Over the past decade, wood-energy use in Alaska has grown dramatically.

Northwest Forest Plan—the first 20 years (1994-2013): status and trends of northern spotted owl habitats.

The Blue Mountains Adaptation Partnership was developed to identify climate change issues relevant to resource management in the Blue Mountains region, to find solutions that can minimize negative effects of climate change, and to facilitate transition of diverse ecosystems to a warmer climate.

This assessment evaluates the effects of future climate change on a select set of ecological systems and ecosystem services in Alaska’s Kenai Peninsula and Chugach National Forest regions. The focus of the assessment was established during a multi-agency/organization workshop that established the goal to conduct a rigorous evaluation of a limited range of topics rather than produce a broad overview.

This is the second in a series of periodic monitoring reports on northern spotted owl (Strix occidentalis caurina) population and habitat trends on federally administered lands since implementation of the Northwest Forest Plan in 1994. Here we summarize results from a population analysis that included data from longterm demographic studies during 1985–2008. This data was analyzed separately by study area, and also in a meta-analysis across all study areas to assess temporal and spatial patterns in fecundity, apparent survival, recruitment, and annual rates of population change.

The primary objectives of the effectiveness monitoring plan for the marbled murrelet (Brachyramphus marmoratus) include mapping baseline nesting habitat (at the start of the Northwest Forest Plan [the Plan]) and estimating changes in that habitat over time. Using vegetation data derived from satellite imagery, we modeled habitat suitability by using a maximum entropy model. We used Maxent software to compute habitat suitability scores from vegetation and physiographic attributes based on comparisons of conditions at 342 sites that were occupied by marbled murrelets (equal numbers of confirmed nest sites and likely nest sites) and average conditions over all forested lands in which the murrelets occurred. We estimated 3.8 million acres of higher suitability nesting habitat over all lands in the murrelet's range in Washington, Oregon, and California at the start of the Plan (1994/96). Most (89 percent) baseline habitat on federally administered lands occurred within reserved-land allocations. A substantial amount (36 percent) of baseline habitat occurred on nonfederal lands. Over all lands, we observed a net loss of about 7 percent of higher suitability potential nesting habitat from the baseline period to 2006/07. If we focus on losses and ignore gains, we estimate a loss of about 13 percent of the higher suitability habitat present at baseline, over this same period. Fire has been the major cause of loss of nesting habitat on federal lands since the Plan was implemented; timber harvest is the primary cause of loss on nonfederal lands. We also found that murrelet population size is strongly and positively correlated with amount of nesting habitat, suggesting that conservation of remaining nesting habitat and restoration of currently unsuitable habitat is key to murrelet recovery.

MUSIC BUSINESS WORLDWIDE and the HOLLYWOOD REPORTER are both carrying reports on rumors that SAUDI ARABIA's PUBLIC INVESTMENT FUND is making an offer to buy WARNER MUSIC GROUP. The fund … more

Statement Highlights: Improving lifestyle habits – such as attaining and maintaining a healthy body weight and getting regular, moderate physical activity – may be useful additions to physician-guided management of atrial fibrillation (AF), a serious...

Sala de prensa de la AHA sobre el COVID-19 DALLAS, 10 de abril del 2020 – Nancy Brown, directora ejecutiva de la American Heart Association, la organización voluntaria líder mundial centrada en la salud del corazón y del cerebro, se reunió con los...

Research Highlights: People who had the best heart health, defined as having healthy sleep in addition to meeting the AHA Life Simple 7, were less likely to have a diagnosis of a heart disease and were less likely to develop heart disease in the ...

As the time passes by, the dependency of humans are increasing day by day on the technology and applications to manage their daily chores. But at the same time, the need of changing habits are in high need now a days due to unnatural life and tough...

The post 9 Apps to help you develop Life-changing Habits for the Worth Living Life appeared first on SmashingApps.com.

For many marketers, emails are the lifeline for most marketing efforts. Every SPAM complaint, unsubscribe, or bounce has an impact on the current ROI as well as on the sender’s reputation which affects the ROI of the future campaigns. Yet the sender reputation, that you accumulate over the period of multiple email campaigns, is only...

Many people think the word “disability” means people who require a wheelchair or walker. In reality, however, there is much more to disability than meets the eye. 

Patients with disabilities must receive the same level of lifesaving medical treatment from hospitals during the coronavirus pandemic as able-bodied patients, the Trump administration said.

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.

