Displaying publications 1 - 20 of 86 in total

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  1. Zehra S, Faseeha U, Syed HJ, Samad F, Ibrahim AO, Abulfaraj AW, et al.
    Sensors (Basel), 2023 Jun 05;23(11).
    PMID: 37300067 DOI: 10.3390/s23115340
    Network function virtualization (NFV) is a rapidly growing technology that enables the virtualization of traditional network hardware components, offering benefits such as cost reduction, increased flexibility, and efficient resource utilization. Moreover, NFV plays a crucial role in sensor and IoT networks by ensuring optimal resource usage and effective network management. However, adopting NFV in these networks also brings security challenges that must promptly and effectively address. This survey paper focuses on exploring the security challenges associated with NFV. It proposes the utilization of anomaly detection techniques as a means to mitigate the potential risks of cyber attacks. The research evaluates the strengths and weaknesses of various machine learning-based algorithms for detecting network-based anomalies in NFV networks. By providing insights into the most efficient algorithm for timely and effective anomaly detection in NFV networks, this study aims to assist network administrators and security professionals in enhancing the security of NFV deployments, thus safeguarding the integrity and performance of sensors and IoT systems.
    Matched MeSH terms: Problem Solving
  2. Emambocus BAS, Jasser MB, Mustapha A, Amphawan A
    Sensors (Basel), 2021 Nov 13;21(22).
    PMID: 34833621 DOI: 10.3390/s21227542
    Swarm intelligence is a discipline which makes use of a number of agents for solving optimization problems by producing low cost, fast and robust solutions. The dragonfly algorithm (DA), a recently proposed swarm intelligence algorithm, is inspired by the dynamic and static swarming behaviors of dragonflies, and it has been found to have a higher performance in comparison to other swarm intelligence and evolutionary algorithms in numerous applications. There are only a few surveys about the dragonfly algorithm, and we have found that they are limited in certain aspects. Hence, in this paper, we present a more comprehensive survey about DA, its applications in various domains, and its performance as compared to other swarm intelligence algorithms. We also analyze the hybrids of DA, the methods they employ to enhance the original DA, their performance as compared to the original DA, and their limitations. Moreover, we categorize the hybrids of DA according to the type of problem that they have been applied to, their objectives, and the methods that they utilize.
    Matched MeSH terms: Problem Solving
  3. Lee SWH, Saw PS
    Am J Pharm Educ, 2021 Sep;85(8):8464.
    PMID: 34615624 DOI: 10.5688/ajpe8464
    Objective. To conduct an innovative workshop activity using plastic building blocks to create a student-centric environment that encouraged development of creative thinking skills and self-reflection in undergraduate pharmacy students.Methods. Students were randomly allocated into small groups of four and assigned the role of either architect or team builder and tasked with creating a LEGO robot. Students were not allowed to speak during the activity. The architect was tasked with providing instructions to team builders on how to build the robot using nonverbal communication. After completion of the task, each group was asked to reflect on the exercise and share what they learned with the entire class. These discussions were video recorded and thematically analyzed.Results. The metaphorical models that students built served as a basis for discussion, problem-solving, and decision-making. Students described how this activity enabled them to mentally and visually link abstract concepts, such as decision-making and problem-solving, to actual practice. Three themes were identified from the qualitative study: thinking with hands, listening with eyes; linking theory to practice; and learning through reflection.Conclusion. This activity offered a non-confrontational way to support communication and the learning process. The use of an interactive game can be a useful teaching strategy to create an active-learning environment, helping pharmacy students improve their social and cognitive skills, such as decision-making, problem-solving, and communication.
    Matched MeSH terms: Problem Solving
  4. Copriady J, Zulnaidi H, Alimin M, Albeta SW
    Heliyon, 2021 May;7(5):e06995.
    PMID: 34027189 DOI: 10.1016/j.heliyon.2021.e06995
    This study aims to determine the level of collaboration, in-service training and teaching resource proficiency amongst Chemistry teachers by investigating the intermediary role of collaboration for training and teaching resources competency. A total of 184 Chemistry teachers in Riau, Indonesia, have participated in the survey. Using AMOS and SPSS 25.0 software to analyse the research data, we find a high level of collaboration, training and teaching resource proficiency amongst Chemistry teachers. Male teachers have higher proficiency level on all aspects than female teachers. The MANOVA test results show a significant difference in teacher resource competency based on gender. Male teachers are significantly more proficient than their female counterparts. However, they do not significantly differ in terms of collaboration and in-service training. The structural equation modelling test results show that collaboration has a significant role in Chemistry teachers' involvement in training and teaching resources. These research findings encourage relevant parties to design effective collaborations amongst Chemistry teachers. They also offer new insights for Chemistry teachers to keep on mastering teaching resources nationally and internationally.
