Hasil untuk "Environmental engineering"

G. Mamba, A. Mishra

H. P. Austin, Mark D. Allen, B. Donohoe et al.

Significance Synthetic polymers are ubiquitous in the modern world but pose a global environmental problem. While plastics such as poly(ethylene terephthalate) (PET) are highly versatile, their resistance to natural degradation presents a serious, growing risk to fauna and flora, particularly in marine environments. Here, we have characterized the 3D structure of a newly discovered enzyme that can digest highly crystalline PET, the primary material used in the manufacture of single-use plastic beverage bottles, in some clothing, and in carpets. We engineer this enzyme for improved PET degradation capacity and further demonstrate that it can also degrade an important PET replacement, polyethylene-2,5-furandicarboxylate, providing new opportunities for biobased plastics recycling. Poly(ethylene terephthalate) (PET) is one of the most abundantly produced synthetic polymers and is accumulating in the environment at a staggering rate as discarded packaging and textiles. The properties that make PET so useful also endow it with an alarming resistance to biodegradation, likely lasting centuries in the environment. Our collective reliance on PET and other plastics means that this buildup will continue unless solutions are found. Recently, a newly discovered bacterium, Ideonella sakaiensis 201-F6, was shown to exhibit the rare ability to grow on PET as a major carbon and energy source. Central to its PET biodegradation capability is a secreted PETase (PET-digesting enzyme). Here, we present a 0.92 Å resolution X-ray crystal structure of PETase, which reveals features common to both cutinases and lipases. PETase retains the ancestral α/β-hydrolase fold but exhibits a more open active-site cleft than homologous cutinases. By narrowing the binding cleft via mutation of two active-site residues to conserved amino acids in cutinases, we surprisingly observe improved PET degradation, suggesting that PETase is not fully optimized for crystalline PET degradation, despite presumably evolving in a PET-rich environment. Additionally, we show that PETase degrades another semiaromatic polyester, polyethylene-2,5-furandicarboxylate (PEF), which is an emerging, bioderived PET replacement with improved barrier properties. In contrast, PETase does not degrade aliphatic polyesters, suggesting that it is generally an aromatic polyesterase. These findings suggest that additional protein engineering to increase PETase performance is realistic and highlight the need for further developments of structure/activity relationships for biodegradation of synthetic polyesters.

A. Khaleque, M. Alam, M. Hoque et al.

Abstract Zeolites with the three-dimensional structures occur naturally or can be synthesized in the laboratory. Zeolites have versatile applications such as environmental remediation, catalytic activity, biotechnological application, gas sensing and medicinal applications. Although, naturally occurring zeolites are readily available, nowadays, more emphasis is given on the synthesis of the zeolites due to their easy synthesis in the pure form, better ion exchange capabilities and uniform in size. Recently, much attention has also been paid on how zeolite is being synthesized from low-cost material (e.g., rice husk), particularly, by resolving the major environmental issues. Hence, the main purpose of this review is to make an effective resolution of zeolite synthesis methods together with potential applications in environmental engineering. Among different synthesis methods, hydrothermal method is commonly found to be used widely in the synthesis of various zeolites from inexpensive raw materials such as fly ash, rice husk ash, blast furnace slag, municipal solid waste, paper sludge, lithium slag and kaolin. Besides, future expectation in the field of synthetic zeolites research is also included.

Lingchen Liu, Mingjie Xu, Yuheng Ye et al.

Plastics and microplastics are difficult to degrade in the natural environment due to their hydrophobicity, the presence of stable covalent bonds and functional groups that are not susceptible to attack. In nature, microplastics are more likely to attract other substances due to their large specific surface area, which further prevents degradation from occurring. Some of these substances are toxic and harmful, and can be spread to various organisms through the food chain along with the microplastics to cause harm to them. Degradation is an effective way to eliminate plastic pollution, and a comprehensive understanding of the methods and mechanisms of plastic degradation is necessary, because it is the result of synergistic effects of several degradation methods, both in nature and in consideration of future engineering applications. The authors firstly summarize the degradation methods of (micro)plastics; secondly, review the influence of intrinsic properties and environmental factors during the degradation process; finally, discuss the environmental impact of the degradation products of (micro)plastics. It is evident that the degradation of (micro)plastics still has many challenges to overcome, and there are no mature and effective methods that can be applied in engineering practice or widely used in nature. Therefore, there is an urgent need for research on the degradation of (micro)plastics.

