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The increasing accumulation of synthetic plastic waste in oceans and landfills, along with the depletion of non-renewable fossil-based resources, has sparked environmental concerns and prompted the search for environmentally friendly alternatives. Biodegradable plastics derived from lignocellulosic materials are emerging as substitutes for synthetic plastics, offering significant potential to reduce landfill stress and minimise environmental impacts. This study highlights a sustainable and cost-effective solution by utilising agricultural residues and invasive plant materials as carbon substrates for the production of biopolymers, particularly polyhydroxybutyrate (PHB), through microbiological processes. Locally sourced residual materials were preferred to reduce transportation costs and ensure accessibility. The selection of suitable residue streams was based on various criteria, including strength properties, cellulose content, low ash and lignin content, affordability, non-toxicity, biocompatibility, shelf-life, mechanical and physical properties, short maturation period, antibacterial properties and compatibility with global food security. Life cycle assessments confirm that PHB dramatically lowers CO₂ emissions compared to traditional plastics, while the growing use of lignocellulosic biomass in biopolymeric applications offers renewable and readily available resources. Governments worldwide are increasingly inclined to develop comprehensive bioeconomy policies and specialised bioplastics initiatives, driven by customer acceptability and the rising demand for environmentally friendly solutions. The implications of climate change, price volatility in fossil materials, and the imperative to reduce dependence on fossil resources further contribute to the desirability of biopolymers. The study involves fermentation, turbidity measurements, extraction and purification of PHB, and the manufacturing and testing of composite biopolymers using various physical, mechanical and chemical tests.

This chapter aims to identify, analyse, classify and rank the sustainability indices and internationalisation challenges of the footwear industry in the emerging economy of Iran. This would provide deeper decision-making insights into Iranian footwear businesses. First, a list of sustainability indices and internationalisation challenges was obtained by reviewing the literature. Then, a combination of multi-criteria decision-making (MCDM) approaches was implemented. The initial sustainability indices and internationalisation challenges were screened using the fuzzy Delphi method, keeping a total of 14 criteria. The best–worst method (BWM) was employed to weigh and rank the criteria. The interpretive structural modelling (ISM) technique and cross-impact matrix applied in MICMAC were employed to visualise the conceptual model based on the levels and classification of the important criteria for the internationalisation of the Iranian footwear industry. The 14 criteria were demonstrated to be important in internationalisation. The most critical sustainability indices were reducing hazardous substances in leather tanning and labour education and training. In contrast, exchange rate instability in Iran’s economy and strict chemical regulations for clothing and footwear were found to be the most important internationalisation challenges. Hence, these criteria should be considered in the internationalisation strategies of the Iranian footwear industry. A combined multilayer sustainable decision-making approach was used to analyse the Iranian footwear industry’s essential sustainability indices and internationalisation challenges. Furthermore, implications and insights are offered to footwear businesses for future decision-making.

The contamination of groundwater by natural arsenic is currently a worldwide epidemic. Arsenic-contaminated groundwater has been reported in Argentina, Chile, Mexico, China, Hungary, West Bengal in India, Bangladesh, and Vietnam. Of these regions, Bangladesh and West Bengal are the most seriously affected in terms of the size of the population at risk and magnitude of health problems. Hence, chronic exposure to arsenic >50′′μg/L in drinking water can result in serious health problems. Common symptoms of arsenic-related ailments are skin, cardiovascular, renal, hematological, and respiratory disorders. Therefore, this chapter focuses on nature, origin, and extent of groundwater arsenic contamination, probable causes, and its impacts on food, drinking water, and social coverage. It further discloses mitigation approaches proposed and practiced by the different research groups to combat this problem and finally concludes.

This chapter outlines the potential market of methane (especially LNG) as vehicle fuel in Europe and China.

A comprehensive report on the existing framework in terms of market capacity, regulations, and incentives is presented. Moreover, the feasibility of using biogas as environmental friendly source gas is considered.

The transport sector represents a major element in the global balance of greenhouse gas (GHG) emissions. Natural gas is considered the alternative fuel that, in the short-medium term, can best substitute conventional fuels in order to reduce their environmental impact, because it is readily available at a competitive price, using technologies that are already in widespread use. It can be used as compressed gas (CNG) or in the liquid phase (LNG). The former is more suitable for light vehicles, while the latter for heavy-duty vehicles. Some barriers need to be overcome for the diffusion of this alternative fuel, especially concerning the supply problem. The incentive policy has been shown to cover a major influence in the feasibility evaluation.

This work shows the state of the art of natural gas as fuel, especially from biogas source, in Europe and China and assesses the incentive scheme necessary to make liquefied biomethane feasible on the basis of the existing scenario in Italy.

The products of transgenic technology have captured the attention of enthusiasts and detractors, but transgenics are just one tool of agricultural biotechnology. Other applications enable scientists to understand biodiversity, to track genes through generations in breeding programs, and to move genes among closely related as well as unrelated organisms. These applications all have the potential to lead to substantial productivity gains.

In this chapter we provide an introduction to basic plant genetic concepts, defining molecular markers, transgenic and cisgenic techniques. We briefly summarize the status of commercialized biotechnology applications to agriculture. We consider the likely future commercialization of products like drought tolerant crops, crops designed to improve human nutrition, pharmaceuticals from transgenic plants, biofuels, and crops for environmental remediation. We identify genomic selection as a potentially powerful new technique and conclude with our reflections on the state of agricultural biotechnology.

Research at universities and other public-sector institutions, largely focused on advancing knowledge, has aroused enormous optimism about the promise of these DNA-based technologies. This in turn has led to large private-sector investments on maize, soybean, canola, and cotton, with wide adoption of the research products in about eight countries. Much has been made of the potential of biotechnology to address food needs in the low-income countries, and China, India, and Brazil have large public DNA-based crop variety development efforts. But other lower income developing countries have little capability to use these tools, even the most straightforward marker applications. Ensuring that these and other applications of biotechnology lead to products that are well adapted to local agriculture requires adaptive research capacity that is lacking in the lowest income, most food-insecure nations. We are less optimistic than many others that private research will fund these needs.

In an evaluation of a job training program, the causal effects of the program on wages are often of more interest to economists than the program's effects on employment or on income. The reason is that the effects on wages reflect the increase in human capital due to the training program, whereas the effects on total earnings or income may be simply reflecting the increased likelihood of employment without any effect on wage rates. Estimating the effects of training programs on wages is complicated by the fact that, even in a randomized experiment, wages are truncated by nonemployment, i.e., are only observed and well-defined for individuals who are employed. We present a principal stratification approach applied to a randomized social experiment that classifies participants into four latent groups according to whether they would be employed or not under treatment and control, and argue that the average treatment effect on wages is only clearly defined for those who would be employed whether they were trained or not. We summarize large sample bounds for this average treatment effect, and propose and derive a Bayesian analysis and the associated Bayesian Markov Chain Monte Carlo computational algorithm. Moreover, we illustrate the application of new code checking tools to our Bayesian analysis to detect possible coding errors. Finally, we demonstrate our Bayesian analysis using simulated data.

Understanding how health status and physiological factors affect performance is a daunting task. This chapter will discuss physiological, behavioral, and psychological factors that influence or determine the capacity to fight, and will consider metrics that can be used to measure their status. The premise of this discussion is that there is a set of physiological and psychological factors that intimately affect performance and that the relative contribution of these variables is individually unique. These factors can be identified and assessed, and are amenable to modification. A fuller understanding of these variables can lead the effort to maintain and improve performance in the adverse and challenging environments of military operations.