Caregivers’ Knowledge on Routine Growth Monitoring of Children Aged 9 Months in Nyamira County, Kenya

DOI: 10.7176/JHMN/72-05 Publication date:March 31st 2020 1. Introduction Growth monitoring is one of the services offered in Maternal Neonatal and Child Health (MNCH) Clinics in health facilities encompassing routine check-ups by health workers to examine whether a child is growing as expected. Other services provided in these clinics are not limited to; vitamin A supplementation, immunization, health education and counselling, minor ailment treatment, screening for nutritional and medical conditions for management and defaulter tracing and follow-ups (Debuo et al. 2017). Measuring the weight and length of children monthly reflects their growth pattern which is compared against WHO’s growth standards to ascertain whether a child is growing consistently, showing a growth concern or trending towards a growth problem that need to be addressed. A study conducted in Southern Ethiopia found out that 53 % of the caregivers had poor knowledge on growth monitoring (Daniel et al. 2017). Majority of them said they did not know what a growth chart entailed nor did they know how to interpret growth curves (Daniel et al. 2017). A study conducted in Ghana revealed that more than 40% of the caregivers lacked good knowledge on routine growth monitoring. This study found out that more than 30% of the caregivers did not understand the meaning of routine growth monitoring and only 18.7% of them were able to interpret the normal, static, upward and decline growth curves (Debuo et al. 2017). A study in Zambia established that majority (92%) of the caregivers of children aged between 0-59 months had knowledge on the importance of growth monitoring (Banda, 2012). Caregivers of children aged between 12-23 months in Zambia and Ethiopia were reported to have poor knowledge on feeding practices (Bilal et al. 2014, Banda, 2012). Daniel et al. (2014), Elana et al. (2009) and Roberfroid et al. (2005) found out that more than half of the caregivers were unable to understand and interpret the growth charts. Low comprehension on growth charts implies that healthcare providers do not educate caregivers using the growth chart (Gyampoh, 2012)

The Next Generation of Mars-GRAM and Its Role in the Autonomous Aerobraking Development Plan

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission applications. Mars-GRAM 2010 is currently being used to develop the onboard atmospheric density estimator that is part of the Autonomous Aerobraking Development Plan. In previous versions, Mars-GRAM was less than realistic when used for sensitivity studies for Thermal Emission Spectrometer (TES) MapYear=0 and large optical depth values, such as tau=3. A comparison analysis has been completed between Mars-GRAM, TES and data from the Planetary Data System (PDS) resulting in updated coefficients for the functions relating density, latitude, and longitude of the sun. The adjustment factors are expressed as a function of height (z), Latitude (Lat) and areocentric solar longitude (Ls). The latest release of Mars-GRAM 2010 includes these adjustment factors that alter the in-put data from MGCM and MTGCM for the Mapping Year 0 (user-controlled dust) case. The greatest adjustment occurs at large optical depths such as tau greater than 1. The addition of the adjustment factors has led to better correspondence to TES Limb data from 0-60 km as well as better agreement with MGS, ODY and MRO data at approximately 90-135 km. Improved simulations utilizing Mars-GRAM 2010 are vital to developing the onboard atmospheric density estimator for the Autonomous Aerobraking Development Plan. Mars-GRAM 2010 was not the only planetary GRAM utilized during phase 1 of this plan; Titan-GRAM and Venus-GRAM were used to generate density data sets for Aerobraking Design Reference Missions. These data sets included altitude profiles (both vertical and along a trajectory), GRAM perturbations (tides, gravity waves, etc.) and provided density and scale height values for analysis by other Autonomous Aero-braking team members

Mars-GRAM 2010: Improving the Precision of Mars-GRAM

It has been discovered during the Mars Science Laboratory (MSL) site selection process that the Mars Global Reference Atmospheric Model (Mars-GRAM) when used for sensitivity studies for Thermal Emission Spectrometer (TES) MapYear=0 and large optical depth values, such as tau=3, is less than realistic. Mars-GRAM's perturbation modeling capability is commonly used, in a Monte-Carlo mode, to perform high fidelity engineering end-to-end simulations for entry, descent, and landing (EDL). Mars-GRAM 2005 has been validated against Radio Science data, and both nadir and limb data from TES. Traditional Mars-GRAM options for representing the mean atmosphere along entry corridors include: (1) TES mapping year 0, with user-controlled dust optical depth and Mars-GRAM data interpolated from NASA Ames Mars General Circulation Model (MGCM) results driven by selected values of globally-uniform dust optical depth, or (2) TES mapping years 1 and 2, with Mars-GRAM data coming from MGCM results driven by observed TES dust optical depth. From the surface to 80 km altitude, Mars-GRAM is based on NASA Ames MGCM. Above 80 km, Mars-GRAM is based on the University of Michigan Mars Thermospheric General Circulation Model (MTGCM). MGCM results that were used for Mars-GRAM with MapYear=0 were from a MGCM run with a fixed value of tau=3 for the entire year at all locations. This choice of data has led to discrepancies that have become apparent during recent sensitivity studies for MapYear=0 and large optical depths. Unrealistic energy absorption by time-invariant atmospheric dust leads to an unrealistic thermal energy balance on the polar caps. The outcome is an inaccurate cycle of condensation/sublimation of the polar caps and, as a consequence, an inaccurate cycle of total atmospheric mass and global-average surface pressure. Under an assumption of unchanged temperature profile and hydrostatic equilibrium, a given percentage change in surface pressure would produce a corresponding percentage change in density at all altitudes. Consequently, the final result of a change in surface pressure is an imprecise atmospheric density at all altitudes

Benefit-cost methodology study with example application of the use of wind generators

An example application for cost-benefit methodology is presented for the use of wind generators. The approach adopted for the example application consisted of the following activities: (1) surveying of the available wind data and wind power system information, (2) developing models which quantitatively described wind distributions, wind power systems, and cost-benefit differences between conventional systems and wind power systems, and (3) applying the cost-benefit methodology to compare a conventional electrical energy generation system with systems which included wind power generators. Wind speed distribution data were obtained from sites throughout the contiguous United States and were used to compute plant factor contours shown on an annual and seasonal basis. Plant factor values (ratio of average output power to rated power) are found to be as high as 0.6 (on an annual average basis) in portions of the central U. S. and in sections of the New England coastal area. Two types of wind power systems were selected for the application of the cost-benefit methodology. A cost-benefit model was designed and implemented on a computer to establish a practical tool for studying the relative costs and benefits of wind power systems under a variety of conditions and to efficiently and effectively perform associated sensitivity analyses

Обучение с веб-поддержкой по программе повышения квалификации "Преподаваниемодулей профессиональной подготовки на английском языке"

Представлена концепция обучения с веб-поддержкой по программе повышения квалификации для преподавателей в области профессиональной подготовки студентов технического вуза на английском языке. Раскрыто содержание четырех модульных блоков программы. Приведены результаты анкетирования слушателей о степени удовлетворенности результатами обучении. Намечены задачи по дальнейшему совершенствованию программы