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Humans have been engineering yeast “for thousands of years,” says Jef Boeke, a researcher with New York University’s medical center who is one of the world’s top yeast biology experts. At first, I thought he was exaggerating. Yeast has been ubiquitous in science labs for decades now, studied in every possible way, like a microscopic lab rat, and I thought Boeke was referring to that.
But he was referring to a more basic sort of manipulation: humans have been growing yeast for their own ends since they figured out how to brew beer and bake bread. “So we have this ancient industrial relationship with this organism,” he says.
Now he has taken the relationship to a whole new level. Boeke recently led a team of biologists in designing and building, from scratch, one chromosome of brewer’s yeast’s DNA. (A chromosome is an individually-packaged portion of a creature’s DNA, like the X or Y chromosomes in humans.) The man-made yeast chromosome represents about three percent of all of the DNA that makes a yeast. This is the first time scientists have been able to assemble a chromosome from a creature as complicated as a yeast.This is the first time scientists have been able to assemble a chromosome from a creature as complicated as a yeast.
“The synthesis and design of the first eukaryotic chromosome is obviously an exciting milestone,” says Farren Isaacs, a cell biologist at Yale University who was not involved in Boeke’s team. “Eukaryotic” refers to the grouping of life that yeast belong to.
You might remember that in 2010, the J. Craig Venter Institute built all of the DNA for a bacterium from scratch. Yeasts are a step up from bacteria. They’re single-celled critters like bacteria, but, among other things they do differently, they manage their DNA in a more complicated way. That lets them do more with same building blocks.
Yeast and bacteria are different enough that scientists give them two different designations. Bacteria are called prokaryotic. Prokaryotes are among the world’s simplest cells, akin to the very first living things to squiggle on the face of the Earth. Yeasts, on the other hand, are eukaryotic, a group of living things that encompasses everything from them to plants to people.
Microscope Photo of Yeast
The yeast are dyed blue.
That said, building the DNA of a eukaryote isn’t that different from building the DNA of a prokaryote. “When it comes down to the actual synthesis,” Boeke says, “DNA is DNA. If you can synthesize prokaryotic DNA, you can basically synthesize eukaryotic DNA.”
To check that the synthetic chromosome is a workable blueprint for yeasty life, Boeke and his colleagues put it back into yeast from which they had removed the natural version of their artificial chromosome. The natural-artificial hybrid yeast grew and reproduced like its wild cousins. “It looks like it, it behaves like it, it smells like it,” Boeke says. “Basically, you wouldn’t know the difference unless you take the next step and introduce what we call the genome scrambling system into it.”
It’s not immediately clear where scientists outside of the team will take this next. Boeke’s lab has its own plans, of course. It’s long worked on building all of the DNA for a yeast, making steady progress. In 2011, not long after the announcement of the world’s first artificial bacterium chromosome, Boeke’s lab announced it had made one arm of a yeast chromosome. It hopes to manufacture all 16 of yeast’s chromosomes over the next few years.
Beyond that, Boeke hopes the DNA-scrambling technology the team created will become a new bioengineering tool for researchers and biotech companies. Scientists and companies have tweaked yeast DNA to make the creatures produce medicine, biofuels and other chemicals people want. Maybe DNA scrambling will help bioengineers find and create yeast that are a little more efficient, or a little hardier, Boeke says.
Isaacs thinks that in the future, bioengineers will combine editing existing DNA—the type of bioengineering that’s most common now—writing new DNA, which is what Boeke did.
Sounds like yeast will be a part of human biotech for many years yet.
Boeke and his colleagues published their work on the yeast chromosome in the journal Science.
_Corrected March 27: This post originally said Jef Boeke is a researcher at Johns Hopkins University. Boeke has moved from Johns Hopkins and is now with New York University’s Langone Medical Center. _
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A risk register is a record employed as a financial planning tool to detect probable development difficulties. This approach tries to detect, assess, and resolve hazards jointly prior to them becoming issues. While risk management is typically associated with enterprises, it is also useful in new products and production.
A risk register file, also known as a risk analysis journal, keeps track of possible hazards within an enterprise. It also provides knowledge about the risk’s importance and the chance of occurrence.
