Sustainable Energy Society of South Africa.
SESSA is one of 50 National Sections of the International Solar Energy Society (ISES). ISES is regarded as the premier body in solar energy with members in over 100 countries. SESSA is the duly appointed African office of ISES.
In response to the energy challenges facing South Africa, Eskom has established an Integrated Demand Management (IDM) division. A key aspect of this demand side management programme is the promotion and implementation of more energy-efficient technologies, processes and behaviours amongst all consumers.
Eskom accredited solar Water Heating installers.
Suppliers of registered solar water heating systems must themselves be registered with Eskom and must be members of the Sustainable Energy Society of Southern Africa (SESSA).
Green Building Council South Africa.
TheGBCSA promote, encourage and facilitate green building in the South African property and construction industry through market-based solutions. The Green Building Council South Africa is a full member of the World Green Building Council and the official certification authority under the Green Star SA Rating System.


text:
QuizUp is a discontinued mobile game originally developed and published by Iceland-based Plain Vanilla Games and later operated by Glu Mobile. The game was a mobile trivia app similar to the game Trivial Pursuit. QuizUp was a multiplayer game where one user competes against another in seven rounds of timed multiple-choice questions of various topics. There were over 1,200 total topics available to users to choose from, and all the questions were voluntarily submitted by content contributors. Most topics were available in several different languages.

QuizUp was initially released for iOS in November 2013. Plain Vanilla Games released an Android version in March 2014.

As of May 2014, QuizUp had 20 million users and had raised over $26 million from venture capital investments. Over a billion matches had been played in over 197 countries by March 2014. The company claims that users play an average of 40 minutes each day. On 30 September 2015, Plain Vanilla Games announced that they had reached a deal with Universal Television, the production arm of NBC, for a 10-episode television game show based on the app. Five days later, on 5 October 2015, it was announced that British channel ITV had also acquired the rights to their own game show version. Production began on the game show and the first episode was to air on 5 March 2017. However, the television show was scuttled by NBC in August 2016.

In September 2016, as a result of NBC cancelling their show, QuizUps creator, Plain Vanilla, laid off all of their employees and announced a plan to sell the app before the end of 2016. QuizUp was acquired by mobile game developer Glu Mobile for $7.5 million USD, and the phrase "[QuizUp is] alive and kicking" was relayed to its community of players through the separate topic QuizUp: Feedback as well as through social media.

On 20 January 2021, QuizUp was removed from the App Store, and on 21 January 2021, it was announced on the QuizUp app that the game is being discontinued on 22 March 2021. On 24 March 2021, QuizUps servers were taken offline and the application and web service became inaccessible, after several hours of delay.

Gameplay
Users started a game by choosing a topic of interest from over 1000 available official categories in addition to custom topics created by users.

After the user picked a topic, they had the ability to either challenge a friend to a match or be paired against a random player. Users had the option of signing into the app through a social media platform such as Facebook, Twitter, or Google+ which allowed the user to see current friends who are using the app, invite friends to join them on the app, or challenge their friends to a game. Users also could choose to sign into QuizUp with an email address and not connect with a social media site. Players had the option of choosing to play with a friend or with a random stranger who may be in another country. When the user challenged someone, and the opposing user agreed to play, the match began. Each match consisted of six normal rounds and one bonus round that concluded the game. In each of the six normal rounds, the same question was given to each player with ten seconds to choose an answer out of the four responses provided. Users were awarded for the accuracy and speed of their answer, with a maximum of 20 points awarded per round. Point totals were doubled during the bonus round. Answering slowly or not giving an answer at all resulted in reduced points or no points respectively. The user earned one point fewer per second that they waited, with a minimum of 11 points if they answered correctly. Incorrect answers earned zero.

The maximum points possible to be scored in a single game was 160 [(6 rounds x 20 points)+(1 bonus round x 40 points)]; the player with the most points won the match.

References

External links

2013 video games
Android (operating system) games
IOS games
Multiplayer and single-player video games
Quiz video games
Video games developed in Iceland
Video games developed in the United States
Windows Phone games
Products and services discontinued in 2021
Glu Mobile games
Inactive online games
Delisted digital-only games

redpajama_set_name: RedPajamaWikipedia


Seamless Communication is the key to any business relationship!
What drives your organization? Your telecom systems must interact to insure effective employee communication and track effectiveness. Biz Telecom connects with your Payroll, CRM, EMR, Reporting Platform and exceeds your Call Recording requirements.
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Our team combines over 50 years of Government and Corporate Security experience. Is your telecom data secure? Unless your provider encrypts your traffic, you may have security related concerns.


Urolithiasis - globally pervasive disease that has changed dramatically over the last half century. Although there are slight differences in trends, it is clear that the burden of urolithiasis increases.
Kidney stone disease is common and often chronic condition with the lifetime risk of stone formation in the US exceeding 12% in men and 6% in women.
Extracorporeal shock wave lithotripsy (ESWL) and and percutaneous nephrolithotomy (PCNL) are the main treatment options to remove kidney stone. Unfortunately, after these surgical procedures men and women can experience severe complications.
Innovative Thermobalancing therapy and Dr Allen's device been working very well and safely for people with kidney stone disease during the last decade. This is the main reason to use this device as the first line treatment to dissolve kidney stones.
ESWL destructs kidney stones physically to small pieces, which are able to get out from the kidney with urine. The so-called shock waves make this breakage. These small pieces of stones can cause heavy bleeding and infection when passing out of the body.
Shock waves not only destroy stone, but can also damage kidney tissue, causing high blood pressure, and often can damage adjacent organs such as the pancreas, causing diabetes melitus in the future.
It should be noted, surgical interventions do not stop the stone formation and 50% of patients after them have new renal calculi in 5 years. Over the years, the percentage of stones recurrence is growing. So, people with reccurent stones and their medical consultants must decide what to do again.
Thermobalancing non-invasive therapy and device received a US patent, No. US 9,408,744 B2, as "Therapeutic device and method".
A 10-year observation shows that Dr Allen's device dissolves kidney stones, despite their size and type. None of the kidney stone patients who received Thermobalancing therapy as monotherapy had side effects.
It should be mentioned that Dr Allen's Device is a Class I medical device, which does not require the involvement of a Notified Body. Thus, everyone can use it at home without worrying, since this treatment option is free from side effects.
The Mayo Clinic has published the results of its investigation in 2006, Diabetes Mellitus and Hypertension Associated With Shock Wave Lithotripsy of Renal and Proximal Ureteral Stones at 19 Years of Followup, confirming that patients who underwent lithotripsy, developed high blood pressure and diabetes at almost four times the rate of those whose kidney stones were treated therapeutically.
Another recent article, Prevalence of diabetes mellitus after extra corporeal shock wave lithotripsy in 15 years follow-up, showed a lower incidence of diabetes after ESWL. So, this problem exists.
The cost effectiveness of this therapy is also a reason for using an innovative device for dissolving kidney stones. The price of ESWL is about US$10.000 and PCNL costs even more. Thus, with the price less than US$200, Dr Allen's device compares preferably to ESWLand PCNL.
Dr. Allen's device is not a traumatic tool for removing kidney stones, unlike ESWL and PCNL, so it's important for doctors to know more about this safe treatment option.


