Southern Shrimp and Grits – English Reading Comprehension

Recipe /ˈrɛsəpi/

Learning a new language isn’t just about learning vocabulary and grammar, you must also learn the culture of that language. You must consider where it is spoken, who speaks it, and what the traditions and customs are of its native speakers. So, what are some ways you can go about learning the traditions and customs of a group of speakers? Well, one great way to start is by learning to cook their food! As mama always says, there’s no better way to a person’s heart than through their stomach!

Here is a recipe for a typical dish from South Carolina, in the south eastern part of the United States. It is usually served at brunch alongside an ice-cold mimosa (a drink made from champagne and orange juice) and great company!

Now have a look at this video: Southern Shrimp and Grits

Ingredients

2 cups (470 milliliters) chicken broth

2 cups (470 milliliters) milk

1/3 cup (76 grams) butter, cubed

3/4 teaspoon (3.5 grams) salt

1/2 teaspoon (2.85 grams) pepper

3/4 cup (100 grams) uncooked old-fashioned grits (substitute with polenta)

1 cup (130 grams) shredded cheddar cheese

SHRIMP:

8 thick-sliced bacon strips, chopped

1 pound (450 grams) uncooked medium shrimp, peeled and deveined

3 garlic cloves, minced

1 teaspoon (5.7 grams) Cajun or blackened seasoning

4 green onions, chopped

Instructions

Mix the broth, milk, butter, salt, and pepper in a large saucepan. Bring the ingredients to a boil. Slowly stir in the grits (or polenta). Cover the saucepan with a lid and cook for 12 – 14 minutes, or until the sauce has thickened. Stir occasionally. Once the sauce is thick, stir in the cheese until it has melted. Put the sauce aside and keep it warm.

Cook the bacon in a large skillet until it becomes crisp. Once the bacon is crisp, set it aside on paper towels and keep 4 teaspoons (20 milliliters) of the drippings. Saute the shrimp, garlic, and seasoning in the bacon drippings until the shrimp turn pink.

Serve the shrimp over grits and sprinkle with green onions.

Now try the following quizzes to check your understanding of the article.

Southern Shrimp and Grits | Match

Match the ingredients with the pictures.

Southern Shrimp and Grits | Fill in the Blank

Fill in the blank with the correct command.

Southern Shrimp and Grits | True or False

Decide if the statement is true or false.

Reading Exercise | | The Pastry AI that Learned to Fight Cancer

Japan’s long history of trade is considered one of the reasons behind the country’s very diverse food tastes. Because of this, unlike French or Italian bakeries that offer only a few options, Japanese bakeries offer pastries of all sizes, shapes, flavors, and colors. They have options like The Carbonara, which is a pastry version of the famous Italian pasta dish, or The Ham Corn, a breakfast pastry topped with ham, corn, and mayonnaise. There are hundreds of different types of pastries in these unique bakeries. Unfortunately, this diversity did not come without a cost: cashiers had to spend months learning the price of each individual pastry based on sight alone. This meant that the checkout process was not only very difficult for cashiers, but also caused long wait times for customers.

A software company called Brain was asked to help resolve the problem of confusion at the cash register. Brain, which was founded by computer programmer and software designer Hisashi Kambe, had always worked on projects based on computer visualization capabilities. The company originally designed computers that could detect errors in formulas for fabric patterns, so resolving the problem of visualizing hundreds of different pastries was no stranger to them. Brain began working on a software called BakeryScan.

BakeryScan is unique because, unlike deep learning software like Google Translate, Siri, and almost every AI system out there, BakeryScan doesn’t need large amounts of specialized data to make decisions; it is created to understand irregularities like the shadow cast into the middle of a donut hole or the slightly darker color of over-baked bread without needing the input of tens of thousands of similar images.

Once BakeryScan was implemented, it became a hit. It was televised all over Japan and became such a cultural phenomenon that it was even referenced in their language proficiency exams.

This was how a doctor at the Louis Pasteur Center for Medical Research, in Kyoto, saw a television segment about the machine. He realized that cancer cells, under a microscope, looked a lot like bread. He contacted Hisashi Kambe’s company Brain to see how they could collaborate to develop a version of the program that could help pathologists detect cancer cells. BakeryScan was already equipped with tools that allowed human experts to give the program feedback, the only thing they needed to change was what exactly the system would be analyzing.

