National Park Service (NPS) biologists found spawning translocated endangered humpback chub (Gila cypha) in Havasu Creek during a recent fisheries monitoring trip that occurred between May 6 and May 15. https://www.nps.gov/grca/learn/news/translocated-humpback-chub-spawn-in-havasu-creek.htm

Grand Canyon National Park will begin replacing a portion of the Trans-Canyon Pipeline at Phantom Ranch beginning on Monday, January 26, 2015. https://www.nps.gov/grca/learn/news/replace-portion-tcp.htm

Replacement of the Transcanyon Pipeline at Phantom Ranch has progressed and the contractor has replaced over a quarter mile of pipeline. https://www.nps.gov/grca/learn/news/construction-continues-on-transcanyon-pipeline-replacement-at-phantom-ranch.htm

Because of a break in the Transcanyon Pipeline, there is no drinking water available on the North Kaibab Trail. https://www.nps.gov/grca/learn/news/pipeline-break.htm

Water utility staff at Grand Canyon National Park will begin repairs to a break in the Transcanyon Pipeline. https://www.nps.gov/grca/learn/news/september-pipeline-break.htm

Crews finished repairing a break in the Transcanyon Pipeline that occurred north of Phantom Ranch earlier this week. https://www.nps.gov/grca/learn/news/pipeline-break-fixed.htm

Grand Canyon National Park is in the process of replacing a portion of the Transcanyon Pipeline (TCP) at Phantom Ranch. As part of the construction process, the TCP will be turned off to allow crews to connect the new portions of the pipeline to the existing pipeline. https://www.nps.gov/grca/learn/news/temporary-pipeline-shutdown.htm

Today additional resources arrived to support the Fuller Fire. https://www.nps.gov/grca/learn/news/type-2-team-fuller.htm

The National Park Service (NPS) is seeking public comment on a proposal to replace the obsolete Trans-Canyon Water Distribution Pipeline (Pipeline). The analysis of the project to replace the Pipeline and development of alternatives through an environmental assessment (EA) is required under the National Environmental Policy Act (NEPA). https://www.nps.gov/grca/learn/news/2017-07-05-pipeline-public-comment-sought.htm

North Rim operations in Grand Canyon National Park will begin day use operations on Thursday November 1, 2018. At that time, the Visitor Center, Backcountry Office and Campground Kiosk will be closed. The Entrance Station will be unstaffed, but fees will continue to be collected via an automated machine. Limited park staff is present on the North Rim year-round https://www.nps.gov/grca/learn/news/grand-canyon-north-rim-transitions-into-day-use-area-november-1-2018.htm

The National Park Service (NPS) is seeking public comment on the Transcanyon Water Distribution Pipeline (Pipeline) Environmental Assessment (EA). Public comments will be accepted for a 30-day period from today, Wednesday, October 10 through Saturday, November 10, 2018. https://www.nps.gov/grca/learn/news/national-park-service-requests-public-review-of-the-transcanyon-water-distribution-pipeline-ea.htm

Finding of No Significant Impact signed for the Transcanyon Water Distribution Pipeline project in Grand Canyon National Park. https://www.nps.gov/grca/learn/news/finding-of-no-significant-impact-for-transcanyon-waterline.htm

The Ikes Fire, which has been managed by a Local Type 3 Incident Management Team (IMT), transitioned to a local Type 4 Incident Commander effective this morning, Sunday, August 25, 2019. This will be the Final Ikes Fire News Release unless significant fire activity occurs. North Rim Closures: Powell Plateau Trail, The North Bass Trail, Fire Point, Swamp Point, and the W4 road north of the intersection of the W4 and W1 Roads. https://www.nps.gov/grca/learn/news/ikes-fire-command-transitions-to-type-4-team-closures-remain-20190825.htm

Grand Canyon National Park's North Rim will transition to seasonally reduced services beginning at noon on Oct. 16, 2019. Grand Canyon National Park would like to remind the public to plan accordingly if they intend to visit the North Rim after Oct. 15. https://www.nps.gov/grca/learn/news/gcnp-n-rim-transitions-to-reduced-services-2019-10-02.htm

Grand Canyon National Park is announcing modifications to operations to implement the latest guidance from the White House, Centers for Disease Control & Prevention (CDC), and local and state authorities. 03/19/2020 https://www.nps.gov/grca/learn/news/grca-np-transitions-to-limited-services-03-19-2020.htm

The procedure, which has only been conducted a few times in history, could be a groundbreaking new treatment for patients suffering from lung cancer.

