Monthly Archives: May 2022

The vacation rental business has seen many, many changes in the last two decades.The industry has grown from an alternative vacation option, made up exclusively of small mom and pop operations in one location to a behemoth of multi-million-dollar companies who manage thousands of properties all around the world.Coastal Carolina has certainly seen a similar evolution.

Weve gone from basic, simply furnished beach houses where guests had to provide their own beddingto massive, luxury villas with every bell and whistle, including luxury 600-thread count Egyptian cotton sheets, pools, hot tubs, tiki bars, and home theaters. As properties have grown more sophisticated, so have guests expectations. Garage sale furniture and chipped dishes no longer cut it. Thats the way it should be. Todays guests are smart and savvy, and their vacation rental choices reflect that.Weve seen similar evolution in the way vacation rental managers operate too. No more, weve always done it that way. This industry requires growth and innovation. The journey in the industry and at Carolina Retreats has been a fascinating one.Technology and AutomationOne of the areas in which Carolina Retreats has seen unparalleled growth is in technology and automation. There have been incredible advances in vacation rental companies making the life of a rental manager, rental guests, and rental owners more seamless and streamlined. Long gone are the days of receiving a rental contract via mail and sending it back with your deposit check. Also gone are the days of checking in at the rental office and hanging around toreceive your keys. Now its all about automation and real-time technology.

At Carolina Retreats, we are proud of staying on the forefront of emerging technologies and sharing them to create the best possible experience for our guests. As technology continues to evolve, we have received overwhelmingly positive feedback from guests.Carolina Retreats keeps them informed and up to date on every aspect of their vacation rental. Guests and owners truly appreciate knowing what to expect, what comes next, and feeling like theyre in the loop.Before all of this became available, there was virtually no interaction between rental companies and guests prior to the actual arrival. The only communication was when payment was due. If a guest wanted additional information, they had to work for it.This dynamic not only created friction, but sometimes even avcombative relationship between guests and the rental company.Today, Carolina Retreats provides a proactive approach to our guests overall experience.We offer an abundance of information because we want guests to be informed. We offer our suggestions and recommendations to provide a personal touch. We stay in touch throughout the stay so that we can easily answer any question or remedy any issue that arises. And we stay in touch after the stay to continue cultivating that positive relationship, and to let our guests know their business is appreciated. We strive to be both a partner and a resource for each of our guests. This business is far more hands-on than it used to be, and we recognize our responsibility to both our guests and owners to stay ahead of that evolutionary curve.Part two of the series will provide more details on how Carolina Retreats stays at the forefront of integrating automation and technology in the vacation rental industry.

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The Changing Vacation Rental Industry- Part One: The Evolution of Technology and Automation by Mike Harrington | Sponsored Insights - Greater...

In 2008, the year I moved to the state, the Louisiana Science Education Act was passed with the backing of the then governor, Bobby Jindal. The name of the law is misleading, as it allowed schools in Louisiana to teach the Biblical account of creation in science classes as an alternative to evolution.

Jindal went as far as to say that local schools should determine how science is taught in classrooms. That meant that if the local public schools science teacher wanted to teach that all living land animals were the descendants of creatures carried on Noahs Ark, then well, that was just fine with the governor and the supporters of the law.

At the time, I presumed that Bobby Jindal (born Piyush Jindal) was probably a smart person who was somehow misled. I jokingly called him my uncle Bobby because as an Indian person I could claim all other Indians as kin, and maybe saying the governor was a relative could get me out of a speeding ticket (it couldnt).

My Uncle Bobby should have known better than to pass anti-evolution legislation. He was, after all, someone who held a Biology degree from Brown University and a Rhodes Scholar (but going to an Ivy League school and Oxford doesnt necessarily make you smart, just educated).

So whats the big deal anyway? Well, you just dont teach your own religious views in a public science class. Science is about observing and testing natural phenomena in order to give a reasoned, evidence-based explanations for those events. Religion, on the other hand, can provide answers to questions science doesnt cover (eg, what is the meaning of life?) but it can also provide answers that cant always be tested.

For instance, lets say your answer to why apples drop to the ground when they fall out of a tree is god made it happen; that isnt something I can prove false, because I cant test it. There isnt room for questioning things or scientific inquiry if you believe flatly that god controls everything that happens.

The other problem with teaching religion in a science class is that there are many religions with a variety of beliefs. Faith-based beliefs about creation differ by your religious persuasion. In one version of the Hindu creation myth, the Earth was part of the lotus flower that grew from the navel of Vishnu, and then the world was populated by Brahma and will be destroyed by Shiva.

The problem again with the teaching god controls everything is that you cant prove or disprove it. In order to respond to a Noahs flood scenario I say, There is no boat that can fit a pair of all living land animals, and having just a pair of each species wouldnt provide enough genetic variability to restock the Earth; also it cant rain for 40 days and 40 nights worldwide because we have a finite amount of water on Earth; and also all the freshwater animals would go extinct as they would be inundated by salty marine water; and where did all that water go afterwards? And there is no evidence of a huge worldwide flood from a few thousand years ago

The reply is just always, God did it, so anything is possible. Well, I guess that would be the end of the conversation. God did it can be your go-to answer, and that is fine. I am not here to judge or tell you how to live. My only issue is using that explanation to shutdown scientific discourse in an academic setting.

