The elegance of classic Renaissance sculptures and the vibrant neon colours of the Vaporwave aesthetic are two contrasting styles you wouldn’t expect to see together, but this combination of imagery has become a popular abstract art style. In this tutorial I’ll show you how to apply a vibrant neon glow to a shape with the […]

The post Vaporwave Neon Effect Photoshop Tutorial appeared first on Spoon Graphics.

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The traditional view is that the brain is surrounded by three layers, the dura, arachnoid, and pia mater. Møllgård et al. found a fourth meningeal layer called the subarachnoid lymphatic-like membrane (SLYM). SLYM is immunophenotypically distinct from the other meningeal layers in the human and mouse brain and represents a tight barrier for solutes of more than 3 kilodaltons, effectively subdividing the subarachnoid space into two different compartments. SLYM is the host for a large population of myeloid cells, the number of which increases in response to inflammation and aging, so this layer represents an innate immune niche ideally positioned to surveil the cerebrospinal fluid.

Female athletes are more susceptible to sport-related concussions (SRCs) and experience worse outcomes compared with male athletes. Although numerous studies on SRC have compared the outcomes of concussions in male and female athletes after injury, research pertaining to why female athletes have worse outcomes is limited.

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with a history of repetitive head impacts (RHI). To better understand the strength of evidence underlying the possible causal relationship between RHI and CTE, we examined the medical literature through the Bradford Hill criteria for causation.

Chronic traumatic encephalopathy (CTE) is a neurodegenerative tauopathy associated with repetitive head impacts. These findings implicate cumulative head impact intensity in CTE pathogenesis.

Psychotherapy is as effective treatment for PTSD patients after multiple traumatic events.

Children who sustain an mTBI are at increased risk for developing new affective or behavioral disorders over four-years post-injury.

Reader is a theme by new theme shop WP Minima, a brand which sells entirely on ThemeForest at the moment. They’ve released two themes so far, one free and one paid. This is the paid theme, which costs $35. Reader, being both new and minimalistic, caught my eye last week. A lot of the time, […]

The post Reader theme review: Minimal, but not in a lazy way appeared first on WPCandy.

Let’s start this review with an honest admission. While in the 90s I collected (and read, mostly) tech books like they were going out of style. These days I barely get my hands around a book, let alone consume it. Frankly, I don’t have the time. I have three kids (two are twins) and a […]

The post Review: Professional WordPress Design and Development, 2nd Edition appeared first on WPCandy.

$35, $75, $40, and $200. One of these doesn’t sound like the others. Dumitru Brinzan, who has a long history in WordPress themes at WPZOOM, has started a new theme project called Hermes Themes. The shop offers strictly hotel themes, in contrast to WPZOOM’s more varied selection. Interestingly, Brinzan is pricing his hotel themes at […]

The post The true value of a WordPress theme: Hermes Themes and a $200 price tag appeared first on WPCandy.

This morning I spent some time investigating feed readers and services to replace Google Reader. A lot of internet users have been since Google announced Reader is going away this summer. It’s easy to pull up a list of possible alternatives, but ultimately I found it necessary to just dig in and try them out […]

The post My experience looking for an RSS service to replace Google Reader appeared first on WPCandy.

IT WAS GETTING late the night of Sept. 12, and Dr. Julian Bailes had settled in to watch a little football. The renowned neurosurgeon and concussions expert tuned in just as Miami Dolphins quarterback Tua Tagovailoa sustained yet another head injury. There was Tagovailoa, lying on the ground with his arms outstretched and his fingers curled into the fencing response, an involuntary position that occurs after a brain injury. To Bailes, it looked almost like a replay from a previous Thursday night game, Sept. 29, 2022, with Tagovailoa on his back, his fingers splayed in front of his face in another automatic response to a concussion.

A study conducted by Harvard-affiliated Brigham and Women’s Hospital revealed that individuals experiencing a broad array of long COVID symptoms are twice as likely to have traces of SARS-CoV-2 proteins in their blood compared to those without symptoms of long COVID. The symptoms frequently associated with long COVID include fatigue, brain fog, muscle and joint pain, back pain, headaches, sleep issues, loss of smell or taste, and gastrointestinal problems.These findings were published in the journal Clinical Microbiology and Infection.