A risk register for a venture not only needs to recognize and assess hazards but also give concrete mitigations. As a result, if the risk escalates, your group will be equipped with answers and enabled to address the challenges.When to Use the Risk Register?
A risk registry is useful in a variety of situations. It must typically be utilized (or ready only when requested) in each project. It can be utilized for equally small and big enterprises, albeit the format of your contingency plan will vary based on the extent and sophistication of your operation.
Although a project may simply demand basic threat data such as incidence, importance, and options, a project scope may have about ten distinct letter fields.
Inadequate preference − Risks such as poor communication and planning mistakes can expose initiatives to scope creep and missed deliveries.
Intermediate documentation − Unexpected or extra work might lead teams to trouble with efficiency and generate confusing goals.What Are All the Risks?
Involve typical risk areas in your risk registration record so you can be ready when they arise. Learn what these dangers are and decide what may apply to your group.Delay Schedule
If programming mistakes and inefficiencies go unrecognized, they could turn into a major issue when constraints are violated. Timeframe and team planning tools, for example, can assist avoid programming problems at an early stage.
Backlogs in the planning phase might lead to −
Rushing deadlines− It’s worse than a job not being adequately performed, which may lead to unfulfilled targets and poor work.
Ambiguity− Without a solid timetable in play, employees might get swamped and confused.
Creating a timetable may assist in keeping outputs on schedule for both everyday activities and one-time initiatives.Un-planned Risks
We’ve each been in situations where work has gone over budget. It’s a frequent danger that is easily mitigated if correctly monitored. Detecting unforeseen processes as soon as possible helps you to correctly allocate the responsibility to the project manager.
Besides a suitable risk register, you may encounter −
Skipped objectives: If the material falls between the gaps, you may end up skipping a timeline entirely.
Occupational stress can result from overscheduling your teammates with unnecessary work, which can generate stress and perhaps even a heavy workload and stress. That is why it is critical to properly define projects.
If you have problems with unexpected work, creating a modification control technique might assist you in communicating the work required to your employees.Identifying the Risk
The evaluation of the threat is one of the initial items in a risk assessment. Typically, this entails the use of a risk name or registration number. An identified risks field must contain the following information
The time of recognition
If necessary, a description works.Explaining the Risk
Once the verification is done, write a brief explanation on your record. A risk assessment must contain the following information
A brief, rising summary of the hazard
The reason why the danger is a possible issue?
The amount of your entries is determined by how extensive you wish your journal to be, although the usual size is 80 to 100 lines.
A summary may convey the major aspects of the danger and the reasons why it is a possible concern, rather than just the size. The essential message is that a statement should correctly represent the danger without being too technical in order for it to be easily caught.Categorization of the Risk
There are different financial intermediation that might assist detect possible risks rapidly. When operating on a massive task with various hazards, quickly recognizing the risk allows you to delegate it to the appropriate team. Any of the following might be classified as a risk category −
To identify the classification type, you must first assess where the threat is emanating from but nobody can assist in resolving it. If the answer is not evident, you might need to collaborate with team members.Risk Likelihood
If hazards are identified well sufficiently, the group may be capable of resolving them before such a meaningful intervention is necessary. As a result, it is conceivable that the concerns indicated on your safety registry will not become issues.
Classifying your hazards by probability might assist you to determine which concerns to address first and how much to postpone.Analyzing the Risk
A risk analysis assesses the probable effect of the risk on your business. This aids in swiftly identifying the most critical hazards to address. This should never be confused with precedence, which considers both incidence and assessment into effect.Mitigation of Risk
Several of the most significant components of an identified risk is a risk control strategy, often known as a risk management program. Even so, the aim of a risk control strategy is to locate and reduce potential hazards. It is, in essence, a plan of action. A risk reduction strategy should incorporate the following elements
A process guide to lowering the danger
A concise explanation of the expected conclusionWhat Effect the Strategy Will Have?
Though some hazards are simple to avoid, others are far more complicated and have no clear answers. In this scenario, the prevention method will necessitate some collaboration. This often occurs outside of the risk analysis paper, such as at a conference or team discussion.Risk Ownership
Because once the risk has occurred, been analyzed, and prioritized, the preventive objectives must be assigned to be delivered. Risk responsibility ought to encompass the following
The one in charge of overseeing the delivery of projects.