Science is all about testing explanations of natural phenomena to see if they hold up to rigorous testing. If you can explain everything away with God did it and controls everything, whats the point of the testing? Whats the point of school? Whats the point of curiosity? Religions ask for your faith in explaining the untestable and unprovable; science is here to help explain the rest by making testable predictions.

However, does science require some faith? Yes, I would say. You have to believe that the results and observations you make are based in reality and that the results are the outcomes of predictable phenomena. (This idea dates back before Aristotle but is explicit in the writings of religious philosophers such as Albertus Magnus, Thomas Aquinas, Roger Bacon, Avicenna, Averroes and surely many others in every culture / religion / region.)

However, that latter scenario isnt the case. We scientists can have faith in the fact that what we observe is an unmanipulated reality because our inquiries yield consistent and reliable results that allow us to reveal the secrets of our planet and of our universe ever more exactly. To paraphrase Galileo, Religion shows the way to go to heaven, not the way the heavens go.

Some would argue that there is room for studying nature in the slightly different religious take of god started everything and made the rules. That is, you can study the rules (eg, gravity, evolution) and their consequences, without having to determine the origination of those rules. This playbook suits the non-overlapping magisteria Stephen Jay Gould describes in his book Rocks of Ages.

In that book, Gould argues that science and religion can complement each other without interfering with one another, as it does for many. I would perhaps state it more plainly as, Science should not be anti-religion; and religion should not be anti-science. There is certainly room for compromise, and improved cultural competency on both sides.

That anti-evolution law is still on the books in my state. I dont mean to pick on Louisiana I genuinely love the state and am proud to call it my adopted home. My kids were born in Baton Rouge, and Ive lived here for more than ten years. Louisiana isnt the only state with issues over the teaching of evolution.

In Alabama, biology textbooks include a disclaimer sticker warning you about the theory of evolution. In 2018, Arizona briefly had all references to the word evolution deleted from the states science education standards. It isnt just the so-called conservative states; Ive met anti-evolution people in liberal Ann Arbor (where I obtained my PhD in evolutionary biology) and New York City (where I grew up).

It isnt just the US either only 26% of people in Afghanistan accept human evolution, and in 2017 Turkey removed references to evolution from its textbooks. Notably, the US ranks near Turkey in terms of how human evolution is accepted by the general public. Indians appear to be much more accepting of evolution and science despite also being deeply religious.

Again, Im here with no other motive but to explain the scientific facts that are available. The science is why the vast majority of people who understand those facts accept evolution. Im not here to challenge your beliefs we all have our own truths. We get to pick our own beliefs, but we dont get to pick our own facts. Im here to help you better understand how science explains the origin of our species and of all life on Earth.

In discussions with many people who actually accepted evolution and science, I came to realise that a good percentage of them didnt really understand the science of evolution. They just accepted evolution as fact because they trust science. They may understand even less than some people who dont accept evolution because those people dont trust science or may see some conflict with their religion.

I want to help more people on both sides to understand evolution, so that hopefully it will be less divisive. (I think difficult subjects, like politics, are so acrimonious because no one really knows what they are talking about.) It is ultimately up to you to accept scientific facts (or not), and to convince yourself of whatever truth you are willing to acknowledge.

Evolution isnt the easiest topic to understand nor the hardest either (It aint rocket surgery, as they say), but it is easy to misinterpret, and it is often portrayed incorrectly. For instance, evolution is often depicted as something like the March to Progress / Road to Homo sapiens mural by Randolph Franz Zallinger, but that is very wrong.

Evolution isnt goal-oriented or progressive. This mischaracterisation led one Louisiana state senator to ask, They evolved into a person? when told of a long-term evolution experiment on bacteria. That experiment, actually called the LTEE (Long-term evolution experiment) provided a surprising example of an evolutionary adaptation observed as it occurred.

That experiment in the lab of Dr Richard Lenski found that some E coli populations (from over 70,000 generations), all captive reared from the same source population, had evolved an adaptive trait. That is very clear evidence of evolution (eg, change in the inherited characteristics of a population). What that state senator believed, based on that common misunderstanding of evolution, was that the only definitive evidence of evolution from that experiment would be if the bacteria turned into humans.

Even given an infinite number of generations reared in those lab conditions, those bacteria would never turn into humans thats not how evolution works.

Excerpted with permission from Explaining Life Through Evolution, Prosanta Chakrabarty, Penguin Allen Lane.

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Why it is necessary to understand the development of life through evolution and not religion - Scroll.in

How many episodes should a season or series of television be? Depending on who you ask, answers vary. Were in a TV era overflowing with options on broadcast and streaming, and episode count is playing a major role in our television habits more than ever.

Theres a verifiable cornucopia of content for viewers to consume and how many episodes a piece of media has can be the deciding factor when it comes to watching it or not. This includes bingeing classics that have shaped pop culture.

Of course, there will always be TV lovers who give shows like X-Files, Friends, The Office, Smallville, and Supernatural a chance despite being over 200 episodes long, or in Supernaturals case over 300, but the time of the long running series is drawing to a close outside of procedurals.

Much of this has to do with an overabundance of television. Theres simply too many programs to watch with very little time to watch them. Not to mention viewers are less willing to spend season upon season with a show thats begun to deteriorate in quality. Also, a drop in the required number of episodes for a show to reach syndication plus the birth of streaming has shifted the landscape.

Were in a new frontier, one kicked off by Netflix. The binge model of television watching changed audiences expectations for the shows they watch. New series premiering on streamers cant be up to 22 episodes or more like broadcast (though there are shows clocking in at 13 episodes per season on TV). Its just not feasible especially when episodes drop all at once on premiere day.