Usability tests are unique. We ask people to do real tasks with the system and watch. As the person completes the task, we watch their behaviour and listen to their stream-of-consciousness narrative. But what makes a good usability task scenario?

Receiving service-related disability compensation does not interfere with the funds veterans receive from the GI Bill, explains Adam.

“It’s impossible to move forward while staying the same”. That’s what motivated Tyler Babin, a 25 year old up & coming filmmaker, who hustled his way into his dream job only to leave it to pursue the riskier thing, an even bigger bet – on himself. I’ve had literally hundreds of requests over the years to have someone on the show who isn’t Richard Branson or Brene Brown or {fill in the blank star}…ie. host someone who hasn’t “made it big” and is, instead, on the come-up themselves…someone from within our very own community who has been listening for years, connecting dots, gleaning knowledge and is now taking major action on that.  Well THIS is Tyler’s story. If you’ve  followed my pal Gary Vaynerchuk, it’s likely you’ve actually seen some of Tyler’s work. For the last 3-4 years, he’s been a whirlwind tour traveling the world with Gary, shooting photo + video, creative directing projects at Vayner… and it all started right here on this show nearly 8 years ago.  This episode goes full circle, friends. Also – instead of the usual studio conversation, Tyler and I recorded the show while grabbing a burger & margarita just around the corner […]

The post Say Yes, Figure It Out Later. Starting from the Start with Tyler Babin appeared first on Chase Jarvis Photography.

The web is awash with words. They’re everywhere. On websites, in emails, advertisements, tweets, pop-ups, you name it. More people are publishing more copy than at any point in history. That means a lot of information, and a lot of competition. In recent years a slew of ‘readability’ programs have appeared to help us tidy up the things we write. (Grammarly, Readable, and Yoast are just a handful that come to mind.

This paper addresses the problem of identifying the graph structure of a dynamical network using measured input/output data. This problem is known as topology identification and has received considerable attention in recent literature. Most existing literature focuses on topology identification for networks with node dynamics modeled by single integrators or single-input single-output (SISO) systems. The goal of the current paper is to identify the topology of a more general class of heterogeneous networks, in which the dynamics of the nodes are modeled by general (possibly distinct) linear systems. Our two main contributions are the following. First, we establish conditions for topological identifiability, i.e., conditions under which the network topology can be uniquely reconstructed from measured data. We also specialize our results to homogeneous networks of SISO systems and we will see that such networks have quite particular identifiability properties. Secondly, we develop a topology identification method that reconstructs the network topology from input/output data. The solution of a generalized Sylvester equation will play an important role in our identification scheme.

We study the regularity of exceptional actions of groups by $C^{1,alpha}$ diffeomorphisms on the circle, i.e. ones which admit exceptional minimal sets, and whose elements have first derivatives that are continuous with concave modulus of continuity $alpha$. Let $G$ be a finitely generated group admitting a $C^{1,alpha}$ action $ ho$ with a free orbit on the circle, and such that the logarithms of derivatives of group elements are uniformly bounded at some point of the circle. We prove that if $G$ has spherical growth bounded by $c n^{d-1}$ and if the function $1/alpha^d$ is integrable near zero, then under some mild technical assumptions on $alpha$, there is a sequence of exceptional $C^{1,alpha}$ actions of $G$ which converge to $ ho$ in the $C^1$ topology. As a consequence for a single diffeomorphism, we obtain that if the function $1/alpha$ is integrable near zero, then there exists a $C^{1,alpha}$ exceptional diffeomorphism of the circle. This corollary accounts for all previously known moduli of continuity for derivatives of exceptional diffeomorphisms. We also obtain a partial converse to our main result. For finitely generated free abelian groups, the existence of an exceptional action, together with some natural hypotheses on the derivatives of group elements, puts integrability restrictions on the modulus $alpha$. These results are related to a long-standing question of D. McDuff concerning the length spectrum of exceptional $C^1$ diffeomorphisms of the circle.

This paper is devoted to the study of the singularity phenomenon of timelike extremal hypersurfaces in Minkowski spacetime $mathbb{R}^{1+3}$. We find that there are two explicit lightlike self-similar solutions to a graph representation of timelike extremal hypersurfaces in Minkowski spacetime $mathbb{R}^{1+3}$, the geometry of them are two spheres. The linear mode unstable of those lightlike self-similar solutions for the radially symmetric membranes equation is given. After that, we show those self-similar solutions of the radially symmetric membranes equation are nonlinearly stable inside a strictly proper subset of the backward lightcone. This means that the dynamical behavior of those two spheres is as attractors. Meanwhile, we overcome the double roots case (the theorem of Poincar'{e} can't be used) in solving the difference equation by construction of a Newton's polygon when we carry out the analysis of spectrum for the linear operator.

