Stephen Hawking, a world-renowned scientist who recently passed away, had a brilliant mind that was trapped inside a paralyzed body, and I could not stop thinking about how the opposite is often the case with traumatic brain injury.

Tags: Brian Foo, Library of Congress, music

““I always hated that word—marketing—and I hate it now. Because for me, and this may sound simplistic, the key to marketing is to make something people want. When they want it, they buy it. When they buy it, you have sales. So the product has to speak. The product is what markets things.””

- Interview with Tom Ford.

The State – Sort of – of HTML5 Audio Scott Schiller discusses the high level of hype around HTML5 and CSS3. The two specs render ”many years of feature hacks redundant by replacing them with native features,” he writes in an insightful blog. Blogging, he says: CSS3’s border-radius, box-shadow, text-shadow and gradients, and HTML5’s <canvas>, Read the rest...

So you’re interested in adding an author box to your WordPress blog? Well, you’ve come to the right place. An […]

The post How to Add a WordPress Author Box to Your Blog Posts appeared first on WPHacks.

Are you looking for a new WordPress theme? The Divi Theme, by Elegant Themes, is easily one of the most […]

The post 40 Beautiful WordPress Divi Theme Examples That Will Wow You appeared first on WPHacks.

By Jessica Corbett Common Dreams Far-reaching global assessment details how humanity is undermining the very foundations of the natural world     On the heels of an Earth Day that featured calls for radical action to address the current “age … Continue reading →

Andrew Rickmann posted a photo:

SS Peter and Paul in Wantage, Oxfordshire.

By Jessica Corbett Common Dreams Far-reaching global assessment details how humanity is undermining the very foundations of the natural world     On the heels of an Earth Day that featured calls for radical action to address the current “age … Continue reading →

By Jill Richardson Other Words If environmental solutions aren’t systemic, living green will always mean going against the grain — and usually failing. Every year around Earth Day, I’m reminded of papers I graded in an environmental sociology class. The … Continue reading →

If you compare the UX research methods we use today with the methods we used 16 years ago, something interesting emerges. We see that UX research is becoming increasingly remote and increasingly unmoderated. In other words, we're moving to a world where UX research is becoming automated. We can learn a lot from automated research. But it comes at the price of understanding our users.

When I first started designing websites in the 1990s, I focused most of my attention on creating striking visuals. In my defense, I was typically designing gaming website with only the occasional local business… but my goal was always to design a site that looked “cool.” In the early 2000s I stumbled across a website […]

The post Does your website need to be beautiful? appeared first on Psychology of Web Design | 3.7 Blog.

You have less than one second to make the right impression. Almost immediately after landing on your website users will make an uninformed, mostly subconscious judgment about what type of organization they’re interacting with. This initial judgment will largely be influenced by layout, design, and visual tone. It will not only influence the rest of […]

The post Hooked: How to engage your website audience in one second or less appeared first on Psychology of Web Design | 3.7 Blog.

Want to add a food menu to your restaurant website? Publishing your restaurant menu on your website comes in handy especially if you’re providing an online restaurant reservation or online food delivery. That way your users can figure out the available food options without having to walk into your restaurant. In this article, we’ll show […]

The post 10 Best Restaurant Menu Plugins for WordPress (Compared) appeared first on IsItWP - Free WordPress Theme Detector.

To prevent spammers from flooding old articles with useless comments you can set WordPress to close comments after a certain […]

There is something instantly remarkable about a website with a strong, dark color scheme.

Language sets humans apart in the animal world. Language allows us to communicate complex ideas and emotions.  But too often after brain injury be it stroke or trauma, language is lost. 

Listening without judgement is one of the best things you can do for someone with PTSD.

