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The following is an introductory profile of the fastest growing firms over the three-year period of the study listed by corporate reputation ranking order. The business activities in which the firms are engaged are outlined to provide background information for the reader.

Ostensibly the Carverian argument is based on the following premise, which is treated as an axiom:Human beings like other living creatures seem to be driven by a force that they neither understand nor care to resist, to keep on living, to consume food and transform it into human energy, and to increase their numbers, thus, in every way, enlarging the stream of human energy. In short, they act unconsciously, driven by their own nature, precisely as they would act consciously if they were convinced by unanswerable logic that the most valuable thing in the world was human energy or human life, and the most profitable thing in the world was to transform the largest possible sum of solar energy into human energy. (p. 12)

To explore the funds of knowledge that six emergent bilingual students build upon as they produce multimodal texts, how the practices surrounding these events are mediated, and the role of student agency within an ethnographic social semiotics framework. Ethnographic methods were used to document this yearlong study that included videotaping small group interactions, writing field notes, conducting interviews, and collecting multimodal work samples. The researcher served as a participant observer in a third-grade classroom where she met with students two days per week to interact with mulitmodal poetry. The findings reveal the media-rich popular culture and home digital practices students bring with them to school and the ways in which these resources were utilized for designing multimodal poetry. Several essential factors are discussed including funds of knowledge, role of play and creativity, nonlinear writing structures, and agentive design decisions. Multimodal text making requires a revamping of classroom literacy instruction that embraces multiple modes especially noting the importance of images, central role of experiential learning, and space for student choice thus empowering them as learners.

How was I going to engage the students in my ancient Roman Art and Architecture course, especially the five football players who had signed up in the fall of 2015? In this chapter, I will discuss the commitment I made to the students and myself to ensure that each class period was one in which an active learning technique was used, often paired with some lecture, and sometimes not, to engage students and help them learn about Roman Art and Architecture. I will discuss what assignments I chose based on research and my own observation, as well as the results of a focus group held with the football players a year later about what they remembered. Football players tend to be kinetic learners and thus were chosen as the follow-up to see how the active learning techniques in this class met objectives. Specifically, this chapter will discuss the inclusion of a Reacting to the Past role-playing game, a research project on “Daily Life in Ancient Rome,” and presentations on different methodologies of interpreting an image from a Pompeiian tavern.

Adsorption parameters (e.g. Langmuir constant, mass transfer coefficient and Thomas rate constant) are involved in the design of aqueous-media adsorption treatment units. However, the classic approach to estimating such parameters is perceived to be imprecise. Herein, the essential features and performances of the ant colony, bee colony and elephant herd optimisation approaches are introduced to the experimental chemist and chemical engineer engaged in adsorption research for aqueous systems. Key research and development directions, believed to harness these algorithms for real-scale water treatment (which falls within the wide-ranging coverage of the Sustainable Development Goal 6 (SDG 6) ‘Clean Water and Sanitation for All’), are also proposed. The ant colony, bee colony and elephant herd optimisations have higher precision and accuracy, and are particularly efficient in finding the global optimum solution. It is hoped that the discussions can stimulate both the experimental chemist and chemical engineer to delineate the progress achieved so far and collaborate further to devise strategies for integrating these intelligent optimisations in the design and operation of real multicomponent multi-complexity adsorption systems for water purification.

Purpose – The purpose of this paper to immobilization provides biosorbent particle with density and mechanichal strength, immobilization can save the cost of separating from biomass, can be regeneration and to increase adsorption capacity for metal ions.

Design/Methodology/Approach – The parameters affecting the adsorption, such as initial metal ion concentration, pH, contact time, and temperature, were studied. The analysis of biosorbent functional group was carried out by Fourier Transform Infrared Spectroscopy, SEM-EDX, for elemental analysis.

Findings – Optimum pH condition for biosorption Cd(II) was pH 5, contact time was 45 min, and initial concentration was 250 mg/L. Biosorbent analysis was characterized using SEM-EDX and FTIR analysis. Kinetics adsorption was studied and analyzed in terms of the pseudo-first-order, pseudo-second-order, and intraparticle diffusion kinetics models. The result showed that the biosorption for Cd(II) ion followed the pseudo-second-order kinetic model. Biosorption data of Cd(II) ion at 300°K, 308°K, and 318°K was analyzed with Temkin, Langmuir, and Freundlich isotherms. Biosorption of Cd(II) by durian seed immobilization in alginate according to the Langmuir isotherm equation provided a coefficient correlation of r² = 0.939 and maximum capacity biosorption of 25.05 mg/g.

The complexity of atmospheric corrosion, further compounded by the effects of climate change, makes existing models inappropriate for corrosion prediction. The commonly used kinetic model and dose-response functions are restricted in their capacity to represent the non-linear behaviour of corrosion phenomena. The application of artificial intelligence (AI)-driven machine learning algorithms to corrosion data can better represent the corrosion mechanism by considering the dynamic behaviour due to changing climatic conditions. Effective use of materials, coating systems and maintenance strategies can then be made with such a corrosivity model. Accurate corrosion prediction will help to improve climate change resilience of the social, economic and energy infrastructure in line with the UN Sustainable Development Goals (SDGs) 7 (Affordable and Clean Energy), 9 (Industry, Innovation and Infrastructure) and 13 (Climate Action). This chapter discusses atmospheric corrosion prediction in relation to the SDGs and the influence of AI in overcoming the challenges.