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Late-onset Alzheimer disease (AD) is a highly complex disease with multiple subtypes, as demonstrated by its disparate risk factors, pathological manifestations, and clinical traits. Discovery of biomarkers to diagnose specific AD subtypes is a key step towards understanding biological mechanisms underlying this enigmatic disease, generating candidate drug targets, and selecting participants for drug trials. Popular statistical methods for evaluating candidate biomarkers, fold change (FC) and area under the receiver operating characteristic curve (AUC), were designed for homogeneous data and we demonstrate the inherent weaknesses of these approaches when used to evaluate subtypes representing less than half of the diseased cases. We introduce a unique evaluation metric that is based on the distribution of the values, rather than the magnitude of the values, to identify analytes that are associated with a subset of the diseased cases, thereby revealing potential biomarkers for subtypes. Our approach, Bimodality Coefficient Difference (BCD), computes the difference between the degrees of bimodality for the cases and controls. We demonstrate the effectiveness of our approach with large-scale synthetic data trials containing nearly perfect subtypes. In order to reveal novel AD biomarkers for heterogeneous subtypes, we applied BCD to gene expression data for 8,650 genes for 176 AD cases and 187 controls. Our results confirm the utility of BCD for identifying subtypes of heterogeneous diseases. [ABSTRACT FROM AUTHOR]

Riverbeds often fine downstream, with a gravel‐bedded reach, a relatively abrupt gravel‐sand transition (GST), and a sand‐bedded reach. Underlying this behavior, bed grain size distributions are often bimodal, with a relative paucity (gap) around the range 1–5 mm. There is no general morphodynamic model capable of producing the grain size gap and gravel‐sand transition autogenically from a unimodal sediment supply. Here we use a one‐dimensional morphodynamic model including size‐specific bedload and suspended load transport, to show that bimodality readily evolves autogenically even under unimodal sediment feed. A GST forms when we include a floodplain width that abruptly increases at some point. Upstream of the transition, non‐gap gravel ceases to move and gap sediment is preferentially transported. At the transition, non‐gap sand rapidly deposits from suspension, enhancing gap sediment mobility and diluting its presence on the bed. Plain Language Summary: The bed surface layer of many rivers is a mixture of sand and gravel. This mixture is described by the probability distribution of grain sizes, and in particular by the median size. Consider the long profile of such a river. Surface median size commonly becomes finer downstream, but often changes abruptly from a value above 5 mm to a value below 1 mm over a short reach. The range 1–5 mm is termed "gap sediment." Here we explain how this abrupt change evolves, even when there is no deficit of gap sediment supplied to the reach, and even though particle abrasion is not included. The grain size distribution autogenically develops two peaks, one in the sand range and one in the gravel range above 5 mm. When abrupt floodplain widening is included, the gravel peak is stronger in the upper reach and the sand peak is stronger in the lower reach, leading to a relatively abrupt gravel‐sand transition. Gap sediment can be diluted both upstream and downstream by a combination of effects due to bedload and suspended load, so that it dominates nowhere in the grain size distribution. Key Points: Numerical simulations show that bed bimodality evolves autogenically, even with unimodal sediment feed and no abrasionAbrupt floodplain widening can lead to the formation of a distinct gravel‐sand transitionThe behavior can be explained by preferential mobility of 1–5 mm sediment over a sand bed combined with fallout of sand from suspension [ABSTRACT FROM AUTHOR]

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. Our objectives were to investigate the association of teat shape with (1) bimodality, (2) incremental milk flow rates (average flow rates during the first 15 s, 15–30 s, 30–60 s, and 60–120 s of milking), and (3) peak milk flow rate in Holstein dairy cows milked 3 times/d. In this prospective cohort study, we analyzed 220,928 milking observations that were collected from 2,520 cows from a single dairy herd over a period of 31 d. Teat shape was visually assessed and classified into 1 of 4 categories as follows: (1) triangular barrel and pointed teat end (TP), (2) square barrel and round teat end (SR), (3) square barrel, round teat end, and flat in the area of the teat orifice (SRF), and (4) square barrel and flat teat end (SF). Individual cow-level milk flow rates were obtained using electronic on-farm milk meters. We considered bimodality to be present if any of the incremental milk flow rates (flow rates during 15–30 s, 30–60 s, or 60–120 s) were lower than any of the previous rates (flow rates during the first 15 s, 15–30 s, or 30–60 s). The frequency distribution of cows with different teat shapes was as follows: TP, 96 (3.8%); SR, 1,751 (69.5%); SRF, 617 (24.5%); and SF, 56 (2.2%). A generalized linear mixed model revealed differences in the odds of bimodality among cows with different teat shapes. Compared with cows in category SR, the odds (95% CI) of bimodality of cows in other categories were as follows: TP, 0.68 (0.48–0.97); SF, 1.96 (1.21–3.19); and SRF, 1.46 (1.23–1.72). General linear mixed models indicated an association between teat shape and all incremental milk flow rates, with higher milk flow rates being present for cows with teat shapes in the SRF and SF categories. The general linear mixed model for the dependent variable peak milk flow rate indicated an association between teat shape and peak milk flow rate. Least squares means and 95% CI were 5.1 (4.9–5.3) kg/min for TP, 5.8 (5.5–6.1) kg/min for SF, 5.6 (5.5–5.7) for SRF, and 5.3 (5.3–5.4) for SR, respectively. We conclude that in this study cohort, bimodality is more likely to occur in cows with flat teat ends compared with those with a round teat ends. We attribute this relationship to the difference in milking speed across cows with different teat shapes. Teat shape may serve as a useful phenotype to identify cows that are more likely to exhibit bimodality. Because our study population was unique, future studies considering different circumstances such as breed, milking system, and milking routine are needed before results can be extrapolated. [ABSTRACT FROM AUTHOR]