If necessary, any extra crew members
The risk management field can assist in swiftly determining which division would manage the risk. It might also aid in visualizing which colleagues are responsible for various risks.Additional Risk Set-ups
Though many chances are on the pessimistic aspect of the spectrum, there is also a chance for a favorable outcome. You may add a section for a high or low answer in this scenario.
Synopsis − To keep data in a single place, put the reduction plan’s timetable or schedule inside the record. Event software is an excellent resource for this.
Harmony, an open source Java implementation, is currently in incubator status at the Apache Software Foundation. The Harmony project mission is to create a compatible, independent implementation of J2SE 5 under the Apache License v2, and “create a community-developed modular runtime (VM and class library) architecture to allow independent implementations to share runtime components, and allow independent innovation in runtime components.”
There is a lot of open source activity currently surrounding Java, from JBoss and Geronimo (open source application servers) to MyFaces and Spring (open source web application frameworks), but Java itself is the last proprietary piece of the puzzle. If Harmony is successful, will Sun still matter?
I asked Dalibor Topic, one of the project founders, to tell us more about the history of the project, its importance to the Java community, and plans for the future.
LinuxPlanet: How did the Harmony project get started?
Dalibor Topic: Not being an Apache Software Foundation member, I can not speak authoritatively on the early history on Apache’s side, so I’ll give you a personal account of how we started to build the bridges that led to Apache Harmony. I am a co-maintainer of the chúng tôi virtual machine, and a developer on the GNU Classpath class library project, which are both long running sister projects to provide a full free software Java implementation.
In 2003 I was involved with making sure that some of Apache Software Foundation’s projects like Apache Ant run well on the then current version of the chúng tôi virtual machine. That started off the merge of Kaffe and GNU Classpath projects and resulted in some first contacts between Kaffe, GNU Classpath and Apache developers. chúng tôi started to gradually switch to GNU Classpath for its class libraries, driven by the needs of the users to run some of the excellent Apache software on a fully free stack.
Later in 2004, Mark Wielaard from GNU Classpath and me started looking at ways to improve the quality of GNU Classpath and Kaffe through automatic regression testing with popular free software written in Java. That immediately led us to the Apache Gump project, a continuous integration project that allows bugs preventing popular software from running to be noticed and caught as they happen, before they slip into releases. With the generous help of Leo Simons and Stefano Mazzochi, both Apache developers, we managed to set up Apache Gump with Kaffe and to set up a regression testing environment on top of it.
Going from that collaboration effort, strong ties to other Apache developers were created, most notably to Geir Magnusson Jr. from Apache Geronimo, and Davanum Srinivas from the Apache Axis project. Tom Tromey from Free Software Foundation’s gcj project, Bruno Souza from SouJava, Sun’s head of the Java Community Process Onno Kluyt, Geir, Mark and me met at the Red Hat Free Runtimes summit in Boston in late 2004, to discuss how to make a free software implementation of Java a reality.
While Sun had no interest in opening up their own implementation, Onno assured us that Sun Microsystems has removed the legal obstacles that existed before, which made it impossible for a free software implementation to be certified as compatible with the proprietary runtimes. Geir has worked together with Onno before to make sure that Apache’s Geronimo, a free software implementation of J2EE, could happen, so he was interested in seeing a certified free software J2SE implementation happen as well, and Bruno has a lot of experience with the JCP.
In spring 2005, Geir, Bruno and me met again at the CafeBrazil conference. We discussed how to build a modular Java runtime and class libraries, similar to the concepts embodied in Apache Geronimo.
One idea was to have well-defined interfaces for parts of the VM and the class libraries where other modules can be plugged in transparently, so companies and independent developers can work together on some parts, and compete on others. The concept of “collaborative competition” has worked great for GNU Classpath, which now covers about 90% of 1.5 APIs, and is used by more than two dozen runtimes, which both compete and collaborate on runtime components and the class library.
Given Apache Software Foundation’s successful dealing with the JCP and Sun Microsystems in the past, the possibility of such a project being attractive to both independent developers and companies developing proprietary Java runtimes, and ASF’s good reputation among Java developers, the ASF’s incubator made for a good, prospective home.
