieved a satisfactory fit: χ25 = 10.8 (P = .21), comparative fit index = .99, root mean square error of approximation = .052. The model accounted for 66% of the variance in trust and 49% of the variance in readiness to act on the advice. Conclusions: Adding variables specific to eHealth enhanced the ability of a model of trust to predict trust and readiness to act on advice
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