text:
Meet the People of Sequim
The Flower Basket Project People
Sequim's flower basket program, a partnership between Sequim High School and City of Sequim, results in 135 hanging flower baskets and 10 ground baskets adorning Washington Street each year from early June through mid-October.
Volunteer extraordinaire Emily Westcott coordinates the program, which she started 25 years ago with Derrell Sharp, agriculture teacher at Sequim High School at that time. The Sequim-Dungeness Valley Chamber of Commerce handles the bookkeeping, and the City of Sequim puts the flower baskets up and keeps them watered.
Westcott undertakes the task of approaching local businesses each year to secure sponsors. Sponsorship is $100 per basket. People can sponsor a basket on behalf of a business and/or split the cost with a friend. It usually takes around 170 sponsors, with some of them sharing.
"This program has always been well received. It even did well in 2020 when COVID affected so many businesses," said Westcott. "Normally we raise around $11,000. We were able to raise $15,000 this year---a record!"
"We give the high school roughly $7,000 as seed money to start the baskets. Some of the money is also used for flowers and Christmas decorations in downtown Sequim."
Students use the seed money to start the plants in January, then they put the baskets together in March. "When schools were closed because of COVID, the teachers had to come over and help finish the baskets," said Westcott. "Everyone worked together to get it done."
Bill McFarlen, Sequim High School agriculture science teacher and Future Farmers of America (FFA) Faculty Advisor for the past four years, explained that students also build the wooden baskets. The baskets have to be replaced after about 5 years, and the group usually constructs around 10 baskets a year to keep an adequate supply.
"Students have the baskets planted and ready for the city to pick up by late March, just before spring break," explained McFarlen. "We are excited that by March 2022, we expect the baskets will be stored in the newly constructed greenhouse on the northeast end of the school's campus. People are able to watch the progress of the construction project, as it is visible from Sequim Avenue."
"The flower basket program is a great partnership and has grown over the years from 25 to 140 baskets," continued McFarlen. "I think that reflects well on our town and one of the reasons I feel that Sequim is so great."
Westcott has another connection to Sequim High School, as she is a frequent substitute teacher. When she is subbing on campus, she will often swing by the greenhouse to work with the ag kids when they are working on the baskets. "I encourage them to put two colors in each basket because one color is boring," she said.
"I was raised in the big city, in Tacoma, and graduated from Woodrow Wilson High School with a class of 560 seniors," said Westcott. "What makes Sequim unique? I like that it is small. People are friendly."
"There's a real passion about being a part of Sequim," concluded Westcott. The weather is great. I was raised in the rain---it is nicer here."
Several businesses have never missed a year as sponsors over the past 25 years. This fall, the Chamber issued certificates and Westcott personally presented them to each sponsor to acknowledge their continued support. 25-year sponsors were Alan Millet, Attorney & Counselor at Law, Blake Tile and Stone, Blue Whole Gallery, Cole's Jewelers, The Co-op Farm and Garden, Fifth Avenue Senior Independent Living, First Federal, Hi-Way 101 Diner, Heidi Kanning DDS MS, Kirby's Barber Shop, Kitsap Bank, The Lodge at Sherwood Village, Mad Maggi Boutique & Salon, McDonald's, MM Fryer & Sons Insurance, Oak Table Café, Olympic Ambulance, Olympic Game Farm, Olympic Medical Center, Over the Fence Home & Garden Store, Rotary Club of Sequim Noon, Sequim Beauty Salon, Sequim Vision Clinic, Sofie's Florist, Sound Community Bank, Sound Publishing/Sequim Gazette/Peninsula Daily News, Subway Sequim, Team McAleer @ RE/MAX Prime, Thomas Building Center, Wilder Toyota, and Zbaraschuk Dental Care.
Dominique Hall
Debbi Soderstrom
Susan and Doug Fahlgren
Greg MacDonald
Donna and Jon Harrison
Judy Reandeau Stipe
Powell Jones
Emma Jane Garcia
Mikie Smith
David Volmut
Dave Herbelin

