Recherche avancée

Sur d’autres sites (10704)

• GA360 Sunset : Is Now the Time to Switch ?

  20 mai 2024, par Erin

  Google pushed the sunset date of Universal Analytics 360 to July 2024, giving enterprise users more time to transition to Google Analytics 4. This extension is also seen by some as time to find a suitable alternative. 

  While Google positions GA4 as an upgrade to Universal Analytics, the new platform has faced its fair share of backlash. 

  So before you rush to meet the new sunset deadline, ask yourself this question : Is now the time to switch to a Google Analytics alternative ?

  In this article, we’ll explain what the new GA360 sunset date means and show you what you could gain by choosing a privacy-friendly alternative. 

  What’s happening with the final GA360 sunset ?

  Google has given Universal Analytics 360 properties with a current 360 licence a one-time extension, which will end on 1 July 2024.

  Why did Google extend the sunset ?

  In a blog post on Google, Russell Ketchum, Director of Product Management at Google Analytics, provided more details about the final GA360 sunset. 

  In short, the tech giant realised it would take large enterprise accounts (which typically have complex analytics setups) much longer to transition smoothly. The extension gives them time to migrate to GA4 and check everything is tracking correctly. 

  What’s more, Google is also focused on improving the GA4 experience before more GA360 users migrate :

  “We’re focusing our efforts and investments on Google Analytics 4 to deliver a solution built to adapt to a changing ecosystem. Because of this, throughout 2023 we’ll be shifting support away from Universal Analytics 360 and will move our full focus to Google Analytics 4 in 2024. As a result, performance will likely degrade in Universal Analytics 360 until the new sunset date.”

  Despite the extension, the July sunset is definitive. 

  Starting the week of 1 July 2024, you won’t be able to access any Universal Analytics properties or the API (not even with read-only access), and all data will be deleted.

  In other words, it’s not just data collection that will cease at the start of July. You won’t be able to access the platform, and all your data will be deleted. 

  What GA360 features is Google deprecating, and when ?

  If you’re wondering which GA360 features are being deprecated and when, here is the timeline for Google’s final GA360 sunset :

  • 1 January 2024 : From the beginning of the year, Google doesn’t guarantee all features and functionalities in UA 360 will continue to work as expected. 
  • 29 January 2024 : Google began deprecating a string of advertising and measurement features as it shifts resources to focus on GA4. These features include :
    • Realtime reports
    • Lifetime Value report
    • Model Explorer
    • Cohort Analysis
    • Conversion Probability report
    • GDN Impression Beta
  • Early March 2024 : Google began deprecating more advertising and measurement features. Deprecated advertising features include Demographic and Interest reports, Publisher reporting, Phone Analytics, Event and Salesforce Data Import, and Realtime BigQuery Export. Deprecated measurement features include Universal Analytics property creation, App Views, Unsampled reports, Custom Tables and annotations.
  • Late March 2024 : This is the last recommended date for migration to GA4 to give users three months to validate data and settings. By this date, Google recommends that you migrate your UA’s Google Ads links to GA4, create new Google Ad conversions based on GA4 events, and add GA4 audiences to campaigns and ad groups for retargeting. 
  • 1 July 2024 : From 1 July 2024, you won’t be able to access any UA properties, and all data will be deleted.

  What’s different about GA4 360 ? 

  GA4 comes with a new set of metrics, setups and reports that change how you analyse your data. We highlight the key differences between Universal Analytics and GA4 below. 

  

  New dashboard

  The layout of GA4 is completely different from Universal Analytics, so much so that the UX can be very complex for first-time and experienced GA users alike. Reports or metrics that used to be available in a couple of clicks in UA now take five or more to find. While you can do more in theory with GA4, it takes much more work. 

  New measurements

  The biggest difference between GA4 and UA is how Google measures data. GA4 tracks events — and everything counts as an event. That includes pageviews, scrolls, clicks, file downloads and contact form submissions. 

  The idea is to anonymise data while letting you track complex buyer journeys across multiple devices. However, it can be very confusing, even for experienced marketers and analysts. 

  New metrics

  You won’t be able to track the same metrics in GA4 as in Universal Analytics. Rather than bounce rate, for example, you are forced to track engagement rate, which is the percentage of engaged sessions. These sessions last at least ten seconds, at least two pageviews or at least one conversion event. 

  Confused ? You’re not alone. 

  New reports

  Most reports you’ll be familiar with in Universal Analytics have been replaced in GA4. The new platform also has a completely different reporting interface, with every report grouped under the following five headings : realtime, audience, acquisition, behaviour and conversions. It can be hard for experienced marketers, let alone beginners, to find their way around these new reports. 

  AI insights

  GA4 has machine learning (ML) capabilities that allow you to generate AI insights from your data. Specifically, GA4 has predictive analytics features that let you track three trends : 

  • Purchase probability : the likelihood that a consumer will make a purchase in a given timeframe.
  • Churn probability : the likelihood a customer will churn in a given period.
  • Predictive revenue : the amount of revenue a user is likely to generate over a given period. 

  Google generates these insights using historical data and machine learning algorithms. 

  Cross-platform capabilities

  GA4 also offers cross-platform capabilities, meaning it can track user interactions across websites and mobile apps, giving businesses a holistic view of customer behaviour. This allows for better decision-making throughout the customer journey.

  Does GA4 360 come with other risks ?

  Aside from the poor usability, complexity and steep learning curve, upgrading your GA360 property to GA4 comes with several other risks.

  GA4 has a rocky relationship with privacy regulations, and while you can use it in a GDPR-compliant way at the moment, there’s no guarantee you’ll be able to do so in the future. 

  This presents the prospect of fines for non-compliance. A worse risk, however, is regulators forcing you to change web analytics platforms in the future—something that’s already happened in the EU. Migrating to a new application can be incredibly painful and time-consuming, especially when you can choose a privacy-friendly alternative that avoids the possibility of this scenario. 

  If all this wasn’t bad enough, switching to GA4 risks your historical Universal Analytics data. That’s because you can’t import Universal Analytics data into GA4, even if you migrate ahead of the sunset deadline.

  Why you should consider a GA4 360 alternative instead

  With the GA360 sunset on the horizon, what are your options if you don’t want to deal with GA4’s problems ? 

  The easiest solution is to migrate to a GA4 360 alternative instead. And there are plenty of reasons to migrate from Google Analytics to a privacy-friendly alternative like Matomo. 

  Keep historical data

  As we’ve explained, Google isn’t letting users import their Universal Analytics data from GA360 to GA4. The easiest way to keep it is by switching to a Google Analytics alternative like Matomo that lets you import your historical data. 