This paper explores bimodal skew-symmetric distributions, a versatile family of distributions characterized by parameters that control asymmetry and kurtosis. These distributions encapsulate both symmetrical and well-known asymmetrical behaviors. A simulation study evaluates the model's estimation accuracy, detailing the score function and the robustness of the observed information matrix, which is proven to be non-singular under specific conditions. We apply the bimodal skew-normal model to protein data from cancer cells, comparing its performance against four established distributions supported on the entire real line. Results indicate superior performance by the proposed model, underscoring its potential for enhancing analytical precision in biological research. [ABSTRACT FROM AUTHOR]

The detection of male dimorphism has seen numerous statistical advances. Packard has recently criticized a widely used method, reanalyzing data from beetles and harvestmen using an alternative method. We disagree with Packard conclusions, probably due to different implicit definitions of male dimorphism. We consider that male dimorphism manifests in a distribution when it is significantly better described by a model with two values of central tendency (bimodality), rather than a model with only one (unimodality). Thus, while Packard suggests sigmoid allometries as alternatives to male dimorphism, we argue that such allometries are manifestations of mechanisms that generate bimodal distributions. Instead of focusing on this dichotomy, we propose an approach to test whether bimodality in a trait simply arises from its allometry by: (1) characterizing the trait static allometry, (2) simulating body size values based on original data parameters, and (3) generating new trait sizes using the static allometries. The percentage of simulations generating equal or greater bimodality than the data represents the likelihood that the bimodality can be explained by the allometry alone. Our method offers a null model linking sigmoid allometries and bimodal distributions, providing a test for mechanisms that accentuate trait bimodality beyond what the trait allometry generates. [ABSTRACT FROM AUTHOR]

Despite criticism for loss of information and power, dichotomization of variables is still frequently used in social, behavioral, and medical sciences, mainly because it yields more interpretable conclusions for research outcomes and is useful for decision making. However, the artificial choice of cut-points can be controversial and needs proper justification. In this work, we investigate the properties of point-biserial correlation after dichotomization with underlying bimodal Gaussian mixture distributions. We propose a dichotomous grouping procedure that considers the largest standardized difference in group mean while minimizing information loss. [ABSTRACT FROM AUTHOR]

The modality is an important topic for modelling. Using parametric models is an efficient way when real data set shows trimodality. In this paper, we propose a new class of trimodal probability distributions, that is, probability distributions that have up to three modes. Trimodality itself is achieved by applying a proper transformation to density function of certain continuous probability distributions. At first, we obtain preliminary results for an arbitrary density function $ g(x) $ g (x) and, next, we focus on the Gaussian case, studying trimodal Gaussian model more deeply. The Gaussian distribution is applied to produce the trimodal form of Gaussian known as normal distribution. The tractability of analytical expression of normal distribution and properties of the trimodal normal distribution are important reasons why we choose normal distribution. Furthermore, the existing distributions should be improved to be capable of modelling efficiently when there exists a trimodal form in a data set. After new density function is proposed, estimating its parameters is important. Since Mathematica 12.0 software has optimization tools and important modelling techniques, computational steps are performed using this software. The bootstrapped form of real data sets are applied to show the modelling ability of the proposed distribution when real data sets show trimodality. [ABSTRACT FROM AUTHOR]

Gradients of latitudinal diversity are one of the biogeographic features calling the most attention in ecology and macroecology. However, in pelagic communities of the marine environment, geographic trends and patterns are poorly known. We evaluated the latitudinal variation in species richness of marine planktonic copepods in the Eastern Pacific using spatial statistical models and approaches that mitigate and account for biases in occurrence data. A Boosted Regression Tree (BRT) and regression-Kriging based models allowed us to estimate and predict alpha diversity in poorly sampled regions, whereas beta diversity patterns were assessed using generalized dissimilarity analysis (GDM). Species richness showed a bimodal pattern, with a maximum of 291 species in the Northern Hemisphere and Tropical Eastern Pacific Ocean. Particulate Organic Carbon, salinity (max), spatial autocovariate, range of salinity and temperature, and Mixed Layer Depth, explained 85.2% of the latitudinal variability of copepods. Beta diversity was structured into four macrozones associated with the main water masses of the North and South Pacific.Our analytical approaches can overcome the limitations of data gaps, predicting greater diversity in subtropical and coastal areas, while providing insights into key drivers modulating spatial diversity patterns. [ABSTRACT FROM AUTHOR]

Skewness and bimodality properties are frequently observed when analyzing environmental data such as wind speeds, precipitation levels, and ambient temperatures. As an alternative to modeling data exhibiting these properties, we propose a flexible extension of the skew-logistic distribution. The proposal corresponds to a weighted version of the skewed logistic distribution, defined by a parametric weight function that allows shapes with up to three modes for the resulting density. Parameter estimation via the maximum likelihood approach is discussed. Simulation experiments are carried out to evaluate the performance of the estimators. Applications to environmental data illustrating the utility of the proposal are presented. [ABSTRACT FROM AUTHOR]