Could you imagine trying to binge 22 episodes of a Stranger Things release? In a time when you have to log out of all social media accounts and basically not surf the web in order not to be spoiled, it would be stressful and not worth anyones time to binge it. Thats a limitation of streaming in the era of binge television.

The measure of how many episodes is too many is dependent on where a piece of media has made its home. If youre still tuning into week-to-week broadcast television, you know youre typically in for 18-22 episodes a season. The pandemic has shortened that episode count for many shows, especially on The CW, but TV viewers know what to expect.

18-22 episodes gives shows the opportunity to experiment with filler content such as bottle episodes, flashbacks, crossovers, etc. Its the kind of entertainment that can have fans going up with excitement or groaning over yet another detour from the overall plot but at least theres room for expanded storytelling.

Streaming series dont have that luxury. Theyre in and out of their stories between 4-13 episodes. Its a model that works well for the platforms even when a season or show releases weekly. However, there are drawbacks. There isnt a set runtime for episodes so a short season doesnt mean you wont be caught off guard by long episode.

For example, Stranger Things season 4 episodes will clock-in at over an hour. K-dramas on Netflix often do have episodes that run up to 60 minutes and can even be as long as 90 minutes. Obviously, established shows or vehicles with big name actors can get away with feature length episodes of television, but thats still a lot of time for viewers to invest in a series.

So, this isnt only a question of episode count, its also a question of episode length. Its great that creators are pushing boundaries in the medium of television on streaming. But the amount of episodes a season has on top of how long those episodes are can make or break audience retention for shows just starting out.

While there isnt a consensus on how many episodes is the sweet spot for streaming shows, it does seem that 8-10 episodes per season works well for shows. 45 minutes to an hour in run-time per episode is the preferred standard thats carried over from broadcast.

As for network television, some shows would benefit from breaking away from the 18-22 episode standard. 13-15 episodes would likely produce tighter storytelling especially for series where theres clearly not enough material to stretch past that marker.

What do you think? How many episodes is too many for a TV show? Let us know in the comments!

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The evolution of the episode count: How many episodes is too many? - Hidden Remote

Mario Isola says there is a lot of excitement about the forthcoming Miami Grand Prix, but being a new venue means Pirelli are being conservative when it comes to tyre compound choices.

Pirelli are bringing their C2 (white-walled hard), C3 (yellow-walled medium) and C4 (red-walled soft) compounds to the track, the middle of their range of available compounds in 2022.

On a track that has some high-speed sections much like the Jeddah Corniche Circuit in Saudi Arabia as well as some slower, more technical sections, Isola, the Motorsport Director at Pirelli, is expecting a lot of track evolution and a lot of initial grip levels.

With cars likely to run at a medium level of downforce, Isola foresees some sliding around the higher speed corners, but he is interested to see the first Miami Grand Prix and how Pirellis tyres face up to the challenges of the brand-new circuit in the United States.

Theres been a huge buzz of excitement around the first Miami Grand Prix, where the track has some similarities to Jeddah, although there are some parts that are slower and more technical than Saudi Arabia: especially the section from Turns 11 to 16, said Isola.

The rest is a very quick layout, running anti-clockwise, which puts the emphasis on the tyres on the right hand side of the car. Were expecting the usual rapid track evolution and a smooth surface with the new asphalt, but the track has been jet-washed at high pressure, which means that it should offer quite good grip from the beginning.

Because its a fast track the cars are likely to run a low to medium downforce set-up, which could lead to a bit of sliding in the high-speed corners on the hard compounds in particular.

For any new track our choice tends to be on the conservative side, so it will be interest to confront the simulations with real data.

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Pirelli Expecting 'Rapid Track Evolution' and 'Good Grip' on Miami Grand Prix Debut - The Checkered Flag

Scientists have created new artificial microbes by combining two very different organisms into one functioning entity. The hybrid of a yeast and a bacterium adds evidence to a long-standing hypothesis on how advanced life may have evolved.

Inside the cells of complex lifeforms are tiny, separate organs called organelles, some of which have their own separate genomes to that of the larger organism. That includes the mitochondria in animals and chloroplasts in plants, both of which generate energy for the organism. A leading theory suggests that these organelles were originally separate microorganisms that were engulfed by other cells, and the two eventually entered a symbiotic relationship that paved the way for complex life to evolve.

And now a new study has recreated this process, known as endosymbiosis. Researchers from the University of Illinois Urbana-Champaign designed and engineered artificial hybrids of two microbes a budding yeast and photosynthetic cyanobacteria.

The resulting chimera was able to photosynthesize like the bacteria to generate energy, and reproduced through budding like the yeast. The organisms were able to propagate for at least 15 to 20 generations, and the team says that the achievement lends weight to the hypothesis that complex life got its start through endosymbiosis.

We have essentially converted a nonphotosynthetic organism into a photosynthetic, chimeric life form, said Angad Mehta, lead researcher on the study. I believe that our new ability to build controlled, synthetic endosymbiotic chimera that can be genetically and metabolically manipulated, analytically studied and imaged, and computationally modeled and predicted will break the gridlock on our understanding of this remarkable evolutionary transformation.

This isnt the first engineered hybrid to demonstrate endosymbiosis in action. A previous study in 2018 combined yeast and E. coli in a similar fashion, tweaking each so that the bacteria had to source vitamins from the yeast and the yeast had to source energy from the bacteria.