  Any business using Google Analytics, whether a GA360 user or otherwise, can import data into Matomo using our Google Analytics Importer plugin. It’s the best way to avoid disruption or losing data when moving on from Universal Analytics.

  Collect 100% accurate data

  Google Analytics implements data sampling and machine learning to fill gaps in your data and generate the kind of predictive insights we mentioned earlier. For standard GA4 users, data sampling starts at 10 million events. For GA4 360 users, data sampling starts at one billion events. Nevertheless, Google Analytics data may not accurately reflect your web traffic. 

  You can fix this using a Google Analytics alternative like Matomo that doesn’t use data sampling. That way, you can be confident that your data-driven decisions are being made with 100% accurate user data. 

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Guarantee user privacy first

  Google has a stormy relationship with the EU-US Data Privacy Framework—being banned and added back to the framework in recent years.

  Currently, organisations governed by GDPR can use Google Analytics to collect data about EU residents, but there’s no guarantee of their ability to do so in the future. Nor does the Framework prevent Google from using EU customer data for ulterior purposes such as marketing and training large language models. 

  By switching to a privacy-focused alternative like Matomo, you don’t have to worry about your user’s data ending up in the wrong hands.

  Upgrade to an all-in-one analytics tool

  Switching from Google Analytics can actually give organisations access to more features. That’s because some GA4 alternatives, like Matomo, offer advanced conversion optimisation features like heatmaps, session recordings, A/B testing, form analytics and more right out of the box. 

  

  This makes Matomo a great choice for marketing teams that want to minimise their tech stack and use one tool for both web and behavioural analytics. 

  Get real-time reports

  GA4 isn’t the best tool for analysing website visitors in real time. That’s because it can take up to 4 hours to process new reports in GA360.

  However, Google Analytics alternatives like Matomo have a range of real-time reports you can leverage.

  

  In Matomo, the Real Time Visitor World Map and other reports are processed every 15 minutes. There is also a Visits in Real-time report, which refreshes every five seconds and shows a wealth of data for each visitor. 

  Matomo makes migration easy

  Whether it’s the poor usability, steep learning curve, inaccurate data or privacy issues, there’s every reason to think twice about migrating your UA360 account to GA4. 

  So why not migrate to a Google Analytics alternative like Matomo instead ? One that doesn’t sample data, guarantees your customers’ privacy, offers all the features GA4 doesn’t and is already used by over 1 million sites worldwide.

  Making the switch is easy. Matomo is one of the few web analytics tools that lets you import historical Google Analytics data. In doing so, you can continue to access your historical data and develop more meaningful insights by not having to start from scratch.

  If you’re ready to start a Google Analytics migration, you can try Matomo free for 21 days — no credit card required. 

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

  Your email address
  

  Your website address
  

  Your Analytics subdomain will be .matomo.cloud (change)

  Choose your analytics subdomain
  

  .matomo.cloud

  I accept the terms and conditions and data processing agreement (DPA)

  
  Your information will be used to create an account on our cloud service. For more information please consult our privacy policy.
  
  
  

  Start improving your websites now

  

• 7 Ecommerce Metrics to Track and Improve in 2024

  12 avril 2024, par Erin

  You can invest hours into market research, create the best ads you’ve ever seen and fine-tune your budgets. But the only way to really know if your digital marketing campaigns move the needle is to track ecommerce metrics.

  It’s time to put your hopes and gut feelings aside and focus on the data. Ecommerce metrics are key performance indicators that can tell you a lot about the performance of a single campaign, a traffic source or your entire marketing efforts. 

  That’s why it’s essential to understand what ecommerce metrics are, key metrics to track and how to improve them. 

  Ready to do all of the above ? Then, let’s get started.

  What are ecommerce metrics ? 

  An ecommerce metric is any metric that helps you understand the effectiveness of your digital marketing efforts and the extent to which users are taking a desired action. Most ecommerce metrics focus on conversions, which could be anything from making a purchase to subscribing to your email list.

  You need to track ecommerce metrics to understand how well your marketing efforts are working. They are essential to helping you run a cost-effective marketing campaign that delivers a return on investment. 

  For example, tracking ecommerce metrics will help you identify whether your digital marketing campaigns are generating a return on investment or whether they are actually losing money. They also help you identify your most effective campaigns and traffic sources. 

  Ecommerce metrics also help you spot opportunities for improvement both in terms of your marketing campaigns and your site’s UX. 

  For instance, you can use ecommerce metrics to track the impact on revenue of A/B tests on your marketing campaigns. Or you can use them to understand how users interact with your website and what, if anything, you can do to make it more engaging.

  What’s the difference between conversion rate and conversion value ?

  The difference between a conversion rate and a conversion value is that the former is a percentage while the latter is a monetary value. 

  There can be confusion between the terms conversion rate and conversion value. Since conversions are core metrics in ecommerce, it’s worth taking a minute to clarify. 

  Conversion rates measure the percentage of people who take a desired action on your website compared to the total number of visitors. If you have 100 visitors and one of them converts, then your conversion rate is 1%. 

  Here’s the formula for calculating your conversion rate :

  Conversion Rate (%) = (Number of conversions / Total number of visitors) × 100

  

  Using the example above :

  Conversion Rate = (1 / 100) × 100 = 1%

  Conversion value is a monetary amount you assign to each conversion. In some cases, this is the price of the product a user purchases. In other conversion events, such as signing up for a free trial, you may wish to assign a hypothetical conversion value. 

  To calculate a hypothetical conversion value, let’s consider that you have estimated the average revenue generated from a paying customer is $300. If the conversion rate from free trial to paying customer is 20%, then the hypothetical conversion value for each free trial signup would be $300 multiplied by 20%, which equals $60. This takes into account the number of free trial users who eventually become paying customers.

  So the formula for hypothetical conversion value looks like this :

  

  Hypothetical conversion value = (Average revenue per paying customer) × (Conversion rate)

  Using the values from our example :

  Hypothetical conversion value = $300 × 20% = $60

  The most important ecommerce metrics and how to track them

  There are dozens of ecommerce metrics you could track, but here are seven of the most important. 

  Conversion rate

  Conversion rate is the percentage of visitors who take a desired action. It is arguably one of the most important ecommerce metrics and a great top-level indicator of the success of your marketing efforts. 

  You can measure the conversion rate of anything, including newsletter signups, ebook downloads, and product purchases, using the following formula :

  

  Conversion rate = (Number of people who took action / Total number of visitors) × 100

  You usually won’t have to manually calculate your conversion rate, though. Almost every web analytics or ad platform will track the conversion rate automatically.

  Matomo, for instance, automatically tracks any conversion you set in the Goals report.

  

  As you can see in the screenshot, your site’s conversions are plotted over a period of time and the conversion rate is tracked below the graph. You can change the time period to see how your conversion rate fluctuates.