Chris Guillebeau has traveled to 193 countries. And just to be clear, that is all of the countries recognized on the planet. He is the first person to do it before the age of 35. More importantly, he has built online businesses, side hustles, and mastered the art of a non-conforming lifestyle since he was 19 years old. There’s almost nobody better person equipped to talk about starting lots of businesses. He has a daily podcast called Side Hustle School where he’s featured more than 850 different side hustle businesses + featured many in his new book called 100 Side Hustles. Chris also started half a dozen or more himself, started one of my favorite conferences, The World Domination Summit, and is a New York Times bestselling author of books like the $100 Start Up and The Art of Non-Conformity and many others. This guy is a beast and he’s so savvy, so humble. In this episode: We go into details about some of Chris’ favorite side hustle businesses he’s come across in his podcast & writing this book – what are some of the most common traits and failures. Chris shares his experience with depression, how he’s faced it, […]

The post Adaptation, Self-Awareness and Art of the Side Hustle with Chris Guillebeau appeared first on Chase Jarvis Photography.

In any uncertain time there, we can both feel anxious, upset, curious and we can also look for opportunities. Opportunities for reinvention, for connection, and community in ways we haven’t seen before. That’s the theme of today’s episode with some of my good friends Mark and Brian Canlis + James Beard Award Winning Chef Brady Williams in a conversation we recorded for CreativeLive TV. Mark and Brian run an iconic restaurant in Seattle named Canlis. It’s been a family business for over 70 years. Faced with these uncertain times, they share how they’ve reinvented their business 3 times over the last couple of months. No matter what industry you’re in, their story of overcoming obstacles, problem solving and heart is wisdom for all of us. Enjoy! FOLLOW CANLIS: instagram | website Listen to the Podcast Subscribe   Watch the Episode This podcast is brought to you by CreativeLive. CreativeLive is the world’s largest hub for online creative education in photo/video, art/design, music/audio, craft/maker, money/life and the ability to make a living in any of those disciplines. They are high quality, highly curated classes taught by the world’s top experts — Pulitzer, Oscar, Grammy Award winners, New York Times best selling authors […]

The post Resilience + Reinvention with Canlis Restaurateurs appeared first on Chase Jarvis Photography.

Icons packs are among the most desirable freebies around. There are several out there, going from a wide array of topics from user interfaces to personal finance. But sometimes you can find some rather unusual but clever additions to the icons universe. This Vector Audio DJ Pack is a nice example, brought to you exclusively …

Freebie: 264 Vector Audio DJ Pack Icons Read More »

For years now I’ve had a thing for old doorways with big old locks – now on Cyprus it escalated a bit due to the number of absolutely beautiful old doors. Many of them not restored but broken or run […]

In this tutorial, you’ll be building a Survey App, where we’ll learn to validate our users form data, implement Authentication in Vue, and be able to receive survey data using Vue and Firebase (a BaaS platform). As we build this app, we’ll be learning how to handle form validation for different kinds of data, including reaching out to the backend to check if an email is already taken, even before the user submits the form during sign up.

St-Donat, Bas-St-Laurent, Québec

St-Donat, Bas-St-Laurent, Québec

St-Donat, Bas-St-Laurent, Québec

St-Donat, Bas-St-Laurent, Québec

St-Donat, Bas-St-Laurent, Québec

Let $1 le r < n$ be integers. We give a proof that the group $mathop{mathrm{Aut}}({X_{n}^{mathbb{N}}, sigma_{n}})$ of automorphisms of the one-sided shift on $n$ letters embeds naturally as a subgroup $mathcal{h}_{n}$ of the outer automorphism group $mathop{mathrm{Out}}(G_{n,r})$ of the Higman-Thompson group $G_{n,r}$. From this, we can represent the elements of $mathop{mathrm{Aut}}({X_{n}^{mathbb{N}}, sigma_{n}})$ by finite state non-initial transducers admitting a very strong synchronizing condition.

Let $H in mathcal{H}_{n}$ and write $|H|$ for the number of states of the minimal transducer representing $H$. We show that $H$ can be written as a product of at most $|H|$ torsion elements. This result strengthens a similar result of Boyle, Franks and Kitchens, where the decomposition involves more complex torsion elements and also does not support practical extit{a priori} estimates of the length of the resulting product.

