Daily Archives: August 2, 2021

Tax professionals are going virtual in droves. Taxpayers need to understand how changes in the tax ... [+] industry will affect customer service in the future.

Even during the best of times, the work environment for tax practitioners during tax season can be described as toxic. Return volume is high, time is short, and clients are oftenproblematic. Then along came Covid-19. In 2020 even though deadlines were extended to help taxpayers and tax practitioners cope with the effects of the lockdowns many tax practitioners struggled to adapt to a business model without face-to-face interaction with clients. Many were completely unprepared. Others, however, were ready. Enrolled Agent and self-described gadget girl Nayo Carter-Gray had been moving towards a fully virtual practice for years when the pandemic hit. During that time she realized that the process for changing from an in-person to a virtual office wasnt taught anywhere. She had learned piecemeal. So in the summer of 2020 she launched the Taking Your Firm Virtual Summit as a comprehensive vehicle for practitioners wishing to move their practices into the 21st century. This years summit runs from August 3-5 and features a broad complement of speakers who will help tax practitioners continue to transform their practices in preparation for what promises to be at least a few more chaotic tax filing seasons.

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Practitioners like Nayo and her speakers are on the leading edge of the tax and accounting future state. They are transforming a staid industry into something much more valuable to its clients while also working to eliminate some of the industrys more toxic traits. But what does that have to do with me, the taxpayer, you may be asking? Quite a bit actually.

The trend toward virtual offices is accelerating a more general trend in the tax and accounting industry toward automating the most routine client interactions and tasks. Newer practitioners see automation as a way to grow their firms while providing an extremely high level of service to their clients. More established practitioners have begun using automation to reallocate their resources from office administrative tasks to more advanced tax planning and issue resolution that can only be done by a human. So what types of changes can taxpayers expect moving forward? Keep reading to find out.

First, finding a retail tax practice with regular hours where you can walk in without an appointment, drop off your paperwork, or even have your tax return prepared while you wait may become more difficult unless you choose one of the large chains. Many smaller practices and solo practitioners have made the post-Covid realization that working from home works for them. Eliminating rent from office overhead means either higher profits or the same profits but a much lower workload. Even practitioners who maintain an office outside of their home may no longer offer walk-in or drop off service, especially solo practitioners.

Some practitioners will no longer accept paper documents. Clients are expected to complete annual engagement paperwork and organizers online and then use a secure portal to upload their tax documents. For security reasons even fully virtual firms will not accept documents attached to e-mail or (crikey!) via text message. Those firms who do accept paper documents usually will also accept uploaded documents or maintain a largely paperless office where client documents are scanned and returned to the client.

Clients should also expect to self-schedule document pick ups and drop offs and phone calls. Solo practitioners especially are learning to use self-scheduling applications and time management tools to block specific times for specific tasks. For example, many practitioners block off their most productive time for working on tax returns and less productive time for returning calls and answering e-mails. Tax returns will be delivered electronically, picked up by appointment, or delivered by mail or courier and, once the documents are in hand, the client will use an app to schedule a review appointment if desired. Some practitioners may still offer in-office appointments, but clients can also expect to be encouraged to choose phone or video chat appointments instead.

Amanda McGowan, owner of Elevating Profits in metropolitan Denver, is both an Enrolled Agent and a business coach. She teaches tax practitioners how to achieve a no call office. Amanda is a big proponent of using time blocking to set professional boundaries especially for seemingly urgent but rarely truly important items (calls, e-mails, drop in visits) that often interrupt more productive workflow and deep work. She encourages using a website for basic tasks such as scheduling and FAQs to provide answers to common questions. The process does meet with client pushback especially for those expecting an immediate response about making an appointment, office hours or prices, wheres my stuff type updates, or to see if the firm is accepting new clients. Nevertheless, the no call office can realize huge benefits for tax practitioners who implement it and, eventually, clients who truly value the practitioners time get used to the boundaries and those who dont find another practitioner.

Annual client interviews and initial client screening are moving online as well. Nayo uses her online client onboarding interview as a screening tool for potential clients. Potential clients who do not take the time to follow her well thought out instructions and process are deemed not a good fit for her practice and left to keep shopping for another provider. Even existing clients who do not make use of written instructions or video tutorials and who insist on calling or e-mailing their tax office for technical support could find themselves looking for a new tax professional. In general, beleaguered taxpros are now much more willing to fire clients who are deemed high maintenance and/or low margin. In other words, too much work for not enough profit.

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Tax practices who depend on high volume may be willing to prepare returns for almost any client but this high-volume business model is disappearing except for certain niche areas. Taxpayers with simple to medium complexity returns often opt for do-it-yourself software rather than paying a preparer. Firms that specialize in medium to high complexity returns often cannot accommodate high client volume during tax season without adding and training additional staff, which often increases overhead in amounts out of proportion to the profit on the additional returns. Rather than add tax season volume, some tax practices are simply adding other services (for example proactive tax planning and business advisory services) that generate revenue throughout the year and using automated proposal and marketing software to attract this new type of business.

In general, cutting edge tax and accounting firms are using automation to streamline office processes, reduce overhead, and optimize the use of human talent. By doing so they can both facilitate growth and provide themselves with some much needed breathing room during and outside of tax season. Jamie OKane, CPA-owner of Abundant Beans Tax & Accounting in Littleton, Colorado says Accountants tend to be helper types that will bend over backwards for their clients in a way that doesnt serve either the client or the professional. Having a virtual practice can compound the problem because of the ability for the practitioner to work anywhere at any time. On the client side the appearance of 24/7 access can create unrealistic expectations about practitioner availability and work turnaround times. On the practitioner side it can erode work-life boundaries to the point where the taxpro never has the downtime necessary to recharge. In addition to burnout, being constantly on can have physical consequences: debilitating headaches, hives, even heart attacks. At this years summit Jamie is teaching virtual taxpros how to streamline their communications to ensure nothing slips through the cracks without spending too much time managing paper and processes. Shes also providing taxpros with the tools necessary to regularly, and sometimes automatically, communicate with clients to reassure them that their documents and questions will be properly handledbut in a way that maintains efficiency for the taxpro.

Tyrone Gregory, The Self Employed Tax Guy from Cerritos, California, is teaching a class called The One Man Band at this years summit. He feels that many solo practices fail because of lack of efficiency on both the practitioner and client side. According to Tyrone, the most common inefficiencies in solo practices stem from issues related to the prompt collection of complete information. There is always something left out and there is always an issue when it comes to trying to get the client in the seat. In other words, practitioners spend too much time trying to force clients to promptly submit necessary information. Tyrones goal is to show both the professional and the clients how all of this could be resolved if they just embrace the technology that we have in front of us.

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Clients who are looking for highly personalized service and who expect a high level of person-to-person interaction throughout the entire return preparation process should be prepared to find a tax professional who provides concierge level service and should expect to pay for it. Good tax professionals are just thatprofessionals. They are passionate about tax and about helping businesses succeed (both their own businesses and their clients). The goal of a good tax professional is to ensure that you pay the correct amount of tax and that you get every possible tax benefit to which you are legally entitled. Moving forward tax professionals will choose to spend their time doing just that and automating the more mundane aspects of running a tax practice: appointment scheduling, answering routine calls, data collection, etc. No one likes change, but clients and practitioners who take the time to adapt and to learn the new tools are likely to realize that the added convenience of well-placed automation makes up for the time spent on the learning curve.

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Not Your Mamas TaxPro - The Evolution Of Professional Tax Return Preparation - Forbes

Abstract

Birds today are the most diverse clade of terrestrial vertebrates, and understanding why extant birds (Aves) alone among dinosaurs survived the Cretaceous-Paleogene mass extinction is crucial to reconstructing the history of life. Hypotheses proposed to explain this pattern demand identification of traits unique to Aves. However, this identification is complicated by a lack of data from non-avian birds. Here, we interrogate survivorship hypotheses using data from a new, nearly complete skull of Late Cretaceous (~70 million years) bird Ichthyornis and reassess shifts in bird body size across the Cretaceous-Paleogene boundary. Ichthyornis exhibited a wulst and segmented palate, previously proposed to have arisen within extant birds. The origin of Aves is marked by larger, reshaped brains indicating selection for relatively large telencephala and eyes but not by uniquely small body size. Sensory system differences, potentially linked to these shifts, may help explain avian survivorship relative to other dinosaurs.