    Matched MeSH terms: Problem Solving
  5. Saw KG, Esa SR
    Sci Rep, 2021 Apr 07;11(1):7644.
    PMID: 33828210 DOI: 10.1038/s41598-021-87386-6
    Time-of-flight secondary ion mass spectrometry fragment analysis remains a challenging task. The fragment appearance regularity (FAR) rule is particularly useful for two-element compounds such as ZnO. Ion fragments appearing in the form of ZnxOy obey the rule [Formula: see text] in the positive secondary ion spectrum and [Formula: see text] in the negative spectrum where the valence of Zn is + 2 and that of O is - 2. Fragment analysis in gallium-doped ZnO (GZO) films can give insights into the bonding of the elements in this important semiconductor. Fragment analysis of 1 and 7 wt% GZO films shows that only the negative ion fragments obey the FAR rule where ZnO‒, 66ZnO‒, 68ZnO‒ and ZnO2‒ ion fragments appear. In the positive polarity, subdued peaks from out-of-the-rule ZnO+, 66ZnO+ and 68ZnO+ ion fragments are observed. The Ga ion peaks are present in both the positive and negative spectra. The secondary ion spectra of undoped ZnO also shows consistency with the FAR rule. This implies that Ga doping even in amounts that exceed the ZnO lattice limit of solubility does not affect the compliance with the FAR rule.
    Matched MeSH terms: Problem Solving
  6. Devadas VV, Khoo KS, Chia WY, Chew KW, Munawaroh HSH, Lam MK, et al.
    Bioresour Technol, 2021 Apr;325:124702.
    PMID: 33487515 DOI: 10.1016/j.biortech.2021.124702
    The accumulation of conventional petroleum-based polymers has increased exponentially over the years. Therefore, algae-based biopolymer has gained interest among researchers as one of the alternative approaches in achieving a sustainable circular economy around the world. The benefits of microalgae biopolymer over other feedstock is its autotrophic complex to reduce the greenhouse gases emission, rapid growing ability with flexibility in diverse environments and its ability to compost that gives greenhouse gas credits. In contrast, this review provides a comprehensive understanding of algae-based biopolymer in the evaluation of microalgae strains, bioplastic characterization and bioplastic blending technologies. The future prospects and challenges on the algae circular bioeconomy which includes the challenges faced in circular economy, issues regard to the scale-up and operating cost of microalgae cultivation and the life cycle assessment on algal-based biopolymer were highlighted. The aim of this review is to provide insights of algae-based biopolymer towards a sustainable circular bioeconomy.
    Matched MeSH terms: Problem Solving
  7. Seif AA, Eldamanhoury HM, Darahim K, Boulos DNK, Bahaa N, A M C, et al.
    Adv Physiol Educ, 2021 Mar 01;45(1):109-120.
    PMID: 33544038 DOI: 10.1152/advan.00166.2020
    The electrocardiogram (ECG) is the primary diagnostic tool in cardiovascular diseases. Hence its interpretation is a core competency in medicine, where obvious deficiencies have been reported among learners. The aim of this study was to introduce the fundamentals of ECG knowledge and interpretation through early clinical exposure (ECE) based on a six-step approach for preclinical students (n = 110) and to study its influence on their knowledge and interpretation skills thereafter. The first step employed a blended learning format using didactic lectures on normal and pathological ECGs, each preceded by preinstructional videos. The second step focused on psychomotor skills and utilized laboratory exercises for ECG recording and interpretation. The third step focused on vertical integration, where the clinical relevance of the procedure was established with integrated lectures. The fourth step used the Moodle platform, where opportunities for peer interactions and clarifications by clinical faculty were made available. The fifth step incorporated clinical and diagnostic reasoning through cardiology ward visits and interpretation of patient ECGs. The sixth step was designed for critical thinking and problem solving through case-based discussions with peers and faculty. Students were assessed with multiple-choice questions and objective structured practical examination. Learner perceptions of the approach were evaluated with a feedback questionnaire and focus group discussion. Statistical analysis showed that ECE through a six-step approach significantly enhanced knowledge and interpretation of ECG as evidenced by the pre- and posttest scores. Analysis of the focus group data revealed that learner engagement and skills of critical thinking were enhanced along with diagnostic and clinical reasoning.
