The company was charges with an unfair labour practice for failure to bargain in good faith. The union alleged that the company was engaged in surface bargaining with no intention of entering into a collective bargaining agreement. The company had begun meeting with the union after the NLRB had certified it. Eighteen bargaining sessions were held over an 11 month period. The negotiations did not result in a contract. The parties did reach agreement on a recognition clause; the numbers, rights, duties of union stewards; the use of a bulletin board by the union; pay for jury duty and other leaves of absence; a procedure for processing grievances and arbitrations; and plant visitations by union representatives.

The administrative law judge hearing the case found that the company met at regular intervals and bore no anti-union animus. The company’s conduct away from the bargaining table did not indicate that the company had no intention to conclude an agreement with the union. As there was no evidence of a failure to meet to discuss terms and conditions, the arbitrator had to examine the proposals by the company and by the union to see whether their substance indicated good-faith bargaining. The company’s proposals are briefly outlined as follows:

1. Wages.

The company insisted that it remain in total control over wages. Wage increases were to be determined on the basis of semiannual merit reviews, in which the union would have no participation. The union had proposed a specific wage schedule, but the company would not adopt it.

2. Management rights.

The company retained absolute right to subcontract work, to assign it to supervisors, to abolish jobs, and to transfer, discontinue, or assign any or all of its operations to others. It required the union to relinquish the employees’ statutory right to notice in bargaining over such actions and their effects. Actions taken under the management clause were subject to the grievance procedure only if that right was limited by express contract provision, and there was no such limitation.

3. Zipper clause.

The company proposed a zipper clause, which waived the union’s right to bargain during the life of the agreement over anything that could have been considered mandatory or permissive under existing law.

4. No-strike clause.

The company proposed a no strike clause, including prohibition against a strike for unfair labour or unfair employment practices.

5. Discipline and discharge.

The company rejected the union’s proposal of a standard right to discipline an employee for “just or sufficient cause only.” The company intended to reserve exclusive authority over discharges and discipline in the management rights clause.

6. Layoff and recall.

The company proposed that the layoff and recall of employees would be at the company’s sole discretion.

7. Dues check-off.

The company rejected a union proposal that dues check-off clause be included in the contract.

8. Nondiscrimination clause.

The company rejected a union proposal that stated the company was not allowed to discriminate against union members. The company’s position was that because discrimination was illegal, a clause forbidding it did not need to be included in the contract.

Questions

1. Was the company bargaining in good faith? Explain your answer. 10 marks

2. Which company proposal was the most important in determining the “in good faith” issue? Explain. 10 marks

3. Suggest how principled negotiations techniques could be used in the case. 10 Marks

Life science 2 thx a lot! 1. Factors that support human migration to Mars include A. runaway climate change B. global pandemics C. possible nuclear war D. possible asteroid strikes E. all of the above 2. A key difficulty of preparing a computer system to house human brain information is trying to emulate the signaling pathways of the nervous system. true false 3. Loss of bone mass during aging leads to A. osteogenesis B. osteosarcoma C. osteoporosis D. loss of connective tissue 4. Signs and symptoms of aging can be slowed by A. eating a healthy diet B. exercising C. caloric restriction D. socialization E. all of the above 5. In order for cross-species transmission to occur A. there must be contact between the virus and host B. the infection needs to be amplified within the host C. variants need to be produced in the new host that allow for transfer to other humans D. all of the above 6. The Fermi Paradox attempts to explain the likelihood of finding intelligent life in other galaxies. true false 7. The most basic part of our brain is the part that controls our autonomic functions, referred to as the mammalian brain. true false 8. In the absence of illness, high mental competence is expected to last until approximately what age A. 80 B. 35 C. 65 D. 50 9. Aging reduces all of the following in the circulatory system except A. white blood cells B. hemoglobin C. lymphocytes 10. Progeria and Werner syndrome, which both cause premature aging, are a result of A. genetic causes B. environmental factors C. epigenetics 11. Caloric restriction, exercise, and a healthy diet A. speed up the aging process B. slow down the aging process C. have no effect on the aging process 12. If humans live on Mars, it is hypothesized that in the next 100,000 years, humans will develop A. eye-shine B. smaller nostrils C. smaller eyes