The post In a Revolutionary Medical Treatment, Man’s Lung Was Removed, Cleaned, and Replaced—No Transplant Necessary appeared first on Good News Network.

This research is a preliminary step for an upcoming project.... more

Divi’s new scroll effects are made for you to easily take your web design experience to the next level. Of course, you can apply it to elements within your section directly, but you can choose to add motion to underlying elements too. Going for an underlying approach allows you to keep content static while having […]

The post How to Use Transformed Motion Shapes as Backgrounds with Divi appeared first on Elegant Themes Blog.

This proceedings compiles papers presented by extensionists, natural resource specialists, scientists, technology transfer specialists, and others at an international conference that examined knowledge and technology transfer theories, methods, and case studies. Theory topics included adult education, applied science, extension, diffusion of innovations, social marketing, technology transfer, and others. Descriptions of methods and case studies collectively covered a wide range of current approaches that include combined digital media, engagement of users and communication specialists in the full cycle of research, integrated forestry applications, Internet-based systems, science writing, training, video conferencing, Web-based encyclopedias, and others. Innovations transferred were best management practices for water quality, forest reforestation practices, a land management system, portable timber bridges, reducedimpact logging, silvicultural practices, urban forestry, and many others. Innovation users included forest-land owners; land managers; logging industry; natural resource professionals; policymakers; public; rural and urban communities-and those in the interface between these two; and others. Technology transfer and related efforts took place in countries throughout the world.

Transportation corridors (notably roads) affect wildlife habitat, populations, and entire ecosystems. Considerable effort has been expended to quantify direct effects of roads on wildlife populations and ecological communities and processes. Much less effort has been expended toward quantifying indirect effects. In this report, we provide a comprehensive review of road/transportation corridor ecology; in particular, how this new field of ecology has advanced worldwide. Further, we discuss how research thus far has shaped our understanding and views of the ecological implications of transportation infrastructures, and, in turn, how this has led to the current guidance, policies, and management options. We learned that the impacts of transportation infrastructures are a global issue, with the potential to affect a wide variety of taxonomically diverse species and ecosystems. Because the majority of research to date has focused on the direct and more aesthetic and anthropocentric implications of transportation corridors, mainly wildlife-vehicle collisions, it is a fairly standard practice to incorporate underpasses, green bridges (i.e., overpasses), fencing, and barriers into road corridors to alleviate such impacts. Few studies, however, have been able to demonstrate the efficiency of these structures. Furthermore, it is becoming increasingly evident that the indirect implications of transportation infrastructures (i.e., behavioral responses of wildlife individuals to roads) may be more pervasive, at least from the standpoint of biological diversity. Understanding how road corridors influence the functional connectivity of landscapes is crucial if we are to effectively manage species of concern. With these issues in mind, we propose a program of study that addresses the indirect and cumulative implications of transportation infrastructure on species distributions, community structure and ecosystem function

Newcastle United fans have been treated to some interesting names when it come to transfer

SUPER HI-FI has surpassed 1 billion monthly music transitions, tripling volume from its last report in back in JANUARY. Each transition reflects a unique AI calculation driving perfect song … more

Another AM station is proposing to run testing of all-digital broadcasting, with BRIAN R. WALSH filing an STA request to operate Oldies WIOE-A/FORT WAYNE in full-time HD RADIO MA3 mode with … more

Staff will now be wearing masks and face shields

HUBBARD RADIO/SEATTLE has announced that CAT THOMAS will become the Brand & Content Director at Top 40 KQMV (MOVIN 92.5) and AC KRWM (WARM 106.9), transferring from HUBBARD’s … more

DALLAS, March 23, 2020 — The American Heart Association, the world’s leading nonprofit organization focused on heart and brain health for all, has released interim guidance for resuscitation care intended specifically for patients with known or suspected...