    Matched MeSH terms: Problem Solving
  8. Wang Y, Lim YY, He Z, Wong WT, Lai WF
    PMID: 33559482 DOI: 10.1080/10408398.2021.1882381
    The last decide has witnessed a growing research interest in the role of dietary phytochemicals in influencing the gut microbiota. On the other hand, recent evidence reveals that dietary phytochemicals exhibit properties of preventing and tackling symptoms of Alzheimer's disease, which is a neurodegenerative disease that has also been linked with the status of the gut microbiota over the last decade. Till now, little serious discussions, however, have been made to link recent understanding of Alzheimer's disease, dietary phytochemicals and the gut microbiota together and to review the roles played by phytochemicals in gut dysbiosis induced pathologies of Alzheimer's disease. Deciphering these connections can provide insights into the development and future use of dietary phytochemicals as anti-Alzheimer drug candidates. This review aims at presenting latest evidence in the modulating role of phytochemicals in the gut microbiota and its relevance to Alzheimer's disease and summarizing the mechanisms behind the modulative activities. Limitations of current research in this field and potential directions will also be discussed for future research on dietary phytochemicals as anti-Alzheimer agents.
    Matched MeSH terms: Problem Solving
  9. Kamaludin K, Sundarasen S, Ibrahim I
    Heliyon, 2021 Jan;7(1):e05851.
    PMID: 33506122 DOI: 10.1016/j.heliyon.2020.e05851
    This study gains insights into what drives the ASEAN-5 equity markets. Using several wavelet approaches, we examine the correlation between the ASEAN-5 equity markets with the daily new Covid-19 cases and the Dow Jones Industrial Average (DowJones), the lead-lag relationships and level of disorder (or randomness) between the ASEAN-5 domestic equity markets and DowJones between February 15 to May 30, 2019 (pre-period) and February 15 to May 30, 2020 (during the pandemic period) respectively. The pandemic period is further divided into three different phases; the beginning (February), mid (March and April), and end (May) of the period. This study finds that Malaysia, Indonesia, and Singapore equity markets react to Covid-19 cases at the beginning of the pandemic phase, whereas, Thailand and the Philippines showed coherency during the mid-period. As the pandemic progresses (mid-period), all ASEAN-5 equity markets exhibited strong coherence with the DowJones Index. However, at the end of the sample period, no coherency was observed among the ASEAN-5 equity markets, local Covid-19 cases, and DowJones index. This study has two main contributions to the literature: First, we provide insights on equity markets' reactions during an epidemic/pandemic crisis in the emerging markets, specifically, the ASEAN-5 countries, which is a less studied area. Second, examining the impact of the Covid-19 and DowJones Index on the ASEAN-5 equity markets using the wavelet method is a novel approach that captures both the time and frequency dimensions. The results of this study have a significant contribution to investors and regulators, particularly in navigating the new 'normal' and data-driven era.
    Matched MeSH terms: Problem Solving
  10. Al-Kumaim NH, Alhazmi AK, Ramayah T, Shabbir MS, Gazem NA
    Front Psychol, 2021;12:637808.
    PMID: 33643168 DOI: 10.3389/fpsyg.2021.637808
    Value Co-Creation (VCC) plays a major role in engaging knowledgeable individuals in a community via innovation, problem solving, and new service/product development. This study investigates the personal factors that influence individuals' engagement in value co-creation in Higher Education Institutions (HEIs) through the use of online platforms. Some higher education institutions have successfully established or used appropriate online platforms, such as online forums, web applications, and mobile applications to engage their community in ideation or crowdsourcing as a part of the value co-creation process. On the other hand, some HEIs have failed to engage their community in value co-creation activities, and even if they managed to engage some individuals in value co-creation once, they failed to sustain these individuals' engagement in value co-creation using online platforms. Using the Stimulus Organism Response (S-O-R) framework, this study examines the relationship between relevant personal factors (commitment and knowledge self-efficacy) and other motivational factors that provide perceived benefits with value co-creation engagement. Data was collected from 308 respondents at five Malaysian research universities. The software analysis tool Smart PLS is used for data analysis and validation. The results demonstrate that personal factors and perceived benefits as a motivational factor has a significant effect on individual engagement in value co-creation. However, the significance of these findings varies from one individual to another. The implications of these findings are discussed.