Evaluate Patagonia’s goal to become carbon neutral, in an absolute sense by 2025 and to do so in a way that other interested companies could replicate. 2. How does Patagonia’s status as a privately held benefit corporation either help or hinder its efforts to achieve its goal of carbon neutrality for itself? 3. How does this status affect Patagonia’s efforts to achieve carbon neutrality in a way that other interested companies could replicate? 4. What pathway, or pathways should Patagonia pursue to achieve its goal of becoming carbon neutral itself? Transcribed image text: Patagonia&qpos;s Path to Carbon Neutrality by 2025 Patagonia wants to take a leadership position on perisaps the greatest environmental challenge facing humankind: climate change. The company, which makes outdoor apparel and gear as well as food through its Provisions line, would like to be carbon neutral by 2025. For several years, Patagonia has been working to address its impact on the climate by implementing several initiatives, including those that increase the use of renewable energy at its owned and operated facilities. The company is now iooking to expand its efforts to include its full value chain, which includes emissions not directly controlled by Patagonia. Furthermore, Patagonia wants to reduce its carbon footprint in absolute terms so that, even as the company grows, its carbon footprint does not and instead reaches zero. Patagonia wants to achieve absolute carbon neutrality in a way that other interested companies could replicate. While Patagonia&qpos;s long-term goal encompasses its full value chain, members of the Patagonia leadership team are currently focused on achieving carbon neutrality for a specific range of the apparel and gear production process: from raw materials extraction and production to customer S purchase. That range covers the vast majority of the company&qpos;s greenhouse gas (GHG) emissions and energy use. However, within that range, Patagonia has limited control over emissions. For example, the company controls how much product it orders and, in some instances, how that product is made. However, Patagonia does not own the factories that produce its goods, many of which are located in Asia, where coal and other fossil fuels are the primary energy sources. Different people within Patagonia see different potential pathways to achieving the company&qpos;s carbon neutrality goals and anticipate different challenges. Leadership team members also have varying perspectives on the extent to which Patagonia&qpos;s business lines should relate directly to the company&qpos;s goal, and how the company can best influence other businesses and consumers. Their goal now is to determine the best route forward. Patagonia&qpos;s History and Mission Rock climber Yvon Chouinard and his wife, Malinda Pennoyer, founded Patagonia in 1973, and the Chouinard family still wholly owns the company. In 2011, Patagonia became a Certified B Corporation, meaning it is a for-profit company that meets “rigorous standards of social and environmental performance, accountability, and transparency." In 2012, Patagonia became the first company to register as a benefit corporation in the State of California under the then-newly revised California Corporations Code, which sets specific requirements. For example, the directors and officers of a benefit corporation must consider the non-financial interests of stakeholders, including shareholders, company employees, employees of subsidiaries and suppliers, the local and global environment, and others. Benefit corporations must also prepare a publicly available annual report that complies with an independent, third-party standard. The registration both codifies Patagonia&qpos;s values of activism and transparency and protects the company&qpos;s mission in the eveni of a change in ownership or other corporate succession. The company&qpos;s mission is to “Build the best product, cause no unnecessary harm, use business to inspire and implement solutions to the eavironmental crisis." The company works on a variety of environmental issues, paying particular attention to how its products are made. However, it&qpos;s placing special emphasis on carbon neutrality. "It&qpos;s recognition that, if we as a society don&qpos;t get our carbon emissions under control, if we don&qpos;t work on this climate issue, everything else probably won&qpos;t matter," said Paul Hendricks, Environmental Responsibility Manager for Patagonia. To build the best product, Patagonia emphasizes quality, durability, and multi-functionality. These characteristics relate directly to minimizing the overall impact of Patagonia&qpos;s products because the longer a product is in use, the lower its total environmental footprint, and the more uses a product serves, the fewer total products a person needs to purchase. "Cause no unnecessary harm” is Patagonia&qpos;s way of acknowledging that the mere act of producing anything causes harm, but that Patagonia is committed to doing all it can to reduce that harm. No matter how responsibly a garment is made, making it consumes resources such as petroleum derivatives and energy—but Patagonia has a long history of innovating to reduce these negative impacts. For example, it switched from a petroleum-based material for its Wetsuits to Yulex, a natural rubber material that reduced GHG emissions for those products by 80 percent. Another innovation challenge has related to finding a durable water repellant (DWR) finish for its jackets and other outerwear that has lower chemical impacts than, yet remains as durable as, currently available options. Reduced DWR durability increases the overall impact of the garment by shortening its useful life and causing consumers to purchase replacements more frequently In using business to inspire and implement solutions to the environmental crisis, Patagonia often both innovates, such as with Yulex, and attempts to influence other companies to adopt these innovations. Rather than maintaining long-term exclusivity over new materials or processes it develops, Patagonia shares these with other companies after approximately a year, which Patagonia does for two reasons. The company believes that protecting the environment is the right thing to do, and getting other companies to adopt new materials or processes helps reduce Patagonia&qpos;s costs by increasing total demand. Patagonia also devises other ways to address its environmental impact, which the company also shares. For example, in 2009, Patagonia partnered with other firms in the apparel industry to develop a unified approach to measuring sustainability performance within the footwear and apparel industries. That partnership evolved into the Sustainable Apparel Coalition (SAC), which developed the Higg Index, a suite of self-assessment tools that footwear and apparel companies can use to measure the environmental, social, and labor impacts of manufacturing sites, brand operations, and their products. The index consists of multiple modules, including those that cover environmental policies, materials and design choices, and individual facility operations. The SAC now has more than 200 members, including apparel brands, retailers, academic institutions, and government agencies. The Higg Index has helped factory owners producing apparel for participating brands by reducing the