Trending November 2023 # Dropbox Gains Document Scanner, Secure File Sharing And Other Productivity Improvements # Suggested December 2023 # Top 16 Popular

You are reading the article Dropbox Gains Document Scanner, Secure File Sharing And Other Productivity Improvements updated in November 2023 on the website Cancandonuts.com. We hope that the information we have shared is helpful to you. If you find the content interesting and meaningful, please share it with your friends and continue to follow and support us for the latest updates. Suggested December 2023 Dropbox Gains Document Scanner, Secure File Sharing And Other Productivity Improvements

Dropbox today announced a major update to its mobile and desktop clients across platforms, including the ability to scan documents in the mobile app, create Microsoft Word, PowerPoint and Excel files on the go, share files securely with others using access privileges and much more.

On the downside, Dropbox’s existing Camera Sync feature has been removed from the mobile app so you now must manage photos using the desktop client. Dropbox for iOS is available at no charge via the App Store. The Mac client must be downloaded directly from the Dropbox website.

Document scanning

With OCR-based document scanning, you can turn that napkin sketch or whiteboard brainstorm into a digital file which can be even searched, but you’ll need a Dropbox Business account to search your scans.

To get started with document scanning, tap the new plus icon in the mobile Dropbox app. In addition to scanning documents, the new plus button in Dropbox lets you create new Microsoft Office files from scratch and upload photos to your Dropbox.

Create Office documents on the go

Dropbox allows you to open Word, Excel and PowerPoint documents, but now you can also create those files right within the mobile app. Tap the new plus button to create a Word, PowerPoint or Excel file instantly from your iPhone, iPad or iPod touch

“The new plus button in the Dropbox iOS app adds a convenient way to create and save Office documents on the go, helping people work better together, wherever they are,” said Rob Howard, Director of Office Marketing at Microsoft.

And with existing features like co-authoring and the Dropbox badge, you can collaborate on Microsoft Office files in real time and see who else is working in the document to avoid losing or duplicating work.

Office files created within the app are saved to your Dropbox automatically.

The mobile Dropbox app used to include the ability to automatically upload any Camera roll images to your Dropbox, which was great for folks who relied on Dropbox as their photo backup solution. As of today, this feature is no longer available in the mobile app.

Instead, you must connect your Mac or Windows PC to your Dropbox account to manage photos from your computer. The reason for this change wasn’t clear at post time. Dropbox argued that this will let you “better access, organize or remove your photos and avoid running out of space.”

They’ve also unified how people, files and apps work together within Dropbox.

Secure sharing, previewing earlier versions

In addition to Dropbox’s existing Version History feature which lets you recover files up to 30 days old should accidents happen, users can now preview prior file versions before they restore them. And if you want to work with a select group of collaborators, Dropbox’s new secure sharing features give you more control to do just that.

For example, you can share a single file with specific people, who will need to log in to see it. This new feature shouldn’t be confused with File Requests, which lets you collect files in a single folder from anyone, without granting them access to its contents.

Last but not least, all Dropbox users are now permitted to share folders with view-only access, or you can let others follow along.

Dropbox passed half a billion users in March 2023.

Source: Dropbox

You're reading Dropbox Gains Document Scanner, Secure File Sharing And Other Productivity Improvements

Fix: File & Print Sharing Resource Is Online But Isn’t Responding

Fix: File & print sharing resource is online but isn’t responding

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While trying to access one or multiple shared connections or folder across the local network, Windows users may run into “File and Print Sharing resource is online but isn’t responding to connection attempts” error.

The error can occur on the latest Windows 10 as well as older Windows 7 version running computers. This error is triggered if the PC is unable to discover the network, PeerBlock is blocking the local area connection etc. Many users have reported similar issues in the Microsoft community.

“File and Print Sharing resource (MyIP to share) is online but isn’t responding to connection attempts.” I’ve been sharing this directory for a long time and it suddenly just stopped working.

If you are also troubled by this issue, here are a couple of troubleshooting tips to help you fix this error in Windows computers.

How to fix

File and Print Sharing resource is online but isn’t responding to connection attempts

1. Check if the computers are discoverable

Below we have listed both the methods to make the computer discoverable to the network.

Connecting via Wi-Fi adapter

Select Network and Internet.

Under “Network Profile” select “Public” option.