Abstract Riverbeds often fine downstream, with a gravel‐bedded reach, a relatively abrupt gravel‐sand transition (GST), and a sand‐bedded reach. Underlying this behavior, bed grain size distributions are often bimodal, with a relative paucity (gap) around the range 1–5 mm. There is no general morphodynamic model capable of producing the grain size gap and gravel‐sand transition autogenically from a unimodal sediment supply. Here we use a one‐dimensional morphodynamic model including size‐specific bedload and suspended load transport, to show that bimodality readily evolves autogenically even under unimodal sediment feed. A GST forms when we include a floodplain width that abruptly increases at some point. Upstream of the transition, non‐gap gravel ceases to move and gap sediment is preferentially transported. At the transition, non‐gap sand rapidly deposits from suspension, enhancing gap sediment mobility and diluting its presence on the bed.

With age, skeletal muscle stem cells (MuSCs) activate out of quiescence more slowly and with increased death, leading to defective muscle repair. To explore the molecular underpinnings of these defects, we combined multiomics, single-cell measurements, and functional testing of MuSCs from young and old mice. The multiomics approach allowed us to assess which changes are causal, which are compensatory, and which are simply correlative. We identified glutathione (GSH) metabolism as perturbed in old MuSCs, with both causal and compensatory components. Contrary to young MuSCs, old MuSCs exhibit a population dichotomy composed of GSHhigh cells (comparable with young MuSCs) and GSHlow cells with impaired functionality. Mechanistically, we show that antagonism between NRF2 and NF-κB maintains this bimodality. Experimental manipulation of GSH levels altered the functional dichotomy of aged MuSCs. These findings identify a novel mechanism of stem cell aging and highlight glutathione metabolism as an accessible target for reversing MuSC aging.

The beta model is the most important distribution for fitting data with the unit interval. However, the beta distribution is not suitable to model bimodal unit interval data. In this paper, we propose a bimodal beta distribution constructed by using an approach based on the alpha-skew-normal model. We discuss several properties of this distribution, such as bimodality, real moments, entropies and identifiability. Furthermore, we propose a new regression model based on the proposed model and discuss residuals. Estimation is performed by maximum likelihood. A Monte Carlo experiment is conducted to evaluate the performances of these estimators in finite samples with a discussion of the results. An application is provided to show the modelling competence of the proposed distribution when the data sets show bimodality. [ABSTRACT FROM AUTHOR]

This paper explores bimodal skew-symmetric distributions, a versatile family of distributions characterized by parameters that control asymmetry and kurtosis. These distributions encapsulate both symmetrical and well-known asymmetrical behaviors. A simulation study evaluates the model’s estimation accuracy, detailing the score function and the robustness of the observed information matrix, which is proven to be non-singular under specific conditions. We apply the bimodal skew-normal model to protein data from cancer cells, comparing its performance against four established distributions supported on the entire real line. Results indicate superior performance by the proposed model, underscoring its potential for enhancing analytical precision in biological research.

This paper introduces a novel three-parameter invertible bimodal Gumbel distribution, addressing the need for a versatile statistical tool capable of simultaneously modeling maximum and minimum extremes in various fields such as hydrology, meteorology, finance, and insurance. Unlike previous bimodal Gumbel distributions available in the literature, our proposed model features a simple closed-form cumulative distribution function, enhancing its computational attractiveness and applicability. This paper elucidates the behavior and advantages of the invertible bimodal Gumbel distribution through detailed mathematical formulations, graphical illustrations, and exploration of distributional characteristics. We illustrate using financial data to estimate Value at Risk (VaR) from our suggested model, considering maximum and minimum blocks simultaneously. [ABSTRACT FROM AUTHOR]

Background and aims: Hyperaccumulation is generally defined as plants exhibiting concentrations of metal(loid)s in their shoots at least an order of magnitude higher than that found in 'normal' plants, but this notional threshold appears to have limited statistical underpinning. The advent of massive (handheld) X-ray fluorescence datasets of herbarium specimens makes it increasingly important to accurately define threshold criteria for recognising hyperaccumulation of metal(loid)s such as manganese, cobalt, nickel, zinc, arsenic, selenium, and rare earth elements. Methods: We use an extensive dataset of X-ray fluorescence elemental data of ~ 27,000 herbarium specimens together with Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES) elemental data of 1710 specimens to corroborate threshold values for hyperaccumulator plants. The distribution of elemental data was treated as a Gaussian mixture model due to subpopulations within the dataset and sub-populations were clustered in 'normal' and 'hyperaccumulator' classes. The historical hyperaccumulator thresholds were compared to the concentrations corresponding to the value for which the cumulative distribution function of the Gaussian model of the hyperaccumulator class reaches a probability of 99%. Results: Our analysis of X-ray fluorescence data indicates that the historical thresholds for manganese (10,000 µg g−1), cobalt (300 µg g−1), nickel (1000 µg g−1), zinc (3000 µg g−1), arsenic (1000 µg g−1), and selenium (100 µg g−1) are substantially higher than then the concentrations required to have a 99% probability of falling in the hyperaccumulator class at 1210 µg g−1 for manganese, 32 µg g−1 for cobalt, 280 µg g−1 for nickel, 181 µg g−1 for zinc, 8 µg g−1 for arsenic, and 10 µg g−1 for selenium. All of the historical hyperaccumulation thresholds exceed the mean concentration of the hyperaccumulator populations and fall in the far-right tail of the models. Conclusions: The historical thresholds for manganese, cobalt, nickel, zinc, arsenic, and selenium are considerably higher than necessary to identify hyperaccumulators. Our findings provide a more precise understanding of the statistical underpinnings of the phenomenon of hyperaccumulation, which will ensure consistency in reporting on these plants. [ABSTRACT FROM AUTHOR]

