A systematic literature review of the major factors causing yield gap by affecting growth, feed conversion ratio and survival in Nile tilapia (Oreochromis niloticus)

Abstract Productivity among small- and medium-scale tilapia farms varies considerably. The difference between the best performers and lower ones (yield gap), is affected by differences in growth rate and feed conversion ratio (FCR). FCR at the farm level is strongly influenced by survival of fish. In this study a systematic literature review of two databases (ASFA and CAB-Abstracts) identified 1973 potentially relevant articles. Data from 32 articles that met the inclusion criteria were analysed using linear mixed models for the most important factors with significant contributions to growth [investigated through analysis of the thermal growth coefficient (TGC)], survival and FCR of Nile tilapia. Increasing crude protein (CP), dissolved oxygen (DO) and pH significantly decreased FCR and increased TGC. Increasing stocking weight (SW) significantly improved both FCR and survival. Temperature had the largest effect on FCR followed by DO, pH and CP. DO had the largest effect on TGC followed by CP and pH. This study confirms that the optimal rearing temperature for Nile tilapia is between 27 and 32°C. Improving management to optimize DO (> 5 mg/L), stocking density (3–5 fish/m2), SW (> 10 g) and CP (25 − 30%) will improve performance and survival in small- and medium-scale tilapia farming. However, it is hard to influence temperature in ponds and cages while DO is largely influenced by aeration. Since many small- and medium-sized farms do not have aeration, these major tilapia farming systems could benefit from genetically improved strains selected for resilience to highly fluctuating diurnal temperature and DO levels

NATURAL LANGUAGE QUERYING OF HISTORICAL DATABASES -- THE QE-III LANGUAGE DEFINITION AND EXAMPLES

Information Systems Working Papers Serie

Evaluation of Nutrient (Protein) – Organism (Fish) relationship using a saturation kinetic model

The primary objective of this thesis was to demonstrate that the net nutrient (protein) deposition and weight gain as a function of nutrient (protein) intake fits the Saturation Kinetic Model and utilize the model parameters to describe and predict intake-deposition relationship. Groups of Nile tilapia, Oreochromis niloticus, fry (0.01 g) and small fingerlings (0.15 g) were each separately fed twelve semi purified diets in triplicates to the fingerling and duplicate to the fry trial. Each test diet contains a percentage of protein. Protein levels were 0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50 and 54 percent respectively. Each group of fish was randomly assigned a test diet. Fingerlings were fed at a rate of 10% their body weight per day for 8 weeks while the fry were fed at a rate of 25% of their weight per day for 4 weeks. The mathematical model (the four parameter saturation kinetics) was used to analyze the relationships between dietary crude protein intake and each of growth rate and protein depositions. It was found that tilapia protein-response (deposition) and weight gain as a result of feeding the test diets fit the saturation kinetic model. O. niloticus weight gain and net nutrient (crude protein) deposition were described as a function of the protein intake graphically and numerically. Maximum efficiency and protein requirements were calculated from the model for the fries and the small fingerlings. Dietary protein requirements for fry and fingerlings were calculated and compared to other estimation using different model techniques

The QUALOG User’s Manual (Preliminary Version)

In qualitative research, data analysis is the stage of organizing, interpreting, synthesizing, conceptualizing, and reporting information collected over a period of time and by various means. The researcher organizes the information into “manageable units”, searches for recurring topics and patterns of words or phrases, decides on a focus, and refines the thesis or theme so that it accounts for supporting and negative evidence (Bogdan and Biklen, 1982). The major tasks of data analysis include organizing the data, developing categories around patterns or recurring pieces of information, discovering and testing the strength of relationships among categories, and developing a theme or thesis. Using a logic programming system, we are developing and refining a collection of computer programs to facilitate the mechanical tasks of formatting, coding, and hypothesis testing which are part of the analysis stage. Logic programming is a relatively new method of writing computer programs (Kowalski, 1974) based on earlier work in mechanized theorem-proving (Robinson, 1965). Unlike conventional programs, which specify the sequence of steps the machine should follow to obtain the desired result, logic programs specify the conditions the result should satisfy, and leave the details to the computer. The notation of logic programs is that of mathematical logic, more specifically a subset of the of the first-order predicate calculus, adapted somewhat for use in the computer. Logic programs are “executed” (one also says “interpreted”) by a theorem-proving program which establishes the existence of a result satisfying the specified conditions, and yields the result itself as a by-product of the proof

Portland Daily Press: December 15,1883

https://digitalmaine.com/pdp_1883/1277/thumbnail.jp

Complexity of knee extensor torque in patients with frailty syndrome : a cross-sectional study

Background: Frailty syndrome is characterized by a marked reduction in physiological reserves and a clinical state of vulnerability to stress. Torque complexity analysis could reveal changes in the musculoskeletal systems that are the result of having the syndrome. Objective: The aim of this study was to evaluate the complexity of submaximal isometric knee extensor torque in frail, pre-frail, and non-frail older adults. A secondary aim was to analyze the torque complexity behavior in different force levels in each group. Methods: A cross-sectional study was conducted. Forty-two older adults were divided into three groups: non-frail (n=15), pre-frail (n=15), and frail (n=12). The data collected included body composition, five times sit-to-stand test, walking speed, and isometric knee extensor torque at 15, 30, and 40% of maximal voluntary contraction. The knee extensor torque variability was evaluated by coefficient of variation, and the torque complexity was evaluated by approximate entropy and sample entropy. Results: The frail group presented a reduction in body mass and peak torque value compared to the non-frail group. Also, the frail group showed worse physical performance (on the five times sit-to-stand test and walking speed) compared to the pre-frail and non-frail groups. In addition, the frail older adults showed reduced torque complexity compared to the non-frail group. Finally, the association between torque complexity and force levels remained similar in all groups. Conclusion: Torque complexity is reduced in the presence of frailty syndrome