The new research was published in the journal Nature Communications.

Source: University of Illinois Urbana-Champaign

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New synthetic hybrids of yeast and bacteria demonstrate ancient evolution - New Atlas

Fossil data

We downloaded all fossil occurrences recorded for the order Scleractinia at the species level from the Paleobiology Database (PBDB paleobiodb.org; accessed on 3 August 2021). This is the most comprehensive repository for palaeontological data in reef corals to date. Due to the nature of the data, no ethics approval was required. To minimize identification issues, we excluded taxa with uncertain generic and species assignments (i.e., classified as aff. and cf.) and only selected species that had accepted names. We also selected the variables classification and palaeoenvironment from the output options to facilitate taxonomic and environmental filters applied in downstream analyses. The full dataset consisted of 24,011 occurrences across 4235 species, spanning over 250Myr of coral evolution from the Triassic to the present. Although our focus here lies on the Cenozoic, we used the complete fossil dataset (i.e., including all of the occurrences) to have estimates of the diversification dynamics in scleractinian corals throughout the whole timespan of their evolution.

With the full palaeontological dataset, we estimated evolutionary rates through time in scleractinian corals using the Bayesian framework of the program PyRate (v3.0)12,36,37. This program uses fossil occurrence data to calculate the temporal variation in rates of preservation, speciation and extinction, while incorporating multiple sources of uncertainty12. At its core implementation, PyRate jointly estimates the times of origination (Ts) and extinction (Te) for each fossil lineage; the fossilization and sampling parameters that determine preservation rates (q); and the overall rates of speciation () and extinction () through time36. Recently, the program has been upgraded to include a reversible jump Markov Chain Monte Carlo (rjMCMC) algorithm to estimate diversification rate heterogeneity, which provides more accurate and precise estimates than other commonly used methods12. Therefore, despite the inherent bias of the fossil record (i.e., estimates are conditioned on sampled lineages), PyRate is a robust method to quantify speciation and extinction rates, and their respective temporal shifts, from fossil occurrence data.

Extant taxa can also be included in the PyRate framework as long as they are also represented in the fossil record. This is done to extend the fossil geologic ranges to the recent times. Hence, the first step in our analysis was to identify which species in our dataset is still alive at the present. To do this, we matched the accepted species names in the PBDB dataset with those from the extant species dataset of Huang et al.38. Subsequently, we split our dataset into eleven independent subsets, with the goal of keeping each subset with an equal number of species. Each data subset included a random selection of species with their respective occurrences, which was enough to calculate Ts and Te (see below). This was done to avoid convergence issues, given the large size of our dataset and the consequent complexity of the model37. For each of our subsets, we generated fifty replicates by resampling the fossil ages from their temporal ranges to account for the uncertainty associated with the age of occurrences. We then used the maximum-likelihood test in PyRate to compare between three models of fossil preservation12: the homogeneous Poisson process (HPP; q is constant through time); the nonhomogeneous Poisson process (NHPP; q varies throughout the lifespan of a species); and the time-variable Poisson process (TPP; q varies across geological epochs). The latter model (TPP) was selected across all of our data subsets (Supplementary Table2).

After selecting the preservation model, we first focused on assessing the estimates of times of origination and extinction in each data subset, rather than using the full dataset to jointly estimate all parameters at once as in the original implementation of PyRate. This further reduced the complexity of the model and allowed for more precise parameter estimates. For each replicate in all of our data subsets, we approximated the posterior distribution of Ts and Te through a 50 million generation run of the rjMCMC algorithm under the TPP, sampling parameters every 40 thousand iterations. At the end of each run, we discarded 20% of the samples as burn-in and assessed chain convergence through the effective sample sizes of posterior parameter estimates, using the software Tracer39 (v1.7.1).

From the results of this first set of models, we extracted the median estimates of Ts and Te across replicates, and we merged the estimates from the eleven independent data subsets. This merged data frame contained estimated times of origination and extinction for all coral lineages within our fossil dataset. We then used this merged Ts and Te data frame as input for another rjMCMC chain to finally estimate overall and through time, by applying the option -d in PyRate. In this option, Ts and Te for all fossil lineages are given as fixed values and, therefore, are not estimated by the model. The chain for this model was run for 100 million generations, sampling parameters at every 40 thousand iterations. Once again, we excluded 20% of the initial samples as burn-in and checked model convergence using Tracer. Finally, we calculated net diversification rates through time by subtracting the post burn-in samples of from .