Traits hypothesized to explain differential patterns of dinosaur survivorship of the Cretaceous-Paleogene (K-Pg) mass extinction include aspects of neuroanatomy (1, 2) and feeding ecology (3, 4). Extant birds (Aves) have brains with relative volumes (5) and neuronal densities (6) that surpass all other reptiles (57). These traits may have provided a selective advantage over other dinosaurs in the face of rapidly changing environmental conditions at the K-Pg boundary. Dietary shifts associated with modification of the jaws and palate have also been proposed as drivers of both this survivorship and highly disparate diversification rates in the Early Paleogene (3, 8). Of the two basal-most avian lineages, Neognathae today comprises more than 10,000 extant species, while Palaeognathae is known from fewer than 100. This disparity in diversification has been hypothesized to have been driven by greater beak adaptability imparted by a mobile palate detached from the cranium, a feature historically considered derived for Neognathae (8). However, a paucity of well-preserved skulls from small-bodied outgroups of living birds has limited estimates of ancestral brain and craniofacial characteristics. This lack of data has confounded identification of unique crown traits demanded by hypotheses explaining K-Pg survivorship. Furthermore, body size and other traits proposed to have influenced dinosaur survivorship are known to scale allometrically (e.g., brain size, flight, growth rate, habitat preference, and metabolism) (4, 915). However, investigations of body mass evolution in Aves have rarely included data from the stem, allowing distantly related non-avialan theropods and basally diverging ratites, both large-bodied, to disproportionately influence ancestral avian body mass estimates.

Ichthyornis dispar is a toothed stem bird (Avialae) known from the Late Cretaceous of North America and has traditionally been considered the nearest known well-understood relative of extant birds (16, 17). Thus, Ichthyornis is essential to estimation of ancestral avian traits. Recent studies have cast uncertainty over the phylogenetic affinities of Ichthyornis recovering Late Cretaceous toothed bird Hesperornis as more closely related to extant birds (18, 19). Well-preserved skull material from Ichthyornis is rare, and although recent work has provided valuable insights on its cranial anatomy (18), crucial gaps remain, including the palatal and brain morphology. Early reconstructions of the brains of Ichthyornis and Hesperornis (16) were later shown to be hypothetical illustrations, lacking anatomical basis (20). The brain of Ichthyornis has been proposed based on a previously reported braincase (FHSM 18702) (18) to have a brain shaped like extant birds, including an expanded cerebrum and ventrally shifted optic lobes, although details about the brain shape in this specimen are obscured. Now, our only other published fossil insights into bird brain morphology in the Mesozoic come from the skulls of ~150-million-year (Ma) Archaeopteryx lithographica (1, 21) and Cerebavis cenomanica (2224). Archaeopteryx, the earliest known potentially volant avialan (25), had a brain shape more like non-avialan maniraptoran dinosaurs (e.g., Zanabazar and Incisivosaurus; figs. S1 and S2) than extant birds. By contrast, Cerebavis shows an expanded cerebrum and ventrally shifted optic lobes, although it is known only from an isolated partial skull, and its phylogenetic affinities remain unclear (2224). Better understanding of the Ichthyornis condition can help fill our >70-Ma gap in neuroanatomical data separating Archaeopteryx from extant birds.

We describe a specimen of I. dispar preserving a nearly complete skull (Fig. 1 and figs. S1 to S14) and use x-ray computed tomography (CT) to digitally reconstruct the facial skeleton (Fig. 1) and partial brain endocast (Fig. 2, A and B). We reinvestigate phylogenetic relationships within Avialae using a matrix of 223 morphological characters scored for 43 avian and non-avian birds. We test the effects of stem taxon sampling by first estimating ancestral avian body and relative brain size using a sample of 2003 avians, Archaeopteryx, and seven non-avialan dinosaurs. We then reestimate ancestral body mass with the addition of two sets of stem birds: First, we add data for 26 stem birds with well-understood phylogenetic affinities. Then, to that sample, we add data for 16 additional stem birds with poorly understood phylogenetic affinities but that provide insight into avialan body size immediately preceding the K-Pg mass extinction (see Materials and Methods) (19).

(A) Photograph of skull block including the neurocranium and partial upper and lower jaws. (B) Rendering of the skull block showing the position of the endocast (pink) relative to the cranium and nearby preserved facial elements (translucent white). (C) Photograph of the block including the premaxilla, left maxilla, and left palatine. Digital reconstructions of the facial skeleton in (D) lateral, (E) dorsal (mandible removed), and (F) ventral (mandible removed) views. Preserved elements are colored; symmetrical elements mirrored from the opposite side are in gray. Numbers correspond to novel insights from this specimen: 1, complete orbital process of the quadrate; 2, complete nasomaxillary contact; 3, segmented hemipterygoid. den, dentary; fr, frontals; hpt, hemipterygoid; ju, jugal; la, lacrimal; max, maxilla; mes, mesethmoid; na, nasal; nc, neurocranium; pa, palatine; pd, predentary; pman, posterior mandible; pre, premaxilla; qj, quadratojugal; qu, quadrate; vo?, tentative vomer. Photo credit: Christopher R. Torres, University of Texas at Austin.

(A and B) Reconstruction of the Ichthyornis endocast in (A) right lateral and (B) dorsal views. (C to H) CT slice data showing the endocranial surface in the area of the vallecula (arrowheads) in (C to E) coronal and (F to H) sagittal planes. Yellow, telencephalon; red, optic lobe; blue, cerebellum.

The endocast from the new specimen shows that Ichthyornis lacks the expanded cerebrum and ventrally shifted optic lobes characteristic of extant birds (Figs. 2 and 3). The braincase preserves impressions of the lateral sides of the telencephalon, optic lobes, and cerebellum, but the dorsal-most and ventral surfaces and rostral and caudal ends are lost to mediolateral crushing (Fig. 2, A and B). These data shed new light on the timing of the multiphase acquisition of the extant bird brain shape (Fig. 3). Basally diverging non-maniraptoran theropods (e.g., Tyrannosaurus and Alioramus) retained ancestrally linear brains with unexpanded cerebella and cerebra (26). Non-avialan maniraptoran dinosaurs (e.g., Zanabazar and Incisivosaurus) are marked by relative expansion of both these brain subregions coinciding with ventral deflection of the midbrain (including the optic lobes) and dorsal deflection of the cerebrum (1, 27, 28). Further expansion of the cerebellum occurred near the divergence of Avialae (e.g., Archaeopteryx), resulting in exclusion of the midbrain from the dorsal brain margin by contact between the cerebellum and the cerebrum (1, 21). Last, an episode of relative brain and cerebrum expansion has been shown to have occurred sometime after the divergence of Avialae (21), with optic lobes positioned entirely ventral to the cerebrum. Although the new endocast is incomplete, the position of the optic lobes relative to the mediolaterally widest point of the cerebrum strongly suggests that Ichthyornis had an Archaeopteryx-like brain shape. Thus, the most recent phase of bird brain shape change occurred near the origin of, and is synapomorphic for, extant birds. Unique expansion of the avian visual system may have been a driver of this reshaping. Among extant birds, eye size has been proposed to be correlated with and may constrain deflection of the optic lobes and cerebrum, relative cerebrum size, and relative brain size (29, 30). Despite the crown clade being marked by a derived brain shape, previous studies fail to recover shifts at the divergence of Aves in evolutionary rates of relative volume of either the total brain or individual regions (2, 31). However, these studies necessarily exclude data from stem birds due to a dearth of samples, obscuring any evolutionary shifts that might have occurred along the >70-Ma branch separating the divergences of Avialae and Aves. Better understanding of the sensory systems of non-avian dinosaurs will be crucial for elucidating the potential role of visual expansion as a driver of these shifts.

Ichthyornis exhibits an incipient wulst (Fig. 2), a derived cerebral structure previously thought to be restricted to living birds based on virtual reconstructions of osseous braincase architecture (1). In Aves, the wulst is a dorsal expansion of the cerebrum unique to birds among extant reptiles and that corresponds to a subregion of the cerebrum thought to be homologous to parts of the mammalian neocortex (3234). On the right dorsolateral surface of the Ichthyornis cerebrum, there is a shallow sulcus associated with a change in slope of the endocranial surface. Among extant birds, sulci in the dorsolateral surface of the brain correspond to the vallecular groove, demarcating the lateral margin of the wulst (Fig. 2) (7). A similar feature was tentatively identified in Archaeopteryx but was later shown to be a taphonomic artefact (1, 21). The original scan data of the corresponding preserved skull region in Ichthyornis where the dorsal deflection in slope is marked show no crushing and confirm that the structure observed here is natural (Fig. 2). The wulst is a visual processing center with a proposed role in flight but is more generally involved in somatosensory integration (32, 35). Although the presence of a wulst has been proposed to be the only recognized neuroanatomical correlate for flight among avialans (21, 35), if the wulst arose in response to increasingly efficient integration of sensory input imposed by flight, powered flight should have arisen first. This prediction is consistent with the apparent lack of a wulst in Archaeopteryx, the earliest known dinosaur capable of powered flight (25). However, as mentioned, the wulst is a brain structure with diverse functions not limited to those deployed in flight (32).