B. Nedjimi

Toxic metal contamination of soil is a major environmental hazard. Chemical methods for heavy metal's (HMs) decontamination such as heat treatment, electroremediation, soil replacement, precipitation and chemical leaching are generally very costly and not be applicable to agricultural lands. However, many strategies are being used to restore polluted environments. Among these, phytoremediation is a promising method based on the use of hyper-accumulator plant species that can tolerate high amounts of toxic HMs present in the environment/soil. Such a strategy uses green plants to remove, degrade, or detoxify toxic metals. Five types of phytoremediation technologies have often been employed for soil decontamination: phytostabilization, phytodegradation, rhizofiltration, phytoextraction and phytovolatilization. Traditional phytoremediation method presents some limitations regarding their applications at large scale, so the application of genetic engineering approaches such as transgenic transformation, nanoparticles addition and phytoremediation assisted with phytohormones, plant growth-promoting bacteria and AMF inoculation has been applied to ameliorate the efficacy of plants as candidates for HMs decontamination. In this review, aspects of HMs toxicity and their depollution procedures with focus on phytoremediation are discussed. Last, some recent innovative technologies for improving phytoremediation are highlighted.

Hamza Rafeeq, N. Afsheen, Sadia Rafique et al.

In the recent era, the increasing persistence of hazardous contaminants is badly affecting the globe in many ways. Due to high environmental contamination, almost every second species on earth facing the worst issue in their survival. Advances in newer remediation approaches may help enhance bioremediation's quality, while conventional procedures have failed to remove hazardous compounds from the environment. Chemical and physical waste cleanup approaches have been used in current circumstances; however, these methods are costly and harmful to the environment. Thus, there has been a rise in the use of bioremediation due to an increase in environmental contamination, which led to the development of genetically engineered microbes (GEMs). It is safer and more cost-effective to use engineered microorganisms rather than alternative methods. GEMs are created by introducing a stronger protein into bacteria through biotechnology or genetic engineering to enhance the desired trait. Biodegradation of oil spills, halobenzoates naphthalenes, toluenes, trichloroethylene, octanes, xylenes etc. has been accomplished using GEMs such bacteria, fungus, and algae. Biotechnologically induced microorganisms are more powerful than naturally occurring ones and may degrade contaminants faster because they can quickly adapt to new pollutants they encounter or co-metabolize. Genetic engineering is a worthy process that will benefit the environment and ultimately the health of our people.

J. Atkinson, Lin Su, Xu Zhang et al.

Zhiji Gao, Jin’an Xu, Hanjie Qiu et al.

Granite sawdust is a by-product in the process of stone processing, which is usually piled up, thus easily causing environmental pollution. To achieve resource utilization, granite sawdust was used as a partial substitution of cement in this work. The effects of different sawdust contents (10–50%) were systematically studied on the pore structure and the mechanical properties of its dry powder mortar. Combined with the grey correlation theory, the correlation between pore size distribution and compressive strength was analyzed. The results showed that the consistency and mechanical properties of the mortar gradually decreased along with the increasing sawdust content, while its critical pore-diameter decreased. The mortar performance was the best when its sawdust content is 10%, which meets the M25 technical requirements. When content reaches up to 30%, the mortar still met the strength standard of M20. Compared to fly ash, the mortar with 30% sawdust as the substitution has a higher water retention rate but lower mechanical strength. The grey correlation analysis indicated that the pores with diameters less than 10 nm and greater than 1000 nm had the most significant impact on the compressive strength.