In this paper, we are concerned with the numerical solution of one type integro-differential equation by a probability method based on the fundamental martingale of mixed Gaussian processes. As an application, we will try to simulate the estimation of ruin probability with an unknown parameter driven not by the classical L'evy process but by the mixed fractional Brownian motion.

Let $H$ be a Krull monoid with finite class group $G$ such that every class contains a prime divisor. We consider the system $mathcal L (H)$ of all sets of lengths of $H$ and study when $mathcal L (H)$ contains or is contained in a system $mathcal L (H')$ of a Krull monoid $H'$ with finite class group $G'$, prime divisors in all classes and Davenport constant $mathsf D (G')=mathsf D (G)$. Among others, we show that if $G$ is either cyclic of order $m ge 7$ or an elementary $2$-group of rank $m-1 ge 6$, and $G'$ is any group which is non-isomorphic to $G$ but with Davenport constant $mathsf D (G')=mathsf D (G)$, then the systems $mathcal L (H)$ and $mathcal L (H')$ are incomparable.

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 show that a random puncturing of a code with good distance is list recoverable beyond the Johnson bound. In particular, this implies that there are Reed-Solomon codes that are list recoverable beyond the Johnson bound. It was previously known that there are Reed-Solomon codes that do not have this property. As an immediate corollary to our main theorem, we obtain better degree bounds on unbalanced expanders that come from Reed-Solomon codes.

In this paper, we study the problem of fair classification in the presence of prior probability shifts, where the training set distribution differs from the test set. This phenomenon can be observed in the yearly records of several real-world datasets, such as recidivism records and medical expenditure surveys. If unaccounted for, such shifts can cause the predictions of a classifier to become unfair towards specific population subgroups. While the fairness notion called Proportional Equality (PE) accounts for such shifts, a procedure to ensure PE-fairness was unknown.

In this work, we propose a method, called CAPE, which provides a comprehensive solution to the aforementioned problem. CAPE makes novel use of prevalence estimation techniques, sampling and an ensemble of classifiers to ensure fair predictions under prior probability shifts. We introduce a metric, called prevalence difference (PD), which CAPE attempts to minimize in order to ensure PE-fairness. We theoretically establish that this metric exhibits several desirable properties.

We evaluate the efficacy of CAPE via a thorough empirical evaluation on synthetic datasets. We also compare the performance of CAPE with several popular fair classifiers on real-world datasets like COMPAS (criminal risk assessment) and MEPS (medical expenditure panel survey). The results indicate that CAPE ensures PE-fair predictions, while performing well on other performance metrics.

Sparse models require less memory for storage and enable a faster inference by reducing the necessary number of FLOPs. This is relevant both for time-critical and on-device computations using neural networks. The stabilized lottery ticket hypothesis states that networks can be pruned after none or few training iterations, using a mask computed based on the unpruned converged model. On the transformer architecture and the WMT 2014 English-to-German and English-to-French tasks, we show that stabilized lottery ticket pruning performs similar to magnitude pruning for sparsity levels of up to 85%, and propose a new combination of pruning techniques that outperforms all other techniques for even higher levels of sparsity. Furthermore, we confirm that the parameter's initial sign and not its specific value is the primary factor for successful training, and show that magnitude pruning cannot be used to find winning lottery tickets.

We study the specification and verification of hyperproperties for probabilistic systems represented as Markov decision processes (MDPs). Hyperproperties are system properties that describe the correctness of a system as a relation between multiple executions. Hyperproperties generalize trace properties and include information-flow security requirements, like noninterference, as well as requirements like symmetry, partial observation, robustness, and fault tolerance. We introduce the temporal logic PHL, which extends classic probabilistic logics with quantification over schedulers and traces. PHL can express a wide range of hyperproperties for probabilistic systems, including both classical applications, such as differential privacy, and novel applications in areas such as robotics and planning. While the model checking problem for PHL is in general undecidable, we provide methods both for proving and for refuting a class of probabilistic hyperproperties for MDPs.