    Matched MeSH terms: Problem Solving
  11. Guangnan Z, Tao H, Rahman MA, Yao L, Al-Saffar A, Meng Q, et al.
    Work, 2021;68(3):871-879.
    PMID: 33612530 DOI: 10.3233/WOR-203421
    BACKGROUND: An isolated robot must take account of uncertainty in its world model and adapt its activities to take into account such as uncertainty. In the same way, a robot interaction with security and privacy issues (RISAPI) with people has to account for its confusion about the human internal state, as well as how this state will shift as humans respond to the robot.

    OBJECTIVES: This paper discusses RISAPI of our original work in the field, which shows how probabilistic planning and system theory algorithms in workplace robotic systems that work with people can allow for that reasoning using a security robot system. The problem is a general way as an incomplete knowledge 2-player game.

    RESULTS: In this general framework, the various hypotheses and these contribute to thrilling and complex robot behavior through real-time interaction, which transforms actual human subjects into a spectrum of production systems, robots, and care facilities.

    CONCLUSION: The models of the internal human situation, in which robots can be designed efficiently, are limited, and achieve optimal computational intractability in large, high-dimensional spaces. To achieve this, versatile, lightweight portrayals of the human inner state and modern algorithms offer great hope for reasoning.

    Matched MeSH terms: Problem Solving
  12. Ding K, Choo WC, Ng KY, Ng SI, Song P
    Front Psychol, 2021;12:659481.
    PMID: 33967922 DOI: 10.3389/fpsyg.2021.659481
    This study aims to examine key attributes affecting Airbnb users' satisfaction and dissatisfaction through the analysis of online reviews. A corpus that comprises 59,766 Airbnb reviews form 27,980 listings located in 12 different cities is analyzed by using both Latent Dirichlet Allocation (LDA) and supervised LDA (sLDA) approach. Unlike previous LDA based Airbnb studies, this study examines positive and negative Airbnb reviews separately, and results reveal the heterogeneity of satisfaction and dissatisfaction attributes in Airbnb accommodation. In particular, the emergence of the topic "guest conflicts" in this study leads to a new direction in future sharing economy accommodation research, which is to study the interactions of different guests in a highly shared environment. The results of topic distribution analysis show that in different types of Airbnb properties, Airbnb users attach different importance to the same service attributes. The topic correlation analysis reveals that home like experience and help from the host are associated with Airbnb users' revisit intention. We determine attributes that have the strongest predictive power to Airbnb users' satisfaction and dissatisfaction through the sLDA analysis, which provides valuable managerial insights into priority setting when developing strategies to increase Airbnb users' satisfaction. Methodologically, this study contributes by illustrating how to employ novel approaches to transform social media data into useful knowledge about customer satisfaction, and the findings can provide valuable managerial implications for Airbnb practitioners.
    Matched MeSH terms: Problem Solving
  13. Abdullah AH, Neo TK, Low JH
    F1000Res, 2021;10:1076.
    PMID: 35035894 DOI: 10.12688/f1000research.73210.2
    Background: Studies have acknowledged that social media enables students to connect with and learn from experts from different ties available in the students' personal learning environment (PLE). Incorporating experts into formal learning activities such as scaffolding problem-solving tasks through social media, allows students to understand how experts solve real-world problems. However, studies that evaluate experts' problem-solving styles on social media in relation to the tie strength of the experts with the students are scarce in the extant literature. This study aimed to explore the problem-solving styles that the experts portrayed based on their ties with the students in problem-based learning (PBL) on Facebook. Methods: This study employed a simultaneous within-subject experimental design which was conducted in three closed Facebook groups with 12 final year management students, six business experts, and one instructor as the participants. The experts were invited by the students from the weak and strong ties in their PLE. Hinging on the Strength of Weak Ties Theory (Granovetter, 1973) and problem-solving styles (Selby et al., 2004), this study employed thematic analysis using the ATLAS.ti qualitative data analysis software to map the experts' comments on Facebook. Results:  The experts from strong and weak ties who had a prior relationship with the students showed people preference style by being more sensitive to the students' learning needs and demonstrating firmer scaffolding compared to the weak ties' experts who had no prior relationship with the students. Regardless of the types of ties, all experts applied all manner of processing information and orientation to change but the degree of its applications are correlated with the working experience of the experts. Conclusion: The use of weak or strong ties benefited the students as it expedited their problem-solving tasks since the experts have unique expertise to offer depending on the problem-solving styles that they exhibited.
