986 resultados para Correction factor


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The far-field intensity distribution of hollow Gaussian beams was investigated based on scalar diffraction theory. An analytical expression of the M-2 factor of the beams was derived on the basis of the second-order moments. Moreover, numerical examples to illustrate our analytical results are given. (c) 2005 Optical Society of America.

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We investigated M-2 factor and far-field distribution of beams generated by Gaussian mirror resonator. And we found usable analytical expressions of the M2 factor and the far-field distribution intensity with respect to variation of diffraction parameters. Particular attention was paid to the parameters such as mirror spot size and reflectance of the Gaussian mirror. (c) 2006 Elsevier GrnbH. All rights reserved.

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We evaluated measures of bioelectrical impedance analysis (BIA) and Fulton’s condition factor (K) as potential nonlethal indices for detecting short-term changes in nutritional condition of postsmolt Atlantic salmon (Salmo salar). Fish reared in the laboratory for 27 days were fed, fasted, or fasted and then refed. Growth rates and proximate body composition (protein, fat, water) were measured in each fish to evaluate nutritional status and condition. Growth rates of fish responded rapidly to the absence or reintroduction of food, whereas body composition (% wet weight) remained relatively stable owing to isometric growth in fed fish and little loss of body constituents in fasted fish, resulting in nonsignificant differences in body composition among feeding treatments. The utility of BIA and Fulton’s K as condition indices requires differences in body composition. In our study, BIA measures were not significantly different among the three feeding treatments, and only on the final day of sampling was K of fasted vs. fed fish significantly different. BIA measures were correlated with body composition content; however, wet weight was a better predictor of body composition on both a content and concentration (% wet weight) basis. Because fish were growing isometrically, neither BIA nor K was well correlated with growth rate. For immature fish, where growth rate, rather than energy reserves, is a more important indicator of fish condition, a nonlethal index that reflects shortterm changes in growth rate or the potential for growth would be more suitable as a condition index than either BIA measures or Fulton�

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A compilation of 48 estimates of Caribbean and Pacific coral reef fish catches, ranging from 0.1 to 23.7 t km super(-2) year super(-1), obtained from coral reef areas ranging from 0.1 to nearly 4-10 super(5) km super(2), are used to show that observed catches, and hence potential yield estimates, depend strongly on the reference area. The implications for coral reef fisheries assessments are discussed.

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A study was conducted in 54 wetlands of 13 districts of Assam, India to evaluate the causes of fish depletion. Twenty-two variables were considered for the study. Seven factors were extracted through factor analysis (Principal Component Analysis) based on Eigen Value Criteria of more than one. These seven factors together accounted for 69.3% of the total variance. Based on the characteristics of the variables, all the factors were given descriptive names. These variables can be used to measure the extent of management deficiency of the causes of fish depletion in the wetlands. The factors are management deficiency, organic load interference, catchment condition, extrinsic influence, fishermen’s ignorance, external environment and aquaculture program. Management deficiency accounted for a substantial portion of the total variance.

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Introduction The identification of the genetic risk factors that could discriminate non-thrombotic from thrombotic antiphospholipid antibodies (aPLA) carriers will improve prognosis of these patients. Several human studies have shown the presence of aPLAs associated with atherosclerotic plaque, which is a known risk factor for thrombosis. Hence, in order to determine the implication of atherosclerosis in the risk of developing thrombosis in aPLA positive patients, we performed a genetic association study with 3 candidate genes, APOH, LDLR and PCSK9. Material & Methods For genetic association study we analyzed 190 aPLA carriers -100 with non-thrombotic events and 90 with thrombotic events-and 557 healthy controls. Analyses were performed by chi(2) test and were corrected by false discovery rate. To evaluate the functional implication of the newly established susceptibility loci, we performed expression analyses in 86 aPLA carrier individuals (43 with thrombotic manifestations and 43 without it) and in 45 healthy controls. Results Our results revealed significant associations after correction in SNPs located in LDLR gene with aPLA carriers and thrombotic aPLA carriers, when compared with healthy controls. The most significant association in LDLR gene was found between SNP rs129083082 and aPLA carriers in recessive model (adjusted P-value = 2.55 x 10(-3); OR = 2.18; 95% CI = 1.49-3.21). Furthermore, our work detected significant allelic association after correction between thrombotic aPLA carriers and healthy controls in SNP rs562556 located in PCSK9 gene (adjusted P-value = 1.03 x 10(-2); OR = 1.60; 95% CI = 1.24-2.06). Expression level study showed significantly decreased expression level of LDLR gene in aPLA carriers (P-value < 0.0001; 95% CI 0.16-2.10; SE 0.38-1.27) in comparison to the control group. Discussion Our work has identified LDLR gene as a new susceptibility gene associated with the development of thrombosis in aPLA carriers, describing for the first time the deregulation of LDLR expression in individuals with aPLAs. Besides, thrombotic aPLA carriers also showed significant association with PCSK9 gene, a regulator of LDLR plasma levels. These results highlight the importance of atherosclerotic processes in the development of thrombosis in patients with aPLA.

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Body length measurement is an important part of growth, condition, and mortality analyses of larval and juvenile fish. If the measurements are not accurate (i.e., do not reflect real fish length), results of subsequent analyses may be affected considerably (McGurk, 1985; Fey, 1999; Porter et al., 2001). The primary cause of error in fish length measurement is shrinkage related to collection and preservation (Theilacker, 1980; Hay, 1981; Butler, 1992; Fey, 1999). The magnitude of shrinkage depends on many factors, namely the duration and speed of the collection tow, abundance of other planktonic organisms in the sample (Theilacker, 1980; Hay, 1981; Jennings, 1991), the type and strength of the preservative (Hay, 1982), and the species of fish (Jennings, 1991; Fey, 1999). Further, fish size affects shrinkage (Fowler and Smith, 1983; Fey, 1999, 2001), indicating that live length should be modeled as a function of preserved length (Pepin et al., 1998; Fey, 1999).