  If you want to go even further, track your new visitor conversion rate to see how engaging your site is to first-time visitors. 

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Cost per acquisition

  Cost per acquisition (CPA) is the average cost of acquiring a new user. You can calculate your overall CPA or you can break CPA down by email campaign, traffic source, or any other criteria. 

  Calculate CPA by dividing your total marketing cost by the number of new users you acquire.

  

  CPA = Total marketing cost​ / Number of new users acquired 

  So if your Google Ads campaign costs €1,000 and you acquire 100 new users, your CPA is €10 (1000/100=10).

  It’s important to note that CPA is not the same as customer acquisition cost. Customer acquisition cost considers the number of paying customers. CPA looks at the number of users taking a certain action, like subscribing to a newsletter, making a purchase, or signing up for a free trial.

  Cost per acquisition is a direct measure of your marketing efforts’ effectiveness, especially when comparing CPA to average customer spend and return on ad spend. 

  If your CPA is higher than the average customer spend, your marketing campaign is profitable. If not, then you can look at ways to either increase customer spend or decrease your cost per acquisition.

  Customer lifetime value

  Customer lifetime value (CLV) is the average amount of money a customer will spend with your ecommerce brand over their lifetime. 

  Customer value is the total worth of a customer to your brand based on their purchasing behaviour. To calculate it, multiply the average purchase value by the average number of purchases. For instance, if the average purchase value is €50 and customers make 5 purchases on average, the customer value would be €250.

  Use this formula to calculate customer value :

  

  Customer value = Average purchase value × Average number of purchases

  Then you can calculate customer lifetime value using the following formula :

  

  CLV = Customer value × Average customer lifespan

  In another example, let’s say you have a software company and customers pay you €500 per year for an annual subscription. If the average customer lifespan is 5 years, then the Customer Lifetime Value (CLV) would be €2,500.

  Customer lifetime value = €500 × 5 = €2,500

  Knowing how much potential customers are likely to spend helps you set accurate marketing budgets and optimise the price of your products. 

  Return on investment

  Return on investment (ROI) is the amount of revenue your marketing efforts generate compared to total spend. 

  It’s usually calculated as a percentage using the following formula :

  

  ROI = (Revenue / Total spend) × 100

  If you spend €1,000 on a paid ad campaign and your efforts bring in €5,000, then your ROI is 500% (5,000/1,000 × 100).

  With a web analytics tool like Matomo, you can quickly see the revenue generated from each traffic source and you can drill down further to compare different social media channels, search engines, referral websites and campaigns to get more granular view. 

  

  In the example above in Matomo’s Marketing Attribution feature, we can see that social networks are generating the highest amount of revenue in the year. To calculate ROI, we would need to compare the amount of investment to each channel. 

  Let’s say we invested $1,000 per year in search engine optimisation and content marketing, the return on investment (ROI) stands at approximately 2576%, based on a revenue of $26,763.48 per year. 

  Conversely, for organic social media campaigns, where $5,000 was invested and revenue amounted to $71,180.22 per year, the ROI is approximately 1323%. 

  Despite differences in revenue generation, both channels exhibit significant returns on investment, with SEO and content marketing demonstrating a much higher ROI compared to organic social media campaigns. 

  With that in mind, we might want to consider shifting our marketing budget to focus more on search engine optimisation and content marketing as it’s a greater return on investment.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Return on ad spend

  Return on ad spend (ROAS) is similar to return on investment, but it measures the profitability of a specific ad or campaign.

  Calculate ROAS using the following formula :

  

  ROAS = Revenue / Ad cost 

  A positive ROAS means you are making money. If you generate €3 for every €1 you spend on advertising, for example, there’s no reason to turn off that campaign. If you only make €1 for every €2 you spend, however, then you need to shut down the campaign or optimise it. 

  Bounce rate

  Bounce rate is the percentage of visitors who leave your site without taking another action. Calculate it using the following formula :

  

  Bounce rate = (Number of visitors who bounce / Total number of visitors) × 100

  Some portion of users will always leave your site immediately, but you should aim to make your bounce rate as low as possible. After all, every customer that bounces is a missed opportunity that you may never get again. 

  You can check the bounce rate for each one of your site’s pages using Matomo’s page analytics report. Web analytics tools like Google Analytics can track bounce rates for online stores also. 

  

  Bounce rate is calculated automatically. You can sort the list of pages by bounce rate allowing you to prioritise your optimisation efforts. 

  Don’t stop there, though. Explore bounce rate further by comparing your mobile bounce rate vs. desktop bounce rate by segmenting your traffic. This will highlight whether your mobile site needs improving. 

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Click-through rate

  Your clickthrough rate (CTR) tells you the number of people who click on your ads as a percentage of total impressions. You can calculate it by dividing the number of clicks your ad gets by the total number of times people see it. 

  So the formula looks like this :

  

  CTR (%) = (Number of clicks / Total impressions​) × 100

  If an ad gets 1,000 impressions and 10 people click on it, then the CTR will be 10/1,000 × 100 = 1%

  You don’t usually need to calculate your clickthrough rate manually, however. Most ad platforms like Google Ads will automatically calculate CTR.

  What is considered a good ecommerce sales conversion rate ?

  This question is so broad it’s almost impossible to answer. The thing is, sales conversion rates vary massively depending on the conversion event and the industry. A good conversion rate in one industry might be terrible in another. 

  That being said, research shows that the average website conversion rate across all industries is 2.35%. Of course, some websites convert much better than this. The same study found that the top 25% of websites across all industries have a conversion rate of 5.31% or higher. 

  How can you improve your conversion rate ?

  Ecommerce metrics don’t just let you track your campaign’s ROI, they help you identify ways to improve your campaign. 

  Use these five tips to start improving your marketing campaign’s conversion rates today :

  Run A/B tests

  The most effective way to improve almost all of the ecommerce metrics you track is to test, test, and test again.

  A/B testing or multivariate testing compares two different versions of the same content, such as a landing page or blog post. Seeing which version performs better can help you squeeze as many conversions as possible from your website and ad campaigns. But only if you test as many things as possible. This should include :

  • Ad placement
  • Ad copy
  • CTAs
  • Headlines
  • Straplines
  • Colours
  • Design

  To create and analyse tests and their results effectively, you’ll need either an A/B testing platform or a web analytics solution like Matomo, which offers one out of the box.

  

  Matomo’s A/B Testing feature makes it easy to create and track tests over time, breaking down each test’s variations by the metrics that matter. It automatically calculates statistical significance, too, meaning you can be sure you’re making a change for the better. 

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

• FFMPEG Output File is Empty Nothing was Encoded (for a Picture) ?

