Absolute Scale Research Articles

Phylloxera and Aphids Show Distinct Features of Genome Evolution Despite Similar Reproductive Modes.

Genomes of aphids (family Aphididae) show several unusual evolutionary patterns. In particular, within the XO sex determination system of aphids, the X chromosome exhibits a lower rate of interchromosomal rearrangements, fewer highly expressed genes, and faster evolution at nonsynonymous sites compared with the autosomes. In contrast, other hemipteran lineages have similar rates of interchromosomal rearrangement for autosomes and X chromosomes. One possible explanation for these differences is the aphid's life cycle of cyclical parthenogenesis, where multiple asexual generations alternate with 1 sexual generation. If true, we should see similar features in the genomes of Phylloxeridae, an outgroup of aphids which also undergoes cyclical parthenogenesis. To investigate this, we generated a chromosome-level assembly for the grape phylloxera, an agriculturally important species of Phylloxeridae, and identified its single X chromosome. We then performed synteny analysis using the phylloxerid genome and 30 high-quality genomes of aphids and other hemipteran species. Unexpectedly, we found that the phylloxera does not share aphids' patterns of chromosome evolution. By estimating interchromosomal rearrangement rates on an absolute time scale, we found that rates are elevated for aphid autosomes compared with their X chromosomes, but this pattern does not extend to the phylloxera branch. Potentially, the conservation of X chromosome gene content is due to selection on XO males that appear in the sexual generation. We also examined gene duplication patterns across Hemiptera and uncovered horizontal gene transfer events contributing to phylloxera evolution.

Interactive Robot Task Learning: Human Teaching Proficiency With Different Feedback Approaches

The deployment of versatile robot systems in diverse environments requires intuitive approaches for humans to flexibly teach them new skills. In our present work, we investigate different user feedback types to teach a real robot a new movement skill. We compare feedback as star ratings on an absolute scale for single roll-outs versus preference-based feedback for pairwise comparisons with respective optimization algorithms (i.e., a variation of co-variance matrix adaptation -evolution strategy (CMA-ES) and random optimization) to teach the robot the game of skill cup-and-ball. In an experimental investigation with users, we investigated the influence of the feedback type on the user experience of interacting with the different interfaces and the performance of the learning systems. While there is no significant difference for the subjective user experience between the conditions, there is a significant difference in learning performance. The preference-based system learned the task quicker, but this did not influence the users’ evaluation of it. In a follow-up study, we confirmed that the difference in learning performance indeed can be attributed to the human users’ performance.

The health of mothers caring for a child with a disability: a longitudinal study

BackgroundRaising a child with disabilities requires a significant parental investment that is greater than that required by typically developing children. Previous studies have shown that parents caring for a child with a disability experience a range of health problems, particularly the mothers. However, few of these studies have controlled for maternal health prior to birth.MethodsThis study used a sample from the Norwegian administrative register that comprised all children born between 2009 and 2015. We followed the mothers and their children for 11 years, between 2009 and 2019. The outcome variable was the mothers’ physical and mental health, which was assessed using specific ICD-10 diagnoses recorded in the Norwegian Patient Register (NPR). The data included information on the mothers’ health before and after the birth of their first child, enabling us to control for maternal health prior to birth in our analysis, in addition to socio-demographic characteristics. The analyses of maternal health were performed using multiple logistic regression, and the results are presented on both a relative scale (odds ratio [OR]) and an absolute scale (average marginal effect [AME]), both with 95% confidence intervals.ResultsMothers caring for a child with a disability have higher odds of having a diagnosis of a musculoskeletal disorder, depression, anxiety, sleeping disorder or migraines than mothers of children without a disability. The differences between the two groups of mothers decrease after adjusting for the characteristics of the children, mothers and families, but remain significant for musculoskeletal disorder, depression, anxiety and sleeping disorder, although the absolute differences are modest.ConclusionThe findings suggest that mothers caring for a child with a disability are more likely to have health problems than mothers of children without a disability after controlling for maternal health prior to birth. Providing more support for mothers of children with a disability might help to improve their health.