redpajama_set_name: RedPajamaCommonCrawl


text:
Article | Open | Published: 22 September 2016
Quantifying overlap between the Deepwater Horizon oil spill and predicted bluefin tuna spawning habitat in the Gulf of Mexico
Elliott L. Hazen1, 2
, Aaron B. Carlisle1, 3
, Steven G. Wilson3
, James E. Ganong3
, Michael R. Castleton3
, Robert J. Schallert3
, Michael J. W. Stokesbury4
, Steven J. Bograd1
& Barbara A. Block3
Scientific Reports volume 6, Article number: 33824 (2016) | Download Citation
Animal migration
Ecological modelling
A Corrigendum to this article was published on 10 November 2016
Atlantic bluefin tuna (Thunnus thynnus) are distributed throughout the North Atlantic and are both economically valuable and heavily exploited. The fishery is currently managed as two spawning populations, with the GOM population being severely depleted for over 20 years. In April-August of 2010, the Deepwater Horizon oil spill released approximately 4 million barrels of oil into the GOM, with severe ecosystem and economic impacts. Acute oil exposure results in mortality of bluefin eggs and larvae, while chronic effects on spawning adults are less well understood. Here we used 16 years of electronic tagging data for 66 bluefin tuna to identify spawning events, to quantify habitat preferences, and to predict habitat use and oil exposure within Gulf of Mexico spawning grounds. More than 13,600 km2 (5%) of predicted spawning habitat within the US EEZ was oiled during the week of peak oil dispersal, with potentially lethal effects on eggs and larvae. Although the oil spill overlapped with a relatively small portion of predicted spawning habitat, the cumulative impact from oil, ocean warming and bycatch mortality on GOM spawning grounds may result in significant effects for a population that shows little evidence of rebuilding.
The Atlantic bluefin tuna (Thunnus thynnus) is a large endothermic, highly migratory species that is broadly distributed throughout the Atlantic Ocean from the waters off Greenland and Norway in the north to Argentina in the south1,2,3. Atlantic bluefin tuna are one of the most highly valued fish in the world which has led to the heavy exploitation of all three bluefin tuna species (Atlantic bluefin, southern bluefin T. maccoyii, Pacific bluefin T. orientalis)4,5. Atlantic bluefin tuna (ABFT) migrate seasonally between productive temperate and subpolar foraging habitats to warm subtropical habitats where they feed and spawn3,6,7,8. Historically, fish from the western population were hypothesized to spawn in the Gulf of Mexico (GOM) and those from the eastern population to spawn largely in the Mediterranean3,9,10,11,12. A recent study has shown spawning in Atlantic slope waters but it remains unclear how much this spawning area contributes to the western Atlantic bluefin tuna stock13. Both Mediterranean and GOM spawning populations are now known to mix and feed in waters off the western north Atlantic, particularly along the eastern seaboard of North America, while recent tagging, otolith michrochemistry, and genetic studies have shown that large adult fish feeding in the Gulf of St. Lawrence are largely fish from the western population6,7,9,14. Following feeding in the waters off the east coast of North America, fish from the western Atlantic stock migrate south to the GOM from November to August with a peak in spawning during the spring and early summer6,12,15,16.
Both the GOM and Mediterranean Atlantic bluefin tuna populations have been greatly reduced due to overexploitation, however the GOM population is smaller and has been more heavily impacted by overfishing than the Mediterranean population17. The GOM spawning stock biomass is 20% of 1970 levels and the ensuing 20-year rebuilding plan has not stemmed declines, highlighting the long term effects of fishing pressure on this depleted population10,18. Although no bluefin tuna are targeted in the US portion of the GOM due to existing fishery restrictions, they are caught as bycatch on yellowfin longline fisheries, prompting seasonal closures in the past two years7,12,16.
Bluefin tuna in the GOM spawn primarily in March – June in waters warmer than 24 °C yet often avoiding the warmest loop current waters, likely minimizing physiological stress and optimizing survival of spawned larvae12,16,19. Predictions of future warming scenarios for the GOM indicate that physiology may limit available spawning habitat unless tuna spawning shifts to earlier in the year20. Given the importance of the GOM as a spawning location for the western population6,12,16,19, cumulative effects from anthropogenic activities that impact this critical habitat during the spawning season need to be assessed.
On April 20th 2010, the Deepwater Horizon (DWH) oil platform exploded in the northern GOM, releasing approximately 4 million barrels of crude oil into the ocean until the well was sealed in September 2010, resulting in one of the largest oil spills in history21,22. The shelf and slope waters of the northern GOM are a biodiverse area that serve as a spawning location for many pelagic fish species, including bluefin tuna, dolphinfish, marlin and swordfish12,16,23, in addition to supporting a variety of economically important commercial and recreational fisheries. Impacts of oil on the biology of higher trophic levels are particularly difficult to assess, as observed mortality is typically a significant underestimate, less than 10% of actual mortality24. Exposure of fish eggs and larvae to crude oil and weathered oil byproducts has a variety of deleterious, sublethal effects, including reduced growth rates, genotoxicity, impaired cardiac function, morphological malformations and premature hatching25,26,27,28,29. Less is known about impacts on juvenile or adult tunas. Given the depleted status of the GOM population of bluefin tuna18, their use of the GOM as a spawning area16, and the vulnerability of eggs and larvae to Polycyclic aromatic hydrocarbon contaminants26,27, the oil spill may have had significant effects on the health of the GOM population of bluefin tuna. Therefore, continued monitoring of adult tuna in addition to the 2010 year class is needed to understand population level effects.
Understanding the risks incurred by marine species in relation to anthropogenic stressors requires information on the habitat use and movements of marine animals as well as the spatial and temporal patterns of their stressors30,31. Published data on spawning events and larval distribution show a peak in May suggesting that multiple bluefin tuna life stages (eggs, larvae and adults) were likely exposed to oiled waters in the GOM12,16. In fact, two electronically tagged adult bluefin tuna exhibited putative spawning behaviors in the vicinity of the oil spill, spending several weeks in the waters around the Macondo well7. Using nekton surveys, Muhling et al.11 estimated that between 5–12% of larval bluefin tuna in the US EEZ were exposed to contaminated waters each week during the oil spill, although the bulk of spawning habitat and larvae were outside the area affected. Predicted adult bluefin habitat use in the GOM can be used to determine their potential exposure to contaminated waters, while the location and timing of spawning will determine the extent that eggs and larvae may be exposed to oil products. Hence, a more complete understanding of the potential impact that the oil spill had on bluefin tuna adults and larvae requires knowledge of how these fish use the GOM and where they spawn.
Here we use an extensive satellite and archival tag dataset from mature Atlantic bluefin tuna7 on GOM spawning grounds to model adult presence and spawning habitat within a generalized additive mixed modeling (GAMM) framework. In addition, we parameterized a Bayesian model to identify potential spawning events. Remotely-sensed oceanographic data were used to generate a spatially and temporally explicit estimate of where bluefin tuna were and where spawning occurred in the GOM during the DWH oil spill. We then combined habitat and spawning predictions with the spatial extent of the oil spill to quantify the overlap between bluefin tuna spawning habitat and oiled waters. Our approach provides both a time-varying and cumulative estimate of the impact of the DWH oil spill on adults and potentially multiple life history stages of bluefin tuna.
A total of 125 bluefin tuna were satellite tagged in the southern Gulf of Saint Lawrence (GSL in the waters off Cape Breton Island, Nova Scotia) in September through October from 2007 to 2014. Tags were programmed to release during their late summer return to the GSL foraging ground in order to recover the tag after fully sampling the Gulf of Mexico. Post-release tags transmitted location via Argos satellites, and when possible tag recovery was attempted from a shore-based recovery team7. In addition, we also examined historical data from surgically implanted or externally attached archival tags deployed in the Gulf of Mexico and off Cape Hatteras and Morehead City, North Carolina from 1999–2005 (n = 24)12. All bluefin tuna were caught on rod and reel and tagged using two generations (MK10 and miniPATs) of Wildlife Computers pop-up satellite archival tags (PAT) over the course of the study. Light levels recorded by the tags were processed to generate daily estimates of latitude and longitude which were then matched sea surface temperature (SST) data from tag and remotely sensed data following Teo et al.32. Position estimates were refined using a probabilistic state space model (SSM) that incorporated maximum dive depth and bottom bathymetry and enabled quantification of the uncertainty associated with each daily position6,33,34. The model was validated with endpoint data from tagged Atlantic bluefin tuna (n = 72). For detailed information on tag preparation, programming, attachment, construction, and geolocation analyses see Block et al. and Wilson et al.6,7. All experimental protocols were carried out in accordance with relevant guidelines and regulations, and were approved by the Administrative Panel on Laboratory Animal Care of Stanford University and the Acadia University Animal Care Committee.
From the electronic tagging dataset, we examined 66 Atlantic bluefin tuna with tags recovered and that entered the GOM (which occurred between November and June) to examine residency and habitat preference (Supplemental Table 1). Bluefin were considered to have entered the GOM once they passed the 80.5° W meridian and remained within the GOM for six days. The resulting GOM bluefin tuna dataset encompassed 5272 tracking days with individual track lengths ranging from 7 to 193 days within the Gulf (for tag deployment details see ref. 7). Two of these tagged tuna (ID 5109026 and 5109029) were present in the GOM during April-August of 2010, overlapping temporally and spatially with the Deepwater Horizon oil spill. The tag data set contained extensive archival data enabling a thorough examination of bluefin tuna behavior in the GOM. We also use model integrated surface oil data from the Environmental Response Management Application (ERMA) as part of the National Resource Damage Assessment (NRDA) to estimate the total surface area of the GOM that was oiled, and to calculate a time series of adult Atlantic bluefin tuna habitat and spawning habitat oiled35,36. These modeled products rely on remotely sensed data for surface waters thus the effects of subsurface oil remain outside the scope of this study.
As tracking data give presence of tuna but no direct measure of absence, correlated random walks (CRWs) were used to represent a null model where tuna could move in the environment independent of oceanographic variables. For each of the 66 bluefin tuna tracks, 100 CRWs were created for use as pseudo-absences in our model framework (Supplemental Figure 1). CRWs are simulated tracks that consist of a succession of random steps, with each position generated using tag-derived turning angle and distance distributions from a specific tuna track37,38. The starting point for each CRW was the tagging location (if tagged in the GOM) or point of entry to the gulf, the initial angle of travel of the CRW matched the initial angle of the corresponding tag, each CRW position was given the same error distribution as the actual track, and each CRW has the same duration as the original tag. CRWs are not true absences because un-tagged tuna movement patterns are unknown and their distribution could potentially overlap with a null track. For each track, a random CRW was chosen from the population of CRWs to create a presence/absence dataset to fit and predict habitat likelihood, with this process repeated 60 times38,39. We also examined spatial and temporal scales of bluefin tuna movement within the GOM using residence time and first-passage time analyses in the R package adehabitat (v. 1.8.18).