number of assessments they need to complete. It has also helped reduce risk for brands by increasing visibility into their suppliers&qpos; sustainability. “Supply chain management and sustainability management are essentially risk management," explained Rick Ridgeway, Vice President of External Engagement at Patagonia. "Many other brands have recognized that as well, and tirey also know that if you manage that risk right, you get brand rewards. And, as I go out and talk to CEOs of other companies, most of them are now starting to recognize the recruitment and retention benefits of sustainability assessment, too. People coming out of school don&qpos;t want to work for companies that don&qpos;t have some level of sustainability commitment and are transparent about it." Although Patagonia&qpos;s largest and perhaps best-known business line is outdoor apparel and gear, Patagonia also sells food through its Provisions line, which it has done since 2012.10 Provisions relates to Patagonia&qpos;s mission because nowhere, according to Chouinard, is the environmental crisis more pressing than in the food industry." Modern practices such as pesticides, herbicides, fertilizers, and antibiotics have broken the food chain, and Provisions&qpos;s focus is finding solutions to repair the chain, with an emphasis on regenerative organic farming practices that help sequester carbon in soil. Provisions then shares these solutions with the food industry. For example, the company created a beer made with Kernza, a crop that can sequester carbon in soil and prevent erosion because it&qpos;s perennial and has roots that grow several feet into the earth. &qpos;3 Provisions paid for the dossier necessary to support the Generally Recognized As Safe classification for Kernza, which had not previously been put in food products. Patagonia&qpos;s venture fund, Tin Shed Ventures, invested in the equipment necessary to process specialized grains like Kernza, which is difficult to mill on equipment built for other grains. That beer, Long Root Ale, was the first Kernza-based product sold in the world. By developing it, Provisions created the initial supply chain for the grain and demonstrated the proof of concept for its use. Now, General Mills is planning to use Kernza in its products, vastly increasing the amount of farmland on which Kernza is grown. (Patagonia&qpos;s current goal does not include Provisions&qpos;s emissions. For more information, see the section titled "Regenerative Organic Agriculture.") Classifying GHG Emissions Emissions of seven gases including carbon dioxide, methare, and nitrous oxide contribute to climate change. Each has a different atmospheric lifetime and a unique global warming potential, which is measured over a one-hundred-year time herizon. The atmospheric lifetime describes how long a GHG remains in the atmosphere before it breaks down. Global warming potential refers to the extent to which a unit of the GHG affects earth&qpos;s temperature, and it&qpos;s measured relative to that of carbon dioxide, the giobal warming potential of which is set to one. When companies measure and report their GHG emissions, they typically convert emissions from all seven gases into carbon dioxide equivalents, CO2-e. With respect to a single entity such as a company, GHG emissions fall into three categories: Scope 1, Scope 2, and Scope 3. Scope 1 covers GHG emissions from sources the company directly controls. These include emissions from company-owned vehicles and from on-site fuel combustion in, for example, a boiler or other piece of equipment. Scope 2 covers indirect GHG emissions caused by purchased electricity, heat, or steam. Scope 3 covers other indirect emissions, including the extraction and production of purchased materials and fuels, transportation in vehicles not owned or controlled by the company, outsourced activities, and waste disposal.&qpos; For example, a trip made in a Patagonia-owned car would fall under Scope 1. Emissions from electricity powering Patagonia&qpos;s headquarters, retail stores, and other offices fall under Scope 2. The production of the raw materials Patagonia uses in its goods, the work of the finished goods factories, and transportation of goods from factories to customers fall under Scope 3. A trip made by a Patagonia employee on a commercial airline would also fall under Scope 3. (See Exhibit 1 for further examples of operations within each Scope.) As a company, Patagonia&qpos;s long-term goal is to address its Scope 1, Scope 2, and Scope 3 emissions, including those resulting from consumer use and end-of-life. For the purposes of this case, the goal excludes consumer use and end-of-life emissions and therefore covers Scope 1, Scope 2, and part of Scope 3 emissions. Reducing GHG Emissions Companies have several options to reduce their GHG emissions. They can lower energy use by increasing the efficiency of their operations or facilities. They can get the energy they do use from sources with few to no emissions, such as solar and wind. For example, companies can install solar panels on their facilities. They can also purchase, when available, renewable energy from the local utility. One concern Patagonia has with the purchasing approach is that it doesn&qpos;t always ensure new renewable energy is being added to the grid. Another concern relates to the fact that renewable energy on the grid often comes from nuclear or hydroelectric sources, neither of which Patagonia supports. 6 The availability of renewable energy or the grid is also limited. According to Google&qpos;s 2016 environmental report, “many utilities have been slow to create renewable energy purchasing options for customers that want them."!? So, Google began working directly with renewable project developers, signing long-term purchase agreements that supported new capacity. Such projects are called offsite renewable energy generation. Companies can also support renewable energy production by purchasing Energy Attribute Certificates that verify the generation of one megawatt hour of renewable electricity. In North America, EACs are called Renewable Energy Certificates (RECs). Once the energy is generated from the renewable source, it goes into the grid, where it mixes with energy from other sources. The EACs separate the actual cnergy from its environmental attributes, and companies can purchase EACs to claim unambiguous ownership of the environmental attributes of the generated energy. If a company wanted to claim it was powered entirely by renewable energy and only some of the electricity it purchased actually came from renewable sources, it could buy EACs to make up the difference. The Greenhouse Gas Protocol Scope 2 Guidance requires that firms making these claims "redeem, retire, or cancel" the EACs rather than sell them. Several EAC tracking systems exist, and most assign each EAC a unique tracking number. To redeem, retire, or cancel an EAC, a company registers that number as "used" with the tracking system, and that EAC cannot then be sold. When companies purchase renewable electricity directly, they are reducing the carbon impact of their emissions. When they purchase and retire EACs, they are essentially offsetting the non- renewable energy they consume. As such, both types of purchases serve to reduce Scope 2 emissions. However, firms purchasing EACs cannot transfer them from one