  4 mars 2023, par Sarah Szabo

  I have a strange issue effecting one of my programs that does bulk media conversions using ffmpeg from the command line, however this effects me using it directly from the shell as well :

  


  ffmpeg -i INPUT.mkv -ss 0:30 -y -qscale:v 2 -frames:v 1 -f image2 -huffman optimal "OUTPUT.png"
fails every run with the error message :
Output file is empty, nothing was encoded (check -ss / -t / -frames parameters if used)

  


  This only happens with very specific videos, and seemingly no other videos. File type is usually .webm. These files have been downloaded properly (usually from yt-dlp), and I have tried re-downloading them just to verify their integrity.

  


  One such file from a colleague was : https://www.dropbox.com/s/xkucr2z5ra1p2oh/Triggerheart%20Execlica%20OST%20%28Arrange%29%20-%20Crueltear%20Ending.mkv?dl=0

  


  Is there a subtle issue with the command string ?

  


  Notes :

  


  removing -huffman optimal had no effect

  


  moving -ss to before -i had no effect

  


  removing -f image2 had no effect

  


  Full Log :

  


  sarah@MidnightStarSign:~/Music/Playlists/Indexing/Indexing Temp$ ffmpeg -i Triggerheart\ Execlica\ OST\ \(Arrange\)\ -\ Crueltear\ Ending.mkv -ss 0:30 -y -qscale:v 2 -frames:v 1 -f image2 -huffman optimal "TEST.png"
ffmpeg version n5.1.2 Copyright (c) 2000-2022 the FFmpeg developers
  built with gcc 12.2.0 (GCC)
  configuration: --prefix=/usr --disable-debug --disable-static --disable-stripping --enable-amf --enable-avisynth --enable-cuda-llvm --enable-lto --enable-fontconfig --enable-gmp --enable-gnutls --enable-gpl --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libdav1d --enable-libdrm --enable-libfreetype --enable-libfribidi --enable-libgsm --enable-libiec61883 --enable-libjack --enable-libmfx --enable-libmodplug --enable-libmp3lame --enable-libopencore_amrnb --enable-libopencore_amrwb --enable-libopenjpeg --enable-libopus --enable-libpulse --enable-librav1e --enable-librsvg --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libsvtav1 --enable-libtheora --enable-libv4l2 --enable-libvidstab --enable-libvmaf --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxcb --enable-libxml2 --enable-libxvid --enable-libzimg --enable-nvdec --enable-nvenc --enable-opencl --enable-opengl --enable-shared --enable-version3 --enable-vulkan
  libavutil      57. 28.100 / 57. 28.100
  libavcodec     59. 37.100 / 59. 37.100
  libavformat    59. 27.100 / 59. 27.100
  libavdevice    59.  7.100 / 59.  7.100
  libavfilter     8. 44.100 /  8. 44.100
  libswscale      6.  7.100 /  6.  7.100
  libswresample   4.  7.100 /  4.  7.100
  libpostproc    56.  6.100 / 56.  6.100
[matroska,webm @ 0x55927f484740] Could not find codec parameters for stream 2 (Attachment: none): unknown codec
Consider increasing the value for the 'analyzeduration' (0) and 'probesize' (5000000) options
Input #0, matroska,webm, from 'Triggerheart Execlica OST (Arrange) - Crueltear Ending.mkv':
  Metadata:
    title           : TriggerHeart Exelica PS2 & 360 Arrange ー 16 - Crueltear Ending
    PURL            : https://www.youtube.com/watch?v=zJ0bEa_8xEg
    COMMENT         : https://www.youtube.com/watch?v=zJ0bEa_8xEg
    ARTIST          : VinnyVynce
    DATE            : 20170905
    ENCODER         : Lavf59.27.100
  Duration: 00:00:30.00, start: -0.007000, bitrate: 430 kb/s
  Stream #0:0(eng): Video: vp9 (Profile 0), yuv420p(tv, bt709), 720x720, SAR 1:1 DAR 1:1, 25 fps, 25 tbr, 1k tbn (default)
    Metadata:
      DURATION        : 00:00:29.934000000
  Stream #0:1(eng): Audio: opus, 48000 Hz, stereo, fltp (default)
    Metadata:
      DURATION        : 00:00:30.001000000
  Stream #0:2: Attachment: none
    Metadata:
      filename        : cover.webp
      mimetype        : image/webp
Codec AVOption huffman (Huffman table strategy) specified for output file #0 (TEST.png) has not been used for any stream. The most likely reason is either wrong type (e.g. a video option with no video streams) or that it is a private option of some encoder which was not actually used for any stream.
Stream mapping:
  Stream #0:0 -> #0:0 (vp9 (native) -> png (native))
Press [q] to stop, [?] for help
Output #0, image2, to 'TEST.png':
  Metadata:
    title           : TriggerHeart Exelica PS2 & 360 Arrange ー 16 - Crueltear Ending
    PURL            : https://www.youtube.com/watch?v=zJ0bEa_8xEg
    COMMENT         : https://www.youtube.com/watch?v=zJ0bEa_8xEg
    ARTIST          : VinnyVynce
    DATE            : 20170905
    encoder         : Lavf59.27.100
  Stream #0:0(eng): Video: png, rgb24, 720x720 [SAR 1:1 DAR 1:1], q=2-31, 200 kb/s, 25 fps, 25 tbn (default)
    Metadata:
      DURATION        : 00:00:29.934000000
      encoder         : Lavc59.37.100 png
frame=    0 fps=0.0 q=0.0 Lsize=N/A time=00:00:00.00 bitrate=N/A speed=   0x    
video:0kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: unknown
Output file is empty, nothing was encoded (check -ss / -t / -frames parameters if used)


  


  Manjaro OS System Specs :

  