Genetic tests showed that certain patients were predisposed to brain injuries if they took the drugs. That information remained secret.

Miami Dolphins quarterback Tua Tagovailoa is rejecting calls to retire after the third official concussion of his NFL career. 

Tua Tagovailoa is set to return to NFL action this weekend after recovering from his latest concussion. Six weeks ago the Miami Dolphins quarterback suffered his third concussion in less than two years - and fourth overall, including his college career. Many pundits and ex-players called for the 26-year-old from Hawaii to retire. Some even said the NFL should take the decision out of his hands. BBC Sport looks at why Tagovailoa has chosen to keep playing and Dr Allen Sills, the NFL's chief medical officer, explains the league's stance.

Western University researchers are taking a unique global approach to finding an effective treatment for people living with long COVID. Led by Schulich School of Medicine & Dentistry professor Dr. Douglas Fraser, the projects represent the first multi-continental research conducted on long COVID, with study sites in Africa and North and South Americas. The long-term effects of long COVID – including symptoms such as brain fog, fatigue and difficulty breathing – can be debilitating and greatly impact quality of life. At least 65 million people around the world are affected by the condition. 

For many people, it’s a ray of hope rooted in research. Recent research is presenting a new way of thinking about suicide prevention, and both experts and patients believe it’s already saving lives.

The American College of Surgeons (ACS) has announced the release of its revised Best Practices Guidelines in the Management of Traumatic Brain Injury, offering healthcare providers comprehensive strategies to improve the care and outcomes of patients with traumatic brain injury (TBI).

New research from the Salk Institute is providing hope for people who suffer from PTSD, panic attacks, migraines, and more. "Our body has an alarm system that detects danger from the environment or inside our body," explains Dr. Sung Han, an Associate Professor at the Salk Institute and lead researcher for this project. "Sometimes our bodies generate false alarms... We need to understand (what) molecules send the false signal to the brain so that we can block (it)."

A high school senior from Bangor, Maine, has decided that when the time comes, he will donate his brain to science. Fionn Parker-Cummings is the youngest person to donate his brain to the University of Pittsburgh National Sports Brain Bank. Researchers will check in with him every year for the rest of his life. Parker-Cummings said he hopes the contribution will advance traumatic brain injury research to protect players like NFL quarterbacks Drake Maye and Tua Tagovailoa, who have recently suffered concussions.

The Department of Veterans Affairs remains convinced that psychedelic therapy can help treat veterans with post-traumatic stress disorder — and it’s going to try to prove it. That commitment comes despite the FDA’s August rejection of a drug company’s plan to offer a psychedelic regimen for PTSD.

A troubling report from the Pentagon earlier this year revealed that suicide is the leading cause of death for Army soldiers—a population that is nearly nine times as likely to die by suicide than in combat.  “Suicide in the military continues to be a public health crisis, despite decades of targeted interventions. The rates are persistently higher than in the general population,” says Jayna Moceri-Brooks, an assistant professor at NYU Rory Meyers College of Nursing who studies firearm injury prevention and suicide among service members and veterans.

Military service is difficult, dangerous, and demanding. But for some veterans, returning to civilian life can also be a challenge. Going from the structure of active duty—with its purpose-driven roles, full-throttle environment, and sense of camaraderie—to the relatively humdrum life of a civilian can be jarring, particularly for veterans who’ve experienced trauma during their service and may suffer from post-traumatic stress disorder (PTSD).  Researchers at Boston University, including Dawne Vogt and Casey Taft—both professors of psychiatry in the Chobanian & Avedisian School of Medicine—are utilizing a variety of data-backed strategies to support veterans struggling to adapt to their new normal lives. 

A commentary, published in the Journal of Neurotrauma, calls for traumatic brain injury to be recognized as a chronic condition as are diabetes, asthma, depression and heart failure. To provide comprehensive care for traumatic brain injury throughout individuals' lifespans, the authors propose that coordinated care models they and others have developed, tested and applied to various populations—including older adults, individuals living with depression and post-intensive care unit survivors—be adapted to improve communication and integration between brain injury specialists—including physical medicine and rehabilitation clinicians—and primary care physicians, fostering better long-term patient care for traumatic brain injury survivors and more support for both patients and their families.