Ichthyornis is only the third Mesozoic taxon for which we have direct data on brain shape after Archaeopteryx and Cerebavis, and the new endocast sheds some light on the latter of these birds. The enigmatic 93-million-year-old C. cenomanica is known just from a poorly preserved, disarticulated braincase (2224). The phylogenetic affinities of Cerebavis are uncertain; it exhibited the expanded cerebrum and ventrally shifted optic lobes characteristic of Aves, but lacked the wulst here recovered as characteristic of at least the clade comprising Ichthyornis and Aves (24). If recovered either within Aves or as a closer relative to Aves than Ichthyornis, Cerebavis would represent a secondary loss of a projected wulst visible on the external surface of the brain, although not necessarily the underlying neuronal structures. Alternatively, Cerebavis, like some derived pterosaurs (36), may represent a taxon with an independent gain of an expanded cerebrum and deflected optic lobes.

The new specimen sheds new light on the ancestral avian palate (Fig. 4). In the new specimen, both palatines are preserved as elongate, mediolaterally broad elements with rostral processes projecting mediodorsally from the medial margins and conformed as rostrally oriented hooks (Figs. 1F and 4, A and B, and figs. S11 and S12). This is unlike the condition previously described for Ichthyornis (18) and observed in extant birds (Fig. 4, C to F) but is like other near-crown avialans, the Hesperornithiformes (37, 38). The right hemipterygoid is preserved in life position medial to the right palatine (Figs. 1F and 4A), the first evidence for the presence of this element in Ichthyornis. Shortly after most neognaths hatch, the pterygoid becomes segmented, with the anterior part (hemipterygoid) fusing to the palatine and the posterior part becoming the element recognized as the pterygoid in the adult bird (Fig. 4, C and D) (39). This process of pterygoid segmentation has been proposed as a synapomorphy for Neognathae and to be the prerequisite innovation to all other characteristics of the mobile neognath palate (40). This process is absent in all known palaeognaths, wherein the unsegmented pterygoid overlaps the palatine, and the palate is immobile (Fig. 4, E and F). This condition has historically been inferred as primitive for extant birds (41).

(A to F) Orange, pterygoid; purple, palatine; teal, hemipterygoid.

The presence of a hemipterygoid in Ichthyornis and multiple hesperornithiforms (37, 38) indicates that a segmented pterygoid, and possibly a mobile palate, arose before the divergence of extant birds and is likely ancestral for all of Aves. Zusi and Livezey (42) suggested that the intrapterygoid joint of Hesperornis was analogous to that observed in Neognathae rather than homologous based on the unique shape of the hesperornithine palatine. If so, the presence of such a joint in Ichthyornis would represent a third independent gain among closely related taxa. Instead, the presence in Ichthyornis of hesperornithine-like palatine and pterygoid morphologies in a neognath-like configuration of elements suggests that the intrapterygoid joint, and possibly the mobile palate observed in extant neognaths, was present at least as early as the divergence of Hesperornis. Fusion of the hemipterygoid to the palatine is absent in known near-crown stem birds and is so far unique to extant neognaths, and an unsegmented pterygoid is likely derived within Palaeognathae. This pattern may indicate that Aves was marked by a shift in palatal ontogeny, as the adult Ichthyornis-hesperornithine condition is only observed in juveniles among extant birds (39, 41, 42).

Adaptive plasticity of the beak associated with a mobile palate has been suggested to explain why neognaths, but not palaeognaths, explosively radiated in the Paleogene (8) but cannot alone explain the unique survivorship of Aves out of the Cretaceous. The mobile neognath palate has three components: articulation of the palatine and segmented pterygoid to the exclusion of the vomer; a mobile articulation between the palatine and pterygoid; and articulation between the parasphenoid and either the palatine, pterygoid, or both (42). Only the third of these components remains unknown in Hesperornis and, now, Ichthyornis, suggesting that these and possibly other Late Cretaceous near-crown stem bird had an incipient mobile palate (e.g., Iaceornis). The failure of these lineages, but not palaeognaths, to survive across the K-Pg boundary indicates that a detached palate alone likely did not influence survivorship dynamics.

Our phylogenetic analyses (see also the Supplementary Materials) recover Ichthyornis in its traditional place crown-ward of Hesperornithiformes as sister to a clade comprising Aves and the Late Cretaceous Iaceornis (Fig. 5A and figs. S15 to S20). Our results also shed further light on the phylogenetic affinities of two other Late Cretaceous birds, Vegavis and Asteriornis. Initially proposed to be a stem anatid within waterfowl (Anseriformes), the phylogenetic affinities of the Antarctic Vegavis have been controversial (4345). We recover Vegavis in its traditional place within crown group waterfowl in a polytomy with the Mallard (Anas platyrhynchus) and the Early Paleocene Antarctic bird Conflicto (Fig. 3) (46). The Belgian Asteriornis was initially recovered with affinities to Galloanserae or with Galliformes (47). We instead recover Asteriornis as potentially a stem palaeognath with very limited support (Fig. 3 and fig. S15). This result underscores the need for additional data to confidently resolve its phylogenetic affinities. Our unconstrained phylogenetic analyses including the 16 fragmentary single-element end-Cretaceous stem birds from Longrich et al. (19) resulted in uninformative polytomies (fig. S19) due to missing data, so we constrained their relationships to match those recovered by the original authors (fig. S20) for ancestral state reconstructions including these taxa.

(A) Body mass evolution across the avian stem. Ancestral body masses were estimated including 26 stem birds with well-supported phylogenetic affinities and mapped across the strict consensus tree from our primary phylogenetic analysis. Gray branches indicate taxa that were used to estimate phylogeny but not ancestral body mass reconstructions. Circles correspond to ancestral body masses estimated for major basal divergences within Aves including data from the total stem bird sample (pink), only stem birds with well-supported phylogenetic affinities (dark gray), and no stem birds except Archaeopteryx (light gray) and are to scale. (B) Comparison of body mass estimates of 1Cretaceous birds known from within 300 ka (thousand years) of the K-Pg boundary (19) to our body mass estimates for divergences within the crown clade and taxa from the Late Cretaceous and Early Paleogene, as well as 2model-based ancestral body masses for Aves, Neognathae, and Neoaves estimated previously (11) without inclusion of outgroup taxa. Cretaceous crown birds: 1, Conflicto antarcticus; 2, Asteriornis maastrichtensis; 3, Polarornis gregorii; 4, Vegavis iaai.

Estimates of avian body mass evolution are highly sensitive to outgroup sampling, underscoring the need to interpret the results of these analyses with extreme caution. Our analyses including data from only those stem birds with well-resolved phylogenetic affinities recovered an ancestral avian body mass of 7.7 kg (Wandering Albatrosssized) compared to 10.9 kg (swan-sized) when stem bird outgroups other than Archaeopteryx were excluded (Fig. 5A). This difference was even more pronounced when we expanded outgroup sampling to include poorly understood end-Cretaceous stem birds known from isolated elements. If these stem birds are included, we recover an ancestral body mass of 2.4 kg (eagle-sized). Our results demonstrate the disproportionate effect that mostly large-bodied palaeognaths and non-avialan dinosaurs had on states recovered by previous studies at the crown node in the absence of data from stem birds (2, 31). Total exclusion of any outgroup data results in an opposite phenomenon, with what are likely artificially low underestimates of ancestral avian body mass. Previous investigations relying on model-based approaches in lieu of outgroup sampling resulted in body mass estimates smaller than most Late Cretaceous stem birds (Fig. 5B) (11).