We also give new proofs of some known results about $mathop{mathrm{Aut}}({X_{n}^{mathbb{N}}, sigma_{n}})$.

Miller and Sheffield introduced a notion of an imaginary surface as an equivalence class of pairs of simply connected proper subdomains of $mathbb{C}$ and Gaussian free fields (GFFs) on them under conformal equivalence. They considered the situation in which the conformal transformations are given by a chordal Schramm--Loewner evolution (SLE). In the present paper, we construct processes of GFF on $mathbb{H}$ (the upper half-plane) and $mathbb{O}$ (the first orthant of $mathbb{C}$) by coupling zero-boundary GFFs on these domains with stochastic log-gases defined on parts of boundaries of the domains, $mathbb{R}$ and $mathbb{R}_+$, called the Dyson model and the Bru--Wishart process, respectively, using multiple SLEs evolving in time. We prove that the obtained processes of GFF are stationary. The stationarity defines an equivalence relation between GFFs, and the pairs of time-evolutionary domains and stationary processes of GFF will be regarded as generalizations of the imaginary surfaces studied by Miller and Sheffield.

In this paper we first review the setting for the geometric Langlands functoriality and establish a result for the `backward' functoriality functor. We illustrate this by known examples of the geometric theta-lifting. We then apply the above result to obtain new Hecke eigen-sheaves. The most important application is a construction of the automorphic sheaf for G=GSp_4 attached to a G^L-local system on a curve X such that its standard representation is an irreducible local system of rank 4 on X.

We consider Landau-Ginzburg models stemming from groups comprised of non-diagonal symmetries, and we describe a rule for the mirror LG model. In particular, we present the non-abelian dual group, which serves as the appropriate choice of group for the mirror LG model. We also describe an explicit mirror map between the A-model and the B-model state spaces for two examples. Further, we prove that this mirror map is an isomorphism between the untwisted broad sectors and the narrow diagonal sectors for Fermat type polynomials.

Let $hat G$ be the finite simply connected version of an exceptional Chevalley group, and let $V$ be a nontrivial irreducible module, of minimal dimension, for $hat G$ over its field of definition. We explore the overgroup structure of $hat G$ in $mathrm{GL}(V)$, and the submodule structure of the exterior square (and sometimes the third Lie power) of $V$. When $hat G$ is defined over a field of odd prime order $p$, this allows us to construct the smallest (with respect to certain properties) $p$-groups $P$ such that the group induced by $mathrm{Aut}(P)$ on $P/Phi(P)$ is either $hat G$ or its normaliser in $mathrm{GL}(V)$.

The main goal of this paper is to achieve a parametrization of the solution set of the truncated matricial Hausdorff moment problem in the non-degenerate and degenerate situation. We treat the even and the odd cases simultaneously. Our approach is based on Schur analysis methods. More precisely, we use two interrelated versions of Schur-type algorithms, namely an algebraic one and a function-theoretic one. The algebraic version, worked out in our former paper arXiv:1908.05115, is an algorithm which is applied to finite or infinite sequences of complex matrices. The construction and discussion of the function-theoretic version is a central theme of this paper. This leads us to a complete description via Stieltjes transform of the solution set of the moment problem under consideration. Furthermore, we discuss special solutions in detail.

We introduce a Gaussian measure formally preserved by the 2-dimensional Primitive Equations driven by additive Gaussian noise. Under such measure the stochastic equations under consideration are singular: we propose a solution theory based on the techniques developed by Gubinelli and Jara in cite{GuJa13} for a hyperviscous version of the equations.