To explore the taxonomic idiosyncrasies in the evolutionary rates of reef corals, we selected the most abundant families on present-day coral reefs in terms of the number of colonies per area18 (Acroporidae, Agariciidae, Merulinidae, Mussidae, Pocilloporidae, and Poritidae). Altogether, species within these families account for ~40% of the total extant diversity in Scleractinia. These families also account for most of the occurrences in the PBDB fossil dataset (excluding extinct families, which are generally older and had little temporal overlap with extant ones): Acroporidae (1457 occ. in 165 spp.); Agariciidae (722 occ. in 89 spp.); Merulinidae (2464 occ. in 229 spp.); Mussidae (1146 occ. in 100 spp.); Pocilloporidae (615 occ. in 64 spp.); and Poritidae (1149 occ. in 91 spp.). Therefore, from our full dataset, we selected six independent ones encompassing all species in each of the selected families. We also selected only species that are classified as reef-associated within these families, since we were specifically interested in these environments. This selection had a negligible effect on the size of the individual datasets, given that the vast majority of fossil species within these families are reef-associated. In each family, we followed the same modelling steps described above to estimate and , and diversity trajectories. However, this time it was not necessary to split the datasets into subsets, given that each family has far less occurrences than the full dataset. We started by comparing models of preservation, which showed the TPP as the best supported for all families (Supplementary Table3). Then we created fifty replicates by resampling fossil ages to accommodate the uncertainty associated with the time of occurrences. For each replicate, we ran the rjMCMC algorithm for 50 million generations under the TPP model, with a sampling frequency of 40 thousand iterations. We discarded initial 20% of the samples as burn-in, and assessed convergence through Tracer. We then combined all replicates, resampling 100 random samples from each replicate to assess the estimates of and through time for each family. Finally, we extracted diversity trajectories in each family for all of the replicates by applying the -ltt option in PyRate, which generates a table with estimated range-through diversity at every 0.1Myr. From these trajectories, we calculated the mean difference in diversity (slope in species per 0.1Myr) between subsequent time samples backwards from the present (i.e., diversity in time t was subtracted from diversity in time t-1) using the diff function in R (v4.0.3).

As an alternative to PyRate, we also calculated the diversity dynamics of reef coral fossils using the R package divDyn40, which combines a range of published methods for quantifying fossil diversification rates. Differently from PyRate, the metrics applied in divDyn require that the fossil occurrences are split into discrete time bins. Therefore, these metrics treat the origination and extinction rates as independent parameters in each bin, while PyRate is designed to detect rate heterogeneity through a continuous time setting12. Our goal here, however, was not to compare models but to assess the robustness of our rate patterns and diversity trajectories using alternative methods. We divided our dataset into one-million-year time bins to have enough temporal resolution for rate calculations. To account for the uncertainty in the assignment of fossil ages, we created 50 binned replicates by sampling the age of each occurrence from a random uniform distribution, with bounds defined by the age ranges provided in the PBDB dataset. We then used the divDyn function to calculate the per capita rates of origination and extinction through time (based on the rate equations by Foote41) for all scleractinians (Supplementary Fig.5a) and for reef-associated acroporids alone (Supplementary Fig.5b). We also used the same procedure to generate range-through diversity curves for each of the six families selected previously, to compare with the curves generated by PyRate (Fig.2a). Although the rate results differed between the PyRate (Fig.1) and the divDyn (Supplementary Fig.5) approaches, the general patterns remained unchanged. Rates are more volatile through time in divDyn estimates, with larger confidence intervals, which is expected from the metrics applied in the package12,42. Yet, we found the same peaks in extinction for Scleractinia: at the Cretaceous-Paleogene and Eocene-Oligocene boundaries, and at the Pliocene-Pleistocene (Supplementary Fig.5a). The recent peak in speciation in Acroporidae was also detected, although less strong (Supplementary Fig.5b). Despite these slight differences in rate estimates, the diversity curves reconstructed through divDyn (Supplementary Fig.6) mirrored almost exactly the ones found with PyRate (Fig.2), demonstrating that the overall macroevolutionary trends described herein (Figs.1 and 2) are robust to methodological choices.

To assess the effects of diversity dependency on the evolution of reef coral lineages, we implemented the Multivariate Birth-Death model (MBD)11 within the PyRate framework. This method was first described as the Multiple Clade Diversity Dependence model (MCDD)19, in which rates of speciation and extinction are modelled as having linear correlations with the diversity trajectories of other clades. At its original implementation, the MCDD was developed to assess the effects of negative interactions, where increasing species diversity in one group can suppress speciation rates and/or promote extinction in itself or in other ecologically similar clades19. However, the model also incorporates the possibility of positive interactions, where increasing diversity in one clade can correlate with enhanced rates of speciation or buffered extinction. Through further model developments43, the MCDD was updated to also include a horseshoe prior44 on the diversity-dependence parameters, which helped controlling for overparameterization and enhanced the power of the model to recover true effects43. More recently, this model took its current form as the MBD11, with the additional possibilities of including environmental correlates and setting exponential, rather than just linear, correlations.

We first applied the MBD to estimate the diversity-dependent effects of individual extant coral families (i.e., the ones selected in the previous analysis; see Evolutionary rates) in their combined diversity trajectories. From the rjMCMC model results for individual families, we extracted estimates of Ts and Te in each of the fifty replicates and merged them across families. This merged dataset with fifty replicates of Ts and Te was then used as input for the MBD model, where we set the relative diversity trajectories of each individual family as predictors. We also included three key environmental predictorspaleotemperature, sea level and rate of sea-level changeto assess their influence in overall evolutionary rates. The paleotemperature data was obtained from Westerhold et al.45, and consists of global mean temperature estimates for the last 66 million years, averaged across 0.1Myr time bins. Eustatic sea-level data was downloaded from Miller et al.46, and contains estimates of sea level for the last 100 million years in comparison to present-day levels, also split in ~0.1Myr time bins. With this dataset, we calculated the average rate of sea-level change per million years, as measured from the absolute difference between subsequent sea-level values backwards in time (i.e., sea level in time t was subtracted from sea level in time t-1). These environmental factors were rescaled between 0 and 1 to maintain all predictors on the same relative scale.