  System:&#xA;  Kernel: 6.1.12-1-MANJARO arch: x86_64 bits: 64 compiler: gcc v: 12.2.1&#xA;    parameters: BOOT_IMAGE=/@/boot/vmlinuz-6.1-x86_64&#xA;    root=UUID=f11386cf-342d-47ac-84e6-484b7b2f377d rw rootflags=subvol=@&#xA;    radeon.modeset=1 nvdia-drm.modeset=1 quiet&#xA;    cryptdevice=UUID=059df4b4-5be4-44d6-a23a-de81135eb5b4:luks-disk&#xA;    root=/dev/mapper/luks-disk apparmor=1 security=apparmor&#xA;    resume=/dev/mapper/luks-swap udev.log_priority=3&#xA;  Desktop: KDE Plasma v: 5.26.5 tk: Qt v: 5.15.8 wm: kwin_x11 vt: 1 dm: SDDM&#xA;    Distro: Manjaro Linux base: Arch Linux&#xA;Machine:&#xA;  Type: Desktop Mobo: ASUSTeK model: PRIME X570-PRO v: Rev X.0x&#xA;    serial: <superuser required="required"> UEFI: American Megatrends v: 4408&#xA;    date: 10/27/2022&#xA;Battery:&#xA;  Message: No system battery data found. Is one present?&#xA;Memory:&#xA;  RAM: total: 62.71 GiB used: 27.76 GiB (44.3%)&#xA;  RAM Report: permissions: Unable to run dmidecode. Root privileges required.&#xA;CPU:&#xA;  Info: model: AMD Ryzen 9 5950X bits: 64 type: MT MCP arch: Zen 3&#x2B; gen: 4&#xA;    level: v3 note: check built: 2022 process: TSMC n6 (7nm) family: 0x19 (25)&#xA;    model-id: 0x21 (33) stepping: 0 microcode: 0xA201016&#xA;  Topology: cpus: 1x cores: 16 tpc: 2 threads: 32 smt: enabled cache:&#xA;    L1: 1024 KiB desc: d-16x32 KiB; i-16x32 KiB L2: 8 MiB desc: 16x512 KiB&#xA;    L3: 64 MiB desc: 2x32 MiB&#xA;  Speed (MHz): avg: 4099 high: 4111 min/max: 2200/6358 boost: disabled&#xA;    scaling: driver: acpi-cpufreq governor: schedutil cores: 1: 4099 2: 4095&#xA;    3: 4102 4: 4100 5: 4097 6: 4100 7: 4110 8: 4111 9: 4083 10: 4099 11: 4100&#xA;    12: 4094 13: 4097 14: 4101 15: 4100 16: 4099 17: 4100 18: 4097 19: 4098&#xA;    20: 4095 21: 4100 22: 4099 23: 4099 24: 4105 25: 4098 26: 4100 27: 4100&#xA;    28: 4092 29: 4103 30: 4101 31: 4100 32: 4099 bogomips: 262520&#xA;  Flags: 3dnowprefetch abm adx aes aperfmperf apic arat avic avx avx2 bmi1&#xA;    bmi2 bpext cat_l3 cdp_l3 clflush clflushopt clwb clzero cmov cmp_legacy&#xA;    constant_tsc cpb cpuid cqm cqm_llc cqm_mbm_local cqm_mbm_total&#xA;    cqm_occup_llc cr8_legacy cx16 cx8 de decodeassists erms extapic&#xA;    extd_apicid f16c flushbyasid fma fpu fsgsbase fsrm fxsr fxsr_opt ht&#xA;    hw_pstate ibpb ibrs ibs invpcid irperf lahf_lm lbrv lm mba mca mce&#xA;    misalignsse mmx mmxext monitor movbe msr mtrr mwaitx nonstop_tsc nopl npt&#xA;    nrip_save nx ospke osvw overflow_recov pae pat pausefilter pclmulqdq&#xA;    pdpe1gb perfctr_core perfctr_llc perfctr_nb pfthreshold pge pku pni popcnt&#xA;    pse pse36 rapl rdpid rdpru rdrand rdseed rdt_a rdtscp rep_good sep sha_ni&#xA;    skinit smap smca smep ssbd sse sse2 sse4_1 sse4_2 sse4a ssse3 stibp succor&#xA;    svm svm_lock syscall tce topoext tsc tsc_scale umip v_spec_ctrl&#xA;    v_vmsave_vmload vaes vgif vmcb_clean vme vmmcall vpclmulqdq wbnoinvd wdt&#xA;    x2apic xgetbv1 xsave xsavec xsaveerptr xsaveopt xsaves&#xA;  Vulnerabilities:&#xA;  Type: itlb_multihit status: Not affected&#xA;  Type: l1tf status: Not affected&#xA;  Type: mds status: Not affected&#xA;  Type: meltdown status: Not affected&#xA;  Type: mmio_stale_data status: Not affected&#xA;  Type: retbleed status: Not affected&#xA;  Type: spec_store_bypass mitigation: Speculative Store Bypass disabled via&#xA;    prctl&#xA;  Type: spectre_v1 mitigation: usercopy/swapgs barriers and __user pointer&#xA;    sanitization&#xA;  Type: spectre_v2 mitigation: Retpolines, IBPB: conditional, IBRS_FW,&#xA;    STIBP: always-on, RSB filling, PBRSB-eIBRS: Not affected&#xA;  Type: srbds status: Not affected&#xA;  Type: tsx_async_abort status: Not affected&#xA;Graphics:&#xA;  Device-1: NVIDIA GA104 [GeForce RTX 3070] vendor: ASUSTeK driver: nvidia&#xA;    v: 525.89.02 alternate: nouveau,nvidia_drm non-free: 525.xx&#x2B;&#xA;    status: current (as of 2023-02) arch: Ampere code: GAxxx&#xA;    process: TSMC n7 (7nm) built: 2020-22 pcie: gen: 4 speed: 16 GT/s lanes: 8&#xA;    link-max: lanes: 16 bus-ID: 0b:00.0 chip-ID: 10de:2484 class-ID: 0300&#xA;  Device-2: AMD Cape Verde PRO [Radeon HD 7750/8740 / R7 250E]&#xA;    vendor: VISIONTEK driver: radeon v: kernel alternate: amdgpu arch: GCN-1&#xA;    code: Southern Islands process: TSMC 28nm built: 2011-20 pcie: gen: 3&#xA;    speed: 8 GT/s lanes: 8 link-max: lanes: 16 ports: active: DP-3,DP-4&#xA;    empty: DP-1, DP-2, DP-5, DP-6 bus-ID: 0c:00.0 chip-ID: 1002:683f&#xA;    class-ID: 0300 temp: 