Eduard Enoiu, Jean Malm, Gregory Gay

We explore the concept of folklore within software engineering, drawing from folklore studies to define and characterize narratives, myths, rituals, humor, and informal knowledge that circulate within software development communities. Using a literature review and thematic analysis, we curated exemplar folklore items (e.g., beliefs about where defects occur, the 10x developer legend, and technical debt). We analyzed their narrative form, symbolic meaning, occupational relevance, and links to knowledge areas in software engineering. To ground these concepts in practice, we conducted semi-structured interviews with 12 industrial practitioners in Sweden to explore how such narratives are recognized or transmitted within their daily work and how they affect it. Synthesizing these results, we propose a working definition of software engineering folklore as informally transmitted, traditional, and emergent narratives and heuristics enacted within occupational folk groups that shape identity, values, and collective knowledge. We argue that making the concept of software engineering folklore explicit provides a foundation for subsequent ethnography and folklore studies and for reflective practice that can preserve context-effective heuristics while challenging unhelpful folklore.

Jorge Melegati

The adoption of Generative AI (GenAI) suggests major changes for software engineering, including technical aspects but also human aspects of the professionals involved. One of these aspects is how individuals perceive themselves regarding their work, i.e., their work identity, and the processes they perform to form, adapt and reject these identities, i.e., identity work. Existent studies provide evidence of such identity work of software professionals triggered by the adoption of GenAI, however they do not consider differences among diverse roles, such as developers and testers. In this paper, we argue the need for considering the role as a factor defining the identity work of software professionals. To support our claim, we review some studies regarding different roles and also recent studies on how to adopt GenAI in software engineering. Then, we propose a research agenda to better understand how the role influences identity work of software professionals triggered by the adoption of GenAI, and, based on that, to propose new artifacts to support this adoption. We also discuss the potential implications for practice of the results to be obtained.

T. Reynolds, P. Richards

T. Lincoln

A classic example of how human intervention in natural processes can have severe unforeseen side-effects comes from the Hawaiian island of Oahu. Coastal armouring structures, designed to prevent shoreline erosion, do indeed do that. But erosional forces instead become concentrated on the beaches in front of them, and the beaches no longer have the continual renewal of sandy substrate from sources locked into the shoreline. About 27 per cent of Oahu's 115 kilometres of beaches have been lost or severely affected in this way over the past 27 years.

Marwan Fahs, Behzad Ataie-Ashtiani, Behzad Ataie-Ashtiani et al.

Sifan Gu, Zhengyu Liu, Ning Zhao et al.

Abstract The rapid CO2 rise during the early deglaciation is often linked to enhanced ventilation by intensified Antarctic Bottom Water (AABW) overturning. The recorded radiocarbon ventilation seesaw during the early deglaciation, which describes improved Southern Ocean and reduced North Atlantic abyssal radiocarbon ventilation, has been interpreted as intensified AABW and reduced North Atlantic Deep Water convections. However, abyssal radiocarbon records also reflect changes in surface reservoir ages and interior water mass mixing. Using isotope-enabled simulations, we show that this seesaw results from weakened AABW overturning and decreased Southern Ocean surface reservoir age. With AABW occupying the abyssal ocean, weakened AABW overturning increases transit time, with the magnitude increasing northward. This transit time increase outpaced the declining $$\Delta ^{14}C_{{atm}}$$ Δ 14 C a t m induced Southern Ocean surface reservoir age decrease in the abyssal North Atlantic, but not in the abyssal Southern Ocean, thus producing a radiocarbon ventilation seesaw. Our results suggest sluggish deep water overturning from both poles during the early deglaciation.

Max Ofsa, Taylan G. Topcu

Systems engineering (SE) is evolving with the availability of generative artificial intelligence (AI) and the demand for a systems-of-systems perspective, formalized under the purview of mission engineering (ME) in the US Department of Defense. Formulating ME problems is challenging because they are open-ended exercises that involve translation of ill-defined problems into well-defined ones that are amenable for engineering development. It remains to be seen to which extent AI could assist problem formulation objectives. To that end, this paper explores the quality and consistency of multi-purpose Large Language Models (LLM) in supporting ME problem formulation tasks, specifically focusing on stakeholder identification. We identify a relevant reference problem, a NASA space mission design challenge, and document ChatGPT-3.5's ability to perform stakeholder identification tasks. We execute multiple parallel attempts and qualitatively evaluate LLM outputs, focusing on both their quality and variability. Our findings portray a nuanced picture. We find that the LLM performs well in identifying human-focused stakeholders but poorly in recognizing external systems and environmental factors, despite explicit efforts to account for these. Additionally, LLMs struggle with preserving the desired level of abstraction and exhibit a tendency to produce solution specific outputs that are inappropriate for problem formulation. More importantly, we document great variability among parallel threads, highlighting that LLM outputs should be used with caution, ideally by adopting a stochastic view of their abilities. Overall, our findings suggest that, while ChatGPT could reduce some expert workload, its lack of consistency and domain understanding may limit its reliability for problem formulation tasks.

