OBJECTIVE: The present study intends to monitor variations in deaths and identify the growth phases such as pre-growth, growth, and post-growth phases in Pakistan due to the COVID-19 pandemic.
METHODS: New approaches are needed that display the death patterns and signal an alarming situation so that corrective actions can be taken before the condition worsens. To meet this purpose, secondary data on daily reported deaths due to the COVID-19 pandemic have been considered, and the $c$ and exponentially weighted moving average (EWMA) control charts are used To meet this purpose, secondary data on daily reported deaths in Pakistan due to the COVID-19 pandemic have been considered. The $ c$ and exponentially weighted moving average (EWMA) control charts have been used for monitoring variations.
RESULTS: The chart shows that Pakistan switches from the pre-growth to the growth phase on 31 March 2020. The EWMA chart demonstrates that Pakistan remains in the growth phase from 31 March 2020 to 17 August 2020, with some indications signaling a decrease in deaths. It is found that Pakistan moved to a post-growth phase for a brief period from 27 July 2020 to 28 July 2020. Pakistan switches to re-growth phase with an alarm on 31/7/2020, right after the short-term post-growth phase. The number of deaths starts decreasing in August in that Pakistan may approach the post-growth phase shortly.
CONCLUSION: This amalgamation of control charts illustrates a systematic implementation of the charts for government leaders and forefront medical teams to facilitate the rapid detection of daily reported deaths due to COVID-19. Besides government and public health officials, it is also the public's responsibility to follow the enforced standard operating procedures as a temporary remedy of this pandemic in ensuring public safety while awaiting a suitable vaccine to be discovered.
Aim: To identify levels of self-efficacy and foot care behaviour and their relationship with demographic characteristics in elderly patients with diabetes.
Methods: A cross-sectional study was conducted in two general hospitals in Malaysia from May to June 2015. Diabetes patients aged 60 years with specific inclusion criteria were invited to participate in this study. The respondents were interviewed using a set of validated questionnaires. Data were analysed with descriptive and inferential statistics (multiple linear regression) using Statistical Package for the Social Sciences version 20.0.
Results: Levels of foot self-efficacy (mean+31.39; standard deviation=7.76) and foot care behaviour (mean=25.37; SD=5.88) were high. There was a positive significant relationship between foot self-efficacy (β = 0.41, p < 0.001) and gender (β = 0.30, p < 0.001) with foot care behaviour.
Conclusion: Self-efficacy can be incorporated in diabetes education to improve foot care behaviour. High-risk patients should be taught proper foot inspection and protection as well as the merits of skin care to prevent the occurrence of diabetic foot problems.
METHOD: The repeat identification method was introduced for misassembly by prior identification of repetitive sequences, creating a repeat knowledge base to reduce ambiguity during the assembly process, thus enhancing the accuracy of the assembled genome. Also, hybridization between assembly approaches resulted in a lower misassembly degree with the aid of the reference genome. The assembly performance is optimized through data structure indexing and parallelization. This article's primary aim and contribution are to support the researchers through an extensive review to ease other researchers' search for genome assembly studies. The study also, highlighted the most recent developments and limitations in genome assembly accuracy and performance optimization.
RESULTS: Our findings show the limitations of the repeat identification methods available, which only allow to detect of specific lengths of the repeat, and may not perform well when various types of repeats are present in a genome. We also found that most of the hybrid assembly approaches, either starting with de novo or reference-guided, have some limitations in handling repetitive sequences as it is more computationally costly and time intensive. Although the hybrid approach was found to outperform individual assembly approaches, optimizing its performance remains a challenge. Also, the usage of parallelization in overlapping and reads alignment for genome assembly is yet to be fully implemented in the hybrid assembly approach.
CONCLUSION: We suggest combining multiple repeat identification methods to enhance the accuracy of identifying the repeats as an initial step to the hybrid assembly approach and combining genome indexing with parallelization for better optimization of its performance.