54.0 C&#xA;  Device-3: Microdia USB 2.0 Camera type: USB driver: snd-usb-audio,uvcvideo&#xA;    bus-ID: 9-2:3 chip-ID: 0c45:6367 class-ID: 0102 serial: <filter>&#xA;  Display: x11 server: X.Org v: 21.1.7 with: Xwayland v: 22.1.8&#xA;    compositor: kwin_x11 driver: X: loaded: modesetting,nvidia dri: radeonsi&#xA;    gpu: radeon display-ID: :0 screens: 1&#xA;  Screen-1: 0 s-res: 5760x2160 s-dpi: 80 s-size: 1829x686mm (72.01x27.01")&#xA;    s-diag: 1953mm (76.91")&#xA;  Monitor-1: DP-1 pos: 1-2 res: 1920x1080 dpi: 93&#xA;    size: 527x296mm (20.75x11.65") diag: 604mm (23.8") modes: N/A&#xA;  Monitor-2: DP-1-3 pos: 2-1 res: 1920x1080 dpi: 82&#xA;    size: 598x336mm (23.54x13.23") diag: 686mm (27.01") modes: N/A&#xA;  Monitor-3: DP-1-4 pos: 1-1 res: 1920x1080 dpi: 93&#xA;    size: 527x296mm (20.75x11.65") diag: 604mm (23.8") modes: N/A&#xA;  Monitor-4: DP-3 pos: primary,2-2 res: 1920x1080 dpi: 82&#xA;    size: 598x336mm (23.54x13.23") diag: 686mm (27.01") modes: N/A&#xA;  Monitor-5: DP-4 pos: 2-4 res: 1920x1080 dpi: 82&#xA;    size: 598x336mm (23.54x13.23") diag: 686mm (27.01") modes: N/A&#xA;  Monitor-6: HDMI-0 pos: 1-3 res: 1920x1080 dpi: 93&#xA;    size: 527x296mm (20.75x11.65") diag: 604mm (23.8") modes: N/A&#xA;  API: OpenGL v: 4.6.0 NVIDIA 525.89.02 renderer: NVIDIA GeForce RTX&#xA;    3070/PCIe/SSE2 direct-render: Yes&#xA;Audio:&#xA;  Device-1: NVIDIA GA104 High Definition Audio vendor: ASUSTeK&#xA;    driver: snd_hda_intel bus-ID: 5-1:2 v: kernel chip-ID: 30be:1019 pcie:&#xA;    class-ID: 0102 gen: 4 speed: 16 GT/s lanes: 8 link-max: lanes: 16&#xA;    bus-ID: 0b:00.1 chip-ID: 10de:228b class-ID: 0403&#xA;  Device-2: AMD Oland/Hainan/Cape Verde/Pitcairn HDMI Audio [Radeon HD 7000&#xA;    Series] vendor: VISIONTEK driver: snd_hda_intel v: kernel pcie: gen: 3&#xA;    speed: 8 GT/s lanes: 8 link-max: lanes: 16 bus-ID: 0c:00.1&#xA;    chip-ID: 1002:aab0 class-ID: 0403&#xA;  Device-3: AMD Starship/Matisse HD Audio vendor: ASUSTeK&#xA;    driver: snd_hda_intel v: kernel pcie: gen: 4 speed: 16 GT/s lanes: 16&#xA;    bus-ID: 0e:00.4 chip-ID: 1022:1487 class-ID: 0403&#xA;  Device-4: Schiit Audio Unison Universal Dac type: USB driver: snd-usb-audio&#xA;  Device-5: JMTek LLC. Plugable USB Audio Device type: USB&#xA;    driver: hid-generic,snd-usb-audio,usbhid bus-ID: 5-2:3 chip-ID: 0c76:120b&#xA;    class-ID: 0300 serial: <filter>&#xA;  Device-6: ASUSTek ASUS AI Noise-Cancelling Mic Adapter type: USB&#xA;    driver: hid-generic,snd-usb-audio,usbhid bus-ID: 5-4:4 chip-ID: 0b05:194e&#xA;    class-ID: 0300 serial: <filter>&#xA;  Device-7: Microdia USB 2.0 Camera type: USB driver: snd-usb-audio,uvcvideo&#xA;    bus-ID: 9-2:3 chip-ID: 0c45:6367 class-ID: 0102 serial: <filter>&#xA;  Sound API: ALSA v: k6.1.12-1-MANJARO running: yes&#xA;  Sound Interface: sndio v: N/A running: no&#xA;  Sound Server-1: PulseAudio v: 16.1 running: no&#xA;  Sound Server-2: PipeWire v: 0.3.65 running: yes&#xA;Network:&#xA;  Device-1: Intel I211 Gigabit Network vendor: ASUSTeK driver: igb v: kernel&#xA;    pcie: gen: 1 speed: 2.5 GT/s lanes: 1 port: f000 bus-ID: 07:00.0&#xA;    chip-ID: 8086:1539 class-ID: 0200&#xA;  IF: enp7s0 state: up speed: 1000 Mbps duplex: full mac: <filter>&#xA;  IP v4: <filter> type: dynamic noprefixroute scope: global&#xA;    broadcast: <filter>&#xA;  IP v6: <filter> type: noprefixroute scope: link&#xA;  IF-ID-1: docker0 state: down mac: <filter>&#xA;  IP v4: <filter> scope: global broadcast: <filter>&#xA;  WAN IP: <filter>&#xA;Bluetooth:&#xA;  Device-1: Cambridge Silicon Radio Bluetooth Dongle (HCI mode) type: USB&#xA;    driver: btusb v: 0.8 bus-ID: 5-5.3:7 chip-ID: 0a12:0001 class-ID: e001&#xA;  Report: rfkill ID: hci0 rfk-id: 0 state: up address: see --recommends&#xA;Logical:&#xA;  Message: No logical block device data found.&#xA;  Device-1: luks-c847cf9f-c6b5-4624-a25e-4531e318851a maj-min: 254:2&#xA;    type: LUKS dm: dm-2 size: 3.64 TiB&#xA;  Components:&#xA;  p-1: sda1 maj-min: 8:1 size: 3.64 TiB&#xA;  Device-2: luks-swap maj-min: 254:1 type: LUKS dm: dm-1 size: 12 GiB&#xA;  Components:&#xA;  p-1: nvme0n1p2 maj-min: 259:2 size: 12 GiB&#xA;  Device-3: luks-disk maj-min: 254:0 type: LUKS dm: dm-0 size: 919.01 GiB&#xA;  Components:&#xA;  p-1: nvme0n1p3 maj-min: 259:3 size: 919.01 GiB&#xA;RAID:&#xA;  Message: No RAID data found.&#xA;Drives:&#xA;  Local Storage: total: 9.1 TiB used: 2.79 TiB (30.6%)&#xA;  SMART Message: Unable to run smartctl. Root privileges required.