Spawning dates were determined based on the diving behavior and internal temperature of archival tagged tuna (see Supplemental methods for additional information and ref. 16). Diving behavior in the GOM was characterized by deep diving as the fish entered and exited the GOM (crossing 80.5° W), and periods of shallow oscillatory diving during the night when internal temperatures increased. Telemetry-derived rapid oscillatory diving behaviors have been used to identify putative spawning, such as for skipjack tuna in the eastern Pacific40, bluefin tuna in the GOM16,41, and bluefin tuna in the Balearic sea42. While we lack direct observations of spawning from telemetry records, these oscillatory dives are uniquely found on spawning grounds and occur spatially and temporally in areas of high larval abundance12,16. Each fish with diving behavior was examined for oscillatory night diving (ref. 16) using both expert opinion of two scientists and a Bayesian model (fully described in the Supplemental methods). Putative spawning dates were combined with transiting dates to create a binary response variable with negative binomial link in the spawning likelihood generalized additive mixed model.
Modeled spawning behavior could only be calculated for the electronic tags with continuous time series records including archival tags and recovered PAT tags. Switching state-space models have been used to identify putative foraging events via distance and turn and angles34, and here we use both horizontal and vertical movement data with additional proxies to identify presumed spawning events. Dates and locations from state space modeled output were classified as "spawning" or "non-spawning." We identified ten "proxy" functions to separate days hypothesized as spawning behavior from non-spawning days (see supplement). This method of combining proxies is tolerant of false detections, and allows for overlapping probability distributions. Note that this method does not require that a proxy be high or low to indicate spawning, rather it requires that the proxy values are concentrated at some point along the proxy axis during spawning. Spawning and non-spawning dates that were identified in the archival tag validation data set were also compared to visually identified spawning from a pair of human experts. These two approaches showed 87% agreement suggesting that by combining both methods we are able to robustly identify changes in behavior that typify spawning.
Remotely sensed environmental data were obtained for both actual and CRW tracks using Xtractomatic (http://coastwatch.pfel.noaa.gov/xtractomatic). The data sets included time-series of sea surface temperature (SST) and SST variability (standard deviation, SSTsd – 8 day) merged from Pathfinder and AVHRR, surface chlorophyll-a concentration (chl a – 8 day) merged from SeaWiFS and MODIS, sea surface height anomaly (SSHa – 1 day) from Aviso, SSHa variability (standard deviation, SSHsd) from Aviso, eddy kinetic energy (EKE – 1 day) derived from Aviso, vertical Ekman pumping (wekman – 8 day) derived from merged Quikscat and Ascat data, north winds (uy10 – 8 day) merged from Quikscat and Ascat data, moon phase (moon – 1 day) from NOAA, bathymetry (bathy) and rugosity (standard deviation, bathysd) both from eTOPO2. For each oceanographic variable, the geolocation error radius from each daily SSM and CRW position was used to calculate a mean value. Transformations of the environmental variables were explored to ensure data were normally distributed. A logarithmic transformation was required for Chl-a and EKE.
In order to quantify habitat use in the GOM, a binary presence/absence generalized additive mixed model (GAMM) was fit as a function of oceanographic variables incorporating a negative binomial link function. We use state space model derived geolocation error at each position to determine the radius of sampled predictor variables, which provides a probabilistic estimate of experienced environmental covariates. In addition, we assess error introduced by pseudo-track choice via AUC scores of multiple CRW combinations, and we assess model diagnostics for habitat and spawning using k-fold cross-validation with test-training datasets. Spawning likelihood models were fit using a binary spawning/non-spawning GAMM for each daily position along the track against similar oceanographic variables, and also used a negative binomial link function. GAMMs are semi-parametric models that use smoothing splines to identify the relationship between dependent variable and predictor43. GAMMs allow for non-linearity, non-constant variance, and non-monotonicity in contrast to more conservative linear models. The mixed model can incorporate random effects, and in our case used tag ID as a random variable to account for correlations among observations. The advantage of pairing track points with CRW points in a GAMM framework is that both absence and presence are sampled at the same spatiotemporal scales minimizing the residual autocorrelation. Various combinations of environmental data sets were included in the GAMMs based on a priori designation to determine the best model. The models' explanatory and predictive power were compared using Akaike Information Criterion (AIC) and area under the curve (AUC) statistics44,45. The GAMMs were run in R (version 3.12) using the MGCV package (version 1.7–6) with cross-validation using the ROCR package (version 1.07). The GAMM model with highest AUC values and subsequently lowest AIC value was run 60 times with randomly chosen pseudo-absence tracks for each tag to quantify error derived from CRW selection. We ran model diagnostics using k-fold cross-validation in two configurations. Models were fit with randomly selected 75 training/25% test data, and subsequently each year was removed when fitting the model as test data to examine interannual predictive ability. The cross-validation process was repeated for the spawning model and a single best-fit spawning model was chosen for prediction purposes.
Environmental relationships from the best-fit GAMMs were used to predict (1) adult ABFT habitat and (2) spawning likelihood within that habitat, both as a function of ocean variables from April 1st to August 26th, 2010 in weekly increments. Response surfaces for the time of the oil spill were aggregated by week at 0.25° x 0.25° spatial resolution. Binary cut-offs were determined using the ROCR package (version 1.0-7) in order to minimize the false positive rates and provide conservative estimates of both habitat and spawning likelihood. Modeled habitat likelihood and spawning likelihood were multiplied together to get estimates of total spawning habitat during the duration of the oil spill. Oil products were also interpolated to the nearest date to provide comparable oil extent in the Gulf of Mexico. The amount of spawning habitat in the GOM was summarized for the US EEZ for comparison with previous studies, as well as for the entire Gulf of Mexico in relation to overlap with oil layers. We calculated the percentage of habitat within the oil spill that was predicted bluefin spawning habitat in addition to the total percentage of spawning habitat that was oiled. These two metrics provide complementary statistics on the overlap between oil and tuna and secondarily quantify potential impact on spawning adult tuna in the GOM.
Tag data from 1997–2014 indicate that the peak occupancy in the GOM for bluefin tuna (40% of tagged fish) occurs from March 15th to May 31st (Fig. 1A,B) which agrees with previous analyses of Atlantic bluefin tuna electronic tag data, larval data, and bycatch data7,11,12,46. Proposed spawning behavior was identified between April 1st and June 28th with a peak (>20% of tags with spawning) between April 15th and May 20th (Fig. 1B). Bluefin tuna occupied the entire GOM, while spawning was generally more restricted to the northern GOM slope waters (>23° N latitude). Residence time and first-passage time analyses for the entire GOM dataset indicated that the average scale of movement was 100 km every 4.3–10.1 days (Fig. 1C). Given that tuna could easily move out of a 100 km × 100 km grid cell within a week (Fig. 1C), each week was considered new habitat.
Figure 1: Atlantic bluefin tuna residence and spawning behavior in the Gulf of Mexico from tag data (1997–2014).
(A) State-space modeled presence is shown in blue with tag-derived spawning events shown in red. (B) Temporal occupation of the gulf is shown in blue measured by percentage of tagged fish with peak percentage of fish spawning shown in red. The period of the Macondo well oil spill in 2010 is shown in grey. (C) Residence time and first passage time illustrate spatio-temporal scales of movement patterns of tagged bluefin tuna within the gulf. Figures were made in R v. 3.2.0: A Language and Environment for Statistical Computing, R Core Team, R Foundation for Statistical Computing, Vienna, Austria (2016) https://www.R-project.org.
Models of bluefin habitat (presence vs. simulated absence) resulted in a subset of 6 environmental variables selected in the most parsimonious model (Table 1, Supplemental Table 2, Supplemental Fig. 2). The summary statistics showed that these variables remained significant across all 60 runs of the models (100%), except for SSHa and SSHsd, which were significant in 78% and 93% of the CRW iterations respectively (Table 1). The spawning model selected included 9 out of 11 terms from the full model (Supplemental Table 2). The final habitat and spawning models both had higher AUC values than the reduced model (SST, SSHa, EKE), so the best-fit models were chosen for predictive purposes to maximize our accuracy (Table 1, Supplemental Table 2, Supplemental Figures 3–5). Cross validation for 75% training/25% test with 5 folds resulted in mean AUC values of 0.789 and 0.905 for the presence/absence and spawning model respectively. Cross validation by year (13 folds) resulted in mean AUC values of 0.758 for the presence/absence, and 0.901 for the spawning model.
Table 1: Generalized additive mixed model output for the selected best model (presence/absence), reduced model (presence/absence), and the selected best spawning model.
Full size table
The models demonstrated that Atlantic bluefin tuna in the GOM had strong associations with SSTs between 15 and 25 °C, higher EKE values (>0.001 log m2·s−2), and slightly positive SSHa values (between −0.16 and 0.2 cm). Tuna also avoided shallower shelf waters with a preference for the shelf break, slope and deeper waters (Fig. 2, Supplemental Figs 2,4 and 5). Spawning habitat preferences had similar environmental drivers to total habitat with some notable exceptions. Bluefin tuna were more likely to exhibit spawning behavior at high temperatures (>22 °C), and low SSHa values (<−0.05 cm), and spawning behavior was more likely during full moons. Adult tuna avoided the loop current (higher EKE values, Fig. 2G) and warmer waters as the season progressed (higher SST values) and predicted spawning habitat also excluded the loop current (Figs 2F and 3). The combined habitat predictions showed preferred bluefin tuna habitat was most persistent in the western and northern GOM throughout the duration of the oil spill. However, the overall availability of preferred habitat decreased particularly after June 1st of 2010 (Fig. 3).
Generalized additive mixed model response curves for (A) presence-absence and (B) spawning likelihood. Positive values on the y-axis indicate increased likelihood of presence or spawning. The four most significant explanatory variables, sea surface temperature, eddy kinetic energy, sea surface height, and bathymetry are shown here, with complete GAMM splines shown in Supplemental Figs 3 and 4. Figures were made in R v. 3.2.0: A Language and Environment for Statistical Computing, R Core Team, R Foundation for Statistical Computing, Vienna, Austria (2016) https://www.R-project.org.
(A–D) Spawning habitat predictions and oil spill extent over the duration of the oil spill. Likelihood of habitat ranges from low (white and pink) to high (yellow and green). Timeseries of (E) the habitat contained within the oil spill (percentage of oil spill area) represents how much of the oiled extent was considered tuna habitat, while (F) the amount of tuna habitat oiled (percentage of total habitat) represents the how much of predicted Gulf of Mexico spawning habitat was covered in oil. Figures were made in R v. 3.2.0: A Language and Environment for Statistical Computing, R Core Team, R Foundation for Statistical Computing, Vienna, Austria (2016) https://www.R-project.org.
Estimates of oiled spawning habitat were predicted beginning on April 21st, and oil was largely absent from surface waters by July 28th. Importantly, the timing of the oil spill directly overlapped with the maximum extent of adult bluefin tuna foraging and spawning habitat in the gulf (Fig. 3). Weekly oiled habitat ranged from 0 to 2.6% (mean 1%) of total bluefin habitat in the Gulf (Fig. 3F), and 0 to 5.5% (mean 1.8%) of habitat in the US EEZ, at the peak on June 6th, 2010. This corresponds to 13,600 km2 habitat oiled out of 518,505 km2 total habitat available on that date. At the same time, >70% of the extent of the oil spill was identified as preferred bluefin tuna habitat through May 12th with that amount dropping to near 0% in early June (Fig. 3E). However, there was a secondary peak between July 1st and July 21st when tuna habitat and the oil spill overlapped again (20% of oil extent was habitat and <1% of total bluefin preferred spawning habitat was oiled). Summing the area of the predicted habitat and the oil spill overlap by week, the cumulative oiled tuna habitat was 86,305 km2 out of 8,086,130 0 km2 total habitat representing the potential for a significant impact on adult and potentially larval bluefin tuna in the GOM.