Our analyses failed to recover patterns in bird body mass evolution across the K-Pg boundary consistent with hypotheses that small body masses contributed to the unique survival of extant birds. We recovered an increase in body size from at least the divergence of Hesperornithiformes through the origin of extant birds, followed by continued increase in Palaeognathae and decrease early in Neognathae (Fig. 3A). Avian birds from either side of the K-Pg boundary were generally larger-bodied than end-Cretaceous stem birds (Fig. 5B) (11), albeit without statistically significant difference. Ancestral body masses for most major basal divergences within extant birds (i.e., Aves, Neognathae, Galloanserae, and Neoaves) were estimated to be larger than most end-Cretaceous stem birds regardless of which taxonomic subsample we used (Table 1). Our analysis represents one of the broadest samplings of body mass from stem birds yet published, but our understanding of Mesozoic bird diversity remains highly incomplete, and trends in body mass evolution may significantly change with future discoveries. These recovered trends will be influenced by revision of our understanding of stem bird phylogenetics. Inclusion of highly fragmentary, small-bodied birds from the Latest Cretaceous had a profound influence on estimated ancestral body masses (Fig. 5), but the phylogenetic affinities of these taxa are poorly understood. The relationships of several of these taxa to the crown clade, or even their inclusion within it, are ambiguous, and their treatment is likely to severely bias inferred ancestral trait values.

Ancestral body masses were estimated from three alternative outgroup samples: Total, total sample including stem birds with poorly resolved phylogenetic affinities (19); Sub, taxonomic subsample including only stem birds with well-resolved phylogenetic affinities; AO, Archaeopteryx only.

Estimation of ancestral avian brain size and other allometrically scaling traits that may have influenced end-Cretaceous extinction dynamics is highly sensitive to outgroup body mass sampling (Fig. 6 and Table 1). This effect is especially pronounced at the divergence of crown-group birds, with increased outgroup sampling recovering ancestral avian brain sizes more consistent with extant birds than non-avian dinosaurs (Fig. 6A). The recovered shift in relative brain size from the divergence of Avialae to the divergence of extant birds is increasingly marked based on sampling strategy (Fig. 6B). Thus, it is perhaps expected that recent investigations have failed to detect a significant shift in evolutionary rates of either total or regional brain volume at or near the divergence of extant birds in the absence of data from the avian stem (2, 31). Despite our increased body mass sampling along the avian stem, neuroanatomical data from these taxa remain lacking, suggesting that our estimates of ancestral avian brain size are likely still influenced by taxonomic bias. It is likely that our understanding of ancestral avian brain size will shift markedly with improved sampling.

(A) Brain size versus body size for extant birds (gray) and select non-avian dinosaurs (triangles) and a regression representing the ancestral avian and near-crown scaling relationship from (2). Increasingly dense outgroup body mass sampling (dark and pink) recovers ancestral avian relative brain size more consistent with extant birds than non-avian dinosaurs. (B) The same data depicted in (A) showing that increased outgroup body mass sampling recovers an increasingly marked shift in relative brain size from the divergences of total birds (Avialae) to major extant clades. 1Data for extant birds and non-avian dinosaurs and regression from (2).

Ancestral maniraptoran brain shape was retained by birds until at least the divergence of Ichthyornis (Fig. 2). Aves was marked by a major neuroanatomical reshaping relative to known outgroups, including inflation of the telencephalon and ventral deflection of the optic lobes (fig. S21). Our identification of this condition as synapomorphic for extant birds implicates it as a trait so far unique to the Paleogene survivors. Aves may also have been marked by a major increase in relative brain size (Fig. 6), but our understanding of brain size evolution remains highly sensitive to outgroup sampling. Small body size characterizes many volant birds from lineages that are not known past the latest Cretaceous (e.g., Enantiornithes and non-crown Ornithurae). Living bird lineages present before this event are estimated to have been larger than most contemporary stem birds (Fig. 5), inconsistent with previous hypotheses that relatively small body sizes provided the ancestors of extant birds a selective advantage in the face of the K-Pg mass extinction (11, 19). However, our analyses underscore the extreme sensitivity of ancestral body mass reconstructions to stem taxon sampling, casting uncertainty on the fidelity of these estimates both here and in all other studies to the true ancestral avian condition. We estimate the wulst and a segmented and possibly mobile palate arose before Aves (fig. S21), despite previously being considered features of that clade or derived within. The segmented palate may have arisen as a consequence of general reshaping of the skull associated with expansion of the brain that has been proposed to be linked to elaboration of the visual system (48). A combination of changes in craniofacial ontogeny, brain size, and shape is recovered as characterizing crown birds and may signal as yet poorly understood shifts in ecology that are linked to dinosaur survivorship.

Cranial material of the new Ichthyornis specimen (AMNH FARB 32773; fig. S1) was scanned at the University of Texas (UT) High-Resolution X-ray CT Facility in Austin, Texas, on an NSI scanner with a Fein Focus High Power source. The block containing the neurocranium was scanned on 25 February 2019 with the following settings: x-ray beam power of 150 kV/0.19 mA, pixel dimensions of 1869 989, 3665 total slices, and voxel size of 17.9 m. The blocks containing the premaxilla, left maxilla, and left palatine were scanned simultaneously on 11 February 2020 with the following settings: x-ray beam power of 160 kV/0.16 mA, pixel dimensions of 714 714, 1894 total slices, and voxel size of 30.8 m. Scan data are freely available on MorphoSource (media ID 000367065 and 000367056). CT scan data of Asteriornis were taken from Field et al. (47). We segmented the data using Avizo 2019.1 (Thermo Fisher Scientific) following the best practices proposed by Balanoff et al. (49), manipulated models in three-dimensional (3D) space using Netfabb 2019 (Autodesk), and rendered models using Avizo 2019.1 and Blender 2.91.0 (www.blender.org). Our retro-deformed reconstruction of the new skull is provided as STL files on MorphoSource (media ID 000367046).

To reinvestigate the relationship of Ichthyornis to other avialans, we modified the morphological character matrix first constructed by Clarke and Norell (50) and subsequently modified by Clarke et al. (51), Li et al. (52), Huang et al. (53), and, most recently, Field et al. (18). We added scorings to this matrix for proposed Late Cretaceous stem galloanserine Asteriornis maastrichtensis from Field et al. (47) and our digital reconstruction of its skull (fig. S22), Early Paleocene stem anseriform Conflicto antarcticus from Tambussi et al. (46), and proposed Late Cretaceous stem anatid Vegavis iaai from Clarke et al. (43). We made the following scoring changes for Ichthyornis: 8:1, 12:1, 43:1, and 222:1. We rescored character 221 for all birds lacking teeth from 1 (absent) to ? (unknown/noncomparable); the character describes the presence or absence of dental socketing along the region of the maxilla and dentary occupied by embryonic dental lamina, the presence of which we could not confirm in embryos of extant birds. We also removed two characters from the matrix. We considered original character 210, describing the anteroposterior location of the apex of the sternal carina, to be non-independent with character 72, describing the anterior extent of the carina proper. Original character 221, describing the relative contribution of the premaxilla to the margin of the jaw, was a duplicate of character 8. Last, to include the end-Cretaceous stem birds scored by Longrich et al. (19), we added 11 characters from their matrix, which was also a modification of the Clarke and Norell (50) matrix. Our final character matrix is provided in data file S1.

We analyzed the resulting character matrix in TNT 1.5 using an unconstrained traditional heuristic search with Wagner starting trees and all characters equally weighted. We performed 1000 replicates of random stepwise addition using the tree bisection and reconnection algorithm, with 10 trees saved per replication and branches with minimum lengths of 0 collapsed into polytomies. We used the resulting most parsimonious trees (MPTs) to calculate a strict consensus tree. That consensus tree was used in standard (sample with replacement) bootstrap analyses using a traditional search replicated 1000 times with results reported as absolute frequencies. To test the sensitivity of our results to taxonomic sampling, we analyzed our matrix using the following schema: Our primary unconstrained analysis included 9 avian birds, 32 stem birds plus Archaeopteryx, and Dromaeosauridae as outgroup (henceforth referred to as our core taxonomic sample). We then analyzed our core taxonomic sample plus Gansus yumenensis to test the sensitivity of our results to the latter taxons inclusion. To test the sensitivity of our results to constraints on the position of Asteriornis, we reanalyzed our core taxonomic sample with Asteriornis constrained to within Galloanserae and then constrained as a stem galloanserine. Last , we analyzed our taxonomic sample plus the 16 end-Cretaceous stem birds from Longrich et al. (19), both without constraints and constrained to match the relationships recovered by those authors.

