Motivation and Confidence: More than Cheerleading

What empowers self-confidence in athletic performance? Most of us know the psychology and language of motivation in positive reinforcement: way to go ; good work ; I believe in you are some examples. It\u27s a sort of cheerleading. But confidence goes much deeper into the realm of how the athlete understands the existential self in the world. Is he more than a point getter? Is she more than all-conference or a record holder ? Literature (novels, poetry, essays) often demonstrates that the depth of confidence is found in demonstrative love. If one feels worthy of love, and the love is demonstrated, fear of failure is diminished, and the I can do this dominates. Hear concrete examples of how this can work even in difficult challenges

Visualization and Analysis of Sensory Data

Recently, California has suffered a severe drought, making water a scarce resource to its population. Many viticulturists are based in this area who rely on heavy irrigation to produce a better grape and a better wine. Not just in California, but throughout the nation, irrigation must be applied intelligently for efficient use of water and funding. By taking measurements of physical characteristics of a vineyard over time, one may be able to visualize trends in the data which lend itself to describing preferred growing methods. Wireless sensors can be used to take measurements including moisture, temperature, sunlight, and more. Sensors have been installed at multiple locations about a vineyard. A framework has been put in place to capture, adjust, and calibrate the data as well as store it for future retrieval. The data are visualized over time to see the effects of techniques in the long term. These are helpful for suggesting irrigation strategy that will lead to the best yield. Sensors are cheap and effective, but are prone to malfunction and transmission errors. When these problems occur, the faulty time-series data can be cleaned by correlating with similar time-series data in the same time span. The data system will be a necessity for competitive viticulturists, reducing cost of irrigation and improving quality of wine. In the future, the tool could be applied to other crops. Also, if any new important values must be derived or measured, the system can be extended to include them

Estimation of the national disease burden of influenza-associated severe acute respiratory illness in Kenya and Guatemala : a novel methodology

Background: Knowing the national disease burden of severe influenza in low-income countries can inform policy decisions around influenza treatment and prevention. We present a novel methodology using locally generated data for estimating this burden. Methods and Findings: This method begins with calculating the hospitalized severe acute respiratory illness (SARI) incidence for children <5 years old and persons ≥5 years old from population-based surveillance in one province. This base rate of SARI is then adjusted for each province based on the prevalence of risk factors and healthcare-seeking behavior. The percentage of SARI with influenza virus detected is determined from provincial-level sentinel surveillance and applied to the adjusted provincial rates of hospitalized SARI. Healthcare-seeking data from healthcare utilization surveys is used to estimate non-hospitalized influenza-associated SARI. Rates of hospitalized and non-hospitalized influenza-associated SARI are applied to census data to calculate the national number of cases. The method was field-tested in Kenya, and validated in Guatemala, using data from August 2009–July 2011. In Kenya (2009 population 38.6 million persons), the annual number of hospitalized influenza-associated SARI cases ranged from 17,129–27,659 for children <5 years old (2.9–4.7 per 1,000 persons) and 6,882–7,836 for persons ≥5 years old (0.21–0.24 per 1,000 persons), depending on year and base rate used. In Guatemala (2011 population 14.7 million persons), the annual number of hospitalized cases of influenza-associated pneumonia ranged from 1,065–2,259 (0.5–1.0 per 1,000 persons) among children <5 years old and 779–2,252 cases (0.1–0.2 per 1,000 persons) for persons ≥5 years old, depending on year and base rate used. In both countries, the number of non-hospitalized influenza-associated cases was several-fold higher than the hospitalized cases. Conclusions: Influenza virus was associated with a substantial amount of severe disease in Kenya and Guatemala. This method can be performed in most low and lower-middle income countries

Effect of salinity on the biosynthesis of n-3 long-chain polyunsaturated fatty acids in silverside Chirostoma estor