Research Highlights: Upward income mobility is associated with a trade-off between well-being and cardiometabolic health. Reaching a higher income status is not always beneficial for cardiometabolic health, even if it improves economic standing and...

Transitions (basic animations) are one of the most popular additions in CSS3, and one of the easiest to implement for big gains on your site. A transition is simply an animation from one set of CSS properties to another. So for example; whilst before you may have had links with blue text, which suddenly turned orange when you hovered on them, you would now replace that sudden jump with a more graceful animation. In this post, we'll look at the basic syntax, step through some examples, and finally take a brief look at current browser support.

In the last post, we looked at the basics of CSS transitions, including how to use easing to control how your animation flows. In this post, I want to look deeper at a very powerful easing feature; cubic bezier curves. In short, they let you define exactly what path your animation will take, and thanks to some awesome community tools, they are extremely easy to use (No maths required at all). This gives you total flexibility with your transitions. One of the best tools is the free Cubic-Bezier.com by Lea Verou. It lets you make new curves and see them in action just by dragging the handles. We'll use it for all of the demos in this post, and it's well worth a bookmark!

Preset (Everyday) + transform + exposure + graduated filter + radial filter. If shots like this take more than 2 minutes to edit, it’s probably not worth editing. ⏱
—
Boxing Day will be the last day to get my Lightroom presets discounted, which leaves you only 3 more days! Get on it! ???? (at Toronto, Ontario)

Back in late 2016, we introduced Speech Recognition at Auphonic. This allows our users to create transcripts of their recordings, and more usefully, this means podcasts become searchable.
Now we integrated two more speech recognition engines: Amazon Transcribe and Speechmatics. Whilst integrating these services, we also took the opportunity to develop a complete new Transcription Editor:

Screenshot of our Transcript Editor with word confidence highlighting and the edit bar.
Try out the Transcript Editor Examples yourself!

The new Auphonic Transcript Editor is included directly in our HTML transcript output file, displays word confidence values to instantly see which sections should be checked manually, supports direct audio playback, HTML/PDF/WebVTT export and allows you to share the editor with someone else for further editing.

The new services, Amazon Transcribe and Speechmatics, offer transcription quality improvements compared to our other integrated speech recognition services.
They also return word confidence values, timestamps and some punctuation, which is exported to our output files.

The Auphonic Transcript Editor

With the integration of the two new services offering improved recognition quality and word timestamps alongside confidence scores, we realized that we could leverage these improvements to give our users easy-to-use transcription editing.
Therefore we developed a new, open source transcript editor, which is embedded directly in our HTML output file and has been designed to make checking and editing transcripts as easy as possible.

• Edit the transcription directly in the HTML document.
• Show/hide word confidence, to instantly see which sections should be checked manually (if you use Amazon Transcribe or Speechmatics as speech recognition engine).
• Listen to audio playback of specific words directly in the HTML editor.
• Share the transcript editor with others: as the editor is embedded directly in the HTML file (no external dependencies), you can just send the HTML file to some else to manually check the automatically generated transcription.
• Export the edited transcript to HTML, PDF or WebVTT.
• Completely useable on all mobile devices and desktop browsers.

Examples: Try Out the Transcript Editor

Here are two examples of the new transcript editor, taken from our speech recognition audio examples page:

1. Singletrack Transcript Editor Example

Singletrack speech recognition example from the first 10 minutes of Common Sense 309 by Dan Carlin. Speechmatics was used as speech recognition engine without any keywords or further manual editing.

2. Multitrack Transcript Editor Example

A multitrack automatic speech recognition transcript example from the first 20 minutes of TV Eye on Marvel - Luke Cage S1E1. Amazon Transcribe was used as speech recognition engine without any further manual editing.
As this is a multitrack production, the transcript includes exact speaker names as well (try to edit them!).

Transcript Editing

By clicking the Edit Transcript button, a dashed box appears around the text. This indicates that the text is now freely editable on this page. Your changes can be saved by using one of the export options (see below).
If you make a mistake whilst editing, you can simply use the undo/redo function of the browser to undo or redo your changes.