After further discussion within Apache, the Apache Harmony project was proposed for incubation, accepted, and we started to work on the legal framework for contributions, merging in first large contributions from Archie Cobbs, IBM and Intel.
This article was first published on chúng tôi
Who needs an alarm clock when you’ve got your Android phone handy? In the past year or so that I’ve relied on the Clock app on my Nexus 5X, I’ve rarely overslept. Now that I’ve got the hang of the Clock app’s various features and foibles, I’m close to replacing that “rarely” qualifier with a “never.”
Note: I tested these tips on a Nexus 5X running on Android version 7.1.2. Your settings and features may vary depending on the make and model of your phone.Open the clock app with a single tap
The Android Clock app isn’t the sexiest app on my Nexus phone, but it’s certainly in the top five when it comes to apps I use the most—and given that, I hate having to dig around the Android app drawer to find it.
Ben Patterson / IDG
Opening Android’s Clock app gets a lot more fun once you’re hip to this trick.
Luckily, there’s a handy one-tap shortcut to the Clock app, and it’s probably already sitting on your home screen.
Just tap the Clock widget—the one that looks like a digital or analog clock face—and you’ll jump immediately to the Clock app. That may sound obvious, but I only discovered the shortcut myself a few weeks ago, and I can’t believe I’d missed it so long. (If you’re not already using the Clock widget, just tap and hold a blank space on the Android home screen, tap Widgets, then install a Clock widget by tapping its icon.)Use the clock as your screensaver
Ben Patterson / IDG
When you use the Clock app as your screensaver, a digital clock will appear on your screen (very faintly, if you enabled the “night mode” setting) whenever your Android handset is connected to its charger.Gradually increase sound of alarm
Ben Patterson / IDG
Your Android alarm can gently rouse you with its “gradually increase volume” setting.
That’s why I’m a fan of the Clock app’s “Gradually increase volume” setting. Turn it on, and your alarm tone will start off whisper quiet, then slowly build until it reaches full volume, perfect for those of us who prefer a gentler wake-up call.Use any sound file as an alarm tone
Nope, you don’t have to wake up to a canned Android alarm tone. As it happens, you can set the Clock app to rouse you with any song or sound you want, from Van Halen’s “Jump” to a sound file you grabbed from the web.
Ben Patterson / IDG
Want to wake up to Led Zeppelin? No problem.Manage Do Not Disturb mode
If you’re wondering how you overslept an Android alarm, Android’s Do Not Disturb feature is a likely culprit. When it’s set to “Total Silence” mode, Do Not Disturb will muzzle all Android notifications and alerts, including alarms.
Ben Patterson / IDG
Android will generally warn you about silenced alarms before you turn on Do Not Disturb mode manually; not so with “automatic rules,” though.
If you don’t, just know that any alarms you set during a particular automatic rule period won’t go off, meaning you may doze right through any early-morning meetings.Silence an alarm after a set amount of time
One of the pitfalls of getting up early is forgetting to switch your alarm off—something you may realize when you step out of the shower and hear your alarm wailing…and wailing, and wailing.
Ben Patterson / IDG
You can set your Android alarm to shut itself automatically after a set amount of time, meaning you won’t drive anyone nuts if you step in the shower without dismissing your alarm first.
According to Gartner’s hype cycle of emerging technologies, 2023; Deep Learning and Machine Learning have reached the peak of inflated expectations. Artificial General Intelligence (AGI) and Deep Reinforcement Learning are in the phase of innovation trigger.
We are in 2023. The sentiment over Artificial Intelligence (AI) is euphoric. Every technology firm is jumping on the AI first bandwagon. Companies like Google, Microsoft, Amazon, and Alibaba are pushing the frontiers. There are a plethora of smaller players that are doing cutting-edge work in a niche area. AI is permeating into everyday lives.
As an active practitioner in this field, my views on the top AI trends to look out for in 2023 are as follows:
Firstly, let’s get the context of AI correct.