Incidence and risk prediction of post-Covid-19 cardiovascular disease in the general population: a multivariable prediction model development and validation study

Abstract Background Previous studies showed that relative risks of various cardiovascular events are increased after Covid-19, even in non-hospitalized individuals. The global burden of post-Covid-19 cardiovascular disease is large and not (yet) hospitalized Covid-19 infected adults may represent a potential target for prevention strategies to mitigate this burden. However, good estimates of individual absolute risks in the general population and risk stratification models are lacking, yet pivotal to assess its impact and direct health care policy. Purpose This study aimed to assess the absolute risk of post-Covid-19 cardiovascular events in the general population, and subsequently explore individual risk prediction in this domain. Methods Covid-19 diagnosed adults were identified from the United Kingdom’s Clinical Practice Research Datalink Aurum, a primary care electronic healthcare database. We assessed 180-day incidence rates of atherosclerotic events (acute coronary syndrome, stroke and transient ischaemic accident), venous thrombo-embolic events (pulmonary embolism and deep venous thrombosis), and newly diagnosed atrial fibrillation and heart failure. Multivariable logistic regression models using elastic net penalization were developed on a cohort of 220,751 adults with Covid-19 before 1 December 2020 (before the start of national vaccination campaigns). Candidate predictors included age, sex, body mass index, smoking, medical history and medication. Three models were fit for each endpoint, with increasing numbers of predictors. All models were validated in (1) 138,034 vaccinated and (2) 503,404 non-vaccinated adults with a first Covid-19 diagnosis after 1 December 2020. We evaluated discriminative and calibration performance upon internal cross-validation and in both validation cohorts. Results Post-Covid-19 cardiovascular event incidences ranged from 13 (venous thromboembolic events) down to 4 (heart failure de novo) per 1000 person-years. Incidences were relatively increased up to 50 days after Covid-19 infection. However, on an absolute scale, individual risks were very low: only less than one in twenty adults with Covid-19 had a predicted 180-day risk larger than 1% and these mainly included individuals aged 60 years or older. Even though the best models had high discriminative performance (AUC > 0.90), rare outcomes complicated predictive performance and calibration. Conclusions Risks of atherosclerotic events, venous thromboembolic events, and newly diagnosed atrial fibrillation and heart failure are increased after Covid-19 infection in the general population, notably within the first 50 days after infection and in individuals aged 60 years or older. However, individual risks are too low to be predictive or helpful to guide individual risk management. Risk mitigation strategies should therefore be aimed at population-based prevention (such as increasing vaccination uptake) and at individual management of Covid-19 hospitalized patients.Graphical abstractPredicted 180-day risk after Covid-19

Manifestation of binary collisions in the Raman-allowed bending vibrational band of the S[formula omitted] molecule

A careful, principally experimental Raman study which puts the focus on the ν5 bending vibrational band by gaseous room-temperature sulfur hexafluoride is reported. In essence, our results boil down in the following two findings. Firstly, the anisotropic Raman-allowed spectrum by that band, which for the first time was isolated from the recordings and calibrated on an absolute scale. Secondly, an absolute-calibrated binary collision-induced component, which was also for the first time extracted from the crude measurements in the wavenumber range 475–570 cm−1. Both spectra are depolarized and lead to parameters in agreement with the existing literature. The reported findings bring us one step closer to understanding how vibration mechanisms work in SF6 and show among other things that, at the ν5 frequency, collisions between molecules enhance light scattering by 0.8% at 1 atm and by 13% at 15 atm of sulfur hexafluoride gas pressure.

Transcaruncular double injection technique for peribulbar anesthesia in vitreoretinal surgery.

Local anesthesia is commonly adopted in vitreoretinal surgery to reach painless and akinesia surgical condition. Currently, peribulbar anesthesia (PBA) and subtenonian injection (STN) are the most widely used methods. We propose a transcaruncular double injection peribulbar technique (TRS) and aim to compare it with both standard PBA and STN injections. A total of 105 patients underwent either TRS or PBA or STN. Numerical Rating Scale (NRS) was used to assess pre, post and intraoperative pain. Best akinesia score, onset and duration of akinesia were evaluated by two independent graders. The need for supplementary injection was also registered. TRS group was characterized by a lower intraoperative NRS variation and absolute NRS score both at the beginning of surgery (p 0.046), after 30 minutes (p 0.032) and at the end of surgery (p 0.002) compared to the other groups. TRS group also showed better akinesia score (p 0.004), fastest onset (p 0.002) and longer duration (p 0.042) compared to both PBA ad STN. No injection related complications were reported in the 3 groups. the newly proposed transcaruncular PBA provided superior pain control and akinesia level with no additional adverse events.