region to another, a company buying grid electricity in North America would buy RECs to offset its Scope 2 emissions; a company buying grid electricity in Europe would buy Guarantees of Origin (GOs), the European version of an EAC, and so on for each region. If a company buys grid electricity in the U.S., it cannot use a GO to make claims about its U.S. energy use. The Greenhouse Gas Protocol Scope 2 Guidance requires that EACs "be sourced from the same market in which the reporting entity&qpos;s electricity-consuming operations are located and to which the instrument is applied."19 One of the points of EACs is to support renewable energy generation, according to Saskia Feast, Vice President, Western Region at Natural Capital Partners, which works with companies to meet their renewable energy targets, reduce carbon emissions, and achieve carbon neutrality. "If you buy RECs from the U.S. but consume energy somewhere in Africa, it is never going to make any impact on the electrical grid in Africa. It&qpos;s not at all connected. EACs should be purchased from locations that are grid-connected to your operations,” she explained. Companies can also invest directly in renewable energy projects. To date, Patagonia has created and invested in two solar funds, which are a form of offsite energy generation. The programs also generate RECs, some of which the company retires and applies to its energy-consumption footprint. Patagonia does not currently buy EACs, either in the U.S. or elsewhere, because it views the underlying energy generation as not being additional that is, the fee paid for the EAC is not adding new green energy capacity to the grid. The investments in solar funds, however, do meet Patagonia&qpos;s criteria for additionality. (See the section titled “Tin Shed Ventures” for a full description of Patagonia&qpos;s solar fund investment activities.) Reducing energy consumption, enhancing efficiency, and purchasing renewable power, either directly or through EACs, are not sufficient for many businesses to reach carbon neutrality. Offsets are required. Companies buy carbon credits and in turn fund projects that prevent or sequester GHG emissions; one credit equals one metric ton of CO2-e either diverted from entering the atmosphere or sequestered. For example, a project may develop a new forest or grow an existing one. The projects themselves vary widely in nature. Some, for example, capture landfill gas or agricultural methane, some provide low-cost cook stoves to people in the developing world who would otherwise burn wood for cooking and heating. The stoves run on fuel with fewer GHG emissions than wood or other biomass, and, in some cases, run on solar power. Unlike EACs, offsets are transferrable from one region or country to another. An external party typically verifies carbon credits by defining baseline emissions in a place and monitoring those emissions once the projects are implemented to ensure the reductions are genuine. In order for a company to claim the credits as offsets to their emissions, it must retire them rather than sell them to another entity. Patagonia has not yet purchased carbon credits because the company is uncertain that the projects generating the credits are effective. Patagonia has questions about the reliability of verification systems as well as about additionality, leakage prevention, and permanence. In some cases, offsets require people to change their behavior, such as using the new cook stoves, which can make verification difficult. For carbon credits to be additional, it must be clear that the proposed project reduces emissions that would not be reduced through other incentives. For example, a landfill operator may already have plans to install equipment to capture gas, and an investimeni in that project would not result in additional emission reductions. Leakage prevention refers to the idea that a project does not simply shift emissions to another location or activity. For example, protecting one forest could lead loggers to cut down a different one, and the project would have no net impact on emissions. For carbon-offset projects to offer permanence, they must ensure the emissions prevention or carbon sequestration will last; for example, captured gas could leak or a forest could burn. Furthermore, Patagonia prefers to directly address its emissions rather than pay to offset them, especially because Patagonia wants to serve as a leader on achieving carbon neutrality. The company&qpos;s general strategy is to first look for efficiencies, then invest is onsite generation, and then use offsite generation or other mechanisms to address reruining en:issions. However, the company recognizes that it will not be able to eliminate its einissions through energy efficiency, innovation, and other initiatives. Patagonia will need to use mechanismis such as RECs or offsets, despite its concerns about those mechanisms. Patagonia&qpos;s Emissions Several Patagonia employees, including Hendricks, Logan Duran, Senior Manager of Responsibility, Metrics, and Reporting and Elissa Foster, Senior Manager, Product Responsibility, are working with an external company to validate Patagonia&qpos;s GHG emissions covering from raw material extraction and production to customer receipt. Current estimates are available for Scope 1 and Scope 2 emissions, and they are approximately 1,000 and 3,000 metric tons of CO2-e, respectively. Duran and Hendricks have also estimated the approximate Scope breakdowns of the total emissions for a typical apparel brand&qpos;s processes, in percentage terms. Scope Activities Percentage Scope 1 Onsite facilities 1% to 5% Coinpany vehicles <1% Scope 2 Purchased electricity 2% to 4% Scope 3 Raw material production, 80% including extraction of materials or growing of fibers Finished goods construction Transportation of goods from 5% finished goods factories to distribution centers Transportation of goods from 5% distribution centers to stores and customers Business travel 1% to 2% Patagonia has already taken several steps to reduce its Scope 1 and Scope 2 emissions. For example, the company has installed solar panels on many of the buildings at its Ventura, California headquarters; the panels&qpos; output covers about 20 percent of the total energy use of the campus. Patagonia recently installed two solar arrays in Australia, one that produces energy equal to about 75 percent of the energy use of the company&qpos;s local headquarters, and one that produces about the same percentage of the energy use of one of Patagonia&qpos;s stores. The company No 5% is exploring the option of a solar array at its distribution center in Reno, Nevada; the panels would account for about 75 percent of the facility&qpos;s Scope 2 emissions. Patagonia also worked with other tenants at an office building in The Netherlands, where Patagonia has its European headquarters, to persuade the landlord to switch to wind power. Patagonia&qpos;s Bylaws and Decision-Making In addition to its mission statement, which guides the company&qpos;s overai! direction, Patagonia adheres to several other bylaws, by which it is legally bound through its incorporation as a Benefit Corporation in the State of California. The company has also developed a set of approaches to decision-making and program implementation. These are described in detail in Exhibit 2. ro From Raw