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Premise of the Study Large phylogenies can help shed light on macroevolutionary patterns that inform our understanding of fundamental processes that shape the tree of life. These phylogenies also serve as tools that facilitate other systematic, evolutionary, and ecological analyses. Here we combine genetic data from public repositories (GenBank) with phylogenetic data (Open Tree of Life project) to construct a dated phylogeny for seed plants. Methods We conducted a hierarchical clustering analysis of publicly available molecular data for major clades within the Spermatophyta. We constructed phylogenies of major clades, estimated divergence times, and incorporated data from the Open Tree of Life project, resulting in a seed plant phylogeny. We estimated diversification rates, excluding those taxa without molecular data. We also summarized topological uncertainty and data overlap for each major clade. Key Results The trees constructed for Spermatophyta consisted of 79,881 and 353,185 terminal taxa; the latter included the Open Tree of Life taxa for which we could not include molecular data from GenBank. The diversification analyses demonstrated nested patterns of rate shifts throughout the phylogeny. Data overlap and inference uncertainty show significant variation throughout and demonstrate the continued need for data collection across seed plants. Conclusions This study demonstrates a means for combining available resources to construct a dated phylogeny for plants. However, this approach is an early step and more developments are needed to add data, better incorporating underlying uncertainty, and improve resolution. The methods discussed here can also be applied to other major clades in the tree of life.

Rectal temperature measurement (RTM) from crime scenes is an important parameter for temperature-based time of death estimation (TDE). Various influential variables exist in TDE methods like the uncertainty in thermal and environmental parameters. Although RTM depends in particular on the location of measurement position, this relationship has never been investigated separately. The presented study fills this gap using Finite Element (FE) simulations of body cooling. A manually meshed coarse human FE model and an FE geometry model developed from the CT scan of a male corpse are used for TDE sensitivity analysis. The coarse model is considered with and without a support structure of moist soil. As there is no clear definition of ideal rectal temperature measurement location for TDE, possible variations in RTM location (RTML) are considered based on anatomy and forensic practice. The maximum variation of TDE caused by RTML changes is investigated via FE simulation. Moreover, the influence of ambient temperature, of FE model change and of the models positioning on a wet soil underground are also discussed. As a general outcome, we notice that maximum TDE deviations of up to ca. 2–3 h due to RTML deviations have to be expected. The direction of maximum influence of RTML change on TDE generally was on the line caudal to cranial.

An important challenge in evolutionary biology is to understand how major changes in body form arise. The dramatic transition from a lizard-like to snake-like body form in squamate reptiles offers an exciting system for such research because this change is replicated dozens of times. Here, we use morphometric data for 258 species and a time-calibrated phylogeny to explore rates and patterns of body-form evolution across squamates. We also demonstrate how time-calibrated phylogenies may be used to make inferences about the time frame over which major morphological transitions occur. Using the morphometric data, we find that the transition from lizard-like to snake-like body form involves concerted evolution of limb reduction, digit loss, and body elongation. These correlations are similar across squamate clades, despite very different ecologies and >180 million years (My) of divergence. Using the time-calibrated phylogeny and ancestral reconstructions, we find that the dramatic transition between these body forms can occur in 20 My or less, but that seemingly intermediate morphologies can also persist for tens of millions of years. Finally, although loss of digits is common, we find statistically significant support for at least six examples of the re-evolution of lost digits in the forelimb and hind limb.