This paper analyses the determinants of tourist length of stay in sharing accommodation. Methodologically, the paper proposes a new approach to account for the observed bimodality of length of stay. More specifically, the determinants of length of stay are analyzed by modeling both the conditional mean and conditional modal frequencies, which represent shorter and longer tourist stays, unlike previous contributions on length of stay where modeling has been based exclusively on the conditional mean. The empirical analysis examines the length of stay in sharing accommodation lodgings (Airbnb and Homeaway) of tourists visiting the Canary Islands (Spain) before and after the outbreak of the COVID-19 pandemic. The results show a bimodal distribution of length of stay: 1 and 7 nights in the pre-pandemic period, reduced to 1 and 2 nights in the pandemic period. The results also indicate that the model approach followed in this paper is preferable to other previous bimodality models in terms of estimation simplicity and fit. In addition, the model allows an analysis of the determinants of length of stay and differentiation of the influence of each determinant on shorter and longer stays. [ABSTRACT FROM AUTHOR]

Gradients of latitudinal diversity are one of the biogeographic features calling the most attention in ecology and macroecology. However, in pelagic communities of the marine environment, geographic trends and patterns are poorly known. We evaluated the latitudinal variation in species richness of marine planktonic copepods in the Eastern Pacific using spatial statistical models and approaches that mitigate and account for biases in occurrence data. A Boosted Regression Tree (BRT) and regression-Kriging based models allowed us to estimate and predict alpha diversity in poorly sampled regions, whereas beta diversity patterns were assessed using generalized dissimilarity analysis (GDM). Species richness showed a bimodal pattern, with a maximum of 291 species in the Northern Hemisphere and Tropical Eastern Pacific Ocean. Particulate Organic Carbon, salinity (max), spatial autocovariate, range of salinity and temperature, and Mixed Layer Depth, explained 85.2% of the latitudinal variability of copepods. Beta diversity was structured into four macrozones associated with the main water masses of the North and South Pacific.Our analytical approaches can overcome the limitations of data gaps, predicting greater diversity in subtropical and coastal areas, while providing insights into key drivers modulating spatial diversity patterns.

ABSTRACT: The objectives were to examine the effect of an automated premilking stimulation (APS) by means of a high pulsation frequency (300 cycles/min) without a reduction of the vacuum in the pulsation chamber or claw piece on (1) milking performance, (2) teat tissue condition, and (3) udder health in dairy cows. In a randomized controlled field study, Holstein cows (n = 427) from 1 commercial dairy farm with a milking schedule of 3 times per day were assigned to treatment and control groups over a 90-d period. Treatments consisted of a maximum of 80 s (APS80) or 99 s (APS99) of mechanical stimulation at a pulsation rate of 300 pulses per minute and a ratio of 25:75 (no reduction of the pulsation chamber or milking vacuum). Cows in the control group (CON) received traditional premilking stimulation by means of manual forestripping for 8 s. Milking characteristics were documented with on-farm milk meters. Short- and long-term changes in teat tissue condition induced by machine milking were assessed visually on a weekly basis. Composite milk samples were analyzed once per month to determine somatic cell count. Generalized linear mixed models were used to study the effect of the treatment on the outcome variables. We observed no meaningful differences in milk yield or milking unit-on time. Least squares means and their 95% confidence intervals (95% CI) for cows in the APS80, APS99, and CON groups were 13.5 (13.1–14.0), 13.2 (12.8–13.7), and 13.2 (12.8–13.7) kg for milk yield and 222 (213–231), 219 (210–228), and 223 (214–232) s for milking unit-on time, respectively. The effect of treatment on bimodality was modified by milk yield such that the odds of bimodality increased in the treatment groups with increasing milk yield. Compared with cows in the CON group, the odds ratios (95% CI) of bimodality were 1.08 (0.62–1.89) in the APS80 group and 0.89 (0.55–1.42) in the APS99 group at a milk yield of 11 kg and 2.0 (1.24–3.22) in the APS80 group and 2.08 (1.29–3.35) in the APS99 group at a milk yield of 16 kg. We observed differences in short- and long-term changes in teat tissue condition between the treatment and control groups. Compared with cows in the CON group, the odds (95% CI) of short-term changes were 1.87 (1.35–2.58) for the APS80 group and 1.49 (1.08–2.07) for the APS99 group, and the odds of long-term changes were 1.52 (1.24–1.85) for cows in the APS80 group and 1.59 (1.31–1.94) for cows in the APS99 group. The least squares means (95% CI) for somatic cell counts (log10-transformed) were 4.74 (4.68–4.81) for the APS80 group, 4.77 (4.71–4.83) for the APS99 group, and 4.79 (4.73–4.86) for the CON group. We conclude that the APS system tested here had no negative effects on milk yield or milking unit-on time. However, differences in bimodality and teat tissue condition suggest that the APS system did not provide sufficient stimulation to facilitate a gentle milk harvest and adversely affects teat tissue condition.