Atlantic bluefin tuna are the focus of international fisheries management and significant effort has been invested in trying to rebuild the GOM and Mediterranean populations in part due to their high economic value. Rebuilding plans have not yet resulted in recovery of the GOM population, and seasonal closures have recently been established to protect this population on the GOM spawning grounds7. The discrete GOM bluefin tuna population is largely fished in the Gulf of St. Lawrence, with fisheries landings over 500t per year recently17,18,47,48. Although bluefin tuna are not directly harvested by the US in the GOM, their reliance on the GOM for spawning has resulted in a significant level of bluefin tuna bycatch in yellowfin tuna longline fisheries6,46. The impacts of the DWH oil spill on this vulnerable and rebuilding population remain unknown.
The Deepwater Horizon was the largest oil spill in US history, in an area of huge economic and ecological importance49,50,51, yet the effects of this event on the ecology of the GOM remain unclear, especially for commercially important pelagic species such as the Atlantic bluefin tuna. Numerous pelagic species spawn in the GOM in the spring and summer months including Atlantic bluefin, yellowfin, and blackfin tunas, blue marlin, swordfish and mackerels, and consequently numerous economically important fisheries operate within the GOM12,16,23. We demonstrate that there was significant overlap between bluefin tuna spawning habitat (eggs, larvae and adults) and oiled surface waters in the Gulf of Mexico, up to 2.6% of their total Gulf habitat or 5.5% of their habitat within the US EEZ. Our estimates are slightly lower than those from larval surveys (5–11%), but previous calculations used preliminary oil surface layers and focused only on the northern GOM11. The ultimate effects of having between 2.6% of their total GOM spawning habitat to 11% of their larval habitat within the US EEZ11 exposed to oil are unclear, but they may have potentially important effects on the 2010 year-class of Atlantic bluefin tuna. Monitoring 2010 and future cohorts would allow assessment of whether DWH had an acute effect on bluefin tuna, although chronic impacts may take much longer to manifest52.
There are well documented impacts in larval tuna exposed to oil via the blocking of critical cardiac pathways26,53,54, yet the effects on juveniles and adults remain less clear. Experimental effects of oil on chub mackerel indicated that four days of cumulative exposure significantly impaired their metabolic rates55. Adult bluefin are capable of moving at a scale of ~100 km per week thus it is likely they could move to avoid direct exposure to oil for prolonged periods. Nonetheless, it is possible that even minimal exposure for fish with high gill surface areas when combined with the energetic costs of spawning and high temperatures in the GOM may have a synergistic deleterious effect on adult survival (e.g. ref. 56) or long-term reproductive output57. Similar effects have been observed in Prince William sound where chronic exposure inhibited reproduction and increased mortality rates for fish years after the initial spill52. Bluefin tuna are not obligate spawners and can skip years, although spawning can occur for multiple days and multiple bouts within a season58. Even though there is high variability in output and natural mortality of bluefin tuna larvae59, increased larval mortality due to oil exposure may further reduce the resilience of this population to continued high fishing pressure.
By examining total habitat use by Atlantic bluefin tuna and putative spawning behavior, we were able to predict spawning habitat for adults and presumably the resulting distribution of eggs and larvae7,16. Spawning events were more constrained than adult habitat, with moon phase playing an important role in these models. We found that spawning likelihood was greater in low SSHa waters, and warmer waters similar to previous findings from adult and larval data in the GOM6,12,19,41. In addition, the timing and spatial extent of spawning here matches the phenology and distribution of larval bluefin tuna in the GOM19, providing strong support for our use of night-time, shallow, rapid oscillatory dives as a proxy for spawning. Because tuna entered the GOM as early as November and spawning was largely in the late spring and early summer when water temperatures were warmer, the model predicts spawning at warmer temperatures compared to habitat use models (Fig. 2E,G). Tuna spawning is predicated on presence in the GOM, thus the results of the spawning model must be interpreted in concert with the results of the presence/absence model. In other words, tuna cannot spawn in a location that an adult does not occur. The preference for temperatures cooler than 25 °C in the habitat model suggests that tuna occupy cooler habitat within the GOM, but spawn preferentially later in the season and in lower SSHa waters. Similar to the findings here, bycatch data show increased catch rates at lower SSHa values and cooler temperatures, suggesting preferential use of mesoscale eddies46. Given tuna spawn late in the season before leaving the GOM, spawning likely occurs at an optimal temperature for the larvae, yet close to the physiological thermal limit of bluefin (Figs 1B and 2, refs 12,16 and 46) increasing their potential sensitivity to additional stressors such as oil and bycatch. Larval distribution models fit to climate projections estimated that spawning habitat in late spring would contract due to warming while early spring spawning may become more common, which substantiates these potential physiological limits of adult bluefin20.
The combination of increased capabilities of electronic tags60,61,62 with advances in statistical techniques has expanded the use of habitat models in marine conservation and management63,64. However, the dichotomy between analysis techniques for tag-based movement data and fisheries stock assessments still make combining these approaches difficult65,66. Recently, tag data have been combined with Bayesian movement models to analyze and incorporate mixing among discrete populations for use in improving international quota allocation66. Tag data have been integral in ecosystem based management approaches such as overlap with anthropogenic risks31, designation and assessment of protected areas67, predicted response to climate change68, and assessing bycatch risk in marine fisheries69. Moving beyond static and seasonal closures, tag data have been critical in identifying dynamic management areas such as for turtles in the central Pacific70,71 and bluefin tuna in Australia72. Seasonal closed areas for longlines targeting GOM yellowfin tuna have been implemented in 2014–2017 for April and May to minimize bluefin tuna bycatch7,73. Importantly, the tuna habitat model presented here could be used in either a near-real time predictive mode using satellite data or in forecast mode with forward-looking projections from ocean models to offer dynamic closures that would track key ocean features, potentially minimizing bycatch in longline fisheries72,74,75,76. Combining adult Atlantic bluefin tag data with fisheries observer bycatch data and larval sampling data would provide a holistic picture of bluefin tuna habitat use in the GOM to improve dynamic approaches to conserve this rebuilding population.
How to cite this article: Hazen, E. L. et al. Quantifying overlap between the Deepwater Horizon oil spill and predicted bluefin tuna spawning habitat in the Gulf of Mexico. Sci. Rep. 6, 33824; doi: 10.1038/srep33824 (2016).
A correction has been published and is appended to both the HTML and PDF versions of this paper. The error has been fixed in the paper.
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We thank the Captains and crews of the many fishing vessels involved in tagging Atlantic bluefin tuna particularly in Canada and North Carolina. Numerous members of the Tuna Research and Conservation Center and TAG A Giant helped in the lab and field through the years including Danny Coffey, Ethan Estess, Jake Nogueira, Charles Farwell, Randy Kochevar, Shana Miller, Andre Boustany Steve Teo, Gaelin Rosenwaks, Sal Jorgensen, and George Shillinger. We thank Alan Swithenbank for contributions in the lab for data management and analyses. In Canada we graciously thank the satellite tag recovery team, particular Jeff Beardsall and Aaron Spares, from Dalhousie and Acadia Universities for assisting in recovery of tags. We thank Captain Dennis Cameron and his crew of the Bay Queen IV, for always being able to assist. The Canadian fishers of Port Hood and Prince Edward Island Canada are particularly invested in the effort that led to the data set, and we thank everyone who helped. We are indebted to Troy Baker of the National Oceanic and Atmospheric Administration (NOAA) for his advice and financial support as part of the Natural Resource Damage Assessment (NRDA) efforts. We also thank Drs. Heidi Dewar and Toby Garfield for their critical reviews. Last but not least, we are indebted to Dave Foley for his vision of integrating satellite products into fisheries research and management, without whom this project would not have been conceived or completed. Scientific fishing licenses were issued by the Department of Fisheries and Oceans Canada and NOAA tagging permits in North Carolina waters. All experimental protocols were approved by the Administrative Panel on Laboratory Animal Care of Stanford University and the Acadia Animal Care Committee. This work was supported by grants from the National Oceanic and Atmospheric Administration including Natural Resource Damage Assessment and the Integrated Ecosystem Assessment program funds. We deeply thank Stanford University, TAG A Giant, and the Monterey Bay Aquarium for funding contributions to the North Carolina and Canadian tagging efforts. Dr. Stokebury is supported by the Canada Research Chair in Ecology of Coastal Environments.
Environmental Research Division, NOAA SWFSC, Monterey, California 93940, USA
Elliott L. Hazen
, Aaron B. Carlisle
& Steven J. Bograd
Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, California 95064, USA
Hopkins Marine Station, Stanford University, Pacific Grove, California 93950, USA
Aaron B. Carlisle
, Steven G. Wilson
, James E. Ganong
, Michael R. Castleton
, Robert J. Schallert
& Barbara A. Block
Department of Biology, Acadia University, Wolfville, Nova Scotia, B4P 2R6 Canada
Michael J. W. Stokesbury
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E.L.H., S.J.B. and B.A.B. conceived this manuscript; S.G.W., R.J.S., M.J.W.S. and B.A.B. collected the tag data; E.L.H., A.B.C., S.J.B. and M.R.C. processed and analyzed the remotely sensed and oil data; S.G.W., B.A.B., J.E.G. and M.R.C. modeled the tracking data for location and error and B.A.B., S.G.W. and J.E.G. developed Bayesian models for identification of spawning behavior; E.L.H. and A.B.C. fit habitat models; E.L.H. and A.B.C. drafted the manuscript; E.L.H., A.B.C., S.G.W., S.J.B. and B.A.B. edited the manuscript.
The authors declare no competing financial interests.
Correspondence to Elliott L. Hazen.
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Population connectivity of pelagic megafauna in the Cuba-Mexico-United States triangle
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, Michael A. Dance
, R. J. David Wells
, Matthew J. Ajemian
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This castle is a palatial complex located in Hillerod, Denmark. It is famous as the largest Renaissance residence in Scandinavia.
Carlsberg museum
Learn the history of Carlsberg beer and taste it at its place of origin.
Rosenborg Castle was built in 1606-34 by Christian IV and holds the Danish Crown Jewels and Royal Regalia.
Odense H.C. Andersen Museum
H.C. Andersens Odense is a set of museums dedicated to the famous author Hans Christian Andersen in Odense, Denmark, some of which, at various times in history, have functioned as the main Odense-based museum on the author.
Kronborg castle
Kronborg is a magnificent renaissance castle. Visit the home of Hamlet and a designated UNESCO World Heritage Site.
Tivoli gardens
Tivoli Gardens is an amusement park in central Copenhagen offers rides, games, musicals, ballet, and major concerts.
Amalienborg Palace is home to the royal family. Every day at 12 PM, you can watch the changing of the guards.
LEGOLAND is a lively, vibrant and inspirational destination for a perfect day out.
This statue was a present to the City of Copenhagen from Danish brewer Carl Jacobsen. The sculpture is made of bronze and granite and was influenced by the fairy tale of Hans Christian Andersen.
Louisiana Museum of Modern Art
The most visited modern art museum in Denmark, combining art, nature and architecture in a total experience.


