Global demand for plastic materials has severely harm the environment and marine sea life. Therefore, bioplastics have emerged as an environmentally friendly alternative due to sustainability, minimal carbon footprint, less toxicity and high degradability. This review highlights the sustainable and environmentally friendly approach towards bioplastic production by utilizing microalgae as a feed source in several ways. First, the microalgae biomass obtained through the biorefinery approach can be processed into PHA under certain nutrient limitations. Additionally, microalgae biomass can act as potential filler and reinforcement towards the enhancement of bioplastic either blending with conventional bioplastic or synthetic polymer. The downstream processing of microalgae via suitable extraction and pre-treatment of bioactive compounds such as lipids and cellulose are found to be promising for the production of bioplastics. Moving on, the intermediate processing of bioplastic via lactic acid synthesized from microalgae has favoured the microwave-assisted synthesis of polylactic acid due to cost efficiency, minimum solvent usage, low energy consumption, and fast rate of reaction. Moreover, the reliability and effectiveness of microalgae-based bioplastics are further evaluated in terms of techno-economic analysis and degradation mechanism. Future improvement and recommendations are listed towards proper genetic modification of algae strains, large-scale biofilm technology, low-cost cultivation medium, and novel avocado seed-microalgae bioplastic blend.
Biochar is a high-carbon-content organic compound that has potential applications in the field of energy storage and conversion. It can be produced from a variety of biomass feedstocks such as plant-based, animal-based, and municipal waste at different pyrolysis conditions. However, it is difficult to produce biochar on a large scale if the relationship between the type of biomass, operating conditions, and biochar properties is not understood well. Hence, the use of machine learning-based data analysis is necessary to find the relationship between biochar production parameters and feedstock properties with biochar energy properties. In this work, a rough set-based machine learning (RSML) approach has been applied to generate decision rules and classify biochar properties. The conditional attributes were biomass properties (volatile matter, fixed carbon, ash content, carbon, hydrogen, nitrogen, and oxygen) and pyrolysis conditions (operating temperature, heating rate residence time), while the decision attributes considered were yield, carbon content, and higher heating values. The rules generated were tested against a set of validation data and evaluated for their scientific coherency. Based on the decision rules generated, biomass with ash content of 11-14 wt%, volatile matter of 60-62 wt% and carbon content of 42-45.3 wt% can generate biochar with promising yield, carbon content and higher heating value via a pyrolysis process at an operating temperature of 425°C-475°C. This work provided the optimal biomass feedstock properties and pyrolysis conditions for biochar production with high mass and energy yield.
BACKGROUND: Patients' expectations can influence antibiotic prescription by primary healthcare physicians. We assessed knowledge, attitude and practices towards antibiotic use for upper respiratory tract infections (URTIs), and whether knowledge is associated with increased expectations for antibiotics among patients visiting primary healthcare services in Singapore.
METHODS: Data was collected through a cross-sectional interviewer-assisted survey of patients aged ≥21 years waiting to see primary healthcare practitioners for one or more symptoms suggestive of URTI (cough, sore throat, runny nose or blocked nose) for 7 days or less, covering the demographics, presenting symptoms, knowledge, attitudes, beliefs and practices of URTI and associated antibiotic use. Univariate and multivariate logistic regression was used to assess independent factors associated with patients' expectations for antibiotics.
RESULTS: Nine hundred fourteen out of 987 eligible patients consulting 35 doctors were recruited from 24 private sector primary care clinics in Singapore. A third (307/907) expected antibiotics, of which a substantial proportion would ask the doctor for antibiotics (121/304, 40 %) and/or see another doctor (31/304, 10 %) if antibiotics were not prescribed. The majority agreed "antibiotics are effective against viruses" (715/914, 78 %) and that "antibiotics cure URTI faster" (594/912, 65 %). Inappropriate antibiotic practices include "keeping antibiotics stock at home" (125/913, 12 %), "taking leftover antibiotics" (114/913, 14 %) and giving antibiotics to family members (62/913, 7 %). On multivariate regression, the following factors were independently associated with wanting antibiotics (odds ratio; 95 % confidence interval): Malay ethnicity (1.67; 1.00-2.79), living in private housing (1.69; 1.13-2.51), presence of sore throat (1.50; 1.07-2.10) or fever (1.46; 1.01-2.12), perception that illness is serious (1.70; 1.27-2.27), belief that antibiotics cure URTI faster (5.35; 3.76-7.62) and not knowing URTI resolves on its own (2.18; 1.08-2.06), while post-secondary education (0.67; 0.48-0.94) was inversely associated. Those with lower educational levels were significantly more likely to have multiple misconceptions about antibiotics.
CONCLUSION: Majority of patients seeking primary health care in Singapore are misinformed about the role of antibiotics in URTI. Agreeing with the statement that antibiotics cure URTI faster was most strongly associated with wanting antibiotics. Those with higher educational levels were less likely to want antibiotics, while those with lower educational levels more likely to have incorrect knowledge.