Most people may be familiar with cognitive behavioral therapy (CBT) and other common types of psychotherapy, but art therapy remains somewhat of a mystery to the general public. Not incorporating it into a treatment plan could be a huge missed opportunity for veterans who’ve experienced trauma and other patients in need of mental health support. “Art is a means of therapy and a way to heal,” says Marine Corps veteran Jerry Rael. “It helps me escape some of the things that I went through during my time in service.”  Art can also be therapeutic for families who have lost a loved one in battle, as seen in Make Peace or Die: Honor the Fallen. In the film, Marine Anthony Marquez carves battlefield crosses out of wood for each lost service member and then hand-delivers them to Gold Star families, including a grieving mother who had attempted suicide.

The pounding that sailors’ brains take from years of high-speed wave-slamming in the Special Boat Teams can cause symptoms that wreck their careers — and their lives.

Burts bees

How and why should healthcare providers ask patients if they have PTSD?

Click here to see other video Q&As with Lt. Col. Holcombe.

Click here to return to our BrainLine Military Ask the Expert feature.

How do you test the vision of someone with TBI who cannot communicate — talk or respond otherwise to questions?

Real life is always more complicated than fiction, especially when it comes to brain injury.

Oftentimes balance issues influence restrictions about lifting heavy objects after a brain injury.

A child with a brain injury may develop more injury-related issues as an adult.

NASA’s Juno spacecraft, which has orbited Jupiter since 2016, recently captured striking new images of the gas giant during its 66th close flyby. This solar-powered...

The post Juno’s latest flyby photos reveal Jupiter like never before appeared first on DIY Photography.

A bit of a surprise announcement from Fujifilm! The GFX ETERNA – a cinema camera with a medium format sensor, putting it to to toe...

The post Everything you want to know about the FujiFilm GFX ETERNA Cinema Camera appeared first on DIY Photography.

If you are in the market for a Hasselblad phone, you’ll probably end up with a OnePlus unit, as they have a long collaboration with Hassy. The...

The post Exclusive DIYP report: phone fakes a Hasselblad lens appeared first on DIY Photography.

We are proud to announce that we recently joined the NVIDIA Inception Program, which will help to speed up our deep learning development process and therefore offer the best possible audio processing tools to our users.

What is NVIDIA Inception

NVIDIA is a global leader in hardware and software for Artificial Intelligence (AI).
Their NVIDIA Inception Program will enable us to leverage NVIDIA's cutting-edge technology by accessing more diverse cloud and GPU (Graphics Processing Unit) product offerings, which are used in most Machine Learning and Deep Learning model training instances worldwide. This will allow us to streamline AI development and deployment and train bigger machine-learning models to test and evaluate algorithms faster. The program will also offer us the opportunity to collaborate with industry-leading experts and other AI-driven organizations, among other things.

Our Deep Learning Development Process

For our development process, more GPU capacity means a great saving of time and therewith of course a saving of costs. As an example, one training cycle of our dynamic denoiser model takes almost a week trained with GPUs, however the same training cycle trained with CPUs would take several months.

To illustrate, a CPU (Central Processing Unit) can be compared to a race car, which is very fast but can only transfer a small number of packages, while a GPU in this comparison is a big truck, which can transfer a huge number of packages more slowly. Deep learning algorithms require for training very large datasets consisting of thousands of files, therefore our 'trucks', the GPUs, are the best hardware to choose processing multiple computations simultaneously.

The more GPU capacity we can use, the faster we get results for our tested algorithms, and the faster we know which way we should follow to offer our users the best possible audio processing tools.
Unfortunately, the world is right in the middle of a Global Chip Shortage, so the latest GPUs are very hard to get and super expensive to purchase – unless you have a partnership with a GPU manufacturer.

Conclusion

We are happy to join such a renowned program and look forward to the updates to our product that we will be able to implement and potentially a greater industry transformation.

You can read our full press release here: AuphonicNVIDIAInceptionPressRelease (pdf)

To start a new decade of automatic audio post production with Auphonic, we are happy to launch a few updates:

New Website Design

Opening the new homepage today, you might have noticed that our website looked different from what you had been used to before. Keeping our customers’ feedback from last year in mind, we designed a new vision for Auphonic.

