Objectives: The purpose of this study was to determine the number of physiotherapists who interrupted their services because of the COVID-19 pandemic and to verify the procedures adopted by the physiotherapists who are still working. Methods: It was a Cross sectional study. Study Setting was University of South Asia, Lahore. Data was collected through self-administered questionnaire. Physiotherapists working in Government and Private Hospitals in Lahore were recruited. Data was collected from October 2020 to November 2020. Non-probability Convenient sampling technique was used to recruit participants in study. Sample size of 241 Participants was calculated by using an online calculator (Raosoft,Inc.2004) with 5% margin of error, 95% confidence level and population of 462 physiotherapists working in Lahore in various Government and Private Hospitals Results: Out of 210 participants, males were 154 (73%) while females were 56 (27%). 37 (18%) were working in government hospitals while 173 (82%) were working in private setups. 14 (7%) were holding only undergraduate degree while 196 (93%) were post graduate. 28 (13%) were having up to 4 years of clinical experience working as physiotherapist, 65 (31%) were having up to 8 years of experience while 117 (56%) were having up to 12 years of clinical experience. When asked about Source of information on COVID-19, 16 (8%) chose Official international health organization sites and media, 18 (9%) chose Official government sites and media e.g. Ministry of Health Pakistan, 121 (58%) chose News Media e.g. TVs, radios, Magazines, Newspapers, 52 (25%) chose Social Media e.g. WhatsApp, Facebook, Twitter, Instagram while 2 (1%) chose journals and only 1 participant (.5%) chose others source of information. Conclusion: The distribution of Attitude, Knowledge, and Practice is the same across categories of source of information on COVID-19. Keywords: COVID-19, Coronavirus disease, Knowledge, Attitude, Practice
Leptospermum sp. with dihydroxyacetone in their nectar are a source of high-value medicinal honey production and can provide income from agriculturally marginal lands. The current study was from two newly planted Leptospermum nitens sites, one with duplex soil and the other in deep sandy soil, in the low rainfall areas of the south-west of Western Australia, with the aim of identifying key soil parameters influencing the plantation’s survival and growth. Electromagnetic induction (EMI) at different depths was used to investigate the possible impact of soil variability on the Leptospermum nitens plantations. Two EMI surveys were conducted at each site, at different times of the year, to account for soil moisture variability (relatively dry and wet conditions). A least-square inversion algorithm was used to determine true electrical conductivities at three different soil depths (0–0.5, 0.5–0.8, and 0.8–1.6 m) to produce quasi-3D maps of soil inverted electrical conductivity. Corresponding soil samples from each depth were used for the physico-chemical analysis of soil parameters and to develop laboratory-based electrical resistivity to soil volumetric moisture calibrations with R2 values between 0.95 and 0.99. Shrub survival and growth (canopy diameter) were estimated using unmanned aerial vehicle (UAV) images and machine learning. Comparing EMI soil mapping with UAV imagery results showed significantly greater shrub survival and growth (p < 0.001) in areas with higher ECa ranges of 12–24 mS m−1 at the variable textured site and 6–9 mS m−1 at the uniformly sandy site. Overall, the variable textured site, with an 82% survival rate, had a significantly higher shrub count and larger plants than the uniformly sandy site, with a 75% survival rate. A principal component analysis (PCA) identified inverted EC to be strongly correlated with soil moisture > pH > soil texture. Such soil mapping may be a robust and effective method for risk assessment of new shrub plantations.
