Knowledge, attitude, and practice towards COVID-19; A community survey in North-Borneo (Sabah), Malaysia

Aims: The COVID-19 pandemic has severely impacted the global economy as well as the healthcare delivery systems. Without effective treatment and vaccines in the earlier phase of the pandemic, the public needs to engage in precautionary behaviors and disease surveillance and response at the policy level. This study aimed to describe the knowledge, attitude, and practice toward COVID-19 among the residents in Sabah, Malaysia. Instruments & Methods: An online cross-sectional study was conducted using convenience sampling from March to April 2020. The chi-square test and multiple logistic regression were used to examine the association factors of knowledge, attitude, and practice towards the COVID-19 pandemic. Findings: A total of 536 participants completed the questionnaire. The mean knowledge score was 10.1±1.2, and 84.2% had a correct rate of knowledge. The attitude towards the final success in controlling COVID-19 was significantly different in age groups, marital status, and occupation types (p<0.05). Those with higher knowledge scores were more likely to agree with the confidence of the final success in controlling COVID-19. 94.4% were confident that Malaysia will win the battle against the COVID-19 pandemic. People in government sectors were 6.19 times more likely to wear masks than unemployed respondents. Conclusion: The level of knowledge of the residents in Sabah, Malaysia, about COVID-19 is quite satisfactory. Meanwhile, attitudes and practices towards COVID-19 differ according to the socio-demography of the population in Sabah.

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Encryption function on artificial neural network

Six algorithms that design secrecy keys are used for digital image encryption. The privacy keys generated by stream cipher generators were tested for their randomness applying five tests of randomness. The images generated by applying each algorithm were tested for their regularity and residual intelligibility. The histograms for images ciphered by stream cipher schemes all have approximately flat histogram less information as compared to one-dimensional ciphering algorithms and threshold generator-based image ciphering scheme. Furthermore, the stream cipher schemes were effectively applied to the colored images of 256-color levels of true-color images (24 bit). In this paper, we try to decrypt automatically using artificial neural network by decryption through multilayer perceptron and radial basis function; networks were tested using the interface by calculating the error rates of decrypted images

Metal concentration at surface water using multivariate analysis and human health risk assessment

This study defined the concentration of metals in Kerteh and Paka River water and their potential health  risk  towards human. 54  water  samples  were  collected  and  analyzed  using  ICP-OES. Results revealed that most of the stations in Kerteh River gave the higher concentration of Cd, Cu, Zn, Co, Ni, As, Cr and Pb compared to Paka River. However As, Cr and Pb have exceeded the permissible limit of Malaysia standard for all stations in both rivers. Cd, Cu, Zn, Co and Ni were below than Malaysian  standard permissible levels  during  the sampling period.  The  principal component  analysis (PCA) revealed  that both  geogenic  and  anthropogenic  sources  were responsible to possible metals contamination in both rivers. Moreover, risk assessments for all metals were within the safe limits, except for As in the Kerteh River for both adult and child as well as to Paka River for both genders.Keywords: metal; ICP-OES; principal component analysis; risk assessmen

The effect of temperature factor on the detection of nitrate based on planar electromagnetic sensor and independent component analysis

In this paper, the output parameters of the planar electromagnetic sensor have observed with different kind of water samples at different concentrations. The output parameters have been derived and tested to be incorporated with independent component analysis (ICA) and as inputs for an analysis model. The analysis model targeted to estimate the amount of nitrate contamination in water samples with the assistance of ICA based on FastICAfixed point algorithm under the contrast functions of pow3 and tanh. Nitrates sample in the form of ammonium nitrates (NH 4NO 3), each of different concentration between 5 mg and 20 mg dissolved in 1 litre of deionized water (mili-q) was used as one of the main references. A model based on independent component analysis was developed to estimate nitrate contamination in natural water source. The model was tested with two sets of mixed NH 4NO 3 and (NH 4) 2HPO 4 water samples based on Manawatu river water. From the results, the model can acceptably detect the presence of nitrate in Manawatu River and capable of distinguishing the concentration level in the presence of other type of contamination. Furthermore, the effect of temperature change was also observed in this study. The system and approach presented in this paper has the potential to be used as a useful tool for water sources monitoring

Sensing technologies for intelligent environments : a review

Sensors are fundamental components for making any environment intelligent. Depending on the applications, different sensors are required to implement specific objectives. This chapter will review different applications and consequently the requirements for different sensors and sensing technologies used in intelligent environment with a special emphasis on smart homes.31 page(s