When working with multitrack productions, another helpful feature is the ability to change all speaker names at once throughout the whole transcript just by editing one speaker. Simply click on an instance of a speaker title and change it to the appropriate name, this name will then appear throughout the whole transcript.

Word Confidence Highlighting

Word confidence values are shown visually in the transcript editor, highlighted in shades of red (see screenshot above). The shade of red is dependent on the actual word confidence value: The darker the red, the lower the confidence value. This means you can instantly see which sections you should check/re-work manually to increase the accuracy.

Once you have edited the highlighted text, it will be set to white again, so it’s easy to see which sections still require editing.
Use the button Add/Remove Highlighting to disable/enable word confidence highlighting.

NOTE: Word confidence values are only available in Amazon Transcribe or Speechmatics, not if you use our other integrated speech recognition services!

Audio Playback

The button Activate/Stop Play-on-click allows you to hear the audio playback of the section you click on (by clicking directly on the word in the transcript editor).
This is helpful in allowing you to check the accuracy of certain words by being able to listen to them directly whilst editing, without having to go back and try to find that section within your audio file.

If you use an External Service in your production to export the resulting audio file, we will automatically use the exported file in the transcript editor.
Otherwise we will use the output file generated by Auphonic. Please note that this file is password protected for the current Auphonic user and will be deleted in 21 days.

If no audio file is available in the transcript editor, or cannot be played because of the password protection, you will see the button Add Audio File to add a new audio file for playback.

Export Formats, Save/Share Transcript Editor

Save/Share Editor

The Save Editor button stores the whole transcript editor with all its current changes into a new HTML file. Use this button to save your changes for further editing or if you want to share your transcript with someone else for manual corrections (as the editor is embedded directly in the HTML file without any external dependencies).

Export HTML / Export PDF / Export WebVTT

Use one of these buttons to export the edited transcript to HTML (for WordPress, Word, etc.), to PDF (via the browser print function) or to WebVTT (so that the edited transcript can be used as subtitles or imported in web audio players of the Podlove Publisher or Podigee).
Every export format is rendered directly in the browser, no server needed.

Amazon Transcribe

The first of the two new services, Amazon Transcribe, offers accurate transcriptions in English and Spanish at low costs, including keywords, word confidence, timestamps, and punctuation.

UPDATE 2019:
Amazon Transcribe offers more languages now - please see Amazon Transcribe Features!

Pricing

The free tier offers 60 minutes of free usage a month for 12 months. After that, it is billed monthly at a rate of $0.0004 per second ($1.44/h).
More information is available at Amazon Transcribe Pricing.

Custom Vocabulary (Keywords) Support

Custom Vocabulary (called Keywords in Auphonic) gives you the ability to expand and customize the speech recognition vocabulary, specific to your case (i.e. product names, domain-specific terminology, or names of individuals).
The same feature is also available in the Google Cloud Speech API.

Timestamps, Word Confidence, and Punctuation

Amazon Transcribe returns a timestamp and confidence value for each word so that you can easily locate the audio in the original recording by searching for the text.
It also adds some punctuation, which is combined with our own punctuation and formatting automatically.

The high-quality (especially in combination with keywords) and low costs of Amazon Transcribe make it attractive, despite only currently supporting two languages.
However, the processing time of Amazon Transcribe is much slower compared to all our other integrated services!

Try it yourself:
Connect your Auphonic account with Amazon Transcribe at our External Services Page.

Speechmatics

Speechmatics offers accurate transcriptions in many languages including word confidence values, timestamps, and punctuation.

Many Languages

Speechmatics’ clear advantage is the sheer number of languages it supports (all major European and some Asiatic languages).
It also has a Global English feature, which supports different English accents during transcription.

Timestamps, Word Confidence, and Punctuation

Like Amazon, Speechmatics creates timestamps, word confidence values, and punctuation.