AI encompasses the following:
– Machine Learning (subset of AI)
– Deep Learning (subset of Machine Learning)
Trend #1: Machine Learning to Automated Machine Learning
A typical machine learning process involves the following stages:
A data scientist spends a lot of time in understanding the data. A data scientist tries to fit multiple models. They try out multiple algorithms to find the best model fitment that provides the optimal result.
Automated machine learning attempts to automate the process of performing exploratory analysis. It tries to automate the process of finding hidden patterns. It automates the training of multiple algorithms. In short, automated machine learning saves a lot of data scientist time. Data scientist spends lesser time in spending on model building and more time on evaluation. Automated machine learning is also a blessing for non-data scientists. It helps them to build decent machine learning models without deep-diving into the mathematics of data science.
In 2023, I see that this trend will become mainstream. Google recently launched AutoML in their cloud computing platform. There are niche companies like Data Robot who specialise in this area and are becoming mainstream.
“Automated Machine Learning will mature in 2023.”
Trend #2: Increase in Cloud Adoption for Machine Learning
Machine learning is a lot about data. It is the process of storing data. It is a process of analyzing data, training models and evaluating them. It is a data and compute-intensive process. It is iterative with hits and misses.
Cloud computing provides an ideal platform where machine learning thrives. Cloud computing is not a new concept. Traditional cloud offerings were limited to Infrastructure as a Service (IaaS). Over the past few years, public cloud providers have started offering Machine Learning as a Service. All the big cloud providers have a competitive offering in Machine Learning as a Service.
I see this trend continuing to increase in 2023. The cost of computing and storage in the cloud is lower and on-demand. The costs are controllable. The cloud providers provide out-of-the-box solutions. Data scientist now can spin up analytical sandboxes in the cloud, perform the analysis, experiment with a model and shut it down. They can automate the process as well.Machine learning in the cloud makes the life of a data scientist easier.
“Cloud computing would continue to enable Machine Learning acceleration in 2023.”
Trend #3: Deep Learning Becomes Mainstream
Deep learning is a subset of machine learning that utilizes neural network-based algorithms for machine learning tasks. Deep learning methods have proven to be very useful in the field of computer vision, natural language processing, and speech recognition.
Deep learning has been around for some time now. However, deep learning was in relative obscurity all these years. This obscurity was because of the following two reasons:
The sheer amount of data required to train deep neural networks.
The sheer computing power required to train deep neural networks.
These reasons cease to exist now. There is data now. There is abundant computing process available. The research in deep learning has never been so ebullient as compared to the past. Increasingly, deep learning is powering the fruition of complex use cases. Deep learning’s application ranges from workplace safety to smart cities to image recognition and online-offline shopping.
This trend will continue in 2023.
“Deep Learning will continue to be rapidly adopted by enterprises in 2023.”
Trend #4: AI Regulation Discussion Gains Traction
In 2023, data science community avidly followed the debate between Elon Musk and Mark Zuckerberg. The topic of the debate: Should we fear the rise of AI? Elon Musk had a pessimistic view on the topic. His views: the rise of AI has imminent dangers for humanity. On the other hand, Mark Zuckerberg, had a much more optimistic outlook on the topic. His views: AI would benefit humans.
This debate between these tech tycoons, has everyone thinking about AI and its regulation. In Jan 2023, Microsoft chimed in saying that AI needs to be regulated before it’s too late. There is no easy answer to this question. AI is still an evolving field. Excessive regulations have always stifled innovation. Maintaining a delicate balance is crucial. The regulation of AI is an uncharted territory with technical, legal and even ethical undertones. This is a healthy discussion point.
“Should AI be regulated? This will be a key discussion point in 2023.
About the Author
Pradeep Menon is a seasoned Data Science professional. He has more than 15 years of experience in the field of Data Analytics. He is a hands-on technical expert with a proven track record of helping organizations to transform.
Pradeep can balance business and technical aspects of engagement and cross-pollinate complex concepts across many industries and scenarios. He is a distinguished speaker and blogger and has given various talks on the topics on Big Data and AI.
Currently, he works as a Director of Big Data and AI Solutions with Alibaba Cloud. In this role, he consults his clients to be more data-driven and achieve success by the practical application of Big Data and AI technologies.