Let $(K, u)$ be a valued field, the notions of emph{augmented valuation}, of emph{limit augmented valuation} and of emph{admissible family} of valuations enable to give a description of any valuation $mu$ of $K [x]$ extending $ u$. In the case where the field $K$ is algebraically closed, this description is particularly simple and we can reduce it to the notions of emph{minimal pair} and emph{pseudo-convergent family}. Let $(K, u )$ be a henselian valued field and $ar u$ the unique extension of $ u$ to the algebraic closure $ar K$ of $K$ and let $mu$ be a valuation of $ K [x]$ extending $ u$, we study the extensions $armu$ from $mu$ to $ar K [x]$ and we give a description of the valuations $armu_i$ of $ar K [x]$ which are the extensions of the valuations $mu_i$ belonging to the admissible family associated with $mu$.

In this short note we give a proof of the famous conjecture of Erd"{o}s-Straus for the case $nequiv13 extrm{ mod } 24.$ The Erd"{o}s--Straus conjecture states that the equation $frac{4}{n}=frac{1}{x}+frac{1}{y}+frac{1}{z}$ has positive integer solutions $x,y,z$ for every $ngeq 2$. It is open for $nequiv 1 extrm{ mod } 12$. Indeed, in all of the other cases the solutions are always easy to find. We prove that the conjecture is true for every $nequiv 13 extrm{ mod } 24$. Therefore, to solve it completely, it remains to find solutions for every $nequiv 1 extrm{ mod } 24$.

The aim of this paper is to obtain a generalized CK-extension theorem in superspace for the bi-axial Dirac operator. In the classical commuting case, this result can be written as a power series of Bessel type of certain differential operators acting on a single initial function. In the superspace setting, novel structures appear in the cases of negative even superdimensions. In these cases, the CK-extension depends on two initial functions on which two power series of differential operators act. These series are not only of Bessel type but they give rise to an additional structure in terms of Appell polynomials. This pattern also is present in the structure of the Pizzetti formula, which describes integration over the supersphere in terms of differential operators. We make this relation explicit by studying the decomposition of the generalized CK-extension into plane waves integrated over the supersphere. Moreover, these results are applied to obtain a decomposition of the Cauchy kernel in superspace into monogenic plane waves, which shall be useful for inverting the super Radon transform.

Computer science class enrollments have rapidly risen in the past decade. With current class sizes, standard approaches to grading and providing personalized feedback are no longer possible and new techniques become both feasible and necessary. In this paper, we present the third version of Automata Tutor, a tool for helping teachers and students in large courses on automata and formal languages. The second version of Automata Tutor supported automatic grading and feedback for finite-automata constructions and has already been used by thousands of users in dozens of countries. This new version of Automata Tutor supports automated grading and feedback generation for a greatly extended variety of new problems, including problems that ask students to create regular expressions, context-free grammars, pushdown automata and Turing machines corresponding to a given description, and problems about converting between equivalent models - e.g., from regular expressions to nondeterministic finite automata. Moreover, for several problems, this new version also enables teachers and students to automatically generate new problem instances. We also present the results of a survey run on a class of 950 students, which shows very positive results about the usability and usefulness of the tool.

With the increase in use of Unmanned Aerial Vehicles (UAVs)/drones, it is important to detect and identify causes of failure in real time for proper recovery from a potential crash-like scenario or post incident forensics analysis. The cause of crash could be either a fault in the sensor/actuator system, a physical damage/attack, or a cyber attack on the drone's software. In this paper, we propose novel architectures based on deep Convolutional and Long Short-Term Memory Neural Networks (CNNs and LSTMs) to detect (via Autoencoder) and classify drone mis-operations based on sensor data. The proposed architectures are able to learn high-level features automatically from the raw sensor data and learn the spatial and temporal dynamics in the sensor data. We validate the proposed deep-learning architectures via simulations and experiments on a real drone. Empirical results show that our solution is able to detect with over 90% accuracy and classify various types of drone mis-operations (with about 99% accuracy (simulation data) and upto 88% accuracy (experimental data)).