While the exact definition and implementation of accountability depend on the specific context, at its core accountability describes a mechanism that will make decisions transparent and often provides means to sanction "bad" decisions. As such, accountability is specifically relevant for Cyber-Physical Systems, such as robots or drones, that embed themselves into a human society, take decisions and might cause lasting harm. Without a notion of accountability, such systems could behave with impunity and would not fit into society. Despite its relevance, there is currently no agreement on its meaning and, more importantly, no way to express accountability properties for these systems. As a solution we propose to express the accountability properties of systems using Structural Causal Models. They can be represented as human-readable graphical models while also offering mathematical tools to analyze and reason over them. Our central contribution is to show how Structural Causal Models can be used to express and analyze the accountability properties of systems and that this approach allows us to identify accountability patterns. These accountability patterns can be catalogued and used to improve systems and their architectures.

By using dissipativity approach, we establish the stability condition for the feedback connection of a deterministic dynamical system $Sigma$ and a stochastic memoryless map $Psi$. After that, we extend the result to the class of large scale systems in which: $Sigma$ consists of many sub-systems; and $Psi$ consists of many "stochastic actuators" and "probability controllers" that control the actuator's output events. We will demonstrate the proposed approach by showing the design procedures to globally stabilize the manufacturing systems while locally balance the stock levels in any production process.

We investigate learnability of possibilistic theories from entailments in light of Angluin's exact learning model. We consider cases in which only membership, only equivalence, and both kinds of queries can be posed by the learner. We then show that, for a large class of problems, polynomial time learnability results for classical logic can be transferred to the respective possibilistic extension. In particular, it follows from our results that the possibilistic extension of propositional Horn theories is exactly learnable in polynomial time. As polynomial time learnability in the exact model is transferable to the classical probably approximately correct model extended with membership queries, our work also establishes such results in this model.

Recently, the Edge Computing paradigm has gained significant popularity both in industry and academia. Researchers now increasingly target to improve performance and reduce energy consumption of such devices. Some recent efforts focus on using emerging RRAM technologies for improving energy efficiency, thanks to their no leakage property and high integration density. As the complexity and dynamism of applications supported by such devices escalate, it has become difficult to maintain ideal performance by static RRAM controllers. Machine Learning provides a promising solution for this, and hence, this work focuses on extending such controllers to allow dynamic parameter updates. In this work we propose an Adaptive RRAM Variability-Aware Controller, AVAC, which periodically updates Wait Buffer and batch sizes using on-the-fly learning models and gradient ascent. AVAC allows Edge devices to adapt to different applications and their stages, to improve computation performance and reduce energy consumption. Simulations demonstrate that the proposed model can provide up to 29% increase in performance and 19% decrease in energy, compared to static controllers, using traces of real-life healthcare applications on a Raspberry-Pi based Edge deployment.

In this paper, we present a novel MaxSAT-based technique to compute Maximum Probability Minimal Cut Sets (MPMCSs) in fault trees. We model the MPMCS problem as a Weighted Partial MaxSAT problem and solve it using a parallel SAT-solving architecture. The results obtained with our open source tool indicate that the approach is effective and efficient.

Legal marijuana might be putting dealers out of work, but it's definitely not harming the job market in general.…

We've come a long way since the olden days before legalization, when basically the only product on the market was the flower you got from a dealer.…

The CDC designed a flawed test for COVID-19, then took weeks to figure out a fix so state and local labs could use it. New York still doesn’t trust the test’s accuracy By Caroline Chen, Marshall Allen, Lexi Churchill and Isaac Arnsdorf Propublica…

The transformation of marijuana — aka pot, weed, reefer, ganja, dope, herb, bud, grass, Mary Jane — has been nothing short of dramatic.…

[IMAGE-1] The legal cannabis industry has only been around for a handful of years, but one local farm's green thumb goes back generations. Since the 1950s the Lima family has been in the business of growing — their namesake Lima Greenhouses dominate Vinegar Flats, where they still grow bedding plants and vegetables.…

The Cannabis Issue Like the best gas station treats that tempt even the most mature adults on a good road trip, gummies cater to that need to chew on something sweet while basking in the sunshine.…

The Cannabis Issue In a normal year, cannabis stores would be cashing in this April.…

A modeling framework for evaluating the impact of weather conditions on farming and harvest operations applies real-time, field-level weather data and forecasts of meteorological and climatological conditions together with user-provided and/or observed feedback of a present state of a harvest-related condition to agronomic models and to generate a plurality of harvest advisory outputs for precision agriculture. A harvest advisory model simulates and predicts the impacts of this weather information and user-provided and/or observed feedback in one or more physical, empirical, or artificial intelligence models of precision agriculture to analyze crops, plants, soils, and resulting agricultural commodities, and provides harvest advisory outputs to a diagnostic support tool for users to enhance farming and harvest decision-making, whether by providing pre-, post-, or in situ-harvest operations and crop analyzes.

