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2022 EnVision Boards

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Isaiah Bell
Isaiah Bell

LS Studios Collection - Other LS Issues Part D [BEST]

Engineers can tackle simulations involving material failure and look at how the failure progresses through a part or through a system. Models with large amounts of parts or surfaces interacting with each other are also easily handled, and the interactions and load passing between complex behaviors are modeled accurately. Using computers with higher numbers of CPU cores can drastically reduce solution times.

LS Studios Collection - Other LS Issues Part D

The smoothed particle Galerkin (SPG) method is a new Lagrangian particle method for simulating the severe plastic deformation and material rupture taken place in ductile material failure. The Peridynamics method is another compelling method for brittle fracture analysis in isotropic materials as well as certain composites such as CFRP. These two numerical methods share a common feature in modeling the 3D material failure using a bond-based failure mechanism. Since the material erosion technique is no more necessary, the simulation of the material failure processes becomes very effective and stable.

Many studies reported possible solutions for improving the SWM in developing countries, such as organic waste buyback programs, with compost or biogas production [14], implementation of waste-to-energy plans and technologies [15], waste-to-energy in parallel with recycling of glass, metals, and other inert [16], production of energy from biomass waste by making briquettes [17], involvement of the integration of waste pickers with legal incentives [18], among others. However, many barriers still remain for improving formal collection, treatment and final disposal [19]. Therefore, environmental contamination remains a big issue worldwide, while common solutions should be identified and implemented considering SWM patterns appropriate for each context.

Many reviews were published about SWM in developed and developing countries and about environmental contamination from waste. In particular, about char fuel production [20], management of waste electric and electronic equipment (WEEE) [21], food waste management [22] and treatment [23], recycling of used batteries [24], inclusion of the informal sector [25] and the risks that such activity pose for vulnerable informal workers [26], atmospheric pollution due to SWM [27], household hazardous waste management [28] and healthcare waste (HW) management [29], among others. The novelty of the narrative review presented in this article is its focus on the integrated assessment of these waste streams, analyzing the global issues affecting the environment and the public health, giving attention to the operational risk of the informal recycling sector. Concentration of contamination in water, air and soil are provided, as well as waste quantities and amounts dumped in developing cities or recycled by the informal sector. Results allow suggesting directions for future SWM improvements, considering its planning as an integrated system and providing examples of the consequences of its inadequate implementation.

These issues are visible worldwide. In Banjul (Gambia) the dump site is located in a densely populated area, visible to the residents [39]. It has a negative visible impact on inhabitants and tourists visiting the country. In particular, the smoke from burning debris is the biggest issue, which covers parts of the residential areas, affecting also the life quality of the population. Indeed, the citizens are affected by the smoke from burning debris and the smell of decomposing waste. The nuisances are worst during the rainy period as the area becomes infested with flies and insects. Run off from the dump site with contaminants dissolved inflow into water bodies, while the leachate contaminates the soil and groundwater. Moreover, environmental contamination is due to the high level of fecal and total coliform that polluted the wells located near the site. The households that live around the dump site use well water for various purposes, although with high level of coliforms attributed to the proximity to the dump site [39].

In the West Bank (Palestine), a study shows that 82.2% of HW is disposed of in (unsanitary) dump sites and only 17.9% of healthcare facilities dispose of their waste more than 7 times a week, the frequency recommended by the WHO. Therefore, the final disposal locations in the West Bank are uncontrolled final disposal sites, which are randomly distributed throughout the region, with poor precautions for transporting and colleting the HW [85]. In Ibadan, Nigeria, more than 60% of HW handlers did not discriminate between HW and MSW during collection and handling stages. Similarly, 66% dispose of HW with MSW at the final disposal site (open dumps). Incidences of contacting diseases are prevalent among waste handlers, compared to incidence of other hospital staff, with high incidences of viral blood infections, such hepatitis B and C. Within the open dump sites, technical and hygienic considerations are neglected or absent. For instance, several waste pickers were observed collecting HW for reselling materials considered recyclable, to pass-on to unsuspecting low-income patients. Moreover, leachate from waste disposal sites could be infiltrating and contaminating groundwater resources [86]. In Dhaka, Bangladesh, HW is collected by waste pickers who sort the waste through the bins searching for recyclables and reusable items (syringes, blades, knives, saline bags, plastic materials and metals). Scavenging activities were again observed sorting through the open dumping disposal sites, increasing the risk of diseases (Figure 3). The study reported that both scavengers and recycling operators had any knowledge of the risks from HW exposure. Employers of recycling operators did not consider occupational health and safety training for their employees. The situation was still more worrying among the marginal groups of the society [87].