Pricing

Speechmatics is the most expensive speech recognition service at Auphonic.
Pricing starts at £0.06 per minute of audio and can be purchased in blocks of £10 or £100. This equates to a starting rate of about $4.78/h. Reduced rate of £0.05 per minute ($3.98/h) are available if purchasing £1,000 blocks.
They offer significant discounts for users requiring higher volumes. At this further reduced price point it is a similar cost to the Google Speech API (or lower). If you process a lot of content, you should contact them directly at sales@speechmatics.com and say that you wish to use it with Auphonic.
More information is available at Speechmatics Pricing.

Speechmatics offers high-quality transcripts in many languages. But these features do come at a price, it is the most expensive speech recognition services at Auphonic.

Unfortunately, their existing Custom Dictionary (keywords) feature, which would further improve the results, is not available in the Speechmatics API yet.

Try it yourself:
Connect your Auphonic account with Speechmatics at our External Services Page.

What do you think?

Any feedback about the new speech recognition services, especially about the recognition quality in various languages, is highly appreciated.

We would also like to hear any comments you have on the transcript editor particularly - is there anything missing, or anything that could be implemented better?
Please let us know!

Until recently, Amazon Transcribe supported speech recognition in English and Spanish only.
Now they included French, Italian and Portuguese as well - and a few other languages (including German) are in private beta.

Update March 2019:
Now Amazon Transcribe supports German and Korean as well.

The Auphonic Audio Inspector on the status page of a finished Multitrack Production including speech recognition.
Please click on the screenshot to see it in full resolution!

Amazon Transcribe is integrated as speech recognition engine within Auphonic and offers accurate transcriptions (compared to other services) at low costs, including keywords / custom vocabulary support, word confidence, timestamps, and punctuation.
See the following AWS blog post and video for more information about recent Amazon Transcribe developments: Transcribe speech in three new languages: French, Italian, and Brazilian Portuguese.

Amazon Transcribe is also a perfect fit if you want to use our Transcript Editor because you will be able to see word timestamps and confidence values to instantly check which section/words should be corrected manually to increase the transcription accuracy:

Screenshot of our Transcript Editor with word confidence highlighting and the edit bar.

These features are also available if you use Speechmatics, but unfortunately not in our other integrated speech recognition services.

About Speech Recognition within Auphonic

Auphonic has built a layer on top of a few external speech recognition services to make audio searchable:
Our classifiers generate metadata during the analysis of an audio signal (music segments, silence, multiple speakers, etc.) to divide the audio file into small and meaningful segments, which are processed by the speech recognition engine. The results from all segments are then combined, and meaningful timestamps, simple punctuation and structuring are added to the resulting text.

To learn more about speech recognition within Auphonic, take a look at our Speech Recognition and Transcript Editor help pages or listen to our Speech Recognition Audio Examples.

A comparison table of our integrated services (price, quality, languages, speed, features, etc.) can be found here: Speech Recognition Services Comparison.

Conclusion

We hope that Amazon and others will continue to add new languages, to get accurate and inexpensive automatic speech recognition in many languages.

Don't hesitate to contact us if you have any questions or feedback about speech recognition or our transcript editor!

I've never thought of myself as a "car person". The last new car I bought (and in fact, now that I think about it, the first new car I ever bought) was the quirky 1998 Ford Contour SVT. Since then we bought a VW station wagon in 2011

Last week I demonstrated how to build a split-screen website layout using CSS flexbox and viewport units that offers an alternative way to present a brand’s featured content. Clicking on one side or the other navigates further into the site without a page load, using CSS transitions and 3d transforms. This week, I’ll show you […]

The post Tutorial: Duo Layout With CSS3 Animations & Transitions (Pt. 2) appeared first on Web Designer Wall.

Recently, I walked you through how to create a simple landing page that used a couple different CSS animation techniques. “Animation” is a loose term, in web design usually referring to anything that involves movement. CSS transitions are one tool we are given to manipulate elements on state changes or mouse events, and when combines […]

The post Easy CSS Animation With Transition & Transforms appeared first on Web Designer Wall.

I wish I had found Alix Kates Shulman’s memoir "To Love What Is: A Marriage Transformed" in the first month of my husband’s severe TBI, and yet I may not have absorbed it the way I did reading it fifteen years post-injury.

Doing UX research in a university is very different to doing UX research in a business setting. If you're an academic making the leap, what are the main differences you need to keep in mind?