To investigate the impact of data from the avian stem on estimates of ancestral avian body mass, we time-calibrated the strict consensus trees we recovered from both the analysis of our core taxonomic sample and the constrained analysis of our core taxonomic sample plus the 16 additional stem birds from Longrich et al. (19). First, we added seven non-avialan dinosaurs included in the analyses of Ksepka et al. (2) to our tree following the topology used by those authors. Then, for each extinct taxon in the tree, we obtained first and last appearance data from the literature, corresponding to the lower bound and upper bound of the formation(s) from which the taxon is known. Appearance data are provided in data file S2. We then used these data to calibrate the tree in R using the DatePhylo() function in the strap R package (54), with root length = 0.1 and using the equal method. Then, we extracted the clade comprising Aves from the Ksepka et al. (2) tree, scaled it to match the depth of that clade in our tree, and grafted it onto our time-calibrated tree. Last, we pruned the total tree to match those taxa for which we had either species body mass averages (extant species) or body mass estimates (extant plus extinct species).

Body masses for 26 stem birds were estimated using the correlation with femoral length estimated by Field et al. (55). The femoral lengths we used and their references, as well as estimated body masses, are provided in data file S3. Average species body mass for avians and all brain volume estimates were taken from Ksepka et al. (2). Our total body mass and brain volume dataset is provided in data file S4.

Ancestral body mass and brain volume were estimated separately in R using the fastAnc() function in the phytools R package (56). To investigate the impact of data from the avian stem on reconstructed ancestral body masses, we used three subsets in our taxonomic sample. The primary subset used 2002 avians, 27 non-avian avialans, and 7 non-avialan dinosaurs. The tree pruned to match this sample, as well as the reconstructed ancestral body masses, variances, and 95% confidence intervals are provided in data files S5 to S8. The second expanded taxonomic sample included the primary subset plus the 16 stem birds from Longrich et al. (19). The tree pruned to match this sample, as well as the reconstructed ancestral body masses, variances, and 95% confidence intervals are provided in data files S9 to S12. The final subset included only those taxa for which brain volumetric data were available (i.e., 2002 avians, Archaeopteryx, and seven non-avialan dinosaurs). The tree pruned to match this sample, as well as the reconstructed ancestral body masses, variances, and 95% confidence intervals are provided in data files S13 to S16. Ancestral brain volume reconstruction used the latter sample and tree. Reconstructed ancestral brain volumes, variances, and 95% confidence intervals are provided in data files S17 to S19. Ancestral relative brain size (i.e., encephalization) could not be directly reconstructed for any non-avian avialan except Archaeopteryx due to a lack of brain volume data from 25 stem birds added here. Instead, we calculated the ratio of brain volume to body mass for selected nodes using the corresponding values estimated from each of the above ancestral state reconstructions.

When Gansus was excluded, our analysis yielded six MPTs with 605 steps. These trees plus the strict consensus tree (fig. S16) are provided in data file S20. We recovered Ichthyornis in its traditional position next to a clade comprising Iaceornis plus Aves with weak bootstrap support (26), supported by six synapomorphies: completely fused premaxillae (1:2), presence of ossified connective tissue bridging transverse processes of thoracic vertebrae (59:1), presence of three sacral vertebrae that are short with dorsally directed parapophyses just anterior to the acetabulum (62:1), presence of pneumatic foramen/foramina on the dorsal surface of the sternum (73:1), flat to convex area of the foramen n. supracoracoideus on the medial surface of the coracoid (98:1), and presence of a facet for articulation with the furcula on the acrocoracoid of the coracoid (227:1).

We recovered Iaceornis next to Aves to the exclusion of Ichthyornis with moderate bootstrap support (55) based on four synapomorphies: presence of paired, raised intermuscular ridges on the sternum (77:1); the tip of the extensor process of metacarpal I conspicuously surpasses articular facet by approximately the width of the facet, producing a pronounced knob (143:4); metacarpal III extends farther distally than metacarpal II (148:1); and conformation of the extensor canal on the tibia/tarsal formed condyles as a groove bridged by an ossified supratendinal bridge (182:2).

We recovered the Late Cretaceous V. iaai and the Early Paleocene C. antarcticus, both from the Antarctic Peninsula, in a polytomy with the Mallard with low bootstrap support (24) based on three synapomorphies: presence of pneumatization on the coracoid (91:0); metacarpal II is subequal to or surpasses metacarpal III in distal extent (149:0); and presence of a hypertrophied, shelf-like posterior trochanter on the femur (172:0). Vegavis was originally described as a stem anatid (43), but subsequent analyses variously recovered it as a stem anseriform (57), stem galloanserine (45), or stem avian (47, 58). Our results are consistent with the original placement as a stem anatid, but our low bootstrap support highlights the need for more data to confidently place Vegavis.

The Late Cretaceous A. maastrichtensis was originally described and recovered as a stem galloanserine (47). By contrast, our unconstrained analyses recovered Asteriornis as a stem Palaeognathae with low bootstrap support (12) based on one synapomorphy: a strongly posteriorly forked dentary with the dorsal and ventral rami approximately equal in posterior extent (42:1). Constraining Asteriornis to a clade also including the other galloanserines in our sample resulted in 24 MPTs with 606 steps (one more than when unconstrained; fig. S17), provided in data file S21. This analysis resulted in a weakly supported (bootstrap = 38) polytomy comprising Asteriornis, Conflicto, Vegavis, Chauna torquata, Anas, and Galliformes (Pauxi pauxi + Gallus gallus). Constraining Asteriornis to the stem of Galloanserae resulted in six MPTs with 606 steps (one more than when unconstrained; fig. S18), provided in data file S22. This analysis resulted in a moderately supported (bootstrap = 52) polytomy including Asteriornis, Palaeognathae, Galliformes, and Anseriformes. Together, these results indicate a need for more data before Asteriornis can confidently be placed within Aves.

When our analysis included Gansus, we recovered 14 MPTs with 616 steps (fig. S19). These trees are provided in data file S23. We recovered Ichthyornis in a polytomy also including Hesperornithiformes, Iaceornis, Asteriornis, Palaeognathae, Neognathae, and several other near-crown stem taxa with low bootstrap support (8).

When we included the 17 end-Cretaceous stem birds from Longrich et al. (19) and excluded Gansus in an unconstrained analysis, we recovered 4710 MPTs with 610 steps (fig. S20); MPTs and strict consensus are provided in data file S24. We recovered Ichthyornis in a polytomy also including Galliformes, Hesperornithiformes, and several other crown and near-crown taxa with very low bootstrap support (5). Because this unconstrained analysis failed to recover the relationships recovered by Longrich et al. (19), we reanalyzed this matrix constrained to match those relationships, and we recovered 7030 MPTs with 610 steps (fig. S21); MPTs and strict consensus tree are provided in data file S25.

S. Walsh, A. Milner, in Living Dinosaurs: The Evolutionary History of Modern Birds, G. Dyke, G. Kaiser, Eds. (John Wiley & Sons, 2011), pp. 282305.

A. Chinsamy, in Mesozoic Birds: Above the Heads of Dinosaurs, L. Chiappe, L. Witmer, Eds. (University of California Press, 2002), pp. 421431.

K. Padian, J. Horner, in The Dinosauria, D. Weishampel, P. Dodson, H. Osmolska, Eds. (University of California Press, ed. 2, 2004), pp. 660671.

O. Marsh, Odontornithes: A Monograph on the Extinct Toothed Birds of North America (United States Geological Exploration of the 40th Parallel, U.S. Government Printing Office, 1880).

Acknowledgments: We thank C. Bonner and B. Shelton for long-standing efforts collecting in the Chalk, which made this research possible. We thank M. Ecklund for exquisite preparatory work. For specimen access, we thank C. Mehling (AMNH) as well as K. Bader and C. Sagebiel [University of Texas at Austin (UT)]. For CT scanning, we thank M. Colbert and J. Maisano (UT). For additional images, we thank C. Marrill (AMNH). For comments and discussion, we thank H. Bilger, D. Cannatella, M. Chiappone N. Crouch, S. Davis, D. Hillis, L. Legendre, J. Muhammad, G. Musser, J. Nelson, C. Rodriguez, C. Urban, and H. Zakon (UT); S. Edwards (Harvard University); and P. OConnor (Ohio University). For helpful comments on improving our manuscript, we thank three anonymous reviewers. Funding: This work was funded by Howard Hughes Medical Institute Science Education Program GT10473 (JAC), UT Graduate School Continuing Fellowship (CRT), American Museum of Natural History, and Jackson School of Geosciences, University of Texas at Austin. Author contributions: Conceptualization: M.A.N. and J.A.C.; methodology: C.R.T. and J.A.C.; investigation: C.R.T.; visualization: C.R.T.; supervision: J.A.C.; writing (original draft): C.R.T.; writing (review and editing): C.R.T., M.A.N., and J.A.C. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data are freely available in the Supplementary Materials and on MorphoSource (media ID: 000367046, 000367056, and 000367065).