Luminosity determination in pp collisions at sqrt{s}=13 TeV using the ATLAS detector at the LHC

The luminosity determination for the ATLAS detector at the LHC during Run 2 is presented, with pp collisions at a centre-of-mass energy sqrt{s}=13 TeV. The absolute luminosity scale is determined using van der Meer beam separation scans during dedicated running periods in each year, and extrapolated to the physics data-taking regime using complementary measurements from several luminosity-sensitive detectors. The total uncertainties in the integrated luminosity for each individual year of data-taking range from 0.9% to 1.1%, and are partially correlated between years. After standard data-quality selections, the full Run 2 pp data sample corresponds to an integrated luminosity of 140.1pm 1.2 hbox {fb}^{-1}, i.e. an uncertainty of 0.83%. A dedicated sample of low-pileup data recorded in 2017–2018 for precision Standard Model physics measurements is analysed separately, and has an integrated luminosity of 338.1pm 3.1 hbox {pb}^{-1}.

Astrochronology of the late Oligocene-middle Miocene in the Maldives, central Indian Ocean

Substantial work based on biostratigraphy has been done to constrain the chronology of the late Oligocene-middle Miocene in the Maldives (Indian Ocean), but a high-resolution temporal framework for the sedimentary record of this region remains elusive. This hampers a fuller understanding of the evolution of the carbonate platform, which is the second largest modern isolated carbonate platform. Moreover, the sedimentary record of the Maldives platform has the potential to provide insights on the onset of the ‘modern-like’ South Asian Monsoon (SAM) system. Here we present a detailed astrochronology for International Ocean Discovery Program (IODP) Site U1468 through the late Oligocene-middle Miocene in the Maldives. Our cyclostratigraphy of the site is integrated with existing biostratigraphy and statistical evaluation, providing a robust ∼12-Myr absolute astronomical time scale (ATS). Using this time scale, we assign numerical ages of 12.229 ± 0.46 Ma and 11.561 ± 0.46 Ma for the core depths of 450 mbsf and 430 mbsf, respectively. These depths, constrained by biostratigraphy, have previously been suggested to mark the onset of the SAM in the Maldives. Our ATS provides time constraints on the evolution of the platform sequence stratigraphy, and we find evidence of a ∼1.2-Myr obliquity amplitude modulation (AM) control on sea level changes and sequence development. In addition, our results indicate that the deposition of organic-rich sediments towards the base of the record in this area was driven by obliquity cycles and the combined effect of glacio-eustasy and hydrographic changes.

Absolute scattering length density profile of liposome bilayers obtained by SAXS combined with GIXOS: a tool to determine model biomembrane structure

Lipid membranes play an essential role in biology, acting as host matrices for biomolecules like proteins and facilitating their functions. Their structures and structural responses to physiologically relevant interactions (i.e. with membrane proteins) provide key information for understanding biophysical mechanisms. Hence, there is a crucial need of methods to understand the effects of membrane host molecules on the lipid bilayer structure. Here, a purely experimental method is presented for obtaining the absolute scattering length density profile and the area per lipid of liposomal bilayers, by aiding the analysis of small-angle X-ray scattering (SAXS) data with the volume of bare headgroups obtained from grazing-incidence X-ray off-specular scattering (GIXOS) data of monolayers of the same model membrane lipid composition. The GIXOS data experimentally demonstrate that the variation of the bare headgroup volume upon change in lipid packing density is small enough to allow its usage as a reference value without knowing the lipid packing stage in a bilayer. This approach also has the advantage that the reference volume is obtained in the same aqueous environment as used for the model membrane bilayers. The validity of this method is demonstrated using several typical membrane compositions, as well as one example of a phospholipid membrane with an incorporated transmembrane peptide. This methodology allows us to obtain absolute scale rather than relative scale values using solely X-ray-based instrumentation, retaining a similar resolution to SAXS experiments. The method presented has high potential for understanding the structural effects of membrane proteins on the biomembrane structure.

Numerical Simulation of Fracture Flow Interaction Based on Discrete Fracture Model

Hydraulic fracturing of horizontal wells is a common method for enhancing production in low-permeability and unconventional oil reservoirs. However, due to the interference between fractures, issues such as decreased production and water channeling often occur in hydraulic fracturing of horizontal wells. Therefore, studying how to mitigate the effects of fracture interference is of great significance for optimizing hydraulic fracturing design and improving oil and gas recovery rates. In this paper, an oil–water two-phase discrete fracture model was established, and the grid dissection was carried out by using the optimization method to obtain a triangular grid that can finely characterize the fracture in geometry. Then, typical discrete fracture models were designed, and the influences of the fracture permeability ratio, absolute fracture scale, oil–water viscosity ratio, and fracture length on the fracture flow interference were investigated separately. The degree of fracture interference was evaluated using the fracture fractional flow rate ratio, remaining oil saturation, and sweep efficiency. This study verified fracture interaction and identified that the threshold value of the fracture permeability ratio is 9 to classify the degree of interference. Sensitivity analysis shows that the absolute size of the fracture has a significant impact on fracture interference, while the impact of the oil–water viscosity ratio and fracture length on fracture interference is relatively small.