    Matched MeSH terms: Problem Solving
  14. Chandran DS, Muthukrishnan SP, Barman SM, Peltonen LM, Ghosh S, Sharma R, et al.
    Adv Physiol Educ, 2020 Dec 01;44(4):709-721.
    PMID: 33125254 DOI: 10.1152/advan.00128.2020
    Active learning promotes the capacity of problem solving and decision making among learners. Teachers who apply instructional processes toward active participation of learners help their students develop higher order thinking skills. Due to the recent paradigm shift toward adopting competency-based curricula in the education of healthcare professionals in India, there is an emergent need for physiology instructors to be trained in active-learning methodologies and to acquire abilities to promote these curriculum changes. To address these issues, a series of International Union of Physiological Sciences (IUPS) workshops on physiology education techniques in four apex centers in India was organized in November 2018 and November 2019. The "hands-on" workshops presented the methodologies of case-based learning, problem-based learning, and flipped classroom; the participants were teachers of basic sciences and human and veterinary medicine. The workshop series facilitated capacity building and creation of a national network of physiology instructors interested in promoting active-learning techniques. The workshops were followed by a brainstorming meeting held to assess the outcomes. The aim of this report is to provide a model for implementing a coordinated series of workshops to support national curriculum change and to identify the organizational elements essential for conducting an effective Physiology Education workshop. The essential elements include a highly motivated core organizing team, constant dialogue between core organizing and local organizing committees, a sufficient time frame for planning and execution of the event, and opportunities to engage students at host institutions in workshop activities.
    Matched MeSH terms: Problem Solving
  15. Mey LS, Khairudin R, Muda TEAT, Mokhtar DM, Kamaluddin MR
    Data Brief, 2020 Aug;31:105864.
    PMID: 32613044 DOI: 10.1016/j.dib.2020.105864
    Studies have consistently shown that childhood maltreatment is a significant risk factor for the development of drug addiction across human lifespan. Yet, little is known about the prevalence of childhood maltreatment history among drug addicts in Malaysia. The dataset presented in this article provides demographic information on 200 drug addicts recruited from two rehabilitation centres in Malaysia, the prevalence of different types of childhood maltreatment history and the correlation between all types of maltreatments. Analyses of the data can provide insights into the prevalence of maltreatment history and development of drug addiction, therefore indispensable for mental health professionals designing appropriate interventions for the drug addicts. The data can also provide baseline data for comparative studies in terms of childhood maltreatment history and drug addiction across different countries.
    Matched MeSH terms: Problem Solving
  16. Olakotan OO, Yusof MM
    J Biomed Inform, 2020 06;106:103453.
    PMID: 32417444 DOI: 10.1016/j.jbi.2020.103453
    The overwhelming number of medication alerts generated by clinical decision support systems (CDSS) has led to inappropriate alert overrides, which may lead to unintended patient harm. This review highlights the factors affecting the alert appropriateness of CDSS and barriers to the fit of CDSS alert with clinical workflow. A literature review was conducted to identify features and functions pertinent to CDSS alert appropriateness using the five rights of CDSS. Moreover, a process improvement method, namely, Lean, was used as a tool to optimise clinical workflows, and the appropriate design for CDSS alert using a human automation interaction (HAI) model was recommended. Evaluating the appropriateness of CDSS alert and its impact on workflow provided insights into how alerts can be designed and triggered effectively to support clinical workflow. The application of Lean methods and tools to analyse alert efficiencies in supporting workflow in this study provides an in-depth understanding of alert-workflow fit problems and their root cause, which is required for improving CDSS design. The application of the HAI model is recommended in the design of CDSS alerts to support various levels and stages of alert automations, namely, information acquisition and analysis, decision action and action implementation.
    Matched MeSH terms: Problem Solving
  17. Nurhafizah Moziyana Mohd Yusop, Nooraida Samsudin, Nooraida Samsudin, Anis Shahida Mokhta, Siti Rohaidah Ahmad, Mohd Fahmi Mohammad Amran, et al.
    MyJurnal
    Euler method is a numerical order process for solving problems with the Ordinary Differential Equation (ODE). It is a fast and easy way. While Euler offers a simple procedure for solving ODEs, problems such as complexity, processing time and accuracy have driven others to use more sophisticated methods. Improvements to the Euler method have attracted much attention resulting in numerous modified Euler methods. This paper proposes Cube Polygon, a modified Euler method with improved accuracy and complexity. In order to demonstrate the accuracy and easy implementation of the proposed method, several examples are presented. Cube Polygon’s performance was compared to Polygon’s scheme and evaluated against exact solutions using SCILAB. Results indicate that not only Cube Polygon has produced solutions that are close to identical solutions for small step sizes, but also for higher step sizes, thus generating more accurate results and decrease complexity. Also known in this paper is the general of the RL circuit due to the ODE problem.