The genus Chirostoma (silversides) belongs to the family Atherinopsidae, which contains around 150 species, most of which are marine. However, Mexican silverside (Chirostoma estor) is one of the few representatives of freshwater atherinopsids and is only found in some lakes of the Mexican Central Plateau. However, studies have shown that C. estor has improved survival, growth and development when cultured in water conditions with increased salinity. In addition, C. estor displays an unusual fatty acid composition for a freshwater fish with high docosahexaenoic acid (DHA) : eicosapentaenoic acid (EPA) ratios. Freshwater and marine fish species display very different essential fatty acid metabolism and requirements and so the present study investigated long-chain polyunsaturated fatty acid (LC-PUFA) biosynthesis to determine the capacity of C. estor for endogenous production of EPA and DHA, and the effect that salinity has on these pathways. Briefly, C. estor were maintained at three salinities (0, 5 and 15 ppt) and the metabolism of 14C-labelled 18:3n-3 determined in isolated hepatocyte and enterocyte cells. The results showed that C. estor has the capacity for endogenous biosynthesis of LC-PUFA from 18-carbon fatty acid precursors, but that the pathway was essentially only active in saline conditions with virtually no activity in cells isolated from fish grown in freshwater. The activity of the LCPUFA biosynthesis pathway was also higher in cells isolated from fish at 15 ppt compared to fish at 5 ppt, The pathway was around 5-fold higher in hepatocytes compared to enterocytes, although the majority of 18:3n-3 was converted to 18:4n-3 and 20:4n-3 in hepatocytes whereas the proportions of 18:3n-3 converted to EPA and DHA were higher in enterocytes. The data were consistent with the hypothesis that conversion of EPA to DHA could contribute, at least in part, to the generally high DHA:EPA ratios observed in the tissue lipids of C. estor

Etiology of Severe Non-malaria Febrile Illness in Northern Tanzania: A Prospective Cohort Study.

The syndrome of fever is a commonly presenting complaint among persons seeking healthcare in low-resource areas, yet the public health community has not approached fever in a comprehensive manner. In many areas, malaria is over-diagnosed, and patients without malaria have poor outcomes. We prospectively studied a cohort of 870 pediatric and adult febrile admissions to two hospitals in northern Tanzania over the period of one year using conventional standard diagnostic tests to establish fever etiology. Malaria was the clinical diagnosis for 528 (60.7%), but was the actual cause of fever in only 14 (1.6%). By contrast, bacterial, mycobacterial, and fungal bloodstream infections accounted for 85 (9.8%), 14 (1.6%), and 25 (2.9%) febrile admissions, respectively. Acute bacterial zoonoses were identified among 118 (26.2%) of febrile admissions; 16 (13.6%) had brucellosis, 40 (33.9%) leptospirosis, 24 (20.3%) had Q fever, 36 (30.5%) had spotted fever group rickettsioses, and 2 (1.8%) had typhus group rickettsioses. In addition, 55 (7.9%) participants had a confirmed acute arbovirus infection, all due to chikungunya. No patient had a bacterial zoonosis or an arbovirus infection included in the admission differential diagnosis. Malaria was uncommon and over-diagnosed, whereas invasive infections were underappreciated. Bacterial zoonoses and arbovirus infections were highly prevalent yet overlooked. An integrated approach to the syndrome of fever in resource-limited areas is needed to improve patient outcomes and to rationally target disease control efforts

The effect of Gonioscopy on keratometry and corneal surface topography

BACKGROUND: Biometric procedures such as keratometry performed shortly after contact procedures like gonioscopy and applanation tonometry could affect the validity of the measurement. This study was conducted to understand the short-term effect of gonioscopy on corneal curvature measurements and surface topography based Simulated Keratometry and whether this would alter the power of an intraocular lens implant calculated using post-gonioscopy measurements. We further compared the effect of the 2-mirror (Goldmann) and the 4-mirror (Sussman) Gonioscopes. METHODS: A prospective clinic-based self-controlled comparative study. 198 eyes of 99 patients, above 50 years of age, were studied. Exclusion criteria included documented dry eye, history of ocular surgery or trauma, diabetes mellitus and connective tissue disorders. Auto-Keratometry and corneal topography measurements were obtained at baseline and at three follow-up times – within the first 5 minutes, between the 10(th)-15(th )minute and between the 20(th)-25(th )minute after intervention. One eye was randomized for intervention with the 2-mirror gonioscope and the other underwent the 4-mirror after baseline measurements. t-tests were used to examine differences between interventions and between the measurement methods. The sample size was calculated using an estimate of clinically significant lens implant power changes based on the SRK-II formula. RESULTS: Clinically and statistically significant steepening was observed in the first 5 minutes and in the 10–15 minute interval using topography-based Sim K. These changes were not present with the Auto-Keratometer measurements. Although changes from baseline were noted between 20 and 25 minutes topographically, these were not clinically or statistically significant. There was no significant difference between the two types of gonioscopes. There was greater variability in the changes from baseline using the topography-based Sim K readings. CONCLUSION: Reversible steepening of the central corneal surface is produced by the act of gonioscopy as measured by Sim K, whereas no significant differences were present with Auto-K measurements. The type of Gonioscope used does not appear to influence these results. If topographically derived Sim K is used to calculate the power of the intraocular lens implant, we recommend waiting a minimum of 20 minutes before measuring the corneal curvature after gonioscopy with either Goldmann or Sussman contact lenses