Our new website features a refreshed look with an improved, more engaging, and functional user experience. Moreover, a more straightforward, intuitive, and accessible navigation will give you a seamless workflow and a comfortable exploration of Auphonic’s features.
We hope it will be easier to explore the diversity of applications that Auphonic has. In the end, however, as before, you will have the same full functionality of Auphonic available to you and some extra features if you are using our paid packages or subscriptions.

Take a look yourself: New Auphonic Landing Page

Free Access to our Advanced and Beta Algorithms

In the past, only paying Auphonic users had access to the advanced algorithm parameters, to multitrack advanced audio algorithms, and to our Dynamic Denoising and AutoEQ beta models.

We now enabled all advanced algorithms for free users, and you can use them for 2 hours of audio free each month!

Using the Dynamic Denoiser, you can define whether Auphonic should remove only static or also fast-changing noises and if we should keep or eliminate music. For even greater speech intelligibility control, it is possible to manually adjust the amount of denoising to strike the perfect balance between clarity and ambiance.

The AutoEQ automatically analyzes and optimizes the frequency spectrum of a voice recording to remove sibilance (De-Esser) and to create a clear, warm, and pleasant sound.
The equalization of multi-speaker audio can be complex and time-consuming, as each voice requires its own unique frequency spectrum equalization. Our AutoEQ simplifies this process by creating separate, time-dependent EQ profiles for each speaker, ensuring a consistent and pleasant sound output despite any changes in the voices during the recording.

Our advanced algorithm parameters help you to meet all common audio specifications of platforms like Netflix, Audible, podcasts, broadcasters (EBU R128, ATSC A/85, radio and mobile, commercials) in one click. You can define a set of target parameters (integrated loudness, true peak level, dialog normalization, MaxLRA, MaxM, MaxS), like -16 LUFS for podcasts, and we will produce the audio accordingly.
In addition, they offer more control for multitrack productions and for the Adaptive Leveler.

We would like to give away free hours for new Auphonic users, to try out our free advanced algorithms. Please use this URL to register your new Auphonic account. the code is valid till end of March 2023 and will give you 5 extra production hours for the next month. Happy content creation!

More Audio Examples

There is no better way to experience Auphonic than hearing the difference our post production tool makes when applied to different types of audio and content.
We are happy to share that our new features page now contains some new audio examples you can listen to explore our web tool, and we will add even more examples in the next weeks.

We've listened to your feedback and are excited to announce the introduction of metadata variables in Auphonic for more advanced use of our Basic and Extended Metadata.
This new feature allows you to use metadata fields from your input files to automate workflows. You can easily reference any field by using { curly brackets } and typing the field name, such as {title}, {artist}, {album}, {track}, and more.
To get started, take a look at our Formatting Examples and the Table of all Variables to see all the available options.

Whether you are using the Auphonic Web Service or our API, metadata variables can be applied whenever metadata values are set. They are particularly helpful when working with Presets, Batch Productions, or Watch Folders!

For instance, consider the left column of the following table as input ending up in the metadata as shown in the right column:

Note:
Please mind that fields can not refer to each other in cycles (e.g., if {title} refers to {album}, {album} may not refer to {title}). While the input form will not show any errors, the metadata will most likely not be correct and the production will generate a warning.

Formatting Examples

With metadata variables you can automatically generate your output file basename based on the input filename and podcast metadata, like album, track, and title.
If you have, for example, a podcast preset or input file with the album name "The Placeholder Podcast", you can automatically name your episode title like your input filename. By combining the metadata variables "album" name and your generated episode "title" with any text patterns, like "denoised" in this case, you can create your individual output file basename:

The next example shows how you can create truly unique output file basenames with timestamps. Here, a track number is, together with the input file basename, added up as episode title. So, your unique output file basename could be a combination of this generated episode title with the time and date, when your Auphonic production was started:

See example 3 for more time formatting examples, and this table for the full list of symbols that can be used for formatting dates.

The following time and date example outputs would be possible for a production created at 7:05 pm on Saturday, January 30th in 1999:

See this table for the full list of symbols that can be used for formatting dates.