Haibo Wang, Zhuolin Xu, Shin Hwei Tan

Refactoring is the process of restructuring existing code without changing its external behavior while improving its internal structure. Refactoring engines are integral components of modern Integrated Development Environments (IDEs) and can automate or semi-automate this process to enhance code readability, reduce complexity, and improve the maintainability of software products. Similar to traditional software systems such as compilers, refactoring engines may also contain bugs that can lead to unexpected behaviors. In this paper, we propose a novel approach called RETESTER, a LLM-based framework for automated refactoring engine testing. Specifically, by using input program structure templates extracted from historical bug reports and input program characteristics that are error-prone, we design chain-of-thought (CoT) prompts to perform refactoring-preserving transformations. The generated variants are then tested on the latest version of refactoring engines using differential testing. We evaluate RETESTER on two most popular modern refactoring engines (i.e., ECLIPSE, and INTELLIJ IDEA). It successfully revealed 18 new bugs in the latest version of those refactoring engines. By the time we submit our paper, seven of them were confirmed by their developers, and three were fixed.

Yvonne Dittrich, Helen Sharp, Cleidson de Souza

Ethnography has become one of the established methods for empirical research on software engineering. Although there is a wide variety of introductory books available, there has been no material targeting software engineering students particularly, until now. In this chapter we provide an introduction to teaching and learning ethnography for faculty teaching ethnography to software engineering graduate students and for the students themselves of such courses. The contents of the chapter focuses on what we think is the core basic knowledge for newbies to ethnography as a research method. We complement the text with proposals for exercises, tips for teaching, and pitfalls that we and our students have experienced. The chapter is designed to support part of a course on empirical software engineering and provides pointers and literature for further reading.

Juan M. Murillo, Jose Garcia-Alonso, Enrique Moguel et al.

As quantum computers advance, the complexity of the software they can execute increases as well. To ensure this software is efficient, maintainable, reusable, and cost-effective -key qualities of any industry-grade software-mature software engineering practices must be applied throughout its design, development, and operation. However, the significant differences between classical and quantum software make it challenging to directly apply classical software engineering methods to quantum systems. This challenge has led to the emergence of Quantum Software Engineering as a distinct field within the broader software engineering landscape. In this work, a group of active researchers analyse in depth the current state of quantum software engineering research. From this analysis, the key areas of quantum software engineering are identified and explored in order to determine the most relevant open challenges that should be addressed in the next years. These challenges help identify necessary breakthroughs and future research directions for advancing Quantum Software Engineering.

Ranim Khojah, Mazen Mohamad, Philipp Leitner et al.

Large Language Models (LLMs) are frequently discussed in academia and the general public as support tools for virtually any use case that relies on the production of text, including software engineering. Currently there is much debate, but little empirical evidence, regarding the practical usefulness of LLM-based tools such as ChatGPT for engineers in industry. We conduct an observational study of 24 professional software engineers who have been using ChatGPT over a period of one week in their jobs, and qualitatively analyse their dialogues with the chatbot as well as their overall experience (as captured by an exit survey). We find that, rather than expecting ChatGPT to generate ready-to-use software artifacts (e.g., code), practitioners more often use ChatGPT to receive guidance on how to solve their tasks or learn about a topic in more abstract terms. We also propose a theoretical framework for how (i) purpose of the interaction, (ii) internal factors (e.g., the user's personality), and (iii) external factors (e.g., company policy) together shape the experience (in terms of perceived usefulness and trust). We envision that our framework can be used by future research to further the academic discussion on LLM usage by software engineering practitioners, and to serve as a reference point for the design of future empirical LLM research in this domain.