They started small, analyzing single cells under a microscope, but eventually moved up to more complex images. Now, BakeryScan, adapted and renamed Cyto-Aiscan, is being tested in two major hospitals in Kobe and Kyoto. It is capable of “whole-slide” analysis, meaning that more than analyze a single cell at a time, it is capable of looking at an entire microscope slide and identifying the cells that might be cancerous. Instead of considering the shadows cast into a donut hole or the darker shade of over-baked bread, the software is now considering the color tone of the nucleus, its size and texture, and its overall roundness.

Who knew that the world of pastries could bring us further ahead in cancer research?

Did you enjoy reading this article? Test your reading skills by completing the quizzes below.

The Pastry AI that Learned to Fight Cancer | Definition Match

Match the phrases with their definition.

The Pastry AI that Learned to Fight Cancer | Fill in the Blank II

Fill in the blank with the correct word or phrase:

Learn English with the News – The Pastry AI that Learned to Fight Cancer

Science and food do not have to be mutually exclusive: cancer researchers in Japan have been working with software developers to adapt an innovative computer program that can identify hundreds of different types of pastries at the cash register into a program that can detect cancer cells under a microscope lens.

Watch the video and then do the accompanying English language exercises.

The news is a consistent source of entertainment, knowledge and discovery that never ceases to exist and always comes out with more and more material each day. Because it plays such a vital part in our lives and is so important to keep up with, it is without a doubt a piece of your everyday routine that can’t go ignored.

Whether it is to understand the ramifications of recent legislation passed, to hear about recent events and grasp the potential consequences to your country, or simply hear about what is happening in other countries in order to compare them to what’s happening in yours, the news is certainly a staple in our lives and the most consistent way to get information.

This is why Scrambled Eggs has decided to unite two of your biggest worlds: learning English and keeping up with what is happening in the world. We hope our challenging daily exercises, composed of listening, vocabulary and comprehension exercises in English, will satisfy both of those above worlds in a satisfactory and also entertaining way.

So enough about introductions, let’s get to today’s Learn English with the News topic:

Adapted from this article. 

The Pastry AI that Learned to Fight Cancer | Fill in the Blank

Fill in the blank with the correct preposition.

The Pastry AI that Learned to Fight Cancer | Synonyms Match

Match the words with their synonyms.

The Pastry AI that Learned to Fight Cancer | True or False

Decide if the statement is true or false.

 

Full text:

“A software company called Brain has been working with a cancer research center in Kyoto, Japan to adapt software they created for the Japanese bakeries into a program that can detect cancer cells under a microscope lens.

Brain’s software, BakeryScan, was created in 2007 and has since been improved to allow Japan’s bakeries to easily identify different types of pastries at the cash register.

The pastry industry needed this complex software because of Japan’s very diverse food tastes. The country’s long trade history led to its desire for a variety of flavors. For this reason, unlike French or Italian bakeries that offer only a few options, Japanese bakeries offer pastries of all sizes, shapes, flavors, and colors. There are hundreds of different types of pastries in these unique bakeries.

The many different types of pastries caused cashiers to spend months learning the price of each individual pastry based on sight alone. This meant that the checkout process was not only very difficult for cashiers, but also caused long wait times for customers.

Brain, which was founded by computer programmer and software designer Hisashi Kambe, had always worked on projects based on computer visualization capabilities and so to combat this problem at the cash register they created BakeryScan.

BakeryScan is unique because, unlike deep learning software like Google Translate, Siri, and almost every AI system out there, it doesn’t need large amounts of specialized data to make decisions; it is created to understand irregularities like the shadow cast into the middle of a donut hole or the slightly darker color of over-baked bread without needing the input of tens of thousands of similar images.

When a doctor at the Louis Pasteur Center for Medical Research, in Kyoto, saw a television segment about the machine, he realized that cancer cells, under a microscope, looked a lot like bread. He contacted Hisashi Kambe’s company Brain to see how they could collaborate to develop a version of the program that could help pathologists detect cancer cells.

The program they came up with, Cyto-Aiscan, is currently being tested in two major hospitals in Kobe and Kyoto. It is capable of “whole-slide” analysis, meaning that it can analyze an entire microscope slide and identify the cells that might be cancerous. The software considers the color tone of the nucleus, its size and texture, and its overall roundness and can lead to earlier diagnoses by speeding up the process, ultimately allowing for more effective treatments for cancer patients.”