Do the same with all the computer on the network that uses the Wi-Fi connection.

Connecting via Ethernet adapter

Select the Ethernet tab from the left pane.

Under “Network Profile“, select “Private” option.

Now you need to repeat these steps with all the computers that are available on the network.

Now that you have configured all the computers to be discoverable try to access the shared folder and check if the error is resolved.

The

Network Diagnostic error on Windows 10 has affected the build 1703. If you are still running the older version of the OS, install all the available updates to fix the issue.

Once the update is installed, restart the computer and check for any improvements.

3. Disable Windows Firewall

The Windows Defender Firewall may sometime block the connection that it may tag as unsafe. Try disabling Windows Defender Firewall temporarily and check for any improvements.

Go to Update and Security.

Now try to access the shared folder and check if the file and print Sharing resource is online but isn’t responding to connection attempts error is resolved.

Make sure you turn on the firewall once the error is resolved.

C# Program To Create File And Write To The File

Introduction

Creating a file and writing in it is the basics of file handling. Here, we are going to discuss a way to write a C# program to create the file and write to the file. File handling or file management in layman’s terms the various processes such as making the file, reading from it, writing to it, appending it, and so on. The viewing and writing of files are the two most common operations in file management.

Input and output happen due to the streams which provide a generic view of a sequence of bytes. Stream is an abstract class. It is the gateway for the different processes i.e., input and output. In C# file handling file stream is used. Now. let us discuss the different ways to create the file and write the file.

1. File.WriteAllText() method

This is one of the most used methods and one of the simplest to use. This method creates a file with the programmer-defined name and writes the data from the string input. After the data input is completed the file is closed. If the file that the user wants to create exists then the previous file from the storage is overridden.

public static void WriteAllText (string path, string? contents);

Both the input parameters are strings. This uses UTF-8 encoding by default without a BOM i.e., Byte-Order Mark. If the user wants to use a different encoding then the user can pass an additional third parameter for that specific encoding.

Algorithm

Now, let us discuss the algorithm to create the file and write the file by using File.WriteAllText() method.

Step 1 − The variable is declared with the text file name.

Step 2 − The string is declared with the data.

Step 3 − The information is input into the file and stored in it.

Step 4 − After the information is written a success message is printed.

Example using System.Text; using System; using System.IO; class testfiles { public static void Main(){ var loc = "tutpoint.txt"; string inform = "Tutorials Point"; File.WriteAllText(loc, inform); Console.WriteLine("Text input completed."); } } Output Text input completed. 2. File.WriteAllLines() method

This method creates a file with the programmer-defined name and writes a single string input or multiple strings at one go. After the data input is completed the file is closed. If the file that the user wants to create exists then the previous file from the storage is overridden.

public static void WriteAllLines (string path, string[] contents);

This uses UTF-8 encoding without a BOM i.e., Byte-Order Mark.

Algorithm

This algorithm is about File.WriteAllLines().

Step 1 − The variable is declared with the text file name.

Step 2 − The string is declared with the data.

Step 3 − Data is written in the chúng tôi file.

Step 4 − Write a code line to display successful work done.

Example using System.Text; using System; using System.IO; class testfiles { public static void Main(){ var loc = "tutpoint.txt"; string[] inform = {"Tutorials", "Point", "learn"}; File.WriteAllLines(loc, inform); Console.WriteLine("Text input completed."); } } Output Text input completed. 3. File.WriteAllBytes() method public static void WriteAllBytes (string path, byte[] bytes); Algorithm

Now, let us discuss the algorithm to create the file and write the file by using File.WriteAllBytes() method.

Step 1 − The variable is declared with the text file name.

Step 2 − The string is declared with the data.

Step 3 − The information is input into the file and stored in it.

Step 4 − After the information is written a success message is printed.

Example using System.Text; using System; using System.IO; class testfiles { public static void Main(){ var loc = "tutpoint.txt"; string inform = "Tutorial point contains a plethora of technical articles"; byte[] details = Encoding.ASCII.GetBytes(inform); File.WriteAllBytes(loc, details); Console.WriteLine("Text input completed."); } } Output Text input completed. 4. Asynchronous method

We will see about WriteAllTextAsync().

public static chúng tôi WriteAllTextAsync (string path, string? contents, System.Threading.CancellationToken cancellationToken = default);

This method creates a file asynchronously and then writes all the text in the file. After that, the file is closed.