    Matched MeSH terms: Problem Solving
  18. Shoesmith W, Chua SH, Giridharan B, Forman D, Fyfe S
    PMID: 32577126 DOI: 10.1186/s13033-020-00374-7
    Background: There is strong evidence that collaborative practice in mental healthcare improves outcomes for patients. The concept of collaborative practice can include collaboration between healthcare workers of different professional backgrounds and collaboration with patients, families and communities. Most models of collaborative practice were developed in Western and high-income countries and are not easily translatable to settings which are culturally diverse and lower in resources. This project aimed to develop a set of recommendations to improve collaborative practice in Malaysia.

    Methods: In the first phase, qualitative research was conducted to better understand collaboration in a psychiatric hospital (previously published). In the second phase a local hospital level committee from the same hospital was created to act on the qualitative research and create a set of recommendations to improve collaborative practice at the hospital for the hospital. Some of these recommendations were implemented, where feasible and the outcomes discussed. These recommendations were then sent to a nationwide Delphi panel. These committees consisted of healthcare staff of various professions, patients and carers.

    Results: The Delphi panel reached consensus after three rounds. The recommendations include ways to improve collaborative problem solving and decision making in the hospital, ways to improve the autonomy and relatedness of patients, carers and staff and ways to improve the levels of resources (e.g. skills training in staff, allowing people with lived experience of mental disorder to contribute).

    Conclusions: This study showed that the Delphi method is a feasible method of developing recommendations and guidelines in Malaysia and allowed a wider range of stakeholders to contribute than traditional methods of developing guidelines and recommendations.Trial registration Registered in the National Medical Research Register, Malaysia, NMRR-13-308-14792.

    Matched MeSH terms: Problem Solving
  19. Shafii NZ, Saudi ASM, Pang JC, Abu IF, Sapawe N, Kamarudin MKA, et al.
    Heliyon, 2019 Oct;5(10):e02534.
    PMID: 31667387 DOI: 10.1016/j.heliyon.2019.e02534
    There has been a growing concern on the rising of environmental issues in Malaysia over the last decade. Many environmental studies conducted in this country began to utilise the chemometrics techniques to overcome the limitation in the environmental monitoring studies. Chemometrics becomes an important tool in environmental fields to evaluate the relationship of various environmental variables particularly in a large and complex database. The review aimed to analyse and summarize the current evidences and limitations on the application of chemometrics techniques in the environmental studies in Malaysia. The study performed a comprehensive review of relevant scientific journals concerning on the major environmental issues in the country, published between 2013 and 2017. A total of 29 papers which focused on the environmental issues were reviewed. Available evidences suggested that chemometrics techniques have a greater accuracy, flexibility and efficiency to be applied in environmental modelling. It also reported that chemometrics techniques are more practical for cost effective and time management in sampling and monitoring purposes. However, chemometrics is relatively new in environmental field in Malaysia and various scopes need to be considered in the future as the current studies focused on very limited number of major environmental issues. Overall, chemometrics techniques have a lot of advantages in solving environmental problems. The development of chemometrics in environmental studies in the country is necessary to advance understanding, thus able to produce more significant impacts towards the effective environmental management.
    Matched MeSH terms: Problem Solving
  20. Chia SR, Chew KW, Show PL, Xia A, Ho SH, Lim JW
    Bioresour Technol, 2019 Oct;289:121727.
    PMID: 31279318 DOI: 10.1016/j.biortech.2019.121727
    In this present study, microalgal phycobiliproteins were isolated and purified via potential biphasic processing technique for pharmaceutical as well as food applications. The algal pre-treatment techniques were studied to enhance the yield of microalgal phycobiliproteins from the biomass. The proposed methods were optimised to obtain the best recovery yield of phycobiliproteins that can be isolated from the biomass. The phycobiliproteins were further purified using liquid biphasic system. The results showed that microalgal phycobiliproteins of high purity and yield was achieved using sonication treatment (20% power, 50% duty cycle and 7 min of irradiation time) with the biphasic system, where the purification fold of 6.17 and recovery yield of 94.89% was achieved. This work will provide insights towards the effective downstream processing of biomolecules from microalgae.
    Matched MeSH terms: Problem Solving
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