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Bird neurocranial and body mass evolution across the end-Cretaceous mass extinction: The avian brain shape left other dinosaurs behind - Science...

The state of Americans retirement savings is dire one in four Americans have no retirement savings at all and even those who are saving arent saving enough.

Financial education is more important than ever, and more school districts across the country are beginning to add financial literacy courses to their curriculums. But these courses are not catching on as quickly as they should be. According to the U.S. Financial Literacy and Education Commission, only one-third of adults could answer at least four of five financial literacy questions about mortgages, interest rates, inflation, and risk. Why is it still so hard for people to think long-term about money?

Biologically speaking, humans arent wired to think decades into the future about our needs.

For the vast majority of our history we lived in hunter-gatherer societies, where resources were plentiful and all you could take with you is what you could carry, so were not really hardwired to collect more than we need for the next day or week. The concept of delaying gratification and saving for the long, distant future is just not something we are wired to do. Brad Klontz, financial psychologist, author

Leveraging the power of artificial intelligence (AI) and digital tools, we can start to change that mindset. In fact, its already happening and has the potential to save the financial health of a country.

AI technology is poised to completely overhaul our finances, giving smart banking apps the ability to automate our budgeting, saving and investing. Machines can think deeper and differently than us, but it requires trust to work. Taking that first dive into a pool was scary. Your first bicycle ride was scary. Fear of the unknown is extremely common, but once we face our fears and realize that AI can help free us from financial anxiety, we can all relax a bit.

Every American deserves the right to put their finances on autopilot. While this ideology might seem odd to ordinary people, the top 1% have no problem handing their money over to expensive financial advisers: here, you figure it out. Meanwhile, they sit back and enjoy lofty returns. Now we have so many great apps and financial tools at our disposal that anyone, from retail workers to artists to digital nomads, can have the luxury of an automated financial life, where bills, saving and investing is handled for them.

How can AI fix our brains and make us financially fit?

Remember when your mom kept reminding you to do your chores until you did them? This same principle works with digital nudging, which was used to help people save for their retirement. Whats a nudge? In the mid-1990s, Schlomo Benartzi and Nobel laureate Richard Thaler developed a program called Save More Tomorrow that sent informative emails to help people make smart decisions for retirement. Through the power of these nudges, Benartzi and Thaler were able to get employees to gradually increase their savings rate over time. As of 2017, it has positively affected over 15 million Americans.

Another example is from the Obama administration. More than 800,000 military service members were offered the chance to enroll in a savings program, as a part of an experiment. One group received emails with smart steps they could take toward saving. These included examples of how small contributions could lead to large balances in their accounts. The test group got no guidance or digital nudges. The group with the email nudges had the highest enrollment rate. Through the power of AI technology and machine learning, we can provide even better, more personalized and insightful nudges to millions more Americans, who can then make more prudent decisions around saving for retirement.

Artificial intelligence nudges may look different for different people, and can be as simple as a reminder to save an extra few hundred dollars if spending is low. They can also be suggestions to put money saved into a conservative brokerage account and watch your money grow. When people are shown how compound interest works 5, 10, and even 20 years down the line for instance, theyre more likely to take action and start saving. We just need that little nudge to do it. And with smart banking apps, you dont have to do anything once you set the goals and agree to start saving. The app does that for you automatically, and even calculates how much to allocate and for how long, which eliminates headaches and stress.

While our brains might not be wired to think long term about savings, were certainly smart enough to learn and change as human beings. Financial literacy does not have to just be something we learn formally in schools. It can be learned by doing, and using technology tools that can accelerate the process so we can all live financially healthier lives.

Andy Taylor is chief executive of Douugh, a fintech startup that helps people manage and grow their money autonomously.

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Why is it so hard to save for retirement? Is evolution to blame? - MarketWatch

WRLD1 enlarges its Health /Wellness Networks Group to 9 networks across the sectors of Male/Female Aging, Female Health, Brain Health, Sleep Health, Cancer Global Health News

SAN FRANCISCO, Aug. 1 2021 /PRNewswire/ -- Nathan Sassover, CEO of WRLD1 /TVNET today announced further development and increased strategic presence with the creation of additional Wellness and Longevity news targeting the surging sectors at home Wellness and Disease Prevention.

(PRNewsfoto/TVNET Inc)

Powered by the TVNET APTVE mobile netcast architecture and user interface driving an enlarged platform of therapeutic and preventive health options and general well being and wellness oriented lifestyles video programming.

Sassover further noted: "Our Health/Wellness hubs now provide increased range of topics and content diversity coupled with the fusion of legacy 'standard of care' modalities in transition to enlarging Health/Wellness awareness further impacted by the ongoing challenges of the COVID19 global pandemic as presented by the 9 networks on air:

HealthMedica.com. | Health & Wellness Network

NeuroMedica.com | Brain Health Network

MaleAging.com | Male Health Network

FemaleAging.com | Womens Health Network

GynoMD.com | Womens Health Guide

WorldCancerInstitute.com | Global Cancer Network

E0NS.com | Longevity Network

NiteSleep.com | Sleep Health Network

COVID19TV.com | COVID Global Network

WRLD1: Health in the Future: Redefining Health at Home-Enlarging the Scope of Wellness

Embracing Telemedicine, At Home Fitness, Digital Therapies

Health has emerged as a key focus for consumers readjusting to their 'new normal,' and experts say consumers' approach to fitness and overall wellness may be permanently altered. Mirror

The COVID-19 pandemic has shaken up nearly every consumer category, influencing new consumer behaviors, stifling entire industries and inspiring growth in others, including pockets of the health sector.

The health and wellness industry, already a booming $4.5 trillion business, has seen particularly marked change as housebound consumers adapt to life without gyms, fitness studios or easily accessible doctors' offices, and reconsider overall what it means to be well in the age of a pandemic.

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These new behaviors rely on the power of the internet to maintain human connection and interaction. As consumers comply with social distancing recommendations, the home has become the central stage for everything from eating and socializing to working and working out.

To keep non-COVID-19 patients out of hospitals and doctors' offices, for one, doctor visits have moved online. Indeed, telemedicine and home fitness have been two of the obvious beneficiaries of these shifts, with companies from Doctor on Demand to Peloton, respectively, well-positioned amid the crisis.

Meanwhile, companies running once high-touch operations have found creative ways to bring business online and into customers' homes.

Health has emerged as a key focus for consumers readjusting to their "new normal." And after months of social distancing, consumers' approach to fitness and overall wellness may be permanently altered, experts said.

While "billions will be lost in the wellness industry in 2020 because of months of shuttered brick-and-mortar businesses," said Beth McGroarty, vice president of research for the Global Wellness Institute, "at the big-picture, long-term level, the case for the wellness concept and wellness markets post-pandemic looks very bullish."

Pre-pandemic wellness and the rise of preventative healthcare disruptors

Pre-pandemic, wellness was already emerging as the biggest consumer spending opportunity in decades, Wendy Liebmann, CEO of WSL Strategic Retail stated: "We've been seeing this growth since 2014 [in] what we call the move from 'sick care' to 'well care.'" According to WSL's 2019 How America Shops study, 73% of the U.S. population said it was engaged in some aspect of living well, from healthier eating and meditation to stress reduction and fitness.

"Even before the pandemic, many people around the U.S. were beginning to dabble in proactive and preventative health and wellness practices," Liebmann said. "What this pandemic has revealed is that taking care and control of your own health individual, family, home, etc. is even more critical than before."

Enabled by the internet, startups like 98point6, Plushcare, Maven and the like sprung up to deliver a more convenient and accessible means of seeing a primary care provider. According to Liebmann, this taking control over one's own health, combined with flagging consumer trust in many industries, gives self-service options like digital healthcare and at-home self-testing "every reason to grow," and the data so far confirms her prediction.

According to a recent McKinsey survey, consumer adoption of telehealth soared from 11% in 2019 to 46% in 2020, largely due to the COVID-19 epidemic. McKinsey also estimates that virtual healthcare has the opportunity to represent up to $250 billion in healthcare spending.

The continuing rise of preventative care has the effect of making 'well-care' more accessible to all. "Going forward, opportunities will continue to emerge around telehealth, putting people in increased control of their own well-being," she stated. "More services will become democratized through digitized and affordable models."