Materials to Customer Purchase The materials used in Patagonia&qpos;s garments fall into one of two categories: synthetic or natural. Synthetic fabrics include nylon and polyester, both of woich are extracted from oil. The oil is cracked into components and polymerized into pellets that are about the size of a BB. These pellets are extruded into fiber, which is spun into yarn: tlic yarn is then woven or knit into a textile. This process not only relies on oil as an input but also consumes significant amounts of energy, which is typically generated from fossil fuels Natural materials include cotton, wool, iyoce!!," he op, linen, the rubber used to make Yulex, and down. Although the exact breakdown varies from material to material, the most energy-intensive part of the transformation from raw natural material to fabric is typically the processing of inputs into fiber. For example, spinning raw cotton into yarn creates 46.4 percent of the total emissions related to cotton production. (See Exiribit 3 for percentage breakdowns of the emissions related to the production of five of Patagonia&qpos;s materials. The two main ways to reduce emissions in this phase of production would be to make the processing equipment more efficient and to power that equipment with renewable energy sources. Fabric mills vary substantially in their operations, their access to renewable energy, their use of fuel to power on-site machinery, and their interest in reducing their enviroamental impacts. In general, Patagonia is a relatively small purchaser of any one mill&qpos;s output and therefore has only limited influence over its suppliers. Dyeing both natural materials and synthetics is also an energy-intensive part of producing fabrics. As a result, Patagonia has been exploring the potential of solution dyeing, in which fibers are dyed prior to being woven or knit into a fabric. "It&qpos;s a much more efficient process that uses far less water, which means less heating, less cooling, less drying of fabric, all of which reduce energy use," explained Foster. However, switching to solution dyeing creates new challenges. For example, many factories that use the dyeing technique have minimum order requirements, meaning Patagonia would have to commit to dyeing a specific quantity of fabric a certain color. By contrast, when dyeing takes place after fibers are made into a fabric, Patagonia can decide on the quantities and colors it wants later in the production process. In some cases, it is also possible to re-dye fabrics dyed in this manner. If Patagonia needs more garments in one color and fewer in another color than it originally predicted, it has some flexibility to make changes, especially if the in-demand colors are darker than the originally ordered colors. With solution dyeing, though, there is no way to change the color later. Raw Materials: Shifting to Recycled and Renewable Materials To reduce the emissions associated with materials production, Patagonia is increasing its use of renewable and recycled materials. Renewable materials include natural materials; recycled materials can include both renewables and synthetics, such as polyester and nylon, which are the two biggest synthetic materials Patagonia uses. Switching to recycled synthetic materials has the potential to reduce GHG emissions as compared to using virgin materials because it eliminates the energy use necessary io extract oil and process it into fabric. However, switching to recycled synthetic materials may not result in significant GHG emissions reductions, depending on a variety of factors. There are many ways to recycle materials such as nylon and polyester, but they all involve consuming energy. Many large materials recyclers are located in Asia and burn coal for electricity. They also have few incentives to re-engineer their processes to consume less energy because scale is the primary factor driving operational efficiency. Other factors affect the potential GHG-emission savings from using recycled rather than virgin materials, these include the source of the material being recycled, whether the material is post-consumer or post-industrial, and whether the recycling process is chemical or mechanical Patagonia&qpos;s purchases of recycled materials are a tiny share of the total output of these plants, so Patagonia has little, if any, influence over how they operate. Patagonia also faces other challenges in the switch to recycled synthetics, including traceability and verification, without which Patagonia cannot make marketing claims about the recycled content of a garment. Traceability and verification are also important for Patagonia to know the source of the recycled material. Patagonia wants to ensure that the material it is purchasing, be it pre-or post-consumer recycled material, is indeed going into its products for two reasons: one, so the company can be sure its choices are having the intended environmental impact and two, so the company can verify its recycled content claims in accordance with Federal Trade Commission regulations. Furthermore, recycled materials must meet Patagonia&qpos;s quality standards. Many currently available recycled materials don&qpos;t perform as well as virgin materials do. For example, when Patagonia began using recycled nylon in 2007, it had to overcome challenges related to how the material feit against customers&qpos; skin and the fact that it made noise when customers moved. The recycled version was also more expensive than the virgin version. Even today, Patagonia is still working to find ways to increase the recycled nylon content of many of its products. Measuring the costs and benefits associated with using recycled synthetics is also challenging. "It&qpos;s really easy to measure performance, margin, and quality," explained Matt Dwyer, Director of Materials Innovation at Patagonia. "But if I tell you that for next season, I can make one of our equipment lines with one hundred percent recycled materials and a water-free dyeing process, so you&qpos;re going to save one hundred percent of the water involved and the CO2 footprint will go down seventy percent, but it&qpos;s going to cost twenty-five cents more a yard, the question becomes, "How do we assign value to those impact reductions?"" To answer that question, he and his colleagues would look at a variety of metrics, consider whether Patagonia could either absorb the cost increase or raise the finished product price, and assess the value of marketing the environmental benefits of the revised product. “But that&qpos;s a really difficult conversation to have here at Patagonia. It&qpos;s probably much more difficult at another company that&qpos;s counting tenths of a penny,” Dwyer said. “You&qpos;re trying to assign a value to something that&qpos;s somewhat abstract." Leveraging Patagonia&qpos;s Supply Chain For Dwyer, Patagonia&qpos;s brand and supply chain represent important assets on the path to carbon neutrality, both for the company itself and others in the apparel and gear industries. Many such companies, especially the largest ones, are publicly traded, unlike Patagonia Public ownership creates a significant challenge in reducing GHG emissions: gaining management and shareholder support for operational changes that might benefit the environment but would increase costs. If such changes don&qpos;t result in a differentiated