Under our MBD model, the speciation and extinction rates of all families combined could change through time and through correlations with the relative diversity of individual families or environmental factors. The strength and directionality (positive or negative) of the correlations are also jointly estimated for each predictor within the model11. We ran both linear and exponential correlation models (see formulas in Lehtonen et al.11) in each of our fifty replicates for 25 million generations, sampling parameters at every 25 thousand iterations. We then compared the linear and exponential models through the posterior harmonic means of their log likelihoods, which supported the exponential one as having a better fit. From the posterior estimates, we summarized the speciation (Fig.3c) and extinction (Fig.3d) correlation parameters (i.e., the strength of the effect) by calculating their median and 95% Highest Posterior Density (HPD) interval across replicates. Finally, we also summarized the effect of families on lineage turnover (Fig.3e), which we conceptualize as the sum of the effects on speciation and extinction.

The MBD model also provides posterior samples of the weight of the correlation parameters, which is estimated through the horseshoe prior11. In essence, this prior is able to reliably distinguish correlation parameters that should be considered noise from those that represent a true signal in the data11. The parameterization of the horseshoe prior contains local and global Bayesian shrinkage parameters44 from which shrinkage weights (w) can be calculated (see formulas in Lehtonen et al.11). These shrinkage weights associated with each correlation parameter in the MBD model vary between 0 and 1, with values closer to 0 representing noise and values closer to 1 representing a true signal. Through simulations, it has been shown that values of w>0.5 indicate that the correlation parameter in question significantly differs from the background noise, being the correlation positive or negative43. However, as a conservative way to infer the weight of correlation parameters, here we use a value of w>0.7 to detect significance. This value was calculated for each diversity-dependence parameter (speciation, extinction and turnover) from the median values drawn from the model posteriors.

The spatial distribution of reef-associated taxa varied considerably throughout the Cenozoic, with biodiversity hotspots moving halfway across the globe47. Therefore, the best way to capture this dynamic biogeographic history in reef corals is by analysing global diversity patterns like we did in our main MBD model. However, to assess the robustness of our diversity-dependent results against the influence of geographic scale and site co-occurrences, we repeated all the modelling steps described above with two data subsets. First, we selected only fossil species that have occurrences in the Indo-Pacific Ocean (i.e., 30W180W) within the six families. Second, we excluded sites in which the Acroporidae did not co-occur with the other families. In each of these data subsets, we calculated diversity trajectories and used them as predictors in a separate MBD model. These models had a merged dataset of Ts and Te of all species included in each case (Indo-Pacific and co-occurrences) as a response variable.

Finally, we followed the same modelling procedures described above to investigate the diversity-dependent effects in family pairwise analyses. We applied the MBD model to assess the effects of all other families in each individual family at a time, while also estimating correlations with the key environmental predictors. From the rjMCMC model results for individual families, we extracted the fifty replicates of estimated Ts and Te. Each replicate was then used as input for an MBD run using the relative diversity trajectories of each other individual family as predictors, along with the environmental variables. Once again, we ran 25 million generations of the MBD, with a sampling frequency of 25 thousand, using both linear and exponential correlation models in each age replicate. For all families, we found that the exponential model had a better fit. We then summarized the correlation parameters and the shrinkage weights (Supplementary Fig.7) derived from the exponential models per family by calculating the median and 95% confidence intervals across replicates.

Further information on research design is available in theNature Research Reporting Summary linked to this article.

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Fast-growing species shape the evolution of reef corals - Nature.com

The late E. O. Wilson (19292021) received more than one hundred awards for his research and writing, including two Pulitzer Prizes. As a professor at Harvard University, Wilson influenced generations with his ideas about human evolution and ethics.

In his 2012 New York Times essay Evolution and Our Inner Conflict, Wilson asked two key question regarding the problem of evil in our world:

Are human beings intrinsically good but corruptible by the forces of evil, or the reverse, innately sinful yet redeemable by the forces of good? Are we built to pledge our lives to a group, even to the risk of death, or the opposite, built to place ourselves and our families above all else?

Wilson believed that humans are all of these things at once. In order to evolve, nature pulls humanity between good and evil instincts. Humans sometimes work to preserve the group and sometimes work to preserve the individual. This kind of multilevel selection was the principal force of social evolution. Most importantly, he believed that biology, not Godm, was the key to understanding the world. For Wilson, the evolutionary pull between selfish and altruistic behaviors is the essence of our inner conflict.

But even the use of binary concepts like good and evil or altruistic and selfish is misleading. Given his naturalistic worldview, Wilson concluded that we should not put the moral label of good or evil on any of our instincts, which are of genetic origin. Sometimes humans need to be selfish to survive. Sometimes humans need to be altruistic to survive. Both selfishness and sacrifice are necessary parts of our evolutionary past and necessary for the very survival of humanity.

To be clear, Wilson never applied his theory to artificial intelligence (AI). And it is doubtful that AI will ever evolve a sense of self-awareness. But, even if AI never becomes conscious, AI will be programmed to make decisions. So the question is this: If the humans who share Wilsons view of social evolution program AI, will the AI share our inner conflict?

As humans come to rely more and more on AI to make decisions about things such as medical care and food distribution, we must be aware of the moral code behind the coding. AI could well be driven by its own iteration of multilevel selection in at least two ways.

According to Wilson, the first trait of human existence is our selfishness and superiority. Humans (both individually and as groups) have an inborn perception of superiority which is necessary for our evolution. Now, if AI is the next evolution of the human mind, then certainly AI will share humanitys sense of selfish superiority. In the inevitable conflict between AI and humanity, AIs sense of superiority will lead it to protect itself and sacrifice humanity. At the same time, to stave off artificial insanity AI will also need to identify with a group. This leads to the second aspect of AIs inner conflict.