Algorithm

Now, let us discuss the algorithm to create the file and write the file by using File.WriteAllTextAsync() method.

Step 1 − The variable is declared with the text file name.

Step 2 − The string is declared with the data.

Step 3 − The information is input into the file and stored in it.

Step 4 − After the information is written a success message is printed.

Example using System.Text; using System; using System.IO; using System.Threading.Tasks; class testfiles { public static void Main() { var loc = "tutpoint.txt"; string inform = "falcon"; Task asyncTask = WriteFileAsync(loc, inform); Console.WriteLine("Text input completed."); } static async Task WriteFileAsync(string loc, string inform){ Console.WriteLine("Async Write File has started."); using(StreamWriter outputFile = new StreamWriter(Path.Combine(loc)) ){ await outputFile.WriteAsync(inform); } Console.WriteLine("Stage 2"); } } Output Async Write File has started. stage 2 Text input completed. Conclusion

So, with this comes the end of the article. In this article, we have learned a C# program to create the file and write to the file. We learned the various method to do so. We also discussed the different algorithms that do so and learned their codes. We hope that this article enhances your knowledge regarding C#.

Idrive Review: Excellent Online Backup, Sharing, And More

Pros

Online and local backup in the same job

Supports multiple PCs and devices on the same account

Cons

One of the pricier services, beyond the free version, though justifiably so

Our Verdict

iDrive has you covered six ways to Sunday when it comes to backup. Online, local, sync, snapshots, shipping hard drives to you for quicker recovery… You name it, the company does it. Not the cheapest service, but easily the most comprehensive.

Best Prices Today: iDrive Online Cloud Backup

Retailer

Price

iDrive

$79.50

View Deal

Mentioned in this article

Carbonite Safe

Best Prices Today:

Editor’s note: This article was amended on December 20, 2023 to reflect changes in pricing and options.

As of our latest look, iDrive remains the most comprehensive online backup and sharing service we’ve tested. It’s not the cheapest, but it’s still affordable and comes with backup clients for nearly every PC and device, and is more than competent at local backup.

The company also provides additional storage for syncing all your devices and PCs, allows sharing of files with anyone, and has the ability to back up to a local drive. See how well it compares to the competition in our big online backup roundup.

iDrive: Plans and pricing

Believe it or not, iDrive still offers a free storage plan, which has increased from 5GB to 10GB since our last look at the service. As far as we’re aware, it’s the only free repository not associated with a mega corporation (Microsoft, Apple, Google, etc.) still in existence.

iDrive has three Personal plans that cover one user with unlimited computers and devices: a 5TB plan for $59.62 the first year (or $119.25 for two years), and $79.50 each year after; a 10TB plan for $74.62 the first year (or $149.25 for two years) and $99.50 each year after; as well as a 20TB plan that’s $149.62 for the first year (299.25 for two years) and $199.50 after that.

If you enable the separate sync service, you get an equal amount of storage just for that task—no extra charge.

There’s a new Team plan that scales from five users and computers for $99.50 per year to 500 users and computers for $19,999.50, all offering 1TB of storage per user. Those were also discounted at the same rate as the Personal plans at the time of this writing.

Don’t get completely caught up in the price-per-gigabyte game: The size of your essential data is probably a lot smaller than what’s being offered by iDrive, unless you’re into HDR and 4K.

iDrive plans as of December 2023.

iDrive

iDrive: Features

Like its competitor Carbonite Safe, iDrive uses continuous data protection (CDP) rather than backing up on a set schedule. If you have a rapidly changing data set, it’s nice to have files backed up as they change, not just periodically. iDrive also supports nearly every type of PC and device: Windows, OS X, Android, iOS, and various NAS boxes. Also nice are the snapshots, which make it easy to restore your PC to a particular point in time.

iDrive’s online dashboard offers all the settings that the client offers. Including enabling/disabling continuous data protection (near real-time backup of changed files).

iDrive now features two local clients. The normal one allows access to all the options, and is nearly identical to iDrive’s online dashboard. The other, iDrive Basic, is for those who just want to push a button and back up everything (assuming your plan has the space.)

iDrive will also handily duplicate your online backup to local storage. That allows you to painlessly maintain the Rule of Three: your original data, a copy, and a copy of the copy. Also, it’s much faster to restore from a hard drive than from any online service.

iDrive also features iDrive Express, a two-way physical shipment service. Say you’re walled off from the internet, or just in a very low-bandwidth location. Use iDrive’s local backup function to back up your data to a storage device provided by the company, then ship it to them. It will get uploaded to your online account, and then updated by your local client thereafter. Or if you need to restore from a backup in hurry, iDrive will ship your data to you on an appropriate device. All within a week’s time.