product, the challenge only grows. When evaluating potential operational changes, large, publicly traded apparel companies are often looking at tenths of a penny per garment, according to Dwyer. As a result, any potential nuovation that could reduce GHG emissions needs to fit into a company&qpos;s existing operations without increasing costs or creating any other type of disruption. Thanks in part to private ownership and in part to its owners&qpos; values, Patagonia is willing and able to research and develop these innovations to encourage change and fulfill the third part of its mission statement. But, it also needs these other companies to adopt its innovations in order to gain a volume-based price break for itself. “Our strategy is around trying to reduce the activation energy for other companies as much as possible. That&qpos;s a matter of showing technical and product feasibility and doing all the work required in investigating scaling. We also have the ability to make equity investments in startups who are likeminded and working on these things, but when it comes down to it, whether it&qpos;s for our costing or to fulfill our mission statement, we need other folks to adopt it," Dwyer elaborated. Developing options that seamlessly integrate into other companies&qpos; operations is only part of what&qpos;s necessary to drive adoption. "It really comes down to, "How do you find people who care?"" Dwyer said. Patagonia has recently succeeded in influencing the apparel industry to increase the adoption of greener chemistry practices through Beyond Surface Technologies, a company Patagonia partially owns through its venture fund. Dwyer credits two factors for the success: Beyond Surface Technologies&qpos;s environmentally focused mission and its development of scalable chemistry products. Innovating a Natural Source for Synthetic Materials As Dwyer and his team work to ensure the switch to recycled synthetics does indeed reduce GHG emissions, they are also looking further into the future towards bio-based polymers. He expects that within the next three to five years, availability and pricing of these polymers will dramatically improve. Biopolymers come from natural oils or sugars; with the right process, they could be made into the same molecules that result from fossil fuel based polymers. With such a process, Patagonia could make biopolymer-based products with the same durability and other characteristics it now gets from synthetic-based products. For biopolymers to work for Patagonia, the result of the production process is not all that matters. The biopolymers need to come from plants that aren&qpos;t genetically modified because Patagonia opposes genetically modified organisms and would not use genetically modified raw materials in its products. The plants also need to be grown in a sustainable way that&qpos;s traceable and verifiable, and the resulting materials need to be cost effective and scalable. Patagonia ran into several obstacles related to these criteria when it was developing Yulex, the natural rubber that replaced neoprene in its wetsuits. Initially, Yulex came from a plant grown in the Arizona desert, but it took four years for a farm to scale up to grow the plant, and the materia! cost about ten times as much as the next-best alternative. Patagonia then switched to natural latex derived from trees. In making that transition, Patagonia had to find a plantation tirat operated in the most sustainable way possible, not an easy task when the biggest buyers of commodity rubber base their decisions on cost and availability rather than environmental impact. "Establishing the supply chain was the most difficult part," Dwyer said. "We knew we couid make the product because we&qpos;d already done it with this other rubber source, but getting into ruüher production at our teeny scale was pretty tough.” Many of the other companies researching and developing biopolymers are energy companies, and they also base purchasing decisions primarily on cost and availability. At the end of the useful life of a biopolymer-based product, another process will ideally come into play, one that composts the garment. "Ideally, I&qpos;d get both something that lasts as long as I need it to, and when it&qpos;s done, goes to the right place and turns into the right thing. If that&qpos;s what we can achieve, we&qpos;ve done something special," Dwyer said. Finished Goods Factories and Textile Suppliers Approximately 85 factories, most of which are located in Asia, assemble fabrics, trims, and other inputs into Patagonia&qpos;s apparel and gear." Another 200 suppliers, most of which are also located in Asia, provide textiles. These factories emit GHGs in two ways: by purchasing electricity from the local grid to run equipment and by burning fuel to run on-site equipment. The majority of purchased electricity comes from fossil fuels, and the factories have no direct control over how that electricity is generated. A few factories have installed solar panels, however, which gives them control over the source of at least some of their consumed energy. Patagonia, in turn, does not have direct control over the operations of these contracted factories. All of the factories Patagonia works with also manufacture goods for other brands, and, in order to manage risk, most finished goods factories avoid taking on too much work from any one brand. Therefore, Patagonia&qpos;s influence, based solely on purchasing power, over an individual factory is at least somewhat limited. Patagonia does seek suppliers that share its values, however. The company builds long-term relationships with the factory owners, is in regular communication with factory management, and visits each location multiple times twice a year. All Patagonia suppliers must agree to participate in Patagonia&qpos;s Chemical Environmental Impact Program (CEIP). Through this program, Patagonia asks factories to measure and disclose their energy consumption through the Higg Index. Patagonia and other members of the SAC that share the same factories have access to this information. The CEIP also requires suppliers to take progressive steps to improving their environmental practices, moving from "better” to “best." Patagonia expects suppliers to measure energy use, calculate GHG emissions, and set targets for reducing both.22 Patagonia considers those factories that show proof of energy and emissions reductions to be at the "best" stage with respect to that aspect of environmental performance. Verification is primarily done using the bluesign standard, a certification that focuses on resource productivity, consumer safety, water emissions, air emissions, and occupational health and safety.?? Many, but not all, suppliers are improving environmental performance, and Patagonia works with its suppliers to enhance that performance. However, not all factories have adopted bluesign or another certification. When it comes to other apparel brands, Elisabeth Mast, Patagonia&qpos;s Senior Director of Sourcing, notes that they often select suppliers based on different criteria than what Patagoria requires. For example, Patagonia emphasizes quality when selecting finished goods factories, but many brands, especially those making commodity products, seek the lowest-cost producers. Many large brands also work with far more factories than Patagonia does, and&n