For the list fields "tags", "chapters", "outputfiles", and multitrack "input_filename/basename", you need to reference every value separately by adding .N to your variable – Where N stands for ascending ordinal numbers starting from 0.
Combined with the .N you can refer to the format, bitrate, suffix, and ending of every selected output file, for example {outputfiles.0.format} refers to the format of the first output file in your list of outputfiles:

• Output File 1 – format: WAV 16-bit PCM, bitrate: optimal, suffix: lossless, ending: wav
• Output File 2 – format: MP3, bitrate: 112 kbps, suffix: lossy, ending: mp3

For all available options, please see the Table of List Variables.

All Metadata Variables

The following variables are available:

For detailed use, please see Formatting Examples.

Conclusion

Metadata Variables are a powerful tool for organizing your productions whenever metadata values are set. Those field references are very convenient when distinguishing between different files at a glance, particularly when working with Presets, Batch Productions, or Watch Folders.

Please do not hesitate to contact us if you have any questions or feedback!

We all know the problem: the content is perfectly prepared, and everything is in place, but the moment you hit the record button, your brain freezes, and what pops out of your mouth is a rain of “ums”, “uhs”, and “mhs” that no listener would enjoy.
Cleaning up a record like that by manually cutting out every single filler word is a painstaking task.

So we heard your requests to automate the filler word removing task, started implementing it, and are now very happy to release our new Automatic Filler Cutter feature. See our Audio Examples and Usage Instructions below.

What is removed?

While the definition of filler words is not the same, depending on who you ask, some words can be used as filler as well as content. For example, “like”, “well”, “you know”, etc. cannot be removed without the risk of removing also content and destroying sentences, even if those words are used as filler words in some cases.

Therefore, we decided to focus on the removal of the obvious fillers, namely any kind of “ums”, “uhs”, “mhs”, German “ähm”, “äh”, “öh”, French “euh”, “euhm” and similar.

Audio Examples

1. English Male Speaker

The first audio example is an excerpt from the interview “From Racing Failure to Red Bull Champion: The Untold Christian Horner Story”. Our algorithm found and removed a remarkable ten filler words in this 45-second snippet:

Screenshot of the Auphonic Audio Inspector: each pale red shaded area corresponds to a cut-out filler word.

2. Austrian-German Female Speaker

The following example is an interview with the Austrian Ex-Foreign Minister, Karin Kneissl, who uses seven filler words within 26 seconds:

Usage Instructions

To use the Auphonic Automatic Filler Cutter feature, you just have to create a production or preset as you are used to and select “Cut Fillers” for “Automatic Cutting” in the section “Audio Algorithms”:

When your production is done, all cut-out filler words will appear as pale red shaded areas in the Auphonic Audio Inspector on the production status page, as you can see in the upper screenshot of the Audio Inspector.

If you want to remove silent segments from your audio as well, please also enable our Automatic Silence Cutting feature.

NOTE: Our Automatic Cutting features (for filler and silence) are not available for video files!

Behind the Scenes

For the training of our Automatic Filler Cutter AI-Algorithm, we created datasets that contain manually labeled audio files, collected from 'real world' audio data. So far, we have labeled, trained, and tested the system with English, German, Spanish, and French data.

However, in the Auphonic Web Service, you can activate and test the Automatic Filler Word Cutter for all languages. We would be very happy to hear how the filler removal works out for completely different-sounding languages from, e.g., the Asian, African, or Slavic language families.

Please send us feedback on any problems or error patterns you discover! This will help us generate specific data for the training to improve the algorithm and eliminate your problems.

Conclusion

Automatic filler word cutting is a powerful tool for podcasters looking to enhance the quality of their content. It boosts clarity and professionalism, all while making your editing process more efficient. Some users, however, see a touch of authenticity in filler words within podcasts. So, we leave it up to you to enable or disable the Automatic Filler Cutter feature for your next Auphonic production, depending on your desired style.

We are currently working on filler word cutting optimizations for more languages, so watch our channels to get all the news on our upgrades!

If you have any feedback for us – how the filler cutter is working in your language, what you do or don't like, what you miss, what else you would want to remove from your audio besides silence and filler words, etc. – you are welcome to contact us via email or directly comment on our production interface!