As people work from home in unprecedented numbers, more consumers will incorporate new practices for both self-care and cleaning into their personal spaces. To that end categories of 'functional wellness' will be added to homes, reflecting consumers' interest in protection from electromagnetic pollution like cell phones to circadian lighting that mirrors the natural sleep/wake cycles of the human body.

"Home has turned into a sanctuary," said Shin. "It's also turned into a wellness hub, where people build their self-care routines and find simple joy in their everyday lives."

What this pandemic has revealed is that taking care and control of your own health individual, family, home, etc. is far more critical than before.

The parallel events driving the Remote-work boom drives home-fitness boom

Reflecting the presence of ongoing health challenges driven by a perennial pandemic environment, consumers continue to telework, home fitness has become an especially notable business opportunity, with online sales of home gym equipment skyrocketing as the virus spread and consumers sheltered in place, surging 66% from the same period in 2019.

Yoga retailer Lululemon's recent $500 million acquisition of home workout smart mirror company, Mirror, signals that wellness' major players are getting into the game as well.

Meanwhile, more traditional brick-and-mortar fitness companies such as Crunch and Barry's now offer a wide variety of classes via Instagram Live, said Shin, noting social media's ability to help blur the line between physical and digital activity. In addition, boutique fitness chains Equinox and SoulCycle are moving members online with dedicated home bikes and virtual classes.

The question then becomes: Is this growth of digital fitness platforms sustainable, or will consumers return to the gym as soon as they're able? "The post-virus wellness future will be a 'hybrid' approach for many more people," McGroarty predicts, with consumers making selective trips to gyms, fitness studios or businesses they trust, but otherwise keeping much of their activity online.

Prior to COVID-19, digital/in-home fitness platforms like Peloton and Mirror were already gaining market and under the pandemic, this trend has accelerated putting them in a stronger position post-crisis.

As wellness becomes increasingly homebound, it's also become more accessible to more people, and expanded consumers' ideas of 'wellness' to include mental health, community and preventative lifestyle changes.

"Before the virus, the wellness industry was rightly accused of a too-myopic focus on the wealthy," McGroarty said. "In the future, I believe more people will reject super-elitist, absurdly expensive wellness experiences and products. Wellness in general will become more important in people's lives and command a bigger share of wallet, even if the wallet has shrunk."

WGSN's Shin believes this democratizing effect will only grow as consumers reprioritize the needs of their own families and communities. "Since the coronavirus outbreak, people are increasingly shifting focus from 'me' to 'we,' looking at ways to tackle their anxiety with acts of kindness and compassion," she said. "As a result, the wellness industry is now looking beyond how the individual feels and towards how they exist in a society."

McGroarty predicts that wellness culture will grow to include more everyday, rather than aspirational, activities, such as walking outside or meditating, often with the aid of tools like meditation app Calm, or therapy apps like TalkSpace or BetterHelp. "Mental wellness and meditation app companies are going to be in a much better position financially post-pandemic," she said, "and will invest in bold new directions and platforms."

According to a recent McKinsey survey, consumer adoption of telehealth soared from 11% in 2019 to 46% in 2020, largely due to the COVID-19 epidemic. PlushCare

What the future holds for wellness

Companies in sectors like telehealth and home fitness have made invaluable gains in mindshare throughout the pandemic, shaping the future of consumer behavior and the wellness sector.

"Most of the behaviors that we see remaining will be those that were already ingrained or beginning to be pre-COVID," Liebmann said. For example, the redefining of a healthy lifestyle to include financial, emotional and intellectual wellness will continue, and it will inform behaviors related to sustainability and the environment as well, she said.

Driven less by celebrity trends and influencers, post-pandemic wellness culture will likely center around self-examination and -improvement, and digitally enabled well-being, said Shin. "The democratization of wellness will also come to the fore, with more people seeking brands that make health and fitness more accessible, especially for marginalized communities."

However, as virtual health and fitness becomes the "new normal," the same competition that powered growth of the wellness industry will shape the options consumers face.

"The digital fitness and wellness space will get even more crowded during and after COVID," McGroarty said. "Affordable options will really matter. And the virus has shown the power of how even one yoga teacher can create audiences of millions using Zoom at home.

The WRLD1 Health / Wellness Networks group in addition to all other TVNET categories of geocentric and key industry vertical networks will continue to be resources for AI development that permit more targeted insights and diversity of video programming driving decisions in personal and family health choices leading to improved overall well being.

Sassover noted: "Our challenges with this group of Networks are balance and engaging range of content within our video display innovations to optimize video viewing within the content 'window' to each Health /Wellness news hub and beyond which link to other WRLD1 destinations on the platform."

Contact:

Lauren Holt

News@WRLD1.com

(PRNewsfoto/TVNET Inc)

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WRLD1 / TVNET : Evolution of the Wellness Culture in the Age of Global Health Challenges - Yahoo Finance

INDUSTRY INSIGHT

As recently as five years ago using artificial intelligence and machine learning to develop predictive algorithms was prohibitively expensive. Government agencies needed to provision large clusters of servers, implement Hadoop and data lakes and employ hundreds of data scientists. But now access to AI and ML has been democratized due to furious competition among the three largest cloud service providers: Microsoft Azure, Amazon Web Services and Google Cloud Platform.

The offerings from all three cloud giants have followed a similar pattern. First, the three CSPs all developed AI/ML application programming interfaces, which customers could connect to and offer services like voice transcription, translation and video recognition. An agency did not have to invest in the development of the algorithm, the cloud giants provided it. This allowed agencies to dip their toes into AI/ML projects and invest in the ones that showed the most promise in supporting the mission.

Just in the past two years, the big CSPs introduced cloud-native, automated machine learning. With Auto-ML, there is no pre-existing algorithm. Agencies create their own by bringing data pertaining to a mission challenge and then the CSPs processes develop and validate the solution algorithm. Auto-ML puts the resources of the largest technology companies at the disposal of their customers, allowing hypotheses to be validated and service solutions designed much faster than in the past.

Every agency can benefit from Auto-ML. Any paper-based process can be digitized and the data used for greater efficiency. Recommendation engines can be built to make the workflow of any agency move faster and reduce errors. Brand new applications can be developed by agency IT teams, and/or intelligence can be embedded into existing government applications.

Its become so much easier for agencies to validate a hypothesis using an existing algorithm from a CSP, much in the same way a private company would launch a minimally viable product, or MVP. Then as the business case is proved, agencies can graduate to a variety of cloud-native AI/ML services that allow for additional tuning of the algorithm. Cloud-native AI/ML is the driver for data-based decision-making for better government services and outcomes.

Ive seen what the easy accessibility of AI/ML can do firsthand. When I served at the Transportation Security Administration, we were tasked with improving the credentialing process for enhanced access to critical areas. Using AI/ML we developed algorithms for assessing the severity of the applicants criminal backgrounds. The workload on human reviewers was reduced by 60%, and the algorithm forwarded the hardest decisions -- red cases -- to the most senior adjudicators.

At U.S. Citizen and Immigration Services, paper-based applications were an untapped source for electronic records processing. We digitized these records and used computer vision AI to detect document types, followed by document-specific natural language processing algorithms to automate the creation of digital information from the paper based applications. This digital information enabled electronic processing and workflows that greatly speeded the processing of applications. USCIS was also able to improve application scheduling efficiency by building AI into its interview scheduling process using historic no-show statistics.

The Navy spends billions annually to fight rust and corrosion on its ships. With a corrosion detection and analysis solution built with Google Clouds AI/ML platform and its native computer-vision capabilities, the Navy and its vendor partner successfully used drones to identify corrosion of interest from aerial images of vessels, with confidence scores of more than 90% with very few false positives. This complex integration between emerging software and hardware technologies was only possible due to the recent evolution and accessibility of AI/ML cloud services.

In the span of just a few years AI/ML has gone from fanciful science fiction to a solution only for the largest organizations, and finally to an easily accessible and economical tool for solving complex service delivery challenges. The pace of technological change and market competition between the big CSPs provide government IT leaders with a golden opportunity to improve their workflows.

Never before has such computational power been so available. Cloud-native AI/ML is creating a pathway for agencies to totally transform their service delivery.

About the Author

Aaron Kilinski is principal and chief technologist at Simple Technology Solutions (STS).

See the rest here:

What the evolution of AI/ML means for government IT - GCN.com

Cavan Images/Getty Images

Cavan Images/Getty Images

Think sweat is gross?