Introduction to PostgreSQL Select
According to our requirements, one of the most important purposes of any database is to store the data so that it can be retrieved and fetched whenever we want. Users mostly use the retrieved records for reporting and analysis or sometimes to modify existing results. You use the SELECT clause in the PostgreSQL database to fetch the data. We can retrieve the results from zero, one, or more tables using the select clause. This article will learn how to use the select clause to build the query statements, their Syntax, and examples to understand query building in PostgreSQL better.
Start Your Free Data Science CourseSyntax of PostgreSQL Select
Below is the Syntax of postgresql select:
columns_or_expressions FROM tables [WHERE conditional_restrictions] [GROUP BY column_or_expression] [HAVING conditional_restrictions]
The select clause’s Syntax is very complex and involves many possible combinations to provide flexibility to the user. We will learn the Syntax by learning all the above-used clauses with the select clause.
ALL: To retrieve all the records that the query will fetch after applying all the conditions, restrictions, and expressions.
DISTINCT: To retrieve only unique values of the column and expression from the retrieved results and further filter out the unique entries with respect to the column or expression mentioned in the distinct parameter.
columns_or_expressions: This is the list of the column names or expressions that you wish to retrieve using the select query.
FROM: This keyword helps specify the name of the table from which you wish to retrieve the records. Further, we can use joins of the type left join, right join, natural join, etc., to combine the results of two or more tables while retrieving the records.
WHERE: This clause helps specify the conditions, restrictions, and expressions to filter out the results while retrieving the records in the select query.
GROUP BY: You can group the result set based on a specific column or expression using the group by statement. People most frequently use this when retrieving manipulated columns with aggregate functions, such as the sum or product of certain columns.
HAVING: You can further filter the result by applying conditions and restrictions to the retrieved columns and expressions, including any aggregated values used in the retrieval process.
ORDER BY: You can arrange the result set in an orderly format based on specific columns and expressions by specifying them after the ORDER BY keyword. We can arrange the data in ascending or descending order by using ASC or DESC keyword.
LIMIT: You can limit the number of rows retrieved by using the limit keyword. For example, if the query result would have resulted in 55 records and after applying the limit of 10 statements in the select query, only the first 10 records will be retrieved.
OFFSET: This is the number of the row from which you want to begin retrieving the records. For example, if you specify the offset as 5, the result’s rows will be retrieved starting from the 5th record.
FETCH: Like the limit keyword, this function restricts the number of records that can be retrieved to a specific number.
FOR: The records can be restricted for access and are write-locked if FOR UPDATE is specifies and is allowed for reading operation but not update and insert operations by other transactions when FOR SHARE is specified.
Except for FROM, all other clauses/keywords used in the above select clause syntax are optional in nature.Examples of PostgreSQL Select
Following are the examples of postgresql select:
Let us create one example and insert a few records in the table to learn how to use a select clause to retrieve the records. Open your PostgreSQL command-line prompt and enter the following command to create a table named educba –CREATE TABLE educba (id INTEGER PRIMARY KEY, technologies VARCHAR, workforce INTEGER, address VARCHAR);
Here, * represents all the columns to be retrieved, and firing the above query results in the following output –
Now we will apply the conditions using the where clause and retrieve only records with a workforce of 20 persons. For this, we will have to mention the condition as workforce = 20 in the where clause, and our query statement will be as follows –SELECT * FROM educba WHERE workforce=20;
Now, suppose we only want to retrieve the list of name of technologies with the workforce as 20, then the query statement will be as follows –SELECT technologies FROM educba WHERE workforce=20;
Let us see how we can group the result based on workforce count and retrieve the technologies’ comma-separated string. For this, the query statement will be as follows:SELECT string_agg(technologies,','), workforce FROM educba GROUP BY workforce;
Suppose that instead of retrieving the column head as string_agg, we can give the alias for the same using the “as” keyword as follows:SELECT string_agg(technologies,',') as "List Of Technologies", workforce FROM educba GROUP BY workforce;
Let us order the results alphabetically based on the technology’s name and limit the records to only 7 by using the limit clause. Our query statement will be as follows –SELECT * FROM educba ORDER BY technologies ASC LIMIT 7; Recommended Articles
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