Obesity comes with a whole slew of other health risks, including type 2 diabetes and kidney disease. Kidney disease is a well-known comorbidity of type 2 diabetes, but this is especially true in patients who are excessively overweight and who do not exercise regularly.
Chronic kidney disease can cause a mineral imbalance in patients, affecting their bone density and bone health. This can eventually lead to weakening of the bones to the point of osteoporosis or the development of other bone-related conditions. Early signs of kidney disease in diabetic patients include the presence of high levels of proteins in the patient's urine. At this point, the kidneys may also fail to be able to properly filter waste from the bloodstream.
A new study may have found a way to decrease the risk of kidney disease caused by diabetes in obese patients. The researchers behind the study examined two groups of rats to test the effects of exercise on the condition. The first group were the experimental group or the exercise group and were submitted to exercise sessions between 45 and 60 minutes each day for five days out of the week. The control group of the "sedentary" group was only exercised for 15-minute intervals twice a week.
Both groups of mice included lean and obese subjects, so the effects of exercise versus sedentariness could be examined in each. In both groups, the obese mice showed hardening of the arteries or scarring of the arteries, increased levels of protein in their urine, and fat deposits remaining inside the kidneys' filtration system.
After being subjected to the exercise plan, the obese mice in the exercise group showed a decrease in all of these symptoms of kidney disease, compared to the obese mice in the control group.
The researchers noted that the obese mice's risk of developing osteoporosis remained the same, no matter which group they were included in, however. The most significant finding of the study was the improvement to the health of the blood vessels and better overall kidney health in the obese mice in the experimental group.
In conclusion, the researchers wrote, "the introduction of an exercise program based in AIT (aerobic interval training) is a good strategy to prevent alterations in kidney structure and urinary parameters caused by obesity and the development of diabetic nephropathy (kidney disease) in obese Zucker rats.".