OBJECTIVES: This study aims to retrospectively assess C-lectin-like molecule 1 (CLL-1) bimodal expression on CD34+ blasts in acute myeloid leukemia (AML) patients (total N = 306) and explore potential CLL-1 bimodal associations with leukemia and patient-specific characteristics. METHODS: Flow cytometry assays were performed to assess the deeper immunophenotyping of CLL-1 bimodality. Cytogenetic analysis was performed to characterize the gene mutation on CLL-1-negative subpopulation of CLL-1 bimodal AML samples. RESULTS: The frequency of a bimodal pattern of CLL-1 expression of CD34+ blasts ranged from 8% to 65% in the different cohorts. Bimodal CLL-1 expression was most prevalent in patients with MDS-related AML (P = .011), ELN adverse risk (P = .002), NPM1 wild type (WT, P = .049), FLT3 WT (P = .035), and relatively low percentages of leukemia-associated immunophenotypes (P = .006). Additional immunophenotyping analysis revealed the CLL-1- subpopulation may consist of pre-B cells, immature myeloblasts, and hematopoietic stem cells. Furthermore, (pre)-leukemic mutations were detected in both CLL-1+ and CLL-1- subfractions of bimodal samples (N = 3). CONCLUSIONS: C-lectin-like molecule 1 bimodality occurs in about 25% of AML patients and the CLL-1- cell population still contains malignant cells, hence it may potentially limit the effectiveness of CLL-1-targeted therapies and warrant further investigation.

The length-biased Birnbaum-Saunders distribution is both useful and practical for environmental sciences. In this paper, we initially derive some new properties for the length-biased Birnbaum-Saunders distribution, showing that one of its parameters is the mode and that it is bimodal. We then introduce a new regression model based on this distribution. We implement the maximum likelihood method for parameter estimation, approach interval estimation and consider three types of residuals. An elaborate Monte Carlo study is carried out for evaluating the performance of the likelihood-based estimates, the confidence intervals and the empirical distribution of the residuals. Finally, we illustrate the proposed regression model with the use of a real meteorological data set. [ABSTRACT FROM AUTHOR]

The objectives were to examine the effect of an automated premilking stimulation (APS) by means of a high pulsation frequency (300 cycles/min) without a reduction of the vacuum in the pulsation chamber or claw piece on (1) milking performance, (2) teat tissue condition, and (3) udder health in dairy cows. In a randomized controlled field study, Holstein cows (n = 427) from 1 commercial dairy farm with a milking schedule of 3 times per day were assigned to treatment and control groups over a 90-d period. Treatments consisted of a maximum of 80 s (APS80) or 99 s (APS99) of mechanical stimulation at a pulsation rate of 300 pulses per minute and a ratio of 25:75 (no reduction of the pulsation chamber or milking vacuum). Cows in the control group (CON) received traditional premilking stimulation by means of manual forestripping for 8 s. Milking characteristics were documented with on-farm milk meters. Short- and long-term changes in teat tissue condition induced by machine milking were assessed visually on a weekly basis. Composite milk samples were analyzed once per month to determine somatic cell count. Generalized linear mixed models were used to study the effect of the treatment on the outcome variables. We observed no meaningful differences in milk yield or milking unit-on time. Least squares means and their 95% confidence intervals (95% CI) for cows in the APS80, APS99, and CON groups were 13.5 (13.1–14.0), 13.2 (12.8–13.7), and 13.2 (12.8–13.7) kg for milk yield and 222 (213–231), 219 (210–228), and 223 (214–232) s for milking unit-on time, respectively. The effect of treatment on bimodality was modified by milk yield such that the odds of bimodality increased in the treatment groups with increasing milk yield. Compared with cows in the CON group, the odds ratios (95% CI) of bimodality were 1.08 (0.62–1.89) in the APS80 group and 0.89 (0.55–1.42) in the APS99 group at a milk yield of 11 kg and 2.0 (1.24–3.22) in the APS80 group and 2.08 (1.29–3.35) in the APS99 group at a milk yield of 16 kg. We observed differences in short- and long-term changes in teat tissue condition between the treatment and control groups. Compared with cows in the CON group, the odds (95% CI) of short-term changes were 1.87 (1.35–2.58) for the APS80 group and 1.49 (1.08–2.07) for the APS99 group, and the odds of long-term changes were 1.52 (1.24–1.85) for cows in the APS80 group and 1.59 (1.31–1.94) for cows in the APS99 group. The least squares means (95% CI) for somatic cell counts (log 10 -transformed) were 4.74 (4.68–4.81) for the APS80 group, 4.77 (4.71–4.83) for the APS99 group, and 4.79 (4.73–4.86) for the CON group. We conclude that the APS system tested here had no negative effects on milk yield or milking unit-on time. However, differences in bimodality and teat tissue condition suggest that the APS system did not provide sufficient stimulation to facilitate a gentle milk harvest and adversely affects teat tissue condition. [ABSTRACT FROM AUTHOR]