1) A fast-food chain has been developing a new dessert to add to their menu. They have completed test marketing and are now fully introducing a complete marketing strategy and launching the product. The product is in which stage of the product development process? a) product development b) commercialization c) product analysis d) idea screening e) test marketing   2) When Lexa Beauty promotes its facial wash and lotion to adolescents, it emphasizes acne control and clear skin. However, when it promotes its products to adults, it emphasizes wrinkle control and firm skin. This is an example of how a) different advertising media can be used to reach a desired audience. b) characteristics of the people in the target audience influence advertisement content and form. c) the advertising message may include hard-hitting, high-impact language and symbols to increase large sales. d) the advertising message may use repetition of the brand name to increase brand awareness. e) important it is for advertisers to use meaningful, familiar, and attractive words, symbols, and illustrations to target the right audience.

Part VI: Compare algorithms, and try to speed things up! In this last part of the project, you will write code to facilitate the comparison of the different state-space search algorithms, and you will also attempt to speed things up so that your code can more easily solve puzzles that require many moves. Your tasks In eight_puzzle.py, write a function named process_file(filename, algorithm, param). It should take the following three inputs: a string filename specifying the name of a text file in which each line is a digit string for an eight puzzle. For example, here is a sample file containing 10 digit strings, each of which represents an eight puzzle that can be solved in 10 moves: 10_moves.txt a string algorithm that specifies which state-space search algorithm should be used to solve the puzzles ('random', 'BFS', 'DFS', 'Greedy', or 'A*') a third input param that allows you to specify a parameter for the searcher – either a depth limit (for the uninformed search algorithms) or a choice of heuristic function (for the informed search algorithms). Your function should open the file with the specified filename for reading, and it should use a loop to process the file one line at a time. We discussed line-by-line file processing earlier in the semester. For each line of the file, the function should: obtain the digit string on that line (stripping off the newline at the end of the line) take the steps needed to solve the eight puzzle for that digit string using the algorithm and parameter specified by the second and third inputs to the function report the number of moves in the solution, and the number of states tested during the search for a solution In addition, the function should perform the cumulative computations needed to report the following summary statistics after processing the entire file: number of puzzles solved average number of moves in the solutions average number of states tested For example: >>> process_file('10_moves.txt', 'BFS', -1) 125637084: 10 moves, 661 states tested 432601785: 10 moves, 1172 states tested 025318467: 10 moves, 534 states tested 134602785: 10 moves, 728 states tested 341762085: 10 moves, 578 states tested 125608437: 10 moves, 827 states tested 540132678: 10 moves, 822 states tested 174382650: 10 moves, 692 states tested 154328067: 10 moves, 801 states tested 245108367: 10 moves, 659 states tested solved 10 puzzles averages: 10.0 moves, 747.4 states tested (In this case, because BFS finds optimal solutions, every solution has the same number of moves, but for other algorithms this won’t necessarily be the case.) Notes/hints: You can model your code for solving a given puzzle on the code that we’ve given you in the eight_puzzle driver function. In particular, you can emulate the way that this function: creates Board and State objects for the initial state calls the create_searcher helper function to create the necessary type of searcher object, and handles the possible return value of None from that function Important: Make sure to create a new searcher object for each puzzle (i.e., for each line of the file). Otherwise, the searcher will still have information inside it from previous searches when it starts to solve a new puzzle. When calling the searcher object’s find_solution method, you should do so as follows: soln = None try: soln = searcher.find_solution(s) except KeyboardInterrupt: print('search terminated, ', end='') Making the call to find_solution() in this way will allow you to terminate a search that goes on too long by using Ctrl-C. In such cases, soln will end up with a value of None (meaning that no solution was found), and you should make sure to properly handle such cases. You should not use a timer in this function. This function should not return a value. Testing your function: If you haven’t already done so, download the 10_moves.txt file, putting it in the same folder as the rest of your files for the project. Try to reproduce the results for BFS shown above. Try applying Greedy Search to the same file. You may find that it takes Greedy a very long time to solve some of the puzzles, at least when using h1 (the num-misplaced-tiles heuristic). If this happens, use Ctrl-C as needed to terminate the problematic searches. When we processed 10_moves.txt using our implementation of Greedy, we ended up using Ctrl-C to terminate two of the searches: >>> process_file('10_moves.txt', 'Greedy', h1) 125637084: 204 moves, 658 states tested 432601785: 12 moves, 13 states tested 025318467: search terminated, no solution 134602785: 78 moves, 221 states tested 341762085: 26 moves, 339 states tested 125608437: 162 moves, 560 states tested 540132678: 68 moves, 749 states tested 174382650: search terminated, no solution 154328067: 10 moves, 16 states tested 245108367: 48 moves, 49 states tested solved 8 puzzles averages: 76.0 moves, 325.625 states tested It’s also possible for none of the puzzles to have a solution, and you should handle that situation appropriately. For example, this can happen if you impose a depth limit that is too small: >>> process_file('10_moves.txt', 'DFS', 5) # depth limit of 5 125637084: no solution 432601785: no solution 025318467: no solution 134602785: no solution 341762085: no solution 125608437: no solution 540132678: no solution 174382650: no solution 154328067: no solution 245108367: no solution solved 0 puzzles Note that you can’t compute any averages in this case, so you shouldn’t print the averages line in the results. Create a plain-text file named results.txt, and put your name and email (and those of your partner, if any) at the top of the file. Conduct an initial set of experiments in which you try all of the algorithms on the puzzles in the following files: 5_moves.txt - puzzles that can be solved in 5 moves 10_moves.txt - puzzles that can be solved in 10 moves 15_moves.txt - puzzles that can be solved in 15 moves More specifically, you should run the following algorithms on each file: random BFS DFS with a depth limit of 20 DFS with a depth limit of 50 Greedy (using h1 – the num-misplaced-tiles heuristic) A* (using the same heuristic) Note that it may be necessary to use Ctrl-C to terminate searches that take too much time. You might want to pick a given amount of time (e.g., 30 seconds or 1 minute), and use Ctrl-C to terminate any search that doesn’t complete in that time. In your results.txt file, create three tables that summarize the results of these initial experiments. Use a separate table for each file’s results. For example, the results for 5_moves.txt should be put into a table that looks like this: puzzles with 5-move optimal solutions ------------------------------------- algorithm num. solved avg. moves avg. states tested ------------------------------------------------------------------------ random BFS DFS (depth limit 20) DFS (depth limit 50) Greedy Search (using h1) A* (using h1) Below these tables, write a short reflection (one or two paragraphs) in which you summarize the key points that are illustrated by the results. For example, you might discuss whether the algorithms produce reliably optimal results, and how much work they do in finding a solution. There’s no one correct reflection; we just want to see that you have reflected intelligently on the results and drawn some conclusions. Even informed search algorithms like Greedy Search and A* can be slow on problems that require a large number of moves. This is especially true if the heuristic function used by the algorithm doesn’t do a good enough job of estimating the remaining cost to the goal. Our h1 heuristic function–which uses the number of misplaced tiles as the estimate of the remaining cost–is one example of a less than ideal heuristic. For example, consider the following two puzzles: Both of them have 4 misplaced tiles (the ones displayed in red), but the puzzle on the left can be solved in 4 moves, whereas the puzzle on the right requires 24 moves! Clearly, it would be better if our heuristic could do a better job of distinguishing between these two puzzles. Come up with at least one alternate heuristic, and implement it as part of your classes for informed searchers (GreedySearcher and AStarSearcher). To do so, you should take the following steps: As needed, add one or more methods to the Board class that will be used by your new heuristic function. (Adding a new method to the Board class is not required, but it can be helpful to add one so that the heuristic function can obtain the information needed for its estimate.) Add your new heuristic function(s) to searcher.py, and follow these guidelines: Continue the numbering scheme that we established for the earlier heuristic functions. Call your first alternate heuristic function h2, your next heuristic function (if any) h3, etc. Make sure that each heuristic function is a regular function, not a method. In addition, make sure that it takes a single State object and returns an integer. When conducting tests using a new heuristic function, use its name in the same ways that you would use h0 or h1. For example: >>> g = GreedySearcher(h2) >>> eight_puzzle('142358607', 'Greedy', h2) >>> process_file('15_moves.txt', 'A*', h2) You are welcome to design more than one new heuristic function, although only one is required. When testing and refining your heuristic(s), you can use the files that we provided above, as well as the following files: 18_moves.txt - puzzles that can be solved in 18 moves 21_moves.txt - puzzles that can be solved in 21 moves 24_moves.txt - puzzles that can be solved in 24 moves 27_moves.txt - puzzles that can be solved in 27 moves. Compare the performance of Greedy and A* using the h1 heuristic to their performance using your new heuristic(s). Keep revising your heuristic(s) as needed until you are satisfied. Ideally, you should see the following when using your new heuristic(s): Both Greedy and A* are able to solve puzzles more quickly – testing fewer states on average and requiring fewer searches to be terminated. Greedy Search is able to find solutions requiring fewer moves. A* continues to find optimal solutions. (If it starts finding solutions with more than the optimal number of moves, that probably means that your heuristic is overestimating the remaining cost for at least some states.) Although you are welcome to keep more than one new heuristic function, we will ultimately test only one of them. Please adjust your code as needed so that the heuristic function that you want us to test is named h2. Also, please make sure that we will still be able to test the num-misplaced-tiles heuristic if we specify h1 for the heuristic. In your results.txt file, briefly describe how your best new heuristic works: heuristic h2 ------------ This heuristic ... If your code includes other alternate heuristics, you are welcome to describe them as well, although doing so is not required. Conduct a second set of experiments in which you try both your new heuristic function(s) and the h1heuristic function on the puzzles in the four new files provided above (the ones that require 18, 21, 24, and 27 moves). In your results.txt file, create four tables that summarize the results of these experiments. Use a separate table for each file’s results. For example, the results for 18_moves.txt should be put into a table that looks like this: puzzles with 18-move optimal solutions -------------------------------------- algorithm num. solved avg. moves avg. states tested ---------------------------------------------------------------------- Greedy (heuristic h1) Greedy (heuristic h2) # Greedy with any other heuristics A* (heuristic h1) A* (heuristic h2) # Greedy with any other heuristics Below these tables, write a short reflection (one or two paragraphs) in which you summarize the key points that are illustrated by the results. Here again, there is no one correct reflection; we just want to see that you have reflected intelligently on the results and drawn some conclusions.

