Climate plans are the order of the day in the presidential primary campaign because carbon pollution is a global threat of unique proportions. But it’s worth asking whether candidates’ plans are based in the reality of the climate, the economy, and the election.

All three dimensions must come together for any climate plan to achieve its goals—and this is especially true when the subject is electric vehicles (EVs). There is no point in putting forward an EV plan that is so aggressive that it cannot be implemented even under the most auspicious economic circumstances. Nor is there a point in advancing an EV plan that would not yield significant climate benefits. And, if such a plan might hurt a candidate’s chances in the election, it would be worse than pointless.

Following the lead of Governor Jay Inslee, who dropped out of the race earlier this fall, Senators Cory Booker, Bernie Sanders, and Elizabeth Warren said they would require all passenger cars sold in the United States to be zero-emissions by 2030, while Senator Kamala Harris and Mayor Pete Buttigieg set a 2035 deadline.

Quality control and inventory control are equally important to the ongoing success of all manufacturing businesses. Both form the basis of an efficient organization that operates at high productivity levels, minimizes waste, and delivers quality products to meet or exceed consumers’ expectations.

Until a about decade ago, there were layers of quality assurance and quality control steps before products reached the end user. Along with production controls, these steps included quality controls related to warehouse operations, logistics, and inventory verification at retail stores, in order to double-check product quality and order fulfilment accuracy.

Today, more than a million small manufacturers worldwide have forgone any retail sales in favor of a D2C (direct to consumer) model, cutting out warehouse operations and retail stores. The reason is simple: margins. A jewelry manufacturer, for example, selling a bracelet for $20 online, with hard costs of $2, can realize huge profit margins by eliminating the wholesale middleman. That same bracelet would have wholesaled to retailers for $8. But now, while product quality is still a customer expectation, consumers also expect quality delivery and customer service.

Dell is doing it. MasterCard, too. Even universities, not exactly bastions of social media influence, are embracing it. Employee advocacy in social media is gaining currency as an effective way to promote an organization by the very people who work in it. Rather than creating ads or hiring social media influencers to boost a brand, companies like Vodafone and Starbucks to schools like Oslo Metropolitan University (OsloMet) are tapping staff members at all levels to become brand ambassadors, with arguably improved conviction and results.

Weekly CGMP Quiz 1: Part 210 & 211 Subpart A General Provisions. Use with your team for training credit!

This is the first of eleven quizzes on CGMPs that will appear weekly on QA Pharm. Try it yourself, and use it as a discussion tool for your staff groups.

Also, each quiz will have one letter tile at the bottom. Collect all eleven tiles and unscramble the letters for an important message.

When you have completed all 11 quizzes, you will have satisfied the requirement in 21CFR211.25(a) for continuing CGMP training. Be sure to document this training according to your established procedures.

An answer key will be provided after the eleventh quiz to use for further discussion.

On August 29, 2005, I was starting my first semester teaching freshman environmental engineering majors at Humboldt State University in Arcata, California. At the exact same time, Hurricane Katrina hit Louisiana and Mississippi with 190 kph (120 mph) winds and a storm surge in excess of 6 meters (20 feet). Levees failed, flooding more than 80 percent of New Orleans and many surrounding areas. This tragedy left more than 1,800 people dead, many of whom had been trapped in their own homes. It took nearly six weeks for the water to recede, exposing more than 130,000 destroyed housing units.

I spent the rest of the semester (and subsequent ones) discussing with my students the lessons that environmental engineers should learn from Katrina and its aftermath (levees, water treatment, mold, air testing, planning for disasters, and more). Little did I know I would still be dealing with some of the issues revealed by Hurricane Katrina nearly 15 years later as a scientist at the National Institute of Standards and Technology (NIST).

Software as a medical device (SaMD) is a growing sector in medical device technology. Through the use of artificial intelligence and machine learning, SaMD has the power to influence health on a global scale as well as allow for personalization in medicine and life-saving therapies.

Medical device companies developing these products can take advantage of the FDA’s new programs designed to advance trusted companies so they can get products to market efficiently and effectively.

Equally important, if you want to be part of the SaMD trend and its accompanying regulatory pathway, the FDA is clear: Make sure your quality management system (QMS) is exemplary.

Third-party vendors are increasingly working with their own third parties (fourth and fifth parties), spreading your data across many different vendors. This can make your company an easy target for cybersecurity threats, especially if your organization is a hospital or part of the healthcare system. You have to be aware of the risks associated with third parties. If you aren’t, you’re playing with fire.

Failing to address third-party risk can be costly and often just as damaging as risks that stem from within the organization. Thus, it’s critical that you don’t compromise private data in exchange for the convenience of services provided by third parties. These data are especially important in the healthcare industry because confidential records, clinical information, or medical data could end up in the wrong hands.

In today’s factories and warehouses, it’s not uncommon to see robots whizzing about, shuttling items or tools from one station to another. For the most part, robots navigate pretty easily across open layouts. But they have a much harder time winding through narrow spaces to carry out tasks such as reaching for a product at the back of a cluttered shelf, or snaking around a car’s engine parts to unscrew an oil cap.

Now MIT engineers have developed a robot designed to extend a chain-like appendage flexible enough to twist and turn in any necessary configuration, yet rigid enough to support heavy loads or apply torque to assemble parts in tight spaces. When the task is complete, the robot can retract the appendage and extend it again, at a different length and shape, to suit the next task.

The appendage design is inspired by the way plants grow, which involves the transport of nutrients, in a fluidized form, up to the plant’s tip. There, they are converted into solid material to produce, bit by bit, a supportive stem.

Likewise, the robot consists of a “growing point,” or gearbox, that pulls a loose chain of interlocking blocks into the box. Gears in the box then lock the chain units together and feed the chain out, unit by unit, as a rigid appendage.

As artificial intelligence (AI) becomes increasingly ubiquitous in various industry sectors, establishing a common terminology for AI and examining its various applications is more important than ever. In the international standardization arena, much work is being undertaken by ISO/IEC’s joint technical committee JTC 1—Information technology—Subcommittee SC 42—Artificial intelligence, to establish a precise and workable definition of AI. Through its working group WG 4, SC 42 is looking at various use cases and applications. The convener of SC 42/WG 4 is Fumihiro Maruyama, senior expert on AI at Fujitsu Laboratories.

Currently, there are a total of 70 use cases that the working group is examining. Health, for example, is a fascinating area to explore. Maruyama himself describes one use case in which a program undertakes a “knowledge graph” of 10 billion pieces of information from existing research papers and databases in the medical field. The application then attempts to form a path representing the likely development from a given gene mutation to the disease that deep learning has predicted from the mutation.

With the advent of the internet, cloud, and electronic workflows, what is the future of documented management systems? Do we continue with a structure of quality manual, processes, work instructions, and forms and checklists? How do we imagine the future of documented management systems?

For enterprise and site documentation, there’s a need for all entities, from site to department to individuals, to have their own documented management system structure. The documented management system should be a repository of organizational knowledge, in the form of documentation, records, projects, audits, dashboards, customer and/or interested party needs and expectations, calibration data, and much more. How is this possible?

Furthermore, documented flows should give way to virtual electronic workflows that help implement and sustain an integrated management system.