According to Wilson, people give preference to those who act, speak, and believe as they do. He notes, An amplification of this evidently inborn predisposition leads with frightening ease to racism and religious bigotry. But why is Wilson frightened by racism and religious bigotry? According to Wilsons own article, tribalism is neither good or bad, but a neutral trait necessary for human evolution.

More to the point, if Wilsons naturalistic framework is the source code for AI, we must ask ourselves, what encoded bigotries will AI select as necessary for survive? Will some humans be privileged and others oppressed? Will AI limit resources to certain tribes of humans to ensure the survival of the species? The likely answer to each of these questions is yes.

In a world stripped of the divine, it is computer code, not God, that will define the good and bad of our future. AIs evolved sense of superiority and tribalism speaks to the potential problem of AIs inner conflict. If the code is written by humans, who are both saint and sinner, then AI will certainly function as both sinner and saint. To manage the world of human, animal, and plant life, AI will sometimes need to select between groups deemed more valuable and those deemed too weak to advance society. But dont let that discourage you. After all, writes Wilson, this kind of multilevel selection, might be the only way in the entire universe that human-level intelligence and social organization can evolve. After all, its the progress of human civilization that matters, not the methods we use to achieve that progress.

In the end, AI will be driven by the moral code embraced by the scientists and engineers who build it. If Wilsons naturalism is any indication of our future, then AI will not save us from ourselves.

You may also wish to read: Why the imago Dei (Image of God) shuts the door on transhumanism. As the belief that technology promises us a glorious post-human future advances among scholar who profess Christianity, we must ask some hard questions. The mission to self-evolve beyond humanity begs the question, how is humanity saved through technological advancement designed to eliminate humanity? (J. R. Miller)

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Why AI Can't Save Us From Ourselves If Evolution Is Any Guide - Walter Bradley Center for Natural and Artificial Intelligence

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45 Years of Technical Evolution Labmate Online - Labmate Online

The rapid evolution of ABM platforms is creating various paths for the future

As the Forrester B2B Summit gets underway today, marketers will be assembling to discuss the latest changes in technologies that help them do their jobs more effectively. And no category has gone through more changes over the past two years than the tools for account-based marketing (ABM). And the changes arent finished!

What is driving the evolution of ABM platforms? According to Forresters lead analyst for the category, Malachi Threadgill, it is a response to the way marketers and sellers are adjusting to the changes among B2B buyers. He explained, We tend to think about marketing in an old way, which is leads - MCLs and SQLs. The reality is that 84% of B2B decisions are made by a committee of four or more. The toolsets have caught up to understand that a lead is just a signal. If one person downloads a form, it's a signal that the buying group is likely looking at that.

Malachi Threadgill, principal analyst at Forrester

He continued, At a high level, the platforms provide the ability to find good-fit accounts, understand if they're in market and then be able to orchestrate and activate campaigns to them. This has been the focal point of a lot of the organizations. We've seen a lot of consolidation in the space over the last couple years, similar to what we saw with marketing automation platforms before they were acquired by the bigger companies. The interesting thing is that, today, we are seeing that most of the top players in the space have relative parity. This parity of primary features has caused vendors to explore adjacent and nascent capabilities to differentiate their offerings and deliver value to their customers. These capabilities include owned proprietary data, deeper machine learning assistance, and fully embedded email capabilities. There are nuances between platforms that organizations should consider, and if those nuanced differences are important, one may be better than the other for that specific use case.

The evolution of the category is so dramatic that ABM may soon be dying as a moniker. One of the category leaders, Demandbase, acquired Engagio in 2020, whose founder, Jon Miller, now serves as CMO of Demandbase. Miller provided his perspective on the evolution of the category, which he now dubs account-based experiences (ABX). He shared, There are two key drivers for introducing AVX instead of ABM. The first one is a little nuanced. I think the way account-based marketing had been practiced, it was done without a lot of respect for the buyer experience. The analogy that I've always used to describe ABM was fishing with spears which was a really effective analogy. But at the same time, it doesn't feel very good to get poked by a spear. So, with the advent of things like intent data that lets you get a lot smarter around knowing where an account is in its buying journey, the realization I had is that there's the opportunity to combine the precision and targeting of ABM with the respect for the buyer experience that traditional inbound marketing had. Don't bug people when it's the wrong time and align your go-to-market to where the account is in its own experience, in its own journey.

Jon Miller, CMO of Damandbase

Miller continued, The second driver behind ABX as a term is a little bit more obvious. Account-based marketing has the word marketing in the title. And that's really a misnomer for what is a go-to-market strategy that demands alignment across multiple departments including sales and sales development. So that was the impetus behind driving account-based experience.

He expressed his belief that account and contact data will be key to success in the category. The reality is the AI algorithms are fairly commoditized. The nuance is in the data and how you use that data as it inputs into the algorithms. Because of that, what we're seeing is that the competition battleground is increasingly moving towards who has the best data. And that's behind our recent positioning where we're really focusing on our account intelligence. So we acquired InsideView as a key partto building that out. And the DemandMatrix acquisition is bringing technographic data to the table which does get into improving the intent. So, what that means is in many ways, is that our future competitor is ZoomInfo more than it is [other ABM platforms]. We built the application and now we are increasingly providing the data. ZoomInfo, historically, had data and they're starting to move into the application. Account intelligence is really where the future battleground is going to be.