The health and safety executive s HSE safety culture maturity model SCMM is described in offshore technology Report 2000 /049 The SCMM is a tool that puts the focus on improving behavior and culture As a result, it should only be adopted by organizations that at least have safety basics in place. The SCMM is comprised of 5 levels Regardless of whether your

Using LC-3 Programming Exercise 1 Use .BLKW to set up a remote array of 10 values, starting at memory location x4000, as in lab 3. Now programmatically populate the array with the numbers 0 through 9 (note - NOT the characters '0' through '9'!) – i.e. hard-code just the first value (0), then calculate the rest one at a time, storing them in the array as you go. Remember the proper way of setting a register to 0! After you've stored them all, grab the seventh value (i.e. 6) and store it in R2. Clearly, you can't access this location via a label, so you'll need its actual address. How will you obtain that? And how will you use that address to get the value stored there? As always, step through your program and examine the values as they are stored in the array, and examine the final value stored in R2, to make sure your program works as expected. Exercise 2 You'll notice that Exercise 1 didn't ask you to output to console the array you built. Why not? Because as you know by now, numbers are not characters! So now copy your exercise 1 code into lab4_ex2.asm, and add an output loop, making it output the characters corresponding to the numbers stored in your array. Exercise 3 Let's try another modification of our well-used array program from Exercise 1: This time, instead of calculating and storing the numbers from 0 to 9 in the array, calculate and store the first ten powers of 2, starting with 20 = 1 in array index 0. Finally, grab the seventh value (26) from the array, and store it in R2. In order to do this, you will have to figure out how to calculate powers of 2. Some hints: Mathematically speaking: How do I obtain 2n+1 if I know 2n? What LC-3 operation could I use to multiply a number by 2? As always, place a breakpoint in your program, and step through it, examining the values as they are being stored in the array, and examine the final value stored in R2,  to make sure your program works as expected. Pay attention to both the decimal and hex representations of the values being stored. You already understand that you can't simply output the values in the array to the console “as is”, so we have to manipulate them somehow to turn them into characters. But this time all but the first four are multi-digit numbers when represented as decimal values, so our trick from the last exercise won't work – it can only convert the numbers from 0 to 9 into the single-digit ascii characters '0' through '9'.  Exercise 4 For now, we will instead observe what happens if we attempt to do what we just said can't be done - output the contents of the array "as is", i.e. as if they were ascii codes (which they are not!). Copy your exercise 3 code into your lab4_ex4.asm file, and add a second loop that loads the content of each element of the array into R0 and outputs it to the console using OUT. Now place a breakpoint at the start of your display loop and step through it: You will need to keep an eye on the Console to understand what is going on!! Please add comments!!!