Digital technologies have been contributing to providing quality health care to patients. One aspect of this is providing accurate wait times for patients waiting to be serviced at healthcare facilities. This is naturally a complex problem as there is a multitude of factors that can impact the wait time. However, the problem becomes even more complex if the patient's journey requires visiting multiple stations in the hospital; such as having vital signs taken, doing an ultrasound, and seeing a specialist. The authors aim to provide an accurate method for estimating the wait time by utilising a real dataset of transactions collected from a major hospital over a year. The work employs feature engineering and compares several machine learning‐based algorithms to predict patients' waiting times for single‐stage and multi‐stage services. The Random Forest algorithm achieved the lowest root mean squared error (RMSE) value of 6.69 min among all machine learning algorithms. The results were also compared against a formula‐based system used in the industry, and the proposed model outperformed the existing model, showing improvements of 25.1% in RMSE and 18.9% in MAE metrics. These findings indicate a significant improvement in the accuracy of predicting waiting times compared to existing techniques. The article focuses on multi‐stage queues in smart healthcare facilities. It investigates creating meaningful features out of existing transactional data. The authors show that the use of machine‐learning based solutions is superior to the use of classical methods, showing improvements of 25.1% in RMSE and 18.9% in MAE metrics.

In this study, we describe a technique for estimating meal times using an earphone-type wearable sensor. A small optical sensor composed of a light-emitting diode and phototransistor is inserted into the ear hole of a user and estimates the meal times of the user from the time variations in the amount of light received. This is achieved by emitting light toward the inside of the ear canal and receiving light reflected back from the ear canal. This proposed technique allowed “meals” to be differentiated from having conversations, sneezing, walking, ascending and descending stairs, operating a computer, and using a smartphone. Conventional devices worn on the head of users and that measure food intake can vibrate during running as the body is jolted more violently than during walking; this can result in the misidentification of running as eating by these devices. To solve this problem, we used two of our sensors simultaneously: one in the left ear and one in the right ear. This was based on our finding that measurements from the left and right ear canals have a strong correlation during running but no correlation during eating. This allows running and eating to be distinguished based on correlation coefficients, which can reduce misidentification. Moreover, by using an optical sensor composed of a semiconductor, a small and lightweight device can be created. This measurement technique can also measure body motion associated with running, and the data obtained from the optical sensor inserted into the ear can be used to support a healthy lifestyle regarding both eating and exercise.

Aim: The bipolar disjunction, a biogeographical pattern defined by taxa with a distribution at very high latitudes in both hemispheres (> 55° N; > 52° S), is only known to occur in about 30 vascular plant species. Our aim was to use the bipolar species Carex arctogena to test the four classic hypotheses proposed to explain this exceptional disjunction: convergent evolution, vicariance, mountain-hopping and direct long-distance dispersal. Location: Arctic/boreal and temperate latitudes of both hemispheres. Methods: A combination of molecular and bioclimatic data was used to test phylogeographical hypotheses in C. arctogena. Three chloroplast markers (atpF–atpH, matK and rps16) and the nuclear ITS region were sequenced for all species in Carex sections Capituligerae and Longespicatae; Carex rupestris, C. obtusata and Uncinia triquetra were used as outrgroups. Phylogenetic relationships, divergence-time estimates and biogeographical patterns were inferred using maximum likelihood, statistical parsimony and Bayesian inference. Results: Carex sections Capituligerae and Longespicatae formed a monophyletic group that diverged during the late Miocene. Two main lineages of arctogena were inferred. Southern Hemisphere populations of C. arctogena shared the same haplotype as a widespread circumboreal lineage. Bioclimatic data show that Southern and Northern Hemisphere populations currently differ in their ecological regimes. Main conclusions: Two of the four hypotheses accounting for bipolar disjunctions may be rejected. Our results suggest that direct long-distance dispersal, probably southwards and mediated by birds, best explains the bipolar distribution of C. arctogena.

With the increasing number of cows per farmer in Japan, an automatic cow monitoring system is being introduced. One important aspect of such a system is the ability to identify individual cows and estimate their feeding time. In this study, we propose a method for achieving this goal through facial region analysis. We used a YOLO detector to extract the cow head region from video images captured during feeding with the head region cropped as a face region image. The face region image was used for cow identification and transfer learning was employed for identification. In the context of cow identification, transfer learning can be used to train a pre-existing deep neural network to recognize individual cows based on their unique physical characteristics, such as their head shape, markings, or ear tags. To estimate the time of feeding, we divided the feeding area into vertical strips for each cow and established a horizontal line just above the feeding materials to determine whether a cow was feeding or not by using Hough transform techniques. We tested our method using real-life data from a large farm, and the experimental results showed promise in achieving our objectives. This approach has the potential to diagnose diseases and movement disorders in cows and could provide valuable insights for farmers.