"It could have been so much worse," says Sarah Everts, the author of a new book called The Joy of Sweat, that is all about, you guessed it, the science of sweating.

Turns out human sweat our body's air conditioning system is really pretty tame on the "yuck" scale of animal cooling methods.

Dogs drool to stay cool, while vultures will poop on their legs and seals urinate on their feet, she says. When you think about what evolution could have bequeathed us, Everts says, "sweat is arguably a million times better."

In fact, Everts tells NPR's Short Wave, instead of thinking of sweat as gross, think of it as an "evolutionary marvel." She even calls it a human superpower and a highly efficient one at that. "We effectively dispatch water to our skin and, as it evaporates, it whisks heat away from our bodies," she says.

Everts points out in her book that this superpower enables humans to thrive and dominate across the globe. "Sweating allowed us to forage out in the sun without overheating, while our predators were relegated to the shade for survival," she writes, and for us to adapt to many new environments. "Like the (city) pigeon and desert dove, we're capable of surviving almost anywhere."

Short Wave's Rhitu Chatterjee talked to Everts about the incredible science of sweat, which includes facts most people don't know. Like get this: How much you sweat is affected by both nature and nurture. And did you know you can sweat in different colors? Yep, both are true.

Check out Everts' fascinating interview below. Don't have time to read it? No sweat! You can listen to it by clicking on the audio link above.

This interview has been edited for clarity and length:

In your book, you write that to sweat is human. How much someone sweats is sort of a mix of their genetics and also where they've grown up, right?

It's kind of interesting because these glands they're called eccrine glands you're born with all the eccrine glands that you'll ever have. But these glands don't become fully active until you are in your toddler years. And so in those very early years of your life, your body is kind of learning about the climate that you're in. And researchers are trying to figure out how much of the environment in which you spent your early years is ultimately going to affect how much you sweat as an adult.

That's the nurture part. But there's also a nature part. Some people and some families are just sweatier than others. And, perhaps you have more sweat glands than average. Most people have between 2 [million] and 5 million.

I got mine counted. I have 3 million! And there's also the flow rate, right. So some people are very efficient with their sweating and some, the floodgates just open right up. And so that's also possibly related to genetics but also possibly related to acclimatization and your body learning on the go.

I mean, athletes do this right. In preparing for the Olympics in a really hot place, they will try to train in very similar conditions so that their bodies learn to cool down efficiently in that kind of environment.

You write in the book that sweat contains so much more than water.

Oh, yeah! So this was the thing that really blew my mind. When you think about sweat, it took me a long time until I was writing this book to be like: Where is it really coming from? It's effectively the liquidy parts of blood, minus the big stuff like red blood cells and platelets and immune cells.

And so if you open up a body, you're very wet inside. Right. You have this thing called interstitial fluid that's keeping all your organs damp and moist. And that liquid is sourced from blood. And when your body gets the cool-down directive, then your sweat glands source sweat from that interstitial fluid. So literally anything that's in your blood that's small can percolate out.

So, evidence of my morning coffee comes out in my sweat. When I have a drink of gin and tonic on a hot day definitely the alcohol comes out. Evidence of the food we eat, evidence of our health or even how we're exercising.

There's a story that you write about in the book: the South African nurse whose sweat turned red.

Oh, to be this woman. She was a nurse and wore a white uniform and noticed that her sweat was red. And this is a very strange situation, right?

She was really insecure about it and went to a dermatologist. But they could not for the longest time figure out what was going on because she was in her 20s; she was perfectly healthy. They checked her for everything.

One day she comes to the clinic for a follow-up appointment, and one of the doctors notices her fingers are kind of stained like a reddish brown color. It turns out she had had a pre-appointment snack, and it was this corn chip called Spicy Tomato. She was very fond of these chips. She was eating multiple bags a day so very fond. The dermatologist called it a fetish.

They analyzed her sweat for the same colorants and dyes as the chips and got a match. And so effectively, once she dialed down her predilection for these particular chips, her red sweat disappeared. But other people have turned their sweat all sorts of colors for all sorts of reasons. It's a funny little corner of the medical literature called chromhidrosis: chrome, light colored and hidrosis for sweat.

What about the other components that sort of leak out into sweat? Do they have any role? And what makes sweat stinky?

What's coming out of your sweat pores the entire medical role for it, is to keep you cool. But in the process, your body also dispatches some proteins that do crowd control for the microbiome of your skin. Right. So helping the helpful bacteria thrive and trying to keep pathogens at bay. But most of the stuff that comes out in this watery sweat called eccrine sweat is just what happens to be flowing around your body.

Of course, there is another kind of sweat: The stuff that makes you really stinky. That's the sweat that comes out in your armpits. It's actually an entirely different kind of sweat gland. It's called the apocrine gland, and it gets active at puberty as many of us know.

And that one is not like salt water at all. It's kind of like waxy, a little bit similar to earwax, but a lot more minute, and the bacteria living in your armpits eat that sweat and metabolize it and effectively poop out what is the body odor that comes from your armpit.

So body odor changes, depending on the content of your sweat and the mix of bacteria that are metabolizing the sweat?

Exactly. And so we all have a unique body odor print, right? We all have our own smell. And that is effectively the mix of waxy molecules coming out of those apocrine glands, plus the unique-to-you ecosystem of bacteria living in your armpit. And so that combination is what gives you your unique odor print and mine. And allows dogs, for example, to track humans based on having sniffed something that they've worn.

You write that sweat is poorly understood by scientists. What are the things we still don't understand about sweating, and what are researchers investigating?

Some of the really interesting areas are the evolution of sweat glands and how we actually came to have evolved one of the most efficient ways to cool down in the animal kingdom.

We don't even know how many genes are involved in sweating. And a lot of other really fabulous research is still going on. [Researchers are] trying to, for example, do the forensics of science like monitoring what is coming out when we sweat and monitoring what are the chemical residues in a fingerprint. Because a fingerprint is just a sweat print. And forensic researchers are now able to learn all about your biological identity from the actual chemicals left behind in the fingerprint.

If you can analyze the chemicals of that fingerprint and find out, wow, that person was, you know, drinking alcohol or that person actually has cancer all sorts of very private information is being left behind in the drips we leave on our yoga mats but also literally on everything that we touch.

Read more here:

Sweat Is An Evolutionary Marvel Allowing Humans To Survive And Thrive : Shots - Health News - NPR

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From August 2nd, Australian Radio Network will officially be replaced with ARN. Following a holistic review of the audio landscape, brand proposition and culture at ARN, a rebrand will be launched to market.

Launched in 2019, ARNs Defining Audio saw the introduction of Australias first audio offering; ARNs Audiosphere. For advertisers, ARNs audio solutions seek to leverage the whole Audiosphere, providing audio entertainment, connections, audio messaging, creative and campaign amplification. It was designed to help commercial partners identify the most valuable moments and appropriate content across multiple audio channels to connect with consumers.

While the Defining Audio proposition remains built on a commitment to deliver simplified audio solutions that leverage the whole Audiosphere, it has evolved and amplified through connections and innovations to fuel conversations that hit the right audience, with the right message, every time. This will be brought to life through the trade-facing Connections That Count campaign.

ARNs chief strategy & connections officer Lauren Joyce said, The ARN Audiosphere has become a beacon for simple audio solutions in an increasingly complex category. As our business continues to innovate to reinforce the Defining Audio proposition, it makes sense to highlight the fuel behind that proposition through our campaign; Connections that Count. Quality connection is what moves people and its why listeners and brands choose ARN our commitment to build meaningful and measurable moments in audio should give clients and listeners alike, great confidence in our business.

ARNs CEO Ciaran Davis said, As the holder of Australias most established and complete digital audio platform, iHeartRadio, which delivers radio, music and podcasts all in one place, ARN has been Defining Audio for years now. Todays announcement demonstrates how were continuing to invest and innovate to create the future of audio right here and now; delivering more content for our listeners and deeper insights for our clients. From providing one to one addressability across digital platforms to dynamically created and served advertising across linear radio, were proud to be providing scaleable, measurable solutions to clients in an era of intense ROI accountability.

Under its new name, ARN will continue to power the KIIS, Pure Gold and The Edge networks with the worlds best talent who connect with Australians nationwide, while further serving up the greatest range of local and international radio, music and podcast content in digital formats via the iHeartRadio app.

Link:

Australian Radio Network rebrands, announces evolution of Defining Audio - Mediaweek