&#xA;  ID-1: /dev/nvme0n1 maj-min: 259:0 vendor: Western Digital&#xA;    model: WDS100T3X0C-00SJG0 size: 931.51 GiB block-size: physical: 512 B&#xA;    logical: 512 B speed: 31.6 Gb/s lanes: 4 type: SSD serial: <filter>&#xA;    rev: 111110WD temp: 53.9 C scheme: GPT&#xA;  ID-2: /dev/nvme1n1 maj-min: 259:4 vendor: Western Digital&#xA;    model: WDS100T2B0C-00PXH0 size: 931.51 GiB block-size: physical: 512 B&#xA;    logical: 512 B speed: 31.6 Gb/s lanes: 4 type: SSD serial: <filter>&#xA;    rev: 211070WD temp: 46.9 C scheme: GPT&#xA;  ID-3: /dev/sda maj-min: 8:0 vendor: Western Digital&#xA;    model: WD4005FZBX-00K5WB0 size: 3.64 TiB block-size: physical: 4096 B&#xA;    logical: 512 B speed: 6.0 Gb/s type: HDD rpm: 7200 serial: <filter>&#xA;    rev: 1A01 scheme: GPT&#xA;  ID-4: /dev/sdb maj-min: 8:16 vendor: Western Digital&#xA;    model: WD4005FZBX-00K5WB0 size: 3.64 TiB block-size: physical: 4096 B&#xA;    logical: 512 B speed: 6.0 Gb/s type: HDD rpm: 7200 serial: <filter>&#xA;    rev: 1A01 scheme: GPT&#xA;  ID-5: /dev/sdc maj-min: 8:32 type: USB vendor: SanDisk&#xA;    model: Gaming Xbox 360 size: 7.48 GiB block-size: physical: 512 B&#xA;    logical: 512 B type: N/A serial: <filter> rev: 8.02 scheme: MBR&#xA;  SMART Message: Unknown USB bridge. Flash drive/Unsupported enclosure?&#xA;  Message: No optical or floppy data found.&#xA;Partition:&#xA;  ID-1: / raw-size: 919.01 GiB size: 919.01 GiB (100.00%)&#xA;    used: 611.14 GiB (66.5%) fs: btrfs dev: /dev/dm-0 maj-min: 254:0&#xA;    mapped: luks-disk label: N/A uuid: N/A&#xA;  ID-2: /boot/efi raw-size: 512 MiB size: 511 MiB (99.80%)&#xA;    used: 40.2 MiB (7.9%) fs: vfat dev: /dev/nvme0n1p1 maj-min: 259:1 label: EFI&#xA;    uuid: 8922-E04D&#xA;  ID-3: /home raw-size: 919.01 GiB size: 919.01 GiB (100.00%)&#xA;    used: 611.14 GiB (66.5%) fs: btrfs dev: /dev/dm-0 maj-min: 254:0&#xA;    mapped: luks-disk label: N/A uuid: N/A&#xA;  ID-4: /run/media/sarah/ConvergentRefuge raw-size: 3.64 TiB&#xA;    size: 3.64 TiB (100.00%) used: 2.19 TiB (60.1%) fs: btrfs dev: /dev/dm-2&#xA;    maj-min: 254:2 mapped: luks-c847cf9f-c6b5-4624-a25e-4531e318851a&#xA;    label: ConvergentRefuge uuid: 7d295e73-4143-4eb1-9d22-75a06b1d2984&#xA;  ID-5: /run/media/sarah/MSS_EXtended raw-size: 475.51 GiB&#xA;    size: 475.51 GiB (100.00%) used: 1.48 GiB (0.3%) fs: btrfs&#xA;    dev: /dev/nvme1n1p1 maj-min: 259:5 label: MSS EXtended&#xA;    uuid: f98b3a12-e0e4-48c7-91c2-6e3aa6dcd32c&#xA;Swap:&#xA;  Kernel: swappiness: 60 (default) cache-pressure: 100 (default)&#xA;  ID-1: swap-1 type: partition size: 12 GiB used: 6.86 GiB (57.2%)&#xA;    priority: -2 dev: /dev/dm-1 maj-min: 254:1 mapped: luks-swap label: SWAP&#xA;    uuid: c8991364-85a7-4e6c-8380-49cd5bd7a873&#xA;Unmounted:&#xA;  ID-1: /dev/nvme1n1p2 maj-min: 259:6 size: 456 GiB fs: ntfs label: N/A&#xA;    uuid: 5ECA358FCA356485&#xA;  ID-2: /dev/sdb1 maj-min: 8:17 size: 3.64 TiB fs: ntfs&#xA;    label: JerichoVariance uuid: 1AB22D5664889CBD&#xA;  ID-3: /dev/sdc1 maj-min: 8:33 size: 3.57 GiB fs: iso9660&#xA;  ID-4: /dev/sdc2 maj-min: 8:34 size: 4 MiB fs: vfat label: MISO_EFI&#xA;    uuid: 5C67-4BF8&#xA;USB:&#xA;  Hub-1: 1-0:1 info: Hi-speed hub with single TT ports: 4 rev: 2.0&#xA;    speed: 480 Mb/s chip-ID: 1d6b:0002 class-ID: 0900&#xA;  Hub-2: 1-2:2 info: Hitachi ports: 4 rev: 2.1 speed: 480 Mb/s&#xA;    chip-ID: 045b:0209 class-ID: 0900&#xA;  Device-1: 1-2.4:3 info: Microsoft Xbox One Controller (Firmware 2015)&#xA;    type: <vendor specific="specific"> driver: xpad interfaces: 3 rev: 2.0 speed: 12 Mb/s&#xA;    power: 500mA chip-ID: 045e:02dd class-ID: ff00 serial: <filter>&#xA;  Hub-3: 2-0:1 info: Super-speed hub ports: 4 rev: 3.0 speed: 5 Gb/s&#xA;    chip-ID: 1d6b:0003 class-ID: 0900&#xA;  Hub-4: 2-2:2 info: Hitachi ports: 4 rev: 3.0 speed: 5 Gb/s&#xA;    chip-ID: 045b:0210 class-ID: 0900&#xA;  Hub-5: 3-0:1 info: Hi-speed hub with single TT ports: 1 rev: 2.0&#xA;    speed: 480 Mb/s chip-ID: 1d6b:0002 class-ID: 0900&#xA;  Hub-6: 3-1:2 info: VIA Labs Hub ports: 4 rev: 2.1 speed: 480 Mb/s&#xA;    power: 100mA chip-ID: 2109:3431 class-ID: 0900&#xA;  Hub-7: 3-1.2:3 info: VIA Labs VL813 Hub ports: 4 rev: 2.1 speed: 480 Mb/s&#xA;    chip-ID: 2109:2813 class-ID: 0900&#xA;  Hub-8: 4-0:1 info: Super-speed hub ports: 4 rev: 3.0 speed: 5 Gb/s&#xA;    chip-ID: 1d6b:0003 class-ID: 0900&#xA;  Hub-9: 4-2:2 info: VIA Labs VL813 Hub ports: 4 rev: 3.0 speed: 5 Gb/s&#xA;    chip-ID: 2109:0813 class-ID: 0900&#xA;  Hub-10: 5-0:1 info: Hi-speed hub with single