The challenges facing the developing countries in WEEE and used batteries management include the absence of infrastructure for appropriate waste management, lack of legislation dealing specifically with these waste fractions, the absence of any framework for end-of-life product take-back or implementation of extended producer responsibility (EPR) [100]. Moreover, the growing rate of WEEE amount in developing countries is destined to increase in the next future [101]: A great amount (almost 50%) of current WEEE yearly generated by developed countries continues to be illegally transferred in developing countries, volumes that remains unknown; New electric and electronic products will substitute soon the current ones, influencing both collected volumes, type of recovered materials and recycling processes; Innovative materials composing WEEE, that are currently not correctly managed during their end-of-life (ending into landfills); some electronic parts in WEEE are not again correctly disassembled or recovered [101]. In summary, many challenging issues of WEEE and used batteries management can be detected in developing countries [102]:

The activities of the informal sector regard the degree of formalization, from unorganized individuals in dumpsites, to well organized cooperatives. Therefore, issues such as exploitation by middlemen, child labor and high occupational health risks need to be challenged for addressing sustainability [144]. Globally, SWM remains a negative economy, where individual citizens pay the cost, the financial viability of recycling is disputed, and the sector remains vulnerable to great price volatility. Most of the collection systems in developed countries are subsidized, and also result in substantial exports of recyclables in global secondary resources supply chains. Moreover, if taxes, health insurance, child schooling and training provisions, management costs and other typical costs are included within the informal waste sector, it is not clear if the sector come back to being unsustainable economically [144].

Although he considered the house ugly and uncomfortable, it was spacious enough both to set up his studio in the dining room and to accommodate the collection of china and clocks that he had inherited from his mother; he stayed there until his death almost 30 years later.[24][25]

He was a secretive and mischievous man who enjoyed stories irrespective of their truth.[27] His friends observed that his anecdotes were more notable for humour than accuracy and in many cases he set out deliberately to deceive. His stories about the fictional Ann were inconsistent and he invented other people as frameworks on which to hang his tales. The collection of clocks in his living room were all set at different times: to some people, he said that this was because he did not want to know the real-time; to others, he claimed that it was to save him from being deafened by their simultaneous chimes.[26] The owner of an art gallery in Manchester who visited him at his home, The Elms, noted that while his armchair was sagging and the carpet frayed, Lowry was surrounded by items such as his beloved Rossetti drawing, Proserpine, as well as a Lucian Freud drawing located between two Tompion clocks.[28]

A dramatic increase in computing power has enabled new areas of data science to develop in statistical modeling and artificial intelligence, often called Machine Learning. Machine learning covers predictive and descriptive learning, and bridges theoretical and empirical ideas across disciplines. We will focus on concepts and methods for predictive learning: estimating models from data to predict unknown outcomes. Model types will include decision trees, linear models, nearest neighbor methods, and others as time permits. We will cover classification and regression using these models, as well as methods needed to handle large datasets. Lastly, we will discuss deep neural networks and other methods at the forefront of machine learning. We situate the course components in the "data science life cycle" as part of the larger set of practices in the discovery and communication of scientific findings. The course will include lectures, readings, homework assignments, exams, and a class project. Most of the course activities will use Python with the Pandas library, which students should already be proficient using. Students will learn how to use the scikit-learn Python library for machine learning during this course. 041b061a72


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