A standard approach to evaluating language models analyzes how models assign probabilities to valid versus invalid syntactic constructions (i.e. is a grammatical sentence more probable than an ungrammatical sentence). Our work uses ambiguous relative clause attachment to extend such evaluations to cases of multiple simultaneous valid interpretations, where stark grammaticality differences are absent. We compare model performance in English and Spanish to show that non-linguistic biases in RNN LMs advantageously overlap with syntactic structure in English but not Spanish. Thus, English models may appear to acquire human-like syntactic preferences, while models trained on Spanish fail to acquire comparable human-like preferences. We conclude by relating these results to broader concerns about the relationship between comprehension (i.e. typical language model use cases) and production (which generates the training data for language models), suggesting that necessary linguistic biases are not present in the training signal at all.

How to generate testing scenario libraries for connected and automated vehicles (CAVs) is a major challenge faced by the industry. In previous studies, to evaluate maneuver challenge of a scenario, surrogate models (SMs) are often used without explicit knowledge of the CAV under test. However, performance dissimilarities between the SM and the CAV under test usually exist, and it can lead to the generation of suboptimal scenario libraries. In this paper, an adaptive testing scenario library generation (ATSLG) method is proposed to solve this problem. A customized testing scenario library for a specific CAV model is generated through an adaptive process. To compensate the performance dissimilarities and leverage each test of the CAV, Bayesian optimization techniques are applied with classification-based Gaussian Process Regression and a new-designed acquisition function. Comparing with a pre-determined library, a CAV can be tested and evaluated in a more efficient manner with the customized library. To validate the proposed method, a cut-in case study was performed and the results demonstrate that the proposed method can further accelerate the evaluation process by a few orders of magnitude.

We give an efficient algorithm for robustly clustering of a mixture of two arbitrary Gaussians, a central open problem in the theory of computationally efficient robust estimation, assuming only that the the means of the component Gaussians are well-separated or their covariances are well-separated. Our algorithm and analysis extend naturally to robustly clustering mixtures of well-separated strongly logconcave distributions. The mean separation required is close to the smallest possible to guarantee that most of the measure of each component can be separated by some hyperplane (for covariances, it is the same condition in the second degree polynomial kernel). We also show that for Gaussian mixtures, separation in total variation distance suffices to achieve robust clustering. Our main tools are a new identifiability criterion based on isotropic position and the Fisher discriminant, and a corresponding Sum-of-Squares convex programming relaxation, of fixed degree.

Our starting point are register automata for data words, in the style of Kaminski and Francez. We study the effects of the single-use restriction, which says that a register is emptied immediately after being used. We show that under the single-use restriction, the theory of automata for data words becomes much more robust. The main results are: (a) five different machine models are equivalent as language acceptors, including one-way and two-way single-use register automata; (b) one can recover some of the algebraic theory of languages over finite alphabets, including a version of the Krohn-Rhodes Theorem; (c) there is also a robust theory of transducers, with four equivalent models, including two-way single use transducers and a variant of streaming string transducers for data words. These results are in contrast with automata for data words without the single-use restriction, where essentially all models are pairwise non-equivalent.

Diagnosis of high impedance fault (HIF) is a challenge for nowadays distribution network protections. The fault current of a HIF is much lower than that of a normal load, and fault feature is significantly affected by fault scenarios. A detection and feeder identification algorithm for HIFs is proposed in this paper, based on the high-resolution and synchronous waveform data. In the algorithm, an interval slope is defined to describe the waveform distortions, which guarantees a uniform feature description under various HIF nonlinearities and noise interferences. For three typical types of network neutrals, i.e.,isolated neutral, resonant neutral, and low-resistor-earthed neutral, differences of the distorted components between the zero-sequence currents of healthy and faulty feeders are mathematically deduced, respectively. As a result, the proposed criterion, which is based on the distortion relationships between zero-sequence currents of feeders and the zero-sequence voltage at the substation, is theoretically supported. 28 HIFs grounded to various materials are tested in a 10kV distribution networkwith three neutral types, and are utilized to verify the effectiveness of the proposed algorithm.