text:
Via Twelve Books
A Call to Action for the Large, Cacophonous Mess That is the Democratic Party
The Co-Host of Pod Save America Lays Out a Plan for the
Future of Democracy
By Dan Pfeiffer
The Democratic Party is a broad, diverse coalition that agrees on little more than Trump's general terribleness. Their individual interests often conflict. In 2018, for example, Nancy Pelosi and the DCCC were focused on defeating Republican incumbents in blue and purple districts that Trump lost. This strategy depended on drawing sharp contrasts with the Republicans. Chuck Schumer and the DSCC were defending Democratic incumbents in red states that Trump won, which sometimes called for blurring distinctions with Trump. The left hand and the other left hand were sometimes moving in opposite directions.
To make matters worse, the post-Citizens United campaign finance laws dramatically reduced the influence of the traditional party organizations. Under current law, an individual can give a maximum of $35,500 a year to the DNC. This is far from a paltry sum, but it pales in comparison to the unlimited amounts super PACs and political nonprofits can raise from individuals and corporations. The outside groups have exponentially more resources than the inside groups with little of the accountability to the public or traditional political stakeholders.
The Democratic Party has never been particularly hierarchical or orderly—especially when we are out of power. No one has the power to convene all the players, and everyone has the power to veto any sort of collective action. The whole process tends to work (a little?) better when there is a Democrat in the White House. When Obama was president, his team helped convene a weekly meeting among all the progressive stakeholders under the banner of something called the Common Purpose Project. It was an opportunity for the White House to brief the groups on our agenda and strategy and plot out plans to enact and defend our shared agenda. It didn't always work. We didn't always agree, but getting around a table together was ultimately invaluable. The passage of the Affordable Care Act and the defeat of GOP budget cuts to education, food stamps, and Medicare wouldn't have happened without it. That level of coordination is much harder when Democrats aren't in the White House, which is a cruel twist of fate because it's when we need it the most.
In other words, the whole thing is a large, cacophonous mess.
Before you put this book down, pack your bags, and move to Denmark, keep in mind that the Republican Party was an epic shit show when Obama was in office and very well may still be. Nothing like winning to hide all the warts. The primary function of the Republican National Committee is to employ Trump's flunkies, pay the legal bills of other Trump flunkies, and hold fundraising events at Trump properties, thereby funneling money from Republican campaigns into the pockets of Trump and his dilettante children. The Republican chair is Ronna Romney McDaniel—Mitt's niece and someone with so little dignity that when President Trump told her to stop going by Romney because of his distaste for Mitt, she agreed.
But . . . before you relax and soothe your nerves with Trump's idiocy and endless grift, the Republicans are better organized and much better funded. They have an easier task come election time—they simply need to turn out a group of mostly homogenous very reliable voters. The Democrats have to turn out a larger, more diverse group of people who vote less reliably. We have to overcome voter suppression laws, while getting massively outspent by the other side.
Defeating Trumpism requires reimagining and reforming the Democratic Party. Here is a nonexhaustive list of ideas to do so offered with the humility of someone who would have bet their life on Hillary Clinton being president right now and Donald Trump being the sixth member of The Five on Fox News.
Become the Defenders of Democracy
Fixing democracy needs to become the primary purpose of the Democratic Party. I know this sounds cheesy, but nothing else happens if we don't pursue aggressive steps to fix our democracy. There will be no Medicare for All, no Medicare for some, no Green New Deal, no $15 minimum wage, and no new gun safety laws.
The party platform needs to lead with aggressive reforms—many of which I will lay out in coming chapters. Leaders need to use their platforms to raise the alarm. Democracy needs to be the central message.
This can't be a campaign trail hobby that gets forgotten once the election season is over. Democratic elected officials from the White House to the statehouse need to work every day to make our democracy work better. They need to pull every lever and leave no stone unturned. There is nothing more important.
Leaders need to use their platforms to raise the alarm. Democracy needs to be the central message.
Democratic voters and activists have a critical role to play here. They need to hold Democratic politicians accountable once they are in office. If a Democratic governor is not expanding access to voting, they should be called to the carpet. If someone runs as a reformer but starts palling around with big donors, they should be protested. If they don't respond to the pressure, they should face a primary challenge.
The stakes couldn't be higher. Democracy is under relentless assault from the Republican Party and their special interest supporters. Democrats must launch an aggressive counterattack designed to establish majority rule in the country. If we don't, nothing else matters.
End Our Obsession with the Presidency
This is going to sound weird coming from a former White House staffer who worked on multiple presidential campaigns and co-hosts a podcast that spends an inordinate amount of time covering Trump and the Democrats trying to beat him. But . . . the Democratic Party is too obsessed with the White House.
Don't get me wrong—the presidency is incredibly important. To repurpose an old Obama saying, the president can do a lot with their pen and phone. Without Congress even showing up to work, the next Democratic president can reenter the Paris climate agreement, strengthen the Affordable Care Act, enforce civil and reproductive rights, put back in place regulations that make our air and water cleaner, and repeal Trump's ban on transgender troops serving in the military. The next Democratic president could fill up most of their first term signing executive orders undoing the bad shit Trump has done to America.
However, the Democratic Party's focus on winning the White House has come at the expense of everything else. Democrats have controlled the House of Representatives for only six of the last twenty-five years and the Senate for about nine of the last twenty-five. We have done worse in governorships and lost nearly one thousand state legislative seats during Obama's presidency. The consequences of not controlling Congress are well-known and painfully obvious every time the Supreme Court hands down some right-wing ruling that seems like it came directly off a whiteboard in McConnell's office or Koch HQ.
But in an era where Congress can't agree on naming a post office, statehouses are where policy is made. States manage elections; they can expand or infringe upon reproductive and civil rights. States can make guns easier or more difficult to buy. Most important, state governments draw the congressional and legislative district lines. Traditionally, Democrats have't cared as much about these down-ballot races. This isn't just the fault of the Democratic Party leadership. Democratic donors (big and small) give less money in nonpresidential years. The further you go down the ballot, the less money is raised. The Democratic gubernatorial and state legislative campaign arms usually raise a lot less money than the congressional committees, even though you can argue that those offices have a greater impact on the lives of more people. Voter turnout drops precipitously for Democrats when it's not a presidential election. This dropout explains Democratic losses in 2010 and 2014, which are the losses that allowed the Republicans to gerrymander much of the country and control the Supreme Court for decades. Democratic candidates seem much more interested in running for Congress than state legislatures, which means until recently the Democratic bench looked as shallow as the Warriors bench in the 2019 finals.
The next Democratic president could fill up most of their first term signing executive orders undoing the bad shit Trump has done to America.
Republicans, on the other hand, have spent decades and millions of dollars investing in running and winning state elections. To be fair, Republicans have two advantages (and one of them isn't that they are smarter). First, Republican voters are older, more reliable voters who vote in every election regardless of who is running. Therefore, they don't have the same drop-off in midterms that Democrats do. Second, the Republican donor network invests in politics up and down the ballot. They pay to train candidates. They understand that $50,000 may be a drop in the ocean of a presidential campaign, but it can tip a state legislative race. They know that today's school board candidate is tomorrow's congressional candidate.
We have to win the next presidential race, but a lonely victory at the top of the ballot will not be enough. The Republican response to the last Democratic president was to use every weapon at their disposal to nullify the results of the elections. That will happen again.
Without the Senate, the next Democrat will have a limited impact at best on the federal courts. Democrats need to be prepared for the fact that if a Supreme Court justice retired in the middle of the next Democratic president's inaugural address, McConnell would hold the seat open for four years.
If there is a progressive in the White House and conservatives control the statehouses, most of America will never feel the full impact of progressive policies. The Affordable Care Act included what was essentially free money for states to expand Medicaid to insure their citizens. States with Democratic governors leapt at the opportunity to take care of their citizens without affecting their already tight budgets. Many Republican governors became the first politicians in recorded history to turn down free money and forced their citizens to go without lifesaving health care. There was no argument about fiscal responsibility or small government. The whole point was to fuck with Obama's policy. The less successful the policy, the better the chances of defeating Obama in 2012 or another Democrat in 2016. I don't want to be overdramatic about this, but a lot of people died because Republican politicians cared more about hurting Obama than helping their fellow human beings.
Elected officials, party leaders, and even podcasters need to use their platforms to focus attention on the importance of winning down-ballot races. We need to convince donors and political operatives to invest their money and time in these races. We need to talk about the policy consequences and opportunities that come from political power at the state and local level. For example, one of the best ways to protect a woman's right to choose is to elect governors and legislatures who can pass laws to protect their citizens from an adverse Supreme Court ruling.
There is good news on this front. In 2017 and in 2019, Democrats made huge gains in the Virginia assembly, picking up seats in districts Republicans had held for decades by contesting even the most Republican of seats. In 2018, the turnout among Democratic voters was so high that it was on par with recent presidential elections, which helped the Democrats take control of the House of Representatives and rip the gavel from Paul Ryan's cold, emotionally dead hand. Democrats also flipped seven governors' offices from red to blue.
A lot of people died because Republican politicians cared more about hurting Obama than helping their fellow human beings.