Experimental 7Be production cross section from the [formula omitted] reaction at Ep = 3.5 − 13 MeV

The Li7(p,n)7Be reaction is widely used as neutron source for neutron induced reaction cross section measurements, and for 7Be radioactive source production. There are two prominent structures in the excitation function, a narrow resonance between Ep=2.2−2.3 MeV, and a broad peak, around Ep=5 MeV. There are tension between the experimental data sets both in the position and the width of this latter structure, as well as in the absolute scale of the data. In the present work the Li7(p,n)7Be reaction is investigated using the activation technique, with the aim of providing comprehensive cross section data covering the second structure and connecting prior literature data sets. The irradiations were performed with the Atomki cyclotron accelerator with pairs of thin foil targets, thus with precisely controlled reaction energy in the range of Ep=3.5−13 MeV. After the irradiations the activity of the samples was measured using a high-purity germanium detector. The energy uncertainty of the new data points is much smaller than in any of the previous works, while the cross section uncertainty is comparable with the most precise literature data. A consistent data set was obtained connecting the most recent and most precise literature data sets. With the new data the absolute magnitude of the Li7(p,n)7Be reaction cross section is constrained and became more precise.

The [CII] 158 μm emission line as a gas mass tracer in high redshift quiescent galaxies

A great deal of effort has been made in recent years to probe the gas fraction evolution of massive quiescent galaxies (QGs); however, a clear picture has not yet been established. Recent spectroscopic confirmations at z > 3 offer the chance to measure the residual gas reservoirs of massive galaxies a few hundred Myr after their death and to study how fast quenching proceeds in a highly star-forming Universe. Even so, stringent constraints at z > 2 remain hardly accessible with the Atacama Large Millimeter/submillimeter Array (ALMA) when adopting molecular gas tracers commonly used for the quenched population. In this Letter we propose overcoming this impasse by using the carbon [CII] 158 μm emission line to systematically probe the gaseous budget of unlensed QGs at z > 2.8, when these galaxies could still host non-negligible star formation on an absolute scale and when the line becomes best observable with ALMA (Bands 8 and 7). Predominantly used for star-forming galaxies to date, this emission line is the best choice to probe the gas budget of spectroscopically confirmed QGs at z > 3, reaching 2–4 and 13–30 times deeper than dust continuum emission (ALMA band 7) and CO(2–1)/(1–0) (Very Large Array, VLA, K − Kα bands), respectively, at fixed integration time. Exploiting archival ALMA observations, we place conservative 3σ upper limits on the molecular gas fraction (fmol = MH2/M⋆) of ADF22-QG1 (fmol < 21%) and ZF-COS-20115 (fmol < 3.2%), two of the best-studied high-z QGs in the literature, and GS-9209 (fmol < 72%), the most distant massive QG discovered to date. The deep upper limit found for ZF-COS-20115 is three times lower than previously anticipated for high-z QGs suggesting, at best, the existence of a large scatter in the fmol distribution of the first QGs. Lastly, we discuss the current limitations of the method and propose ways to mitigate some of them by exploiting ALMA bands 9 and 10.

Absolute Quantification of Pan-Cancer Plasma Proteomes Reveals Unique Signature in Multiple Myeloma.

Mass spectrometry based on data-independent acquisition (DIA) has developed into a powerful quantitative tool with a variety of implications, including precision medicine. Combined with stable isotope recombinant protein standards, this strategy provides confident protein identification and precise quantification on an absolute scale. Here, we describe a comprehensive targeted proteomics approach to profile a pan-cancer cohort consisting of 1800 blood plasma samples representing 15 different cancer types. We successfully performed an absolute quantification of 253 proteins in multiplex. The assay had low intra-assay variability with a coefficient of variation below 20% (CV = 17.2%) for a total of 1013 peptides quantified across almost two thousand injections. This study identified a potential biomarker panel of seven protein targets for the diagnosis of multiple myeloma patients using differential expression analysis and machine learning. The combination of markers, including the complement C1 complex, JCHAIN, and CD5L, resulted in a prediction model with an AUC of 0.96 for the identification of multiple myeloma patients across various cancer patients. All these proteins are known to interact with immunoglobulins.