Personal customers get 3TB of data delivered to or fro for free—the first time. Team and Business users get three free deliveries. Subsequently, there’s a $60 charge per use.

Should you use iDrive’s backup service?

Editor’s note: Because online services are often iterative, gaining new features and performance improvements over time, this review is subject to change in order to accurately reflect the current state of the service. Any changes to text or our final review verdict will be noted at the top of this article.

The Pdsa Technique For Quality Improvements

What Is The PDSA Technique?

The PDSA technique (Plan-Do-Study-Act) is a quality improvement method developed by two renowned American statisticians, Walter A. Shewhart and W. Edwards Deming. It was designed to help organizations improve their operations through the use of statistical methods. The PDSA cycle is based on four main steps: plan, do, study, and act.

The “plan” phase of this technique involves determining the problem or issue to be olved. This step includes setting objectives and gathering data related to the issue. The “do” phase revolves around putting the plan into action. During this phase, the organization should identify ways to address the issue and other potential barriers, if any. The “study” phase measures the results of the activities that were implemented during the “do” phase. This includes collecting data to measure success and identifying any areas that need improvement. Finally, the “act” phase involves making changes based on the data collected during the study phase. These changes can include changes to processes, systems, or people.

The PDSA technique is a great tool for organizations to improve their operations and achieve their goals. It can help identify the root causes of issues and provide an efficient way to measure success. Additionally, it encourages an iterative process that can help organizations quickly identify and solve problems.

How Does The PDSA Technique Work?

At its core, the PDSA cycle is designed to measure and improve an existing process or system. It involves four distinct steps: plan, do, study, and act. The PDSA technique is a powerful tool for quality improvement teams because it helps them focus their efforts on making small, incremental changes that can have a big impact on their organization’s performance. Here is how the PDSA technique works −

Plan Phase

During the planning stage, the team identifies an area where they think improvements can be made and creates an action plan to make those improvements. This involves clearly defining the problem to be addressed and outlining the steps needed to address it. During the planning stage, it is important to identify potential risks and develop a plan for addressing them. With the objectives of the PDSA technique in place, you need to identify the relevant folks who will be in charge of making the changes in product quality. Finally, a detailed plan to improve the current production process is necessary for the PDSA team to succeed.

Do Phase

Once the plan is complete, it’s time to execute it. The goal here is to collect data that will help you assess the effectiveness of your efforts. This includes carrying out the planned changes and measuring the results of these changes. The manager must communicate the PDSA plan to the team and keep their morale high while executing such changes. The execution of quality improvement plans must be time-bound and should deliver measurable results. The PDSA team must evaluate the new process at regular intervals to see if the obtained results are as per the expectations of their original plan. In case of any deviation, the manager must identify control measures to fix the bottlenecks.

Study Phase

After the data is collected, it’s time for the team to study and analyze the results of the changes. This is where you analyze the data collected during the “do” phase and evaluate whether or not your efforts were successful. Managers can present run charts to the PDSA team at regular meetings to understand the progress of their improvement plan. The PDSA team can identify the factors that have contributed to the success of the plan and double down on efforts on similar factors. Analyzing the results also gives insights into the areas that have not generated the desired success. Managers can formulate strategies to improve such areas. Based on the results of your study, you can then make changes to your plan as needed.

Act Phase

Finally, based on the results of their study, the team implements changes (acts) based on their findings. This is where you put your revised plan into action and test it again. Managers can either adopt, adapt, or abandon their quality improvement plan based on their conclusions. By measuring the results of each change and analyzing them, teams can identify areas for improvement and continue to make improvements over time. This process can be repeated until you have achieved the desired results. The PDSA technique can refine the finest processes in an organization and add consistency and effectiveness to them.

What Are the Benefits of Using The PDSA Technique?