We prove a continuity result for the shearlet transform when restricted to the space of smooth and rapidly decreasing functions with all vanishing moments. We define the dual shearlet transform, called here the shearlet synthesis operator, and we prove its continuity on the space of smooth and rapidly decreasing functions over $mathbb{R}^2 imesmathbb{R} imesmathbb{R}^ imes$. Then, we use these continuity results to extend the shearlet transform to the space of Lizorkin distributions, and we prove its consistency with the classical definition for test functions.

We study a mean field approximation for the 2D Euler vorticity equation driven by a transport noise. We prove that the Euler equations can be approximated by interacting point vortices driven by a regularized Biot-Savart kernel and the same common noise. The approximation happens by sending the number of particles $N$ to infinity and the regularization $epsilon$ in the Biot-Savart kernel to $0$, as a suitable function of $N$.

We use the classical Fourier analysis to introduce analytic families of weighted differential operators on the unit sphere. These operators are polynomial functions of the usual Beltrami-Laplace operator. New inversion formulas are obtained for totally geodesic Funk transforms on the sphere and the correpsonding lambda-cosine transforms.

Given an one-dimensional Lorenz-like expanding map we prove that the conditionlinebreak $P_{top}(phi,partial mathcal{P},ell)<P_{top}(phi,ell)$ (see, subsection 2.4 for definition), introduced by Buzzi and Sarig in [1] is satisfied for all continuous potentials $phi:[0,1]longrightarrow mathbb{R}$. We apply this to prove that quasi-H"older-continuous potentials (see, subsection 2.2 for definition) have at most one equilibrium measure and we construct a family of continuous but not H"older and neither weak H"older continuous potentials for which we observe phase transitions. Indeed, this class includes all H"older and weak-H"older continuous potentials and form an open and [2].

We develop a distributional framework for the shearlet transform $mathcal{S}_{psi}colonmathcal{S}_0(mathbb{R}^2) omathcal{S}(mathbb{S})$ and the shearlet synthesis operator $mathcal{S}^t_{psi}colonmathcal{S}(mathbb{S}) omathcal{S}_0(mathbb{R}^2)$, where $mathcal{S}_0(mathbb{R}^2)$ is the Lizorkin test function space and $mathcal{S}(mathbb{S})$ is the space of highly localized test functions on the standard shearlet group $mathbb{S}$. These spaces and their duals $mathcal{S}_0^prime (mathbb R^2),, mathcal{S}^prime (mathbb{S})$ are called Lizorkin type spaces of test functions and distributions. We analyze the continuity properties of these transforms when the admissible vector $psi$ belongs to $mathcal{S}_0(mathbb{R}^2)$. Then, we define the shearlet transform and the shearlet synthesis operator of Lizorkin type distributions as transpose mappings of the shearlet synthesis operator and the shearlet transform, respectively. They yield continuous mappings from $mathcal{S}_0^prime (mathbb R^2)$ to $mathcal{S}^prime (mathbb{S})$ and from $mathcal{S}^prime (mathbb S)$ to $mathcal{S}_0^prime (mathbb{R}^2)$. Furthermore, we show the consistency of our definition with the shearlet transform defined by direct evaluation of a distribution on the shearlets. The same can be done for the shearlet synthesis operator. Finally, we give a reconstruction formula for Lizorkin type distributions, from which follows that the action of such generalized functions can be written as an absolutely convergent integral over the standard shearlet group.

In the present paper by the Fourier transform we show that every linear differential equations of $n$-th order has a solution in $L^1(Bbb{R})$ which is infinitely differentiable in $Bbb{R} setminus {0}$. Moreover the Hyers-Ulam stability of such equations on $L^1(Bbb{R})$ is investigated.

We study the time-averaged flux in a model of particles that randomly hop on a finite directed graph. In the limit as the number of particles and the time window go to infinity but the graph remains finite, the large-deviation rate functional of the average flux is given by a variational formulation involving paths of the density and flux. We give sufficient conditions under which the large deviations of a given time averaged flux is determined by paths that are constant in time. We then consider a class of models on a discrete ring for which it is possible to show that a better strategy is obtained producing a time-dependent path. This phenomenon, called a dynamical phase transition, is known to occur for some particle systems in the hydrodynamic scaling limit, which is thus extended to the setting of a finite graph.