Automated precision counting of small lunar craters - A broader view

An automated system for counting small craters at lunar landing sites has been expanded to include selected locations on the Moon's far side and high latitudes. Highland areas were generally excluded from this new survey, because sloping terrain can have a significant effect on crater lifetimes. But some locations on highland light plains units were analysed, as were some young Copernican age crater ejecta blankets and impact melts.This study focuses on craters having diameters between 2.5 m and 50 m, for which counts are so high that they are best plotted as Crater Size Frequency Histograms (CSFHs), rather than the conventional cumulative plots (CSFDs). This histogram representation enables the finest details of the plots to be compared across sites. Using multiple precisely aligned images of each site enables false negatives to be included and false positives rejected, ensuring that no visually recognisable craters are missed, a capability that is not possible when analysing single images.There are some very distinct differences between the curves at different sites. Based on the known ages of boulder tracks and counts of craters formed over the last 50 years, the largest craters within the size range up to 50 m are thought to be no more that a few hundred million years old. A model for the evolution of small crater populations on an absolute time scale is presented and the absolute ages of young features are estimated.There is no evidence in the data for secondary cratering, nor is there any clear variation of counts and slopes with longitude or latitude, so other possible explanations for the variabilities between sites must be found.The results obtained by this project should prove useful for modelling crater formation and destruction and also as training data for machine learning systems.

Power priors for replication studies

The ongoing replication crisis in science has increased interest in the methodology of replication studies. We propose a novel Bayesian analysis approach using power priors: The likelihood of the original study’s data is raised to the power of α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document}, and then used as the prior distribution in the analysis of the replication data. Posterior distribution and Bayes factor hypothesis tests related to the power parameter α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document} quantify the degree of compatibility between the original and replication study. Inferences for other parameters, such as effect sizes, dynamically borrow information from the original study. The degree of borrowing depends on the conflict between the two studies. The practical value of the approach is illustrated on data from three replication studies, and the connection to hierarchical modeling approaches explored. We generalize the known connection between normal power priors and normal hierarchical models for fixed parameters and show that normal power prior inferences with a beta prior on the power parameter α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document} align with normal hierarchical model inferences using a generalized beta prior on the relative heterogeneity variance I2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$I^2$$\\end{document}. The connection illustrates that power prior modeling is unnatural from the perspective of hierarchical modeling since it corresponds to specifying priors on a relative rather than an absolute heterogeneity scale.

Efficacy of a gluten-free diet in reducing the widespread pain index and symptom severity scale in patients affected by fibromyalgia.

Dietary interventions to improve fibromyalgia (FM) symptoms reported conflicting results. This study aimed to treat FM patients with a gluten-free diet (GFD), alternated with a non-restricted gluten-containing diet, followed by a rechallenge of the GFD. Twenty postmenopausal women with FM and no history of celiac disease participated. A GFD was assigned for 6 months. This was followed by 3 months of a non-restricted gluten-containing diet and then a new GFD for another 6 months. At each visit, the widespread pain index (WPI) and the symptom severity scale (SS) scores were evaluated. The mean age of the patients enrolled was 53.9±10 years. None of the patients had a diagnosis of irritable bowel disease, although they reported vague gastrointestinal symptoms. After 6 months of a GFD, a statistically significant reduction was observed for the WPI (10.3±1.8 vs 7.7±1.4; p<0.0001) and the SS scale (6.4±1.8 vs 4.15±1.6; p=0.0002). The D percentage reduction of the WPI after 6 months of GFD was -24%±9%, while for the SS scale, it was -36%±21%. The following reintroduction of a gluten-containing diet brought about a statistically significant rise in the absolute SS scale and WPI, as well as a D modification of the WPI (21%±13%) and of the SS scale (74%±90%). The rechallenge of the GFD showed a significant improvement in absolute and D WPI (-24%±7%) and SS (-36%±11%). No modifications to the body mass index were found. A GFD improved FM symptoms evaluated with WPI and SS. This was confirmed for the first time, also with a rechallenge of the GFD that followed a non-restricted gluten-containing diet.