One of the most widely known probability distributions used to explain the probabilistic behavior of positive data is the log-normal (LN). Although the LN distribution is capable of adjusting data types, it is not always fully true that the model manages to adequately model the behavior of the response of interest since in some cases, the degree of skewness and/or kurtosis of the data are greater or less than those that the LN distribution can capture. Another peculiarity of the LN distribution is that it only fits unimodal positive data, which constitutes a limitation when dealing with data that present more than one mode (bimodality). On the other hand, the log-normal model only fits unimodal positive data and in reality there are multiple applications where the behavior of materials is bimodal. To fill this gap, this paper introduces a new probability distribution that is capable of fitting unimodal or bimodal positive data with a high or low degree of skewness and/or kurtosis. The new distribution is a generalization of the LN distribution. For the new proposal, its main properties are studied and the process of estimation of the parameters involved in the model is carried out from a classical perspective using the maximum likelihood method. An important feature of this distribution is the non-singularity of the Fisher information matrix, which guarantees the use of asymptotic theory to study the properties of the parameter estimators. A Monte Carlo type simulation study is carried out to evaluate the properties of the estimators and finally, an illustration is presented with a set of data related to the concentration of nickel in soil samples, allowing to show that the proposed distribution fits extremely well in certain situations. [ABSTRACT FROM AUTHOR]

A bimodal double log-normal distribution on the real line is proposed using the random sign mixture transform. Its associated statistical inferences are derived. Its parameters are estimated by the maximum likelihood method. The performance of the estimators and the corresponding confidence intervals is checked by simulation studies. Application of the proposed distribution to a real data set from a DNA microarray is presented. [ABSTRACT FROM AUTHOR]

Fine-grained strata deposited on the Eastern Siberian craton are predominantly considered to mainly consist of Neoproterozoic sandstones. Clastic rocks near the unconformity border of the Ediacaran and the Riphean are represented by sandstone and siltstone layers with thicknesses of several tens of meters, belonging to the Nepa, Tira, and Byuk horizons in the Nepa–Botuoba region. These Neoproterozoic sandstones have features characteristic of aeolianites formed under the action of high wind velocity in the Ediacaran period. Sandstone samples near the Riphean–Ediacaran boundary were collected from five deep wells and characterized for granulometry and mineral composition using optical microscopy, XRD, SEM, and ICP-MS techniques. These sandstones have a high proportion of quartz (60–98%) with minor amounts of feldspars, carbonate, and sulfate cements. Thin sections of the sandy rocks feature bimodal distributions of the grains throughout many sections, with large well-rounded quartz grains being several orders of magnitude greater than the silt matrix grains. The monomineralic quartz rocks have an overgrowth of quartz grains. These rocks can be petroleum reservoirs with good porosity and permeability, but in most of the studied intervals, a high content of anhydrite and dolomite interstitial cement significantly reduces both. The porosity of the rocks is low, while the permeability is very low, which may be associated with a significant amount of clay and cement material. Aeolianites normally contain large amounts of bimodal quartz (due to its high stability and resistance to weathering) and possess the presence of heavy minerals. [ABSTRACT FROM AUTHOR]

The aim of this expository paper is to present the properties of the linear skew-t distribution, which is a specific example of a symmetry modulated-distribution. The skewing function remains the distribution function of Student’s t, but its argument is simpler than that used for the standard skew-t. The linear skew-t offers different insights, for example, different moments and tail behavior, and can be simpler to use for empirical work. It is shown that the distribution may be expressed as a hidden truncation model. The paper describes an extended version of the distribution that is analogous to the extended skew-t. For certain parameter values, the distribution is bimodal. The paper presents expressions for the moments of the distribution and shows that numerical integration methods are required. A multivariate version of the distribution is described. The bivariate version of the distribution may also be bimodal. The distribution is not closed under marginalization, and stochastic ordering is not satisfied. The properties of the distribution are illustrated with numerous examples of the density functions, table of moments and critical values. The results in this paper suggest that the linear skew-t may be useful for some applications, but that it should be used with care for methodological work.

Skewness and bimodality properties are frequently observed when analyzing environmental data such as wind speeds, precipitation levels, and ambient temperatures. As an alternative to modeling data exhibiting these properties, we propose a flexible extension of the skew-logistic distribution. The proposal corresponds to a weighted version of the skewed logistic distribution, defined by a parametric weight function that allows shapes with up to three modes for the resulting density. Parameter estimation via the maximum likelihood approach is discussed. Simulation experiments are carried out to evaluate the performance of the estimators. Applications to environmental data illustrating the utility of the proposal are presented.