Rescue vessels are the main actors in maritime safety and rescue operations. At the same time, aerial drones bring a significant advantage into this scenario. This paper presents the research directions of the AutoSOS project, where we work in the development of an autonomous multi-robot search and rescue assistance platform capable of sensor fusion and object detection in embedded devices using novel lightweight AI models. The platform is meant to perform reconnaissance missions for initial assessment of the environment using novel adaptive deep learning algorithms that efficiently use the available sensors and computational resources on drones and rescue vessel. When drones find potential objects, they will send their sensor data to the vessel to verity the findings with increased accuracy. The actual rescue and treatment operation are left as the responsibility of the rescue personnel. The drones will autonomously reconfigure their spatial distribution to enable multi-hop communication, when a direct connection between a drone transmitting information and the vessel is unavailable.

We present a LiDAR-based and real-time capable 3D perception system for automated driving in urban domains. The hierarchical system design is able to model stationary and movable parts of the environment simultaneously and under real-time conditions. Our approach extends the state of the art by innovative in-detail enhancements for perceiving road users and drivable corridors even in case of non-flat ground surfaces and overhanging or protruding elements. We describe a runtime-efficient pointcloud processing pipeline, consisting of adaptive ground surface estimation, 3D clustering and motion classification stages. Based on the pipeline's output, the stationary environment is represented in a multi-feature mapping and fusion approach. Movable elements are represented in an object tracking system capable of using multiple reference points to account for viewpoint changes. We further enhance the tracking system by explicit consideration of occlusion and ambiguity cases. Our system is evaluated using a subset of the TUBS Road User Dataset. We enhance common performance metrics by considering application-driven aspects of real-world traffic scenarios. The perception system shows impressive results and is able to cope with the addressed scenarios while still preserving real-time capability.

We utilize recent results on the exact block error probability of Gaussian random codes in additive white Gaussian noise to analyze Gaussian random coding for massive multiple-access at finite message length. Soft iterative interference cancellation is found to closely approach the performance bounds recently found in [1]. The existence of two fundamentally different regimes in the trade-off between power and bandwidth efficiency reported in [2] is related to much older results in [3] on power optimization by linear programming. Furthermore, we tighten the achievability bounds of [1] in the low power regime and show that orthogonal constellations are very close to the theoretical limits for message lengths around 100 and above.

In a temporal network causal paths are characterized by the fact that links from a source to a target must respect the chronological order. In this article we study the causal paths structure in temporal networks of human face to face interactions in different social contexts. In a static network paths are transitive i.e. the existence of a link from $a$ to $b$ and from $b$ to $c$ implies the existence of a path from $a$ to $c$ via $b$. In a temporal network the chronological constraint introduces time correlations that affects transitivity. A probabilistic model based on higher order Markov chains shows that correlations that can invalidate transitivity are present only when the time gap between consecutive events is larger than the average value and are negligible below such a value. The comparison between the densities of the temporal and static accessibility matrices shows that the static representation can be used with good approximation. Moreover, we quantify the extent of the causally connected region of the networks over time.

Web services often impose inter-parameter dependencies that restrict the way in which two or more input parameters can be combined to form valid calls to the service. Unfortunately, current specification languages for web services like the OpenAPI Specification (OAS) provide no support for the formal description of such dependencies, which makes it hardly possible to automatically discover and interact with services without human intervention. In this article, we present an approach for the specification and automated analysis of inter-parameter dependencies in web APIs. We first present a domain-specific language, called Inter-parameter Dependency Language (IDL), for the specification of dependencies among input parameters in web services. Then, we propose a mapping to translate an IDL document into a constraint satisfaction problem (CSP), enabling the automated analysis of IDL specifications using standard CSP-based reasoning operations. Specifically, we present a catalogue of nine analysis operations on IDL documents allowing to compute, for example, whether a given request satisfies all the dependencies of the service. Finally, we present a tool suite including an editor, a parser, an OAS extension, a constraint programming-aided library, and a test suite supporting IDL specifications and their analyses. Together, these contributions pave the way for a new range of specification-driven applications in areas such as code generation and testing.