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This study aims to demonstrate the possibility of showing the functionality of complex microbial groups, within ancient structures within a process of refurbishment on a heritage building information modelling (BIM) platform.

Both a qualitative and qualitative research method will be used throughout, as observational and scientific results will be obtained and collated. This path being; phenomena – acquisition tools – storage – analysis tools – literature. Using this methodology, one pilot study within the scope of demolition and refurbishment, using suitable methods of collecting and managing data (structural or otherwise), will be used and generated by various software and applications. The principle methods used for the identification of such micro-organisms will incorporate a polymerase chain reaction method (PCR), to amplify DNA and to identify any or all spores present. The BIM/historical BIM (HBIM) process will be used to create a remotely-based survey to obtain and collate data using a laser scanner to produce a three-dimensional point cloud model to evaluate and deduce the condition, make-up and stature of the monument. A documentation management system will be devised to enable the development of plain language questions and an exchange information requirement, to identify such documentation required to enable safe refurbishment and to give health and safety guidance. Four data sampling extractions will be conducted, two for each site, within the research, for each of the periods being assessed, that being the Norman and Tudor areas of the monument.

From laboratory PCR analysis, results show a conclusive presence of micro-organism groups and will be represented within a hierarchical classification, from kingdom to species.

The BIM/HBIM process will highlight results in a graphical form to show data collected, particularly within the PCR application. It will also create standardisation and availability for such data from ancient monuments to make available all data stored, as such analysis becomes substantially important to enable the production of data sets for comparison, from within the framework of this research.

In this final chapter, we explore the ever-evolving 21st century landscape where ethics drive community development toward resilience and progress. Drawing inspiration from the subheadings mapping our journey, we traverse international case studies spanning Canada, Brazil, Sweden, Kenya, China, Australia, Antarctica, and India. Through these global insights, we uncover the impacts of dynamic forces on communities worldwide, navigating ethical dilemmas and opportunities. We present strategies tailored to diverse continent-specific needs, explore inclusive governance models, and highlight the transformative power of ethical engagement. This journey underscores the vital role of resilience and concludes with a global call to embrace ethical approaches for inclusive community development and a sustainable future.

The purpose of this paper is to make the case that ethical guardrails in emerging technology businesses are inadequate and to develop solutions to strengthen these guardrails.

Based on literature and first principles reasoning, the paper develops theoretical arguments about the fundamental purpose of ethical guardrails and how they evolve and then uses this along with the characteristics that distinguish emerging technology businesses to identify inadequacies in the ethical guardrails for emerging technology businesses and develop solutions to strengthen the guardrails.

The paper shows that the ethical guardrails for emerging technology businesses are inadequate and that the reasons for this are systematic. The paper also develops actionable recommendations to strengthen these guardrails.

The paper develops the novel argument that reasons for the inadequate ethical guardrails in emerging technology businesses are systematic and stem from the inadequacy of laws and regulations, inadequacy of boards and the focus of business executives.

Mucorales has been described to be widely distributed during the most recent COVID-19 pandemic, with a greater frequency of disease in India, particularly among those with immune deficiencies. This study aims to use computational tools to develop a vaccine.

The authors investigated at Mucorales proteins that had previously been associated to virulence factors. Recent research suggests that a vaccine based on high-level cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) and B-cell lymphocyte (BCL) epitopes from diverse proteins might be developed. Furthermore, the vaccine assembly contains the targeted epitopes as well as PADRE peptides to induce an immune response. Computational approaches were used to analyze the immunological parameters used to build the suggested vaccine and validate its TLR-3 binding.

These studies show that the vaccination is capable of triggering a particular immune response. The authors offer a technique for developing and evaluating candidate vaccines using computational tools. To the best of their knowledge, this is the first immunoinformatic research of a prospective mucormycosis vaccine.

During this audit, a successful attempt was made to create a subunit MEV against black fungus. In the current study, MEV has been proposed as a suitable neutralizer candidate since it is immunogenic, secure, stable and interacts with human receptors. A stream study, on the other hand, is produced via a mixed vaccinosis approach. Following that, vaccinologists may perform more exploratory testing to evaluate whether the vaccine is effective.

This study aims to investigate the tendency that Malaysian consumers will choose the recombinant collagen-like protein (RCLP) from bacteria as an alternative source of collagen in their consumption and the determinants of the consumer acceptance.

Quantitative approach is adopted in the study. Descriptive analysis and logistic regression are used to analyze primary data collected from a survey.

The likelihood of consumers choosing RCLP as an alternative source of collagen is higher among elderly and females. The choice is significantly influenced by the idea that the collagen should support maqasid al-syariah, approved by national Islamic body, should clear on the ingredients used and could boost local economic activities in the future.

An ethical halal policy should be outlined as the guiding principles to the potential producers of RCLP.

An alternative source of collagen using bacteria as proposed is not yet being introduced in Malaysian industry, and the analysis on probability that consumers will accept this new sourced collagen product is using primary data from survey.

Gamma-aminobutyric acid (GABA) is a four-carbon and nonprotein amino acid, made by various microorganisms, especially lactic acid bacteria (LAB) and probiotics. GABA has various physiological roles, for instance, insomnia, depression, hypotensive activity as well as diuretic effects. The production of GABA-based foods is a favorable result from GABA’s biological and functional properties. The purpose of this study is to investigate different methods of improving GABA production in probiotics and LAB to select the superlative method and bacterial strain.

In this review paper, all articles from five electronic databases containing Google Scholar, Web of Science, PubMed, Scopus and Science Direct were considered from 2000 to January 11, 2023, with keywords “Optimization” OR “Enhance” OR “Increase” AND “Gamma-aminobutyric acid” OR “GABA” AND “Probiotics” OR “Lactic acid bacteria” and selected according to the purpose of the study.

It seems that among all the investigated methods, an effective fermentation procedure with optimal conditions including fermentation medium, 5 L; glutamic acid, 295 g/L; incubation temperature, 32°C; inoculum, 10% (v/v); and agitation, 100 rpm, after 48 h of fermentation led to producing 205,800 mg/L of GABA from the effective bacterial strain Lactobacillus brevis NCL912.

With a simple but optimized fermentation, L. brevis NCL912 can be used for the efficient GABA production in the pharmacy and food factories.

Metaheuristic algorithms based on biology, evolutionary theory and physical principles, have been widely developed for complex global optimization. This paper aims to present a new hybrid optimization algorithm that combines the characteristics of biogeography-based optimization (BBO), invasive weed optimization (IWO) and genetic algorithms (GAs).

The significant difference between the new algorithm and original optimizers is a periodic selection scheme for offspring. The selection criterion is a function of cyclic discharge and the fitness of populations. It differs from traditional optimization methods where the elite always gains advantages. With this method, fitter populations may still be rejected, while poorer ones might be likely retained. The selection scheme is applied to help escape from local optima and maintain solution diversity.

The efficiency of the proposed method is tested on 13 high-dimensional, nonlinear benchmark functions and a homogenous slope stability problem. The results of the benchmark function show that the new method performs well in terms of accuracy and solution diversity. The algorithm converges with a magnitude of 10-4, compared to 102 in BBO and 10-2 in IWO. In the slope stability problem, the safety factor acquired by the analogy of slope erosion (ASE) is closer to the recommended value.

This paper introduces a periodic selection strategy and constructs a hybrid optimizer, which enhances the global exploration capacity of metaheuristic algorithms.