Cognitive abilities are often reported to decline across the lifespan, particularly when assessed with working memory (WM) measures such as the auditory backward digit span and complex back tasks. However, some debate still exists regarding which aspects of cognition are most susceptible to the aging process and which may remain intact. Additionally, time estimation, though a complex psychological dimension, is often studied in relative isolation and is particularly neglected in traditional studies of WM, with little research from the viewpoint of retrospective temporal estimation. In particular, research seldom considers whether the ability to accurately estimate time retrospectively, is correlated with performance on traditional memory and processing speed measures in healthy populations. Thus, we chose to investigate performance of comparably educated young and older adult groups on both classical memory tasks including auditory and visual digit spans, -back, Wechsler Adult Intelligence Scale (WAIS)-based measures of processing speed (i.e., Symbol Search [SS] and Coding [Cod]) and a temporal measure of WM with a focus on retrospective time estimation. Our sample included 66 university students (58 F, 8 M) between the ages of 18-29, and 33 university-educated healthy older adults (25 F, 8 M) between the ages of 60-81. Results indicated that older adults performed significantly worse on auditory but not the visual digit span tasks, as well as on both the SS and Cod, though performed equally well on the = 1 back task. Results also showed that retrospective time estimation was not significantly different between young and older adults, with both groups substantially underestimating duration of a simple task. Retrospective time estimation was not significantly correlated to any memory or processing speed measure, emphasizing the need for future research into the specific cognitive domains underlying the subjective estimation of a temporal interval.

Probabilistic time estimation is an essential part of proper risk management in tunneling projects. In recent decades, several models have been developed for this purpose, one of which was developed by Isaksson and Stille (Rock Mech Rock Eng 38:373–398, 2005). In this paper, Isaksson and Stille’s probabilistic time and cost estimation model was improved and then applied to estimate the total tunneling time of the headrace tunnel in the Uri hydropower project in India. The improvements allow the user to more accurately account for different types of geological features and disruptive events. The result of the estimation is a distribution of tunneling time. The outcome illustrates how a proper understanding of the geological setting of the project and its effect on construction performance can contribute to effective risk management.HighlightsThe application process of an existing model for probabilistic time and cost estimation of tunneling projects was improved. The improved model was used for time estimation in a case study to demonstrate its application. The outcome of the model application is a mixture distribution of total tunneling time. Further discussion is put forward on the general modeling considerations, the shape of the mixture distribution, and application of the model in tunnels with multiple excavation faces.

Living turtles are characterized by extraordinarily low species diversity given their age. The clade’s extensive fossil record indicates that climate and biogeography may have played important roles in determining their diversity. We investigated this hypothesis by collecting a molecular dataset for 591 individual turtles that, together, represent 80% of all turtle species, including representatives of all families and 98% of genera, and used it to jointly estimate phylogeny and divergence times. We found that the turtle tree is characterized by relatively constant diversification (speciation minus extinction) punctuated by a single threefold increase. We also found that this shift is temporally and geographically associated with newly emerged continental margins that appeared during the Eocene–Oligocene transition about 30 million years before present. In apparent contrast, the fossil record from this time period contains evidence for a major, but regional, extinction event. These seemingly discordant findings appear to be driven by a common global process: global cooling and drying at the time of the Eocene–Oligocene transition. This climatic shift led to aridification that drove extinctions in important fossilbearing areas, while simultaneously exposing new continental margin habitat that subsequently allowed for a burst of speciation associated with these newly exploitable ecological opportunities.