Large transformer-based language models have been shown to be very effective in many classification tasks. However, their computational complexity prevents their use in applications requiring the classification of a large set of candidates. While previous works have investigated approaches to reduce model size, relatively little attention has been paid to techniques to improve batch throughput during inference. In this paper, we introduce the Cascade Transformer, a simple yet effective technique to adapt transformer-based models into a cascade of rankers. Each ranker is used to prune a subset of candidates in a batch, thus dramatically increasing throughput at inference time. Partial encodings from the transformer model are shared among rerankers, providing further speed-up. When compared to a state-of-the-art transformer model, our approach reduces computation by 37% with almost no impact on accuracy, as measured on two English Question Answering datasets.

The quantum Fourier transform brings efficiency in many respects, especially usage of resource, for most operations on quantum computers. In this study, the existing QFT-based and non-QFT-based quantum arithmetic operations are examined. The capabilities of QFT-based addition and multiplication are improved with some modifications. The proposed operations are compared with the nearest quantum arithmetic operations. Furthermore, novel QFT-based subtraction and division operations are presented. The proposed arithmetic operations can perform non-modular operations on all signed numbers without any limitation by using less resources. In addition, novel quantum circuits of two's complement, absolute value and comparison operations are also presented by using the proposed QFT based addition and subtraction operations.

Representation learning is a critical ingredient for natural language processing systems. Recent Transformer language models like BERT learn powerful textual representations, but these models are targeted towards token- and sentence-level training objectives and do not leverage information on inter-document relatedness, which limits their document-level representation power. For applications on scientific documents, such as classification and recommendation, the embeddings power strong performance on end tasks. We propose SPECTER, a new method to generate document-level embedding of scientific documents based on pretraining a Transformer language model on a powerful signal of document-level relatedness: the citation graph. Unlike existing pretrained language models, SPECTER can be easily applied to downstream applications without task-specific fine-tuning. Additionally, to encourage further research on document-level models, we introduce SciDocs, a new evaluation benchmark consisting of seven document-level tasks ranging from citation prediction, to document classification and recommendation. We show that SPECTER outperforms a variety of competitive baselines on the benchmark.

Many efforts of research are devoted to semantic role labeling (SRL) which is crucial for natural language understanding. Supervised approaches have achieved impressing performances when large-scale corpora are available for resource-rich languages such as English. While for the low-resource languages with no annotated SRL dataset, it is still challenging to obtain competitive performances. Cross-lingual SRL is one promising way to address the problem, which has achieved great advances with the help of model transferring and annotation projection. In this paper, we propose a novel alternative based on corpus translation, constructing high-quality training datasets for the target languages from the source gold-standard SRL annotations. Experimental results on Universal Proposition Bank show that the translation-based method is highly effective, and the automatic pseudo datasets can improve the target-language SRL performances significantly.

A brain-computer interface (BCI) enables a user to communicate with a computer directly using brain signals. Electroencephalograms (EEGs) used in BCIs are weak, easily contaminated by interference and noise, non-stationary for the same subject, and varying across different subjects and sessions. Therefore, it is difficult to build a generic pattern recognition model in an EEG-based BCI system that is optimal for different subjects, during different sessions, for different devices and tasks. Usually, a calibration session is needed to collect some training data for a new subject, which is time consuming and user unfriendly. Transfer learning (TL), which utilizes data or knowledge from similar or relevant subjects/sessions/devices/tasks to facilitate learning for a new subject/session/device/task, is frequently used to reduce the amount of calibration effort. This paper reviews journal publications on TL approaches in EEG-based BCIs in the last few years, i.e., since 2016. Six paradigms and applications -- motor imagery, event-related potentials, steady-state visual evoked potentials, affective BCIs, regression problems, and adversarial attacks -- are considered. For each paradigm/application, we group the TL approaches into cross-subject/session, cross-device, and cross-task settings and review them separately. Observations and conclusions are made at the end of the paper, which may point to future research directions.