This study examines daily longitudinal locations of South Asia High (SAH) in September and its connection with Asian September rainfall variation. Results suggest that daily longitudinal locations of September SAH exhibits as bimodality, which is featured by two preferable locations with one high‐frequency location lying over southern Tibetan Plateau and the other over southern Iranian Plateau. Referred to the two preferred locations, the SAH is classified into east and west SAH mode. The two modes may be attributed to a warm column over central eastern Tibetan or eastern Iranian Plateau, which warms the above troposphere and maintains a SAH at upper troposphere over corresponding location. In addition, bimodality of the SAH has a close relationship with Asian September rainfall. The east mode of SAH is associated with an increasing rainfall over western China and decreasing rainfall over northern Indian Peninsula, southwestern Tibetan Plateau, Indochina Peninsula, eastern China and Korea Peninsula, while the west mode of SAH is linked with the reverse pattern. Specifically, the atmospheric circulation at upper troposphere is featured by one large anticyclonic circulation above eastern Tibetan Plateau and two cyclonic circulations over northern Iranian Plateau and eastern Korea. In the lower troposphere, southerly and northerly anomalies form a convergence zone over western China. Meantime, a cyclonic moisture circulation with warm and wet southerly vapour flow results in above‐normal rainfall over western China. An anticyclone over northern Iranian Plateau at lower troposphere results in an anticyclonic moisture divergence and deficient rainfall over southwestern Tibetan Plateau and northern India. Moreover, a cyclonic circulation over eastern Korea Peninsula with marked northwesterly and moisture flux divergence results in below‐normal rainfall over eastern China and Korea Peninsula. [ABSTRACT FROM AUTHOR]

The current paper focused on Robertson's and Fryer's (1969) conditions applied to determine the existence of bimodality in the mixture of normals. Best modality test is a pre-requisite to evaluate whether the existing data is unimodal or bimodal. On the basis of the same data, the researchers also assessed bimodality through modality tests. For this purpose, modality tests were compared on the basis of size and power properties designed by Monte Carlo simulations. The results showed that all modality tests were of stable sizes, that is, around the nominal size of 5% on the basis of simulated critical values. In view of power assesment, the Silverman Bandwidth test was found to be the best performer test which was also justified by the real data examples. [ABSTRACT FROM AUTHOR]

In extreme values theory, for a sufficiently large block size, the maxima distribution is approximated by the generalized extreme value (GEV) distribution. The GEV distribution is a family of continuous probability distributions, which has wide applicability in several areas, including hydrology, engineering, science, ecology, and finance. However, the GEV distribution is not suitable for modeling extreme bimodal data. In this paper, we propose an extension of the GEV distribution that incorporates an additional parameter. The additional parameter introduces bimodality and aries tail weight, i.e., this proposed extension is more flexible than the GEV distribution. Inference for the proposed distribution was performed under the likelihood paradigm. A Monte Carlo experiment is conducted to evaluate the performances of these estimators in finite samples with a discussion of the results. Finally, the proposed distribution is applied to environmental data sets, illustrating their capabilities in challenging cases in extreme value theory. [ABSTRACT FROM AUTHOR]

Efficient machine milking requires an optimal interaction of alveolar milk ejection in the udder and milk removal by the milking machine. The aim of the present study was to test whether the equilibrium between continuous milk ejection and milk removal can also be maintained at very fast milking through a particularly high vacuum. Eight Holstein dairy cows were milked at 42, 52, or 60 kPa, with (PS) or without (nPS) prestimulation. Each of the 6 treatments was conducted at 2 afternoon milkings in each animal. The prestimulation lasted 40 s and consisted of forestripping and teat cleaning. The cluster attachment followed after a 20-s latency period. Throughout each milking, B-mode ultrasound videos of the gland cistern of 1 front quarter as well as milk flow and claw vacuum curves were recorded. Total milk yield was neither affected by nPS or PS nor by the vacuum level. Milk removed within the first minute and the first 2 min of milking and average milk flow were higher, and the duration of incline and time until peak milk flow were shorter at PS than at nPS milkings at all vacuum levels. Machine-on time was shorter at PS than at nPS milkings, although only at 42 and 52 kPa vacuum, obviously caused by the high percentage of bimodalities occurring in nPS milkings (17% bimodalities in PS vs. 92% bimodalities in nPS milkings). The frequency of bimodalities was higher at high than at low vacuum both in PS and nPS milkings. Peak flow rate and average milk flow were both higher at higher vacuum levels. The duration of milk flow plateau was shorter at 60 kPa than at 42 kPa milkings. At the highest vacuum (60 kPa), the shorter plateau phase indicated a declining milk ejection rate toward the end of the plateau phase, and milk ejection could no longer keep up with the fast milk removal; hence, a higher milking efficiency at a higher vacuum level could only be achieved as long as the gland cistern remained sufficiently filled by the continuous milk ejection. The ultrasound imaging confirmed this finding as the duration of cisternal area plateau in the recorded front quarter was shorter at high than at low vacuum. Thus, the highest vacuum of 60 kPa did not cause a shorter machine-on time than 52 kPa. In conclusion, milking at a very high vacuum can increase milking efficiency compared with a low vacuum. However, a vacuum reduction at the start and toward the end of milking is required to prevent overmilking if milking is performed at a very high vacuum. [ABSTRACT FROM AUTHOR]

The aim of this expository paper is to present the properties of the linear skew-t distribution, which is a specific example of a symmetry modulated-distribution. The skewing function remains the distribution function of Student's t, but its argument is simpler than that used for the standard skew-t. The linear skew-t offers different insights, for example, different moments and tail behavior, and can be simpler to use for empirical work. It is shown that the distribution may be expressed as a hidden truncation model. The paper describes an extended version of the distribution that is analogous to the extended skew-t. For certain parameter values, the distribution is bimodal. The paper presents expressions for the moments of the distribution and shows that numerical integration methods are required. A multivariate version of the distribution is described. The bivariate version of the distribution may also be bimodal. The distribution is not closed under marginalization, and stochastic ordering is not satisfied. The properties of the distribution are illustrated with numerous examples of the density functions, table of moments and critical values. The results in this paper suggest that the linear skew-t may be useful for some applications, but that it should be used with care for methodological work. [ABSTRACT FROM AUTHOR]

