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We argue this method of inquiry better represents the participants' learning, lives and experiences in the formal neoliberal education system prioritising performativity, categorising and ranking students.

The paper explores using poetry as a research method to reveal the learning experiences of adult learners, who have often had disruptive experiences of the formal schooling system and return to study in community-based education spaces. Inspired by Laurel Richardson’s transgressive technique of presenting sociological data through poetry as method, we use poetic representations of these learners' lives alongside case study research methodology. The research was conducted in conjunction with Neighbourhood Houses in Victoria, Australia. Qualitative data were generated through conducting multiple case studies of learners across various adult community education (ACE) sites. In this research, some case studies were presented in the traditional method of writing biography, others were written in the form of found poetry, which we refer to as data as poetry and text. The paper uses found poetry through participant-voiced poems written from interview transcripts. We argue this method of inquiry better represents the participants' learning, lives and experiences in the formal neoliberal education system prioritising performativity, categorising and ranking students. Our findings highlight the benefits of using poetry to communicate data in case study research as it effectively represents the experiences of adult learners' lives in a creative and concise form, transgressing normative practices of writing education research. These poetic representations of data reveal learner experiences in an embodied and agentic way while providing readers with a deep and rich understanding of these crucial adult learning spaces.

Our findings highlight the benefits of using poetry to communicate data in case study research as it effectively represents the experiences of adult learners' lives in a creative and concise form, transgressing normative practices of writing education research.

This research paper is empirical research and has not been submitted elsewhere for publication.

Factor investment is booming in global asset management, especially environmental, social, and governance (ESG), dividend yield, and volatility factors. In this chapter, we use data from the US securities market from 2003 to 2019 to predict dividends and volatility factors through machine learning and historical data–based methods. After that, we utilize particle swarm optimization to construct the Markowitz portfolio with limits on the number of assets and weight restrictions. The empirical results show that that the prediction ability using XGBoost is superior to the historical factor investment method. Moreover, the investment performance of our portfolio with ESG, high-yield, and low-volatility factors outperforms baseline methods, especially the S&P 500 ETF.

The number of people with special needs, including citizens and military personnel, has increased as a result of terrorist attacks and challenging conditions in Iraq and other countries. With almost 80% of the world’s amputees having below-the-knee amputations, Iraq has become a global leader in the population of amputees. Important components found in lower limb prostheses include the socket, pylon (shank), prosthetic foot and connections.

There are two types of prosthetic feet: articulated and nonarticulated. The solid ankle cushion heel foot is the nonarticulated foot that is most frequently used. The goal of this study is to use a composite filament to create a revolutionary prosthetic foot that will last longer, have better dorsiflexion and be more stable and comfortable for the user. The current study, in addition to pure polylactic acid (PLA) filament, 3D prints test items using a variety of composite filaments, such as PLA/wood, PLA/carbon fiber and PLA/marble, to accomplish this goal. The experimental step entails mechanical testing of the samples, which includes tensile testing and hardness evaluation, and material characterization by scanning electron microscopy-energy dispersive spectrometer analysis. The study also presents a novel design for the nonarticulated foot that was produced with SOLIDWORKS and put through ANSYS analysis. Three types of feet are produced using PLA, PLA/marble and carbon-covered PLA/marble materials. Furthermore, the manufactured prosthetic foot undergoes testing for dorsiflexion and fatigue.

The findings reveal that the newly designed prosthetic foot using carbon fiber-covered PLA/marble material surpasses the PLA and PLA/marble foot in terms of performance, cost-effectiveness and weight.

To the best of the author’s knowledge, this is the first study to use composite filaments not previously used, such as PLA/wood, PLA/carbon fiber and PLA/marble, to design and produce a new prosthetic foot with a longer lifespan, improved dorsiflexion, greater stability and enhanced comfort for the patient. Beside the experimental work, a numerical technique specifically the finite element method, is used to assess the mechanical behavior of the newly designed foot structure.

The purpose of this study is to examine the impact of firm environmental, social and governance (ESG) rating scores on market perception and stock behavior from 2017 to 2021 while controlling for COVID-19 severity score.

The authors used panel regression models with robust standard errors based on cross-country and cross-industry sample of 1,324 ESG firms from 25 emerging countries across four regions. Four separate regression analyses are used. Hausman test is used to determine whether fixed-effect (FE) or random-effect approaches should be used in regression models. Lagrange multiplier test is used to test for time FEs, and F-test for individual effects to choose between pooled ordinary least squares model and FE. Two-unit root tests are conducted to check stationarity. Heteroskedasticity and serial correlation were controlled through a robust covariance matrix estimation.

The authors provide evidence that the stakeholder theory persists in emerging countries. Overall, the results suggest that firms’ stock behavior is positively associated with the level of environmental and social performance in the region. However, the results do not provide empirical evidence to support the link between ESG performance and stock market perception proxied by the price-to-sales ratio. The results suggest that Refinitiv and Bloomberg ESG rating scores have a positive impact on stock performance in emerging markets, albeit the Bloomberg rating score is insignificant.

Favorable impact of environmental and social performance on stock performance suggests that policymakers should take initiatives to raise awareness toward investments in ESG projects. Evidence shows that ESG stock performance in emerging markets does not insulate firms from the COVID-19 severity. Furthermore, this study highlights the inconsistency in calculating the ESG ratings, therefore, a more standardized approach is recommended to support investors seeking sustainable investments.

The findings have social implications for investors with proenvironmental preferences and nonpecuniary motives for ethical investments. Asset fund managers should develop ESG investment strategies to promote investor preferences that are linked to the proenvironmental and prosocial attitudes by increasing their investments in stocks of firms that behave ethically and support the environment. Furthermore, the findings show that investors pay a price for ethical and socially responsible investments as they are evaluating the environmental and social activities, hence, the firm ESG profile influences equity valuation and risk assessment.

The study extends the literature and provides evidence from the unique setting of emerging markets by analyzing the relationship between ESG rating scores and the COVID-19 severity scores on one hand, and stock behavior and market perception on the other.