<p>Farms in Western Australia (WA) are highly variable in soil texture and water retention capacity; therefore, spatial information of soil moisture status in the field is important for crop management. In practice, farmers often rely on point sensors to determine soil moisture in their fields for crop planning. The limitation of point measurements to account for spatial variability highlights the need to develop methods to assess soil moisture across variable broadacre fields. This information could be used for more effective site-specific crop management practices. In this study, we used a mobile nonintrusive electromagnetic induction (EMI) sensor to map soil apparent electrical conductivity (ECa) and to predict soil moisture levels across the field at three depths (0 &#8211; 0.5, 0.5 &#8211; 0.8 and 0.8 &#8211; 1.6m). The predicted soil moisture was compared with the point measurements of soil moisture sensors and soil samples. The inverted electrical conductivity (EC) from EMI surveys was converted into soil moisture using calibrations between electrical resistivity tomography (ERT) to volumetric moisture, which were developed for the different soil textural classes of the field, with R<sup>2</sup> of 0.97 to 0.99. The soil moisture variability of the field was also compared with the spatial distribution of 2019 barley yield production. No significant difference was found between the EMI estimated soil moisture values and the point moisture measurements, as well as moisture extracted from soil samples for 0 &#8211; 0.5m and 0.5 &#8211; 0.8 m depths with Pearson R values of 0.62 and 0.73 respectively. Barley yield was not correlated with mapped soil moisture or soil texture, which may be due to relatively high initial moisture levels following two years of fallow rotation. This study successfully demonstrated spatial soil moisture estimation using EMI sensor in a field with horizontally and vertically variable soil texture.</p>
<p>Knowledge of real time spatial distribution of soil moisture has great potential to improve yield and profit in agricultural systems. Rapid and precise quantification of water in crop fields is challenging due to the influence of highly variable soil properties such as texture and porosity. &#160;Recent advances in non-invasive electromagnetic induction (EMI) techniques have created an opportunity to determine soil moisture content with high-resolution and minimal soil intrusion. So far, EMI has mainly been validated for homogenous soils, which are not common in agriculture. This study from a field site in Western Australia converts time series apparent electrical conductivity data recorded with a Dualem 1Hs EM-meter into spatiotemporal domains. A least square inversion algorithm was used to determine electric conductivities for individual soil layers (0-50cm, 50-80 cm and 80-160 cm) for two EMI surveys at a trial site, with different crop rotations and varying moisture conditions. A laboratory experiment under controlled conditions developed electric conductivity vs volumetric water content relations with power law functions for each layer with R<sup>2</sup> values between 0.98 and 0.99. Subsequently, EMI data were converted to volumetric water contents for each layer and predictions were spatially displayed. These EMI soil moisture predictions were compared with neutron moisture meter measurements, with R<sup>2</sup> values between 0.95 and 0.74 for the two surveys. The method is robust and offers a comparatively fast method to estimate the soil moisture status in fields and to subsequently make informed management decisions.&#160;</p>
To estimate correlation of handgrip strength with arm anthropometric variables of dominant side. METHODS: This cross-sectional study was conducted on 241 male cricketers from July 2017 to August 2018 in Lahore using convenient sampling. Arm anthropometric variables and handgrip strength of dominant side were measured by standard anthropometric techniques & formulas. Pearson correlation coefficient & linear regression analysis were applied to find out extent of relationship. RESULTS: Mean age of 241 players is 25.19±3.493 years. Out of 241 players, 74 (30%) players were batsmen, 69 (29%) were bowlers, 14 (6%) were wicket keepers and 84 (35%) were all-rounder players. Mean handgrip strength of study participants was 65.783±3.365 kg. Mean values for various anthropometric variables included triceps skinfold thickness (13.807±0.815 mm), subscapular skinfold thickness (16.552±0.763 mm), mid arm 2 circumference (33.398±1.274 cm), arm muscle area (67.381±5.149 cm), arm 2 muscle girth (29.070±1.116 cm), arm area (88.986±6.643 cm), arm fat area 2 (21.605±1.836 cm), and arm fat index (24.281±1.055). Handgrip showed positive correlation with triceps skinfold (r=0.608, p=<0.001), mid-arm circumference (r=0.738, p=<0.001), upper arm muscle area (r=0.694, p=<0.001), upper arm muscle girth (r=0.695, p=<0.001), total arm area (r=0.740, p=<0.001), upper arm fat area (r=0.728, p=<0.001), subscapular skinfold (r=0.215, p=0.001), and arm fat index (r=0.158, p=0.013). CONCLUSION: All the anthropometric variables had a positive significant correlation with handgrip strength. Handgrip strength is standard indicator to achieve target of excellent performance as well as can be made a valuable criterion of selection for cricket & multiple games involving grip.
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