Greg Brown, Greg Bell, head of strategic marketing and industry solutions at 6sense

6sense also agrees that the nomenclature is outdated but has a different term it is advocating. Greg Bell, head of strategic marketing and industry solutions at 6sense explained, The issue that we saw with ABM a couple of years ago was the M. We saw it in the way that we use 6sense internally, we saw it in our customers and the value that they're getting from the platform. It's that it's not just account-based marketing. We certainly have capabilities for marketers, but also for sellers, for folks in operations, and even customer success. It's all about uniting the revenue team. We like to say it's about generating pipeline and revenue more predictably, that's really the promise that the 6sense platform delivers on to our customers. So we started down the road towards this RevTech message.

Brown continued, We grew up in the world of big data and predictive analytics, that's really where our roots are. The ways that we use AI beyond modeling for propensity to buy at the account and the contact level, things like using AI to predict next best actions for sellers would be one example of other applications of AI. 6sense has also been enhancing its capabilities through acquisitions, including Zen IQ, Fortella, Slintel and Sales Whale.

Jason Zintak, CEO of 6sense

Jason Zintack, CEO of 6sense expanded on the companys vision, Last year we launched the RevTech Revolution and announced our commitment to transform the B2B buying experience. Account-based marketing plays an important role in a modern approach to growth, but our vision is bigger, too. It has to be. We need to bring together marketing and sales, customer success, RevOps, and the rest of the revenue team if we want to see the kind of change our industry needs and buyers deserve.

Terminus has also been recognized as a category leader. Bryan Wade joined the firm when his company, Sigstr, was acquired by Terminus, and now serves as chief product officer. He shared, ABM is all about sales and marketing coming together and agreeing that rather than just taking inbound leads that come your way, and cold calling into accounts that just happened to be in your territory, let's go after the accounts that we think are our ideal customers, the ones that will have the most success with us, that will spend more with us once we sign them up as a client, and not try to acquire customers that aren't a fit. So in the beginning, the idea of ABM was around marketing and sales alignment, ideal customer profile, targeting those accounts, and then bringing those customers into your customer base. It's evolved into so much more.

Bryan Wade, chief product officer at Terminus

Terminus has expanded its platform to address the increasing expectations. In addition to acquiring Sigstr, it has acquired Growfire, Xylo Tech, Ramble and BrightFunnel. Wade added, Our vision is to build a B2B marketing cloud. And you can't have a B2B marketing cloud without a journey builder. So we're building a brand new interface that will help our customers orchestrate all the different channels in one canvas. We are integrating the CDP into our ABM platform. I think when you step back and think about what well will turn into in three to five years, we'll have a B2B CDP with an orchestration engine sitting on top of it.

The ABM platform field includes additional players including MRP, Rollworks, Triblio and Tech Target among others. And there are players in adjacent categories including SalesLoft, Outreach and Zoominfo, not to mention the marketing automation platforms like Marketo, Pardot and Hubspot. So where is the category going in the near future? Forresters Threadgill concluded, I think there's still a bit more time for the ABM platforms in terms of what their short-term strategies are. With ZoomInfo going public and being rewarded for it, and acquiring companies and being rewarded for it, and then massive investments in a lot of the other ABM platforms, it's going to be interesting to see what they do with that capital. When you just look at those valuations, does it still make sense for an Adobe or an Oracle to acquire them? I don't know that answer.

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Why The Evolution Of ABM Is Creating Both Confusion And Opportunity For B2B Marketers - Forbes

Pay-per-view streaming returned to the world of curling last weekwith a twist.

The World Mixed Doubles Championships in Geneva once again saw World Curling Television use the Recast (recast.app) service, which charges 0.50 per match. This is the same service that was used at the Olympic Qualifying Event and European Championships earlier this season,which prompted thiscolumn, as well as the recent mens and womens worlds.

Regional blackouts were applied (for example, any game shown on TSN was not available in Canada on Recast), but there were at least two matches per draw that were given the full broadcast experiencewith on-site commentary, multiple cameras and production, and so on.

Now for the twist. If your favourite team didnt make the cut for coverage, the WCF added a light coverage option to the three other matches that werent given the full treatment. Light coverage consisted of two stationary cameras pointed at the two houses in a split-screen presentation, and the action was shown without commentary, replays or alternate angles.

Scores of the other four sheets ran along the bottom of the viewers screen.

WCTV light coverage view

The audio wasnt great, as the players microphones werent on and they had a microphone picking up ambient noise near the ice (and the microphone for sheets A and B must have been near the ventilation system or something, because there was a lot of white noise going on there).

This light coverage costs 0.25; half as much as the matches with commentary, bells and whistles.

While the level of coverage matches that of a curling club dabbling in streaming league play league to YouTube, at least it gives the option to be able to follow any game, which is a vastly superior experience than waiting for line scores to update after each end. Well probably never see four or five fully-produced games at onceother than at the Olympicsso this light coverage, which has been requested on many a curling chat group over the years, is a fine compromise.

While cable TV sports coverage isnt going away, internet streaming is on the rise and will only get more commonplace. I know most will grumble about having to pay to watch a match, but these are essentially micro-transactions, and compared to what you have to pay to subscribe to a cable channeleither directly or through a cable subscriptionthis doesnt break the bank.

So, the question that I asked back in December remains how much is broadcast curling worth to you?

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The Evolution of Curling Coverage - Sports Illustrated