Prediction error and accuracy of intraocular lens power calculation in pediatric patient comparing SRK II and Pediatric IOL Calculator

<p>Abstract</p> <p>Background</p> <p>Despite growing number of intraocular lens power calculation formulas, there is no evidence that these formulas have good predictive accuracy in pediatric, whose eyes are still undergoing rapid growth and refractive changes. This study is intended to compare the prediction error and the accuracy of predictability of intraocular lens power calculation in pediatric patients at 3 month post cataract surgery with primary implantation of an intraocular lens using SRK II versus Pediatric IOL Calculator for pediatric intraocular lens calculation. Pediatric IOL Calculator is a modification of SRK II using Holladay algorithm. This program attempts to predict the refraction of a pseudophakic child as he grows, using a Holladay algorithm model. This model is based on refraction measurements of pediatric aphakic eyes. Pediatric IOL Calculator uses computer software for intraocular lens calculation.</p> <p>Methods</p> <p>This comparative study consists of 31 eyes (24 patients) that successfully underwent cataract surgery and intraocular lens implantations. All patients were 12 years old and below (range: 4 months to 12 years old). Patients were randomized into 2 groups; SRK II group and Pediatric IOL Calculator group using envelope technique sampling procedure. Intraocular lens power calculations were made using either SRK II or Pediatric IOL Calculator for pediatric intraocular lens calculation based on the printed technique selected for every patient. Thirteen patients were assigned for SRK II group and another 11 patients for Pediatric IOL Calculator group. For SRK II group, the predicted postoperative refraction is based on the patient's axial length and is aimed for emmetropic at the time of surgery. However for Pediatric IOL Calculator group, the predicted postoperative refraction is aimed for emmetropic spherical equivalent at age 2 years old. The postoperative refractive outcome was taken as the spherical equivalent of the refraction at 3 month postoperative follow-up. The data were analysed to compare the mean prediction error and the accuracy of predictability of intraocular lens power calculation between SRK II and Pediatric IOL Calculator.</p> <p>Results</p> <p>There were 16 eyes in SRK II group and 15 eyes in Pediatric IOL Calculator group. The mean prediction error in the SRK II group was 1.03 D (SD, 0.69 D) while in Pediatric IOL Calculator group was 1.14 D (SD, 1.19 D). The SRK II group showed lower prediction error of 0.11 D compared to Pediatric IOL Calculator group, but this was not statistically significant (p = 0.74). There were 3 eyes (18.75%) in SRK II group achieved acccurate predictability where the refraction postoperatively was within ± 0.5 D from predicted refraction compared to 7 eyes (46.67%) in the Pediatric IOL Calculator group. However the difference of the accuracy of predictability of postoperative refraction between the two formulas was also not statistically significant (p = 0.097).</p> <p>Conclusions</p> <p>The prediction error and the accuracy of predictability of postoperative refraction in pediatric cataract surgery are comparable between SRK II and Pediatric IOL Calculator. The existence of the Pediatric IOL Calculator provides an alternative to the ophthalmologist for intraocular lens calculation in pediatric patients. Relatively small sample size and unequal distribution of patients especially the younger children (less than 3 years) with a short time follow-up (3 months), considering spherical equivalent only.</p