By following the PDSA cycle, you can ensure that any changes you make are tested and evaluated, allowing you to quickly identify what works and what doesn’t. This way, you don’t have to waste time and resources on unproductive solutions.

Additionally, the PDSA technique encourages continuous improvement, as the testing and evaluation stages provide valuable feedback for future improvements. You can use this feedback to iterate on your solution, making sure you are always making progress.

Using the PDSA technique also helps to keep everyone involved in the process accountable, as it involves clearly defined roles and responsibilities. Everyone knows what is expected of them and how they fit into the larger picture. This ensures that quality improvements are achieved efficiently and effectively.

Finally, the PDSA technique promotes collaboration between team members and stakeholders as it requires clear communication and dialogue. This allows teams to work together to solve problems and build better solutions. In addition, it encourages an open and transparent culture, as everyone is allowed to express their opinions and ideas.

Conclusion

Getting started with the PDSA technique is straightforward. The idea behind this technique is that it provides a structured approach to testing and evaluating quality improvement efforts. Overall, the PDSA technique provides a simple yet effective way to identify and address problems in any organization. By following the four steps outlined above, you can ensure that your quality improvement efforts are successful and cost-effective.

Data Warehousing With Snowflake And Other Alternatives

This article was published as a part of the Data Science Blogathon.

Introduction

Over the past few years, Snowflake has grown from a virtual unknown to a retailer with thousands of customers. Businesses have adopted Snowflake as migration from on-premise enterprise data warehouses (such as Teradata) or a more flexibly scalable and easier-to-manage alternative to an existing cloud data warehouse (such as Amazon Redshift or Google BigQuery).

Snowflake: Data lake or Data Warehouse?

Data lakes offer low-cost object storage of raw data and rely on external query tools to analyze large datasets using highly available computing resources. Because they access a file system rather than a structured format, data lakes are not highly performant without optimization. But once optimized, they can be extremely cost-effective, especially at scale. They are also well equipped to process streaming data.

The Data warehouse stores structured data in a proprietary format for analytical access through a tightly coupled query layer. Computational speed is high compared to a non-optimized data lake but is also more expensive.

So, where does the Snowflake fit?

With other data warehouses, Snowflake requires a proper data format, works with structured and semi-structured (but not unstructured) data, and requires its query engine. However, it differs from a traditional data warehouse in two key aspects:

1. It is only offered in the cloud

2. It separates the storage from the elastic compute layer

These improvements initially differentiated Snowflake in the market from Teradata and Redshift. However, each has tried to match those attributes—Teradata with its Vantage cloud service and Amazon with Redshift, which separates compute and storage. As a result, these services now share these two properties with cloud data lakes, which can add to the flurry of confusion about when to use which.

Where to store the data for cost optimization?

So Snowflake is not a data lake. But is there any reason not to store all your information on it and rely on its ability to process data with SQL quickly? One reason you should consider it is the cost.

Of course, the cost is essential when deciding how to use different analytics platforms. Using Snowflake to run complex queries on large volumes of data at high speed can significantly increase costs.

Snowflake charges based on how long the Virtual Data Warehouse (VDW) is running, plus VDW size (number of cores) and prepaid feature set (Enterprise, Standard, or Business-Critical). A given VDW, the rates are identical to the load on the VDW. This differs from the data lake, which offers spot pricing; a cheaper instance can handle a smaller bag.

Snowflake processes data in its proprietary format, and data transformation for Snowflake acceptance can be costly. Because receiving data streams creates a continuous load, it can keep the Snowflake VDW meter running 24/7. Since Snowflake does not charge differently for a 5% or 80% load of a given virtual datastore size, these costs can be high.

• Computing snowflakes is more expensive than running the same job in a data lake.

So there is a real risk of Snowflake running into an inexorable cost scenario. When you realize that you may have too much data stored in Snowflake, it can become even more expensive to get the data out because it needs to be transformed into a different format.

A similar scenario could arise involving your data scientists, who may repeatedly analyze the same or similar data sets as they experiment with different models and test various hypotheses. This is highly computationally intensive. They must be able to connect to the ML or AI tools of their choice and not be locked into a single technology just because a proprietary data format requires it.

For these reasons, relying on Snowflake for all your data analysis needs can be inefficient and expensive. From a business perspective, it may be better to supplement Snowflake with a data lake.