For those of you who like to be in control of every applied cut, we are introducing an update for our Automatic Silence and Filler Word Cutting Algorithms today: The export of Cut Lists allows you to import cuts into your favorite audio/video editor to check and apply the cuts to your files manually.
Thanks to your great feedback, we were able to update our “Filler Word Cutting” algorithm as well.

Cut Lists Export

We now provide the export of various formats of “Cut Lists” in the Auphonic Web Service.
You can use these formats to modify and apply cuts in your post production audio or video editing program:

Screenshot of the Reaper DAW with imported “ReaperRegions.csv”: pale red regions display filler words and pale gray regions mark silence.

To generate the cut lists, choose “Cut List (Filler and Silence)” in the “Output Files” section. By selecting the correct “Ending” you can export the cut lists to a format that is suitable for your post production audio or video editor:

We support regions and EDL (edit decision list) formats:

• Region formats (“AudacityRegions.txt”, “AuditionRegions.csv” and “ReaperRegions.csv”) list filler and silence cut regions with their respective start and end timestamps.
  You can import those cut region lists into your existing Audacity, Audition, or Reaper projects. There you can edit the cut positions to your liking by deleting, moving, or adding individual cut positions. After that, you may apply the cuts manually.
• EDL (edit decision list) formats, “SamplitudeReaper.edl”, “FinalCutProLegacy.xml”, “FinalCutProX.xml” and “DaVinciResolve.edl” (also known as “cmx3600” format and compatible with various editors), can be imported in your software to automatically apply cuts from the EDL file. Depending on the software you use, you may also edit individual cuts manually before applying them. Be aware though that in some editors it may not be possible to add them to an existing project. If this is the case, simply open a new project with the EDL file instead.

Please just let us know if we do not yet provide a cut list format for your favorite audio or video editing program!

Export Uncut Audio

To only detect fillers/silence but NOT cut them, choose the “Export Uncut Audio” mode for “Automatic Cutting” in “Audio Algorithms”. Then you can query cutting times via our API or select your favorite Cut List format as “Output File” to only export cut times for later editing, but without applying cuts during the Auphonic audio post production.

Using the option “Export Uncut Audio”, it is also possible to use our cutting algorithms for video productions. In this case, we will just detect and report cuts, and you can import and apply them in your favorite video editing program afterwards.

Filler Word Cutting Updates

Thanks to your great feedback, we've been able to further optimize our Automatic Filler Word Cutting algorithm.
By now you probably know that our filler word cutter removes all types of “uhm”, “uh”, “mh”, “ähm”, “euh”, “eh” and similar sounds. If you haven't heard about it yet, our release blog post might be a good starting point.

• Enhanced Fade Curves
  We noticed that due to reverb or background noise in input files, some filler cuts did not sound as smooth as they should have. To prevent such rough cuts, we trained our filler detection models with more diverse speech data and compared different fade curve approaches. Now the filler detection is much more robust against noise. Additionally, we developed an asymmetrical fade solution, which, in our opinion, makes the cuts almost inaudible.

  We nonetheless recommend, though, that you use filler cutting in combination with our Dynamic Denoising or Speech Isolation algorithms. These algorithms remove heavy reverb or noise and thus prevent noise artifacts during cutting.

• Handling of Affirmative Sounds
  Some of you were bothered by the fact that affirmative sounds, like “mhm”, “aha”, and “yeah” were cut along with filler words. Driven by your feedback, we tweaked our filler detection algorithm in a way that will remove considerably fewer of these sounds.

• Multitrack Filler Silencing
  We also received requests to optimize filler cutting for crosstalk in Multitrack productions.
  Let's assume that two speech tracks are simultaneously active and one of the two tracks contains a filler word. In this case, we can not cut the filler word in one track without destroying parts of the speech in the other track.
  Our original solution was to skip such a filler. Now, however, we replace it with silence instead. This removes the filler words while preserving all the speech content.

Feedback

If you want to provide us feedback on how you like the updated filler cutting algorithm or about any other features that are missing, you are very welcome to contact us. You can also leave a comment in the feedback section on the status page of your concrete production.