In one embodiment, a system includes a data collection system configured to collect a data from a control system by using an offline mode of operations. The system further includes a configuration management system configured to manage a hardware configuration and a software configuration for the control system based on the data. The system additionally includes a rule engine configured to use the data as input and to output a health assessment by using a rule database, and a report generator configured to provide a health assessment for the control system.

Disclosed are polymeric compositions with improved breakdown strength. The polymeric compositions contain a polyolefin and a voltage stabilizing agent. The voltage stabilizing agent contains a triazine. The triazine may include a substituent that enables keto-enol tautomerism, which provides the voltage stabilizing agent with additional energy dissipation capacity. The present polymeric compositions exhibit improved breakdown strength when applied as an insulating layer for power cable.

Compounds of formula (I) ##STR1## in which R1 is hydrogen, O°, CN, NO, cyanomethyl, C1 -C12 -alkyl, C3 -C12 -alkenyl or C3 -C12 -alkynyl subject to the proviso that the carbon atom attached to the nitrogen atom is a primary carbon atom, C7 -C12 -aralkyl, C1 -C12 -acyl, 2,3-epoxypropyl, OH-monosubstituted C2 -C6 -alkyl or 2,3-dihydroxypropyl, R2 is hydrogen, C1 -C18 -alkyl, C5 -C18 -cycloalkyl, C6 -C18 -aryl or C7 -C18 -aryalkyl, R3 is C6 -C18 -aryl or a group of the formula (II) ##STR2## in which R1 is as defined above, n is an integer from 1 to 4 and R4 is an organic or inorganic radical of a valency equal to n are useful for stabilizing organic material against oxidative, thermal and/or light induced degradation.

Carbohydrate substituted dibenzo[d,g][1,3,2]dioxaphosphocin compounds of formula I ##STR1## where A is a carbohydrate residue are effective stabilizers for polymers processed at elevated temperatures and subject to thermal or oxidative degradation.

Carbohydrate substituted dibenzo[d,f][1,3,2]dioxaphosphepin compounds of formula I ##STR1## where A is a carbohydrate residue are effective stabilizers for polymers processed at elevated temperatures and subject to thermal or oxidative degradation.

A glass ceramic as cooktop for induction heating having improved colored display capability and heat shielding is provided. The cooktop includes a transparent, dyed glass ceramic plate having high-quartz mixed crystals as a predominant crystal phase. The glass ceramic contains none of the chemical refining agents arsenic oxide and/or antimony oxide and has a transmittance values greater than 0.4% at at least one wavelength in the blue spectrum between 380 and 500 nm, a transmittance >2% at 630 nm, a transmittance of less than 45% at 1600 nm, and a light transmittance of less than 2.5% in the visible spectrum.

The invention relates to a granulated powder intended, in particular, for the production of ceramic sintered parts, said powder having the following chemical weight composition, based on dry matter, namely: a zirconia stabiliser selected from the group containing Y2O3, Sc2O3, MgO, CaO, CeO2, and mixtures thereof, the weight content of stabiliser, based on the total zirconia and stabiliser content, being between 2% and 20% and the MgO+CaO content being less than 5% based on the total zirconia and stabiliser content; at least 1% of a first binder having a glass transition temperature less than or equal to 25° C.; 0-4% of an additional binder having a glass transition temperature greater than 25° C.; 5-50% alumina; 0-4% of a temporary additive different from the first binder and the additional binder, the total content of the first binder, the additional binder and the temporary additive being less than 9%; less than 2% impurities; and ZrO2 to make up 100%. According to the invention, the median diameter D50 of the powder is between 80 and 130 μm, the percentile D99.5 is less than 500 μm and the relative density of the granules is between 30% and 60%.

This invention relates to a method for increasing thermal stability of fuel, as well as in reducing nitrogen content and/or enhancing color quality of the fuel. According to the method, a fuel feedstock can be treated with a solid phosphoric acid catalyst under appropriate catalyst conditions, e.g., to increase the thermal stability of the fuel feedstock. Preferably, the fuel feedstock can be treated with the solid phosphoric acid catalyst at a ratio of catalyst mass within a contact zone to a mass flow rate of feedstock through the zone of at least about 18 minutes to increase the thermal stability of the fuel feedstock, along with reducing nitrogen content and/or enhancing color quality.