The Universal Theory for Multiscale Modelling of Infectious Disease Dynamics

The replication-transmission relativity theory, currently used to inform the development of multiscale models of infectious disease dynamics, needs a revision and extension to accommodate new basic science and clinical information about infectious disease dynamics. In this article, we revise and extend the replication-transmission relativity theory into a new scientific theory of infectious disease dynamics called the universal theory for the multiscale modelling of infectious disease dynamics. This new theory states that, for every host–pathogen interaction that results in an infectious disease system, there is no privileged or absolute scale of a disease system form that would determine the dynamics of the infectious disease system, only interactions between the scales of a level of organisation of the pathogen-centred disease system form and the scales of the corresponding levels of organisation of the host-centred disease system form. We further explain the utility of this theory, which is reflected in its flexibility and ability to incorporate new information and explain previous information that could not be accounted for by the replication-transmission relativity theory of infectious disease dynamics.

Tritium Beta Spectrum Measurement and Neutrino Mass Limit from Cyclotron Radiation Emission Spectroscopy.

The absolute scale of the neutrino mass plays a critical role in physics at every scale, from the subatomic to the cosmological. Measurements of the tritium end-point spectrum have provided the most precise direct limit on the neutrino mass scale. In this Letter, we present advances by Project 8 to the cyclotron radiation emission spectroscopy (CRES) technique culminating in the first frequency-based neutrino mass limit. With only a cm^{3}-scale physical detection volume, a limit of m_{β}<155 eV/c^{2} (152 eV/c^{2}) is extracted from the background-free measurement of the continuous tritium beta spectrum in a Bayesian (frequentist) analysis. Using ^{83m}Kr calibration data, a resolution of 1.66±0.19 eV (FWHM) is measured, the detector response model is validated, and the efficiency is characterized overthe multi-keV tritium analysis window. These measurements establish the potential of CRES for a high-sensitivity next-generation direct neutrino mass experiment featuring low background and high resolution.

Orbitally-paced coastal sedimentary records and global sea-level changes in the early Permian

Orbital forcing affects climate system by regulating the amount of solar radiation received at the Earth's surface, which is vital for global hydrological cycles. However, a systematic understanding of the global water cycle with synergistic changes in ice sheets and sea levels under orbital forcing during the late Paleozoic ice age (LPIA) remains elusive. Here, we perform cyclostratigraphic analysis and sedimentary noise modeling for coastal sedimentary records (Well Greer #2 in the Permian Basin) from the early Permian and two sets of high-resolution paleoclimate simulation experiments using the Community Earth System Model. We provide the first high-resolution absolute astronomical time scale for the Permian Basin, which suggests that the timing of the early Permian Lower Leonard and Upper Wolfcamp Formations range from 286.29 ± 0.55 Ma to 289.05 ± 0.55 Ma, and the Lower Wolfcamp Formation ranges from 292.97 ± 0.16 Ma to 298.9 ± 0.15 Ma, respectively. In addition, we find a coupled phase relationship between high sea levels and eccentricity maxima, suggesting that eccentricity may have played a critical role in the early Permian sea-level oscillations. Paleoclimate simulations show that eccentricity and obliquity maxima lead to an overall increase in global mean temperature. Significant changes in surface temperature at middle to high latitudes are manifested as the polar amplification effect during the LPIA. Compared with obliquity, eccentricity leads to higher annual and summer variability in global surface temperature, and enhanced polar amplification results in ice retreat and sea-level rise. Evidence from Earth system modeling elucidates the phase relationship between orbital cycles and sea levels. Therefore, eccentricity, as the leading driving force in low latitudes, may dominate climate changes in the Earth's climate system and regulates global hydrological cycles during the LPIA.

A Large Comparison of Normalization Methods on Time Series

Normalization is a mandatory preprocessing step in time series problems to guarantee similarity comparisons invariant to unexpected distortions in amplitude and offset. Such distortions are usual for most time series data. A typical example is gait recognition by motion collected on subjects with varying body height and width. To rescale the data for the same range of values, the vast majority of researchers consider z-normalization as the default method for any domain application, data, or task. This choice is made without a searching process as occurs to set the parameters of an algorithm or without any experimental evidence in the literature considering a variety of scenarios to support this decision. To address this gap, we evaluate the impact of different normalization methods on time series data. Our analysis is based on an extensive experimental comparison on classification problems involving 10 normalization methods, 3 state-of-the-art classifiers, and 38 benchmark datasets. We consider the classification task due to the simplicity of the experimental settings and well-defined metrics. However, our findings can be extrapolated for other time series mining tasks, such as forecasting or clustering. Based on our results, we suggest to evaluate the maximum absolute scale as an alternative to z-normalization. Besides being time efficient, this alternative shows promising results for similarity-based methods using Euclidean distance. For deep learning, mean normalization could be considered.