Without a doubt, this burst in activity was a response to the racist, authoritarian criminal "working" in the White House. The wind was at our back. But the historic turnout of 2018 was also the product of a wave of activism that started right after Trump was elected. The work of everyday citizens who want to make America better was supercharged by new, innovative, tech-savvy groups like Run for Something, Swing Left, Sister District, Indivisible, and others. These groups are the future of the party. We cannot turn our backs on them once the specter of Trump has been exorcised.
It's easy to be distracted by the presidential election. But we can't afford to let that happen again. The extraordinary results of '17, '18, and '19 need to become ordinary. That's the only path to progressive success.
The Campaign Never Stops
On the first day I walked into the White House, I thought to myself, "The campaign is over. It's time to govern." I had spent my entire career as an itinerant campaign operative. Sure, I had worked in government, but those posts were just way stations to the next campaign. I always felt the most comfortable in a campaign office wearing jeans and being part of a team working around the clock and putting everything on the line. I never loved working on Capitol Hill—the pace was slow, the results few and far between, and besides, I don't like to play softball, which is the primary nonwork activity of Hill staffers.
For a while at least, I loved the political combat of campaign season. I was pretty good at making myself hate the opponent— no matter who they were. But ultimately, I was doing those campaigns because I wanted a shot at working in the White House. That was the ultimate goal. Now that I finally had that opportunity, I wanted to remind myself to govern, not campaign. My mentality at the time was consistent with how Democrats think. There is a time for campaigning and a time for governing. Campaigning is dirty work. Governing is important, and rarely, if ever, shall the two meet. Don't get me wrong—every job in the White House is inherently political, and we thought a lot about how our governing decisions affected Obama's political standing. However, we worked hard to avoid being overtly political.
Despite being in a very politically precarious position heading into the reelection campaign, Obama didn't raise a single dollar for his own race until the spring of 2011—less than eighteen months before the election. And even then, we were very nervous about opening the reelection campaign office.
"What message would it send to voters that Obama wanted their vote?" was in hindsight a really stupid thing to worry about, but worry we did. To be fair, it wasn't just us. The decision to form the reelection campaign in April 2011 was mildly controversial within the hothouse of stupidity that is DC punditry. The right-wing noise machine came after us for launching earlier than any other candidate in recent memory. We announced one whole month earlier in our term than George W. Bush did in his. In the eyes of some, pulling the political calendar forward by one month was a greater sin than invading the wrong country after 9/11.
From the book Un-Trumping America: A Plan to Make America a Democracy Again. Copyright © 2020 by Dan Pfeiffer. Reprinted by permission of Twelve/Hachette Book Group, New York, NY. All rights reserved
Dan PfeifferdemocracynonfictionPod Save AmericapodcastUn-Trumping America
Dan Pfeiffer
Dan Pfeiffer is the #1 New York Times bestselling author of Yes We (Still) Can and a cohost on Pod Save America. One of Barack Obama's longest serving advisors, he was White House director of communications under President Obama (2009-2013) and senior advisor to the president (2013-2015).
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text:
Implications of passivated conductive fillers on dielectric behavior of nanocomposites
Sung Chul Hong, Hye Jin Park, Ji Young Chang, Sang Soo Lee
KU-KIST Graduate School of Converging Science and Technology
In order to fabricate a flexible composite of large dielectric constant, the preparation of dielectric fillers employing single-walled carbon nanotubes (SWNT) passivated with alkyl pyrenes having different alkyl chain lengths and their mixing with a polymer matrix were investigated. When the lengths of alkyl chains (n) of alkyl pyrene for SWNT passivation were varied from 0 to 4, dielectric constant of the composite were almost identical (K k< 25). However, further increase regarding the length of alkyl chains in alkyl pyrene (n=12) dramatically increased the dielectric constant of the epoxy composite (K > 200) without loss of flexibility, despite the concentration of passivated SWNTs being as low as 0.04 wt% in the composite. Especially, highly suppressed dielectric loss was observed for the passivated SWNT/epoxy composite with alkyl pyrene containing an alkyl chain length of 12, which made it an ideal candidate for the embedded flexible capacitor prerequisite to flexible electronics. These dielectric behaviors were attributed to an effective debundling and partially aligned dispersion of SWNTs in the matrix, when alkyl chains with optimum length were employed in the alkyl pyrenes.
Macromolecular Research
Published - 2012 Nov
Alkyl pyrene
Dielectric constant
Nanocomposite.
Passivation
Single walled carbon nanotube
Fingerprint Dive into the research topics of 'Implications of passivated conductive fillers on dielectric behavior of nanocomposites'. Together they form a unique fingerprint.
Pyrene Engineering & Materials Science
Nanocomposites Engineering & Materials Science
Pyrenes Chemical Compounds
Single-walled carbon nanotubes (SWCN) Engineering & Materials Science
Fillers Engineering & Materials Science
pyrene Chemical Compounds
Chain length Engineering & Materials Science
Composite materials Engineering & Materials Science
Hong, S. C., Park, H. J., Chang, J. Y., & Lee, S. S. (2012). Implications of passivated conductive fillers on dielectric behavior of nanocomposites. Macromolecular Research, 20(11), 1191-1196. https://doi.org/10.1007/s13233-012-0199-7
Implications of passivated conductive fillers on dielectric behavior of nanocomposites. / Hong, Sung Chul; Park, Hye Jin; Chang, Ji Young; Lee, Sang Soo.
In: Macromolecular Research, Vol. 20, No. 11, 11.2012, p. 1191-1196.
Hong, SC, Park, HJ, Chang, JY & Lee, SS 2012, 'Implications of passivated conductive fillers on dielectric behavior of nanocomposites', Macromolecular Research, vol. 20, no. 11, pp. 1191-1196. https://doi.org/10.1007/s13233-012-0199-7
Hong SC, Park HJ, Chang JY, Lee SS. Implications of passivated conductive fillers on dielectric behavior of nanocomposites. Macromolecular Research. 2012 Nov;20(11):1191-1196. https://doi.org/10.1007/s13233-012-0199-7
Hong, Sung Chul ; Park, Hye Jin ; Chang, Ji Young ; Lee, Sang Soo. / Implications of passivated conductive fillers on dielectric behavior of nanocomposites. In: Macromolecular Research. 2012 ; Vol. 20, No. 11. pp. 1191-1196.
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abstract = "In order to fabricate a flexible composite of large dielectric constant, the preparation of dielectric fillers employing single-walled carbon nanotubes (SWNT) passivated with alkyl pyrenes having different alkyl chain lengths and their mixing with a polymer matrix were investigated. When the lengths of alkyl chains (n) of alkyl pyrene for SWNT passivation were varied from 0 to 4, dielectric constant of the composite were almost identical (K k< 25). However, further increase regarding the length of alkyl chains in alkyl pyrene (n=12) dramatically increased the dielectric constant of the epoxy composite (K > 200) without loss of flexibility, despite the concentration of passivated SWNTs being as low as 0.04 wt% in the composite. Especially, highly suppressed dielectric loss was observed for the passivated SWNT/epoxy composite with alkyl pyrene containing an alkyl chain length of 12, which made it an ideal candidate for the embedded flexible capacitor prerequisite to flexible electronics. These dielectric behaviors were attributed to an effective debundling and partially aligned dispersion of SWNTs in the matrix, when alkyl chains with optimum length were employed in the alkyl pyrenes.",
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AB - In order to fabricate a flexible composite of large dielectric constant, the preparation of dielectric fillers employing single-walled carbon nanotubes (SWNT) passivated with alkyl pyrenes having different alkyl chain lengths and their mixing with a polymer matrix were investigated. When the lengths of alkyl chains (n) of alkyl pyrene for SWNT passivation were varied from 0 to 4, dielectric constant of the composite were almost identical (K k< 25). However, further increase regarding the length of alkyl chains in alkyl pyrene (n=12) dramatically increased the dielectric constant of the epoxy composite (K > 200) without loss of flexibility, despite the concentration of passivated SWNTs being as low as 0.04 wt% in the composite. Especially, highly suppressed dielectric loss was observed for the passivated SWNT/epoxy composite with alkyl pyrene containing an alkyl chain length of 12, which made it an ideal candidate for the embedded flexible capacitor prerequisite to flexible electronics. These dielectric behaviors were attributed to an effective debundling and partially aligned dispersion of SWNTs in the matrix, when alkyl chains with optimum length were employed in the alkyl pyrenes.
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KW - Dielectric constant
KW - Nanocomposite.
KW - Passivation
KW - Single walled carbon nanotube
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In 2015, two Princeton graduates with no background in jewelry started a line of affordable gold accessories, which they sold directly to consumers online. Two years later, they have a thriving business, a Madison Avenue storefront and have just announced their latest accomplishment: $2.6 million in funding from a number of sources including Arab Angel Fund, Victress Capital and other anonymous investors.
When they founded AUrate, Bouchra Ezzahraoui and Sophie Kahn set out to disrupt traditional jewelry retail by selling ethically sourced pieces online, slashing the margins and markups typically associated with the industry. With no marketing budget and no brick and mortar presence (at first), the pair was nonetheless able to establish a base of loyal customers, who appreciated AUrate's affordable prices and no-nonsense business model.
Now, after three consecutively profitable quarters, with gains averaging around 300%, the team at AUrate intend to spend their new capital on a number of initiatives, including hiring 25 new employees over the next 12 months and expanding their marketing. But their biggest plans have to do with transforming the company from an online business to an omnichannel one with at least two more New York City storefronts and pointed West Coast expansion, starting in Los Angeles.
AUrate opened its first New York store on the Upper East Side in February 2016. Before that, the team hosted a successful Williamsburg, Brooklyn pop-up over the holidays, and they are planning a permanent location in that trendy neighborhood as well as one in downtown Manhattan, in SoHo. "Their storefronts will take the brand to the next level, offering a brick-and-click strategy while providing an AUrate sanctuary for the customer," a representative for the brand says.
Like Warby Parker and Amazon, AUrate joins a growing number of companies that began by selling online and have used that foundation as a way to back into a more conventional retail model, with brick and mortar locations that give buyers the chance to handle the merchandise and further engage with the seller. It's worth noting that Ezzahraoui and Kahn, who were profiled in FORBES in March 2016, are educated in Finance and Retail Marketing and Strategy, respectively.
AUrate, with its minimalist and fashionable pieces, appeals to female customers shopping for themselves: a desirable, growing market within the jewelry industry. This past April, National Jeweler published an article describing the rising rate of female self-purchases and how the trend is concurrent with an increase in female-headed jewelry brands. The upshot: female designers understand what women want, and women customers like buying from them.
Keep an eye out for AUrate. With money for marketing and new stores in fashionable areas, the brand is about to be a lot more visible.