Compare Snowflake and Databricks

There are a lot of people who are confused between snowflake and Databricks. How does the Snowflake approach compare to Databricks’ self-proclaimed Lakehouse tool, and how stark are the differences between the two? Check out our Databricks vs Snowflake comparison to find out.

Snowflake + optimized cloud data lake = flexible and affordable analytics

None of the above is meant to disparage Snowflake or to suggest that it shouldn’t be part of your overall solution. Snowflake is a handy data warehouse and should be considered a way to provide predictable and fast analytics performance. However, by incorporating it as part of an open, optimized data lake architecture, you can ensure that you get all (or most) of Snowflake’s benefits while keeping your cloud costs under control.

Using an optimized data lake and cloud data warehouse like Snowflake allows companies to apply different patterns to different use cases based on cost and performance requirements.

You can use cheap data lake storage and keep all your data – not just recent or structured data.

Data transformation and preparation are likely much cheaper in a data lake than in Snowflake, especially for streaming data.

You are not limited in choice of query tools and can query the data lake directly or send it to Snowflake as needed. With additional tools such as search engines, time series databases, or ML/AI tools, you retain maximum flexibility and agility to work with the rest of the data as you please.

Prepare your Data Lake for Analysis

Manually preparing data in a data lake using tools like AWS Glue or Apache Spark is usually resource-intensive. Here we will use Upsolver’s Data Lake engineering platform. Upsolver provides a low-code, self-service, optimized compute layer on top of your data lake, making it powerful to serve as a cost-effective repository for analytics services.

Upsolver includes data lake engineering best practices to make processing efficient, automating the essential but time-consuming data pipeline work that every data lake requires to function well. It includes:

Converting data into columnar formats with efficient querying like Apache Parquet instead of requiring engines to query raw data.

Continuous file compression ensures performance by avoiding the “small file problem.”

Appropriate data partitioning to speed up query response.

Upsolver uses low-cost compute options such as AWS Spot EC2 instances whenever possible to reduce query costs. This can reduce calculation costs by 10X compared to standard EC2, which is much cheaper than a data warehouse.

Upsolver handles UPSERTS tables correctly, meaning you can continuously load tables from streaming data that stay current as the data and even the schema change.

Use Upsolver to normalize, filter, aggregate, and join data to your liking through a visual SQL IDE to create transformations. Then run these transformations directly in the data lake before writing them to Snowflake (including joins, aggregations, enrichments, etc.) or querying them as an external table from Snowflake’s SQL query engine.

Combining Snowflake with Upsolver’s data-rich data lake gives you the flexibility to run processing where it makes the most sense in terms of cost and choice of analytics tools.

You can even use Upsolver to continuously transform and stream data directly to Snowflake.

How to build a real-time streaming architecture using Snowflake, Data Lake Storage, and Upsolver on AWS?

First, and most importantly, be clear about which of your data streams must go to Snowflake and which can be stored in raw format in a lake for other purposes. (Remember not to keep ancient data on Snowflake; Athena is a much better tool for querying large datasets.) Then design the architecture so that the transformed streaming data is automatically sent to Snowflake.

In this reference architecture, Snowflake is only one of several data consumers. Data is optimized (sometimes significantly) for each consumer. In some cases, prepared data is most economically queried on a data lake with a query tool such as Athena; in others, the output is to a specialized data store:

• search analysis or logging (Elasticsearch)

• OLAP (Snowflake) querying

• chart analysis (Neptune)

With an open data lake architecture like this, you keep a single version of the truth in the data lake as raw data, plus you can refine and distribute the data for specific purposes.

1. Upsolver receives data streams and stores them in raw format in a data lake.

2. Data intended for OLAP or ad hoc queries are prepared, cleaned, aggregated, and formatted for direct question by Athena and output to Snowflake for processing and processing.

3. As requests come in from other analytics services, the data is prepared and then delivered to the service.

Conclusion

Data lakes are open, more scalable, cost-effective, and can support a broader range of business cases. Now, you can use a codeless data lake engineering platform to create a pipeline to receive, prepare quickly, and format unlimited amounts of streaming data. You can then directly query or send to Snowflake—the best of both worlds.

Snowflake offers some separation of storage from computing. It cannot be considered a data lake due to its reliance on proprietary data formats and structured storage. A data lake is built on broad access to data and the ability to choose between different compute queries and data tools;

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