TT ports: 6 rev: 2.0&#xA;    speed: 480 Mb/s chip-ID: 1d6b:0002 class-ID: 0900&#xA;  Device-1: 5-1:2 info: Schiit Audio Unison Universal Dac type: Audio&#xA;    driver: snd-usb-audio interfaces: 2 rev: 2.0 speed: 480 Mb/s power: 500mA&#xA;    chip-ID: 30be:1019 class-ID: 0102&#xA;  Device-2: 5-2:3 info: JMTek LLC. Plugable USB Audio Device type: Audio,HID&#xA;    driver: hid-generic,snd-usb-audio,usbhid interfaces: 4 rev: 1.1&#xA;    speed: 12 Mb/s power: 100mA chip-ID: 0c76:120b class-ID: 0300&#xA;    serial: <filter>&#xA;  Device-3: 5-4:4 info: ASUSTek ASUS AI Noise-Cancelling Mic Adapter&#xA;    type: Audio,HID driver: hid-generic,snd-usb-audio,usbhid interfaces: 4&#xA;    rev: 1.1 speed: 12 Mb/s power: 100mA chip-ID: 0b05:194e class-ID: 0300&#xA;    serial: <filter>&#xA;  Hub-11: 5-5:5 info: Genesys Logic Hub ports: 4 rev: 2.0 speed: 480 Mb/s&#xA;    power: 100mA chip-ID: 05e3:0608 class-ID: 0900&#xA;  Device-1: 5-5.3:7 info: Cambridge Silicon Radio Bluetooth Dongle (HCI mode)&#xA;    type: Bluetooth driver: btusb interfaces: 2 rev: 2.0 speed: 12 Mb/s&#xA;    power: 100mA chip-ID: 0a12:0001 class-ID: e001&#xA;  Hub-12: 5-6:6 info: Genesys Logic Hub ports: 4 rev: 2.0 speed: 480 Mb/s&#xA;    power: 100mA chip-ID: 05e3:0608 class-ID: 0900&#xA;  Hub-13: 6-0:1 info: Super-speed hub ports: 4 rev: 3.1 speed: 10 Gb/s&#xA;    chip-ID: 1d6b:0003 class-ID: 0900&#xA;  Hub-14: 7-0:1 info: Hi-speed hub with single TT ports: 6 rev: 2.0&#xA;    speed: 480 Mb/s chip-ID: 1d6b:0002 class-ID: 0900&#xA;  Device-1: 7-2:2 info: SanDisk Cruzer Micro Flash Drive type: Mass Storage&#xA;    driver: usb-storage interfaces: 1 rev: 2.0 speed: 480 Mb/s power: 200mA&#xA;    chip-ID: 0781:5151 class-ID: 0806 serial: <filter>&#xA;  Device-2: 7-4:3 info: ASUSTek AURA LED Controller type: HID&#xA;    driver: hid-generic,usbhid interfaces: 2 rev: 2.0 speed: 12 Mb/s power: 16mA&#xA;    chip-ID: 0b05:18f3 class-ID: 0300 serial: <filter>&#xA;  Hub-15: 8-0:1 info: Super-speed hub ports: 4 rev: 3.1 speed: 10 Gb/s&#xA;    chip-ID: 1d6b:0003 class-ID: 0900&#xA;  Hub-16: 9-0:1 info: Hi-speed hub with single TT ports: 4 rev: 2.0&#xA;    speed: 480 Mb/s chip-ID: 1d6b:0002 class-ID: 0900&#xA;  Hub-17: 9-1:2 info: Terminus FE 2.1 7-port Hub ports: 7 rev: 2.0&#xA;    speed: 480 Mb/s power: 100mA chip-ID: 1a40:0201 class-ID: 0900&#xA;  Device-1: 9-1.1:4 info: Sunplus Innovation Gaming mouse [Philips SPK9304]&#xA;    type: Mouse driver: hid-generic,usbhid interfaces: 1 rev: 2.0 speed: 1.5 Mb/s&#xA;    power: 98mA chip-ID: 1bcf:08a0 class-ID: 0301&#xA;  Device-2: 9-1.5:6 info: Microdia Backlit Gaming Keyboard&#xA;    type: Keyboard,Mouse driver: hid-generic,usbhid interfaces: 2 rev: 2.0&#xA;    speed: 12 Mb/s power: 400mA chip-ID: 0c45:652f class-ID: 0301&#xA;  Device-3: 9-1.6:7 info: HUION H420 type: Mouse,HID driver: uclogic,usbhid&#xA;    interfaces: 3 rev: 1.1 speed: 12 Mb/s power: 100mA chip-ID: 256c:006e&#xA;    class-ID: 0300&#xA;  Hub-18: 9-1.7:8 info: Terminus Hub ports: 4 rev: 2.0 speed: 480 Mb/s&#xA;    power: 100mA chip-ID: 1a40:0101 class-ID: 0900&#xA;  Device-1: 9-2:3 info: Microdia USB 2.0 Camera type: Video,Audio&#xA;    driver: snd-usb-audio,uvcvideo interfaces: 4 rev: 2.0 speed: 480 Mb/s&#xA;    power: 500mA chip-ID: 0c45:6367 class-ID: 0102 serial: <filter>&#xA;  Device-2: 9-4:11 info: VKB-Sim &#xA9; Alex Oz 2021 VKBsim Gladiator EVO L&#xA;    type: HID driver: hid-generic,usbhid interfaces: 1 rev: 2.0 speed: 12 Mb/s&#xA;    power: 500mA chip-ID: 231d:0201 class-ID: 0300&#xA;  Hub-19: 10-0:1 info: Super-speed hub ports: 4 rev: 3.1 speed: 10 Gb/s&#xA;    chip-ID: 1d6b:0003 class-ID: 0900&#xA;Sensors:&#xA;  System Temperatures: cpu: 38.0 C mobo: 41.0 C&#xA;  Fan Speeds (RPM): fan-1: 702 fan-2: 747 fan-3: 938 fan-4: 889 fan-5: 3132&#xA;    fan-6: 0 fan-7: 0&#xA;  GPU: device: nvidia screen: :0.0 temp: 49 C fan: 0% device: radeon&#xA;    temp: 53.0 C&#xA;Info:&#xA;  Processes: 842 Uptime: 3h 11m wakeups: 0 Init: systemd v: 252&#xA;  default: graphical tool: systemctl Compilers: gcc: 12.2.1 alt: 10/11&#xA;  clang: 15.0.7 Packages: 2158 pm: pacman pkgs: 2110 libs: 495 tools: pamac,yay&#xA;  pm: flatpak pkgs: 31 pm: snap pkgs: 17 Shell: Bash v: 5.1.16&#xA;  running-in: yakuake inxi: 3.3.25&#xA;</filter></filter></filter></filter></filter></filter></vendor></filter></filter></filter></filter></filter></filter></filter></filter></filter></filter></filter></filter></filter></filter></filter></filter></filter></superuser>