This article introduces a bimodal model based on the epsilon-skew-normal distribution. This extension generates bimodal distributions similar to those produced by the mixture of normal distributions. We study the basic properties of this new family. We apply maximum likelihood estimators, calculate the information matrix and present a simulation study to assess parameter recovery. Finally, we illustrate the results to three real data sets, suggesting this new distribution as a plausible alternative for modelling bimodal data. [ABSTRACT FROM AUTHOR]

The genus Agave presents a bimodal karyotype with x = 30 (5L, large, +25S, small chromosomes). Bimodality within this genus is generally attributed to allopolyploidy in the ancestral form of Agavoideae. However, alternative mechanisms, such as the preferential accumulation of repetitive elements at the macrochromosomes, could also be important. Aiming to understand the role of repetitive DNA within the bimodal karyotype of Agave, genomic DNA from the commercial hybrid 11648 (2n = 2x = 60, 6.31 Gbp) was sequenced at low coverage, and the repetitive fraction was characterized. In silico analysis showed that ~67.6% of the genome is mainly composed of different LTR retrotransposon lineages and one satellite DNA family (AgSAT171). The satellite DNA localized at the centromeric regions of all chromosomes; however, stronger signals were observed for 20 of the macro- and microchromosomes. All transposable elements showed a dispersed distribution, but not uniform across the length of the chromosomes. Different distribution patterns were observed for different TE lineages, with larger accumulation at the macrochromosomes. The data indicate the differential accumulation of LTR retrotransposon lineages at the macrochromosomes, probably contributing to the bimodality. Nevertheless, the differential accumulation of the satDNA in one group of macro- and microchromosomes possibly reflects the hybrid origin of this Agave accession. [ABSTRACT FROM AUTHOR]

Probability distribution functions (PDFs) of atmospheric reentry latitude predictions are shown to be bimodal for spacecraft in low-eccentricity, prograde low Earth orbits at altitudes of 300 km and lower. Using two-line element (TLE) data for initial orbit conditions, coupled with coarse estimates for spacecraft aerodynamic characteristics, parametric simulations produce bimodal distributions that suggest a greater likelihood of reentry near the latitudinal maxima of a given spacecraft's ground track. Various computational measures are used to test for and quantify bimodality in the reentry latitude data sets. Also, a method for approximating bandwidth is introduced for the kernel estimation of reentry latitude probability density. Overall, statistical analysis indicates that actual reentry latitudes are generally within 1-σ of observed hemisphere means as demonstrated by six historical reentry cases. [ABSTRACT FROM AUTHOR]

This paper introduces a novel three-parameter invertible bimodal Gumbel distribution, addressing the need for a versatile statistical tool capable of simultaneously modeling maximum and minimum extremes in various fields such as hydrology, meteorology, finance, and insurance. Unlike previous bimodal Gumbel distributions available in the literature, our proposed model features a simple closed-form cumulative distribution function, enhancing its computational attractiveness and applicability. This paper elucidates the behavior and advantages of the invertible bimodal Gumbel distribution through detailed mathematical formulations, graphical illustrations, and exploration of distributional characteristics. We illustrate using financial data to estimate Value at Risk (VaR) from our suggested model, considering maximum and minimum blocks simultaneously.

Elucidating the design principles of regulatory networks driving cellular decision-making has important implications for understanding cell differentiation and guiding the design of synthetic circuits. Mutually repressing feedback loops between 'master regulators' of cell fates can exhibit multistable dynamics enabling "single-positive" phenotypes: (high A, low B) and (low A, high B) for a toggle switch, and (high A, low B, low C), (low A, high B, low C) and (low A, low B, high C) for a toggle triad. However, the dynamics of these two motifs have been interrogated in isolation in silico, but in vitro and in vivo, they often operate while embedded in larger regulatory networks. Here, we embed these motifs in complex larger networks of varying sizes and connectivity to identify hallmarks under which these motifs maintain their canonical dynamical behavior. We show that an increased number of incoming edges onto a motif leads to a decay in their canonical stand-alone behaviors. We also show that this decay can be exacerbated by adding self-inhibition but not self-activation loops on the 'master regulators'. These observations offer insights into the design principles of biological networks containing these motifs and can help devise optimal strategies for the integration of these motifs into larger synthetic networks. [ABSTRACT FROM AUTHOR]

One of the most widely known probability distributions used to explain the probabilistic behavior of positive data is the log-normal (LN). Although the LN distribution is capable of adjusting data types, it is not always fully true that the model manages to adequately model the behavior of the response of interest since in some cases, the degree of skewness and/or kurtosis of the data are greater or less than those that the LN distribution can capture. Another peculiarity of the LN distribution is that it only fits unimodal positive data, which constitutes a limitation when dealing with data that present more than one mode (bimodality). On the other hand, the log-normal model only fits unimodal positive data and in reality there are multiple applications where the behavior of materials is bimodal. To fill this gap, this paper introduces a new probability distribution that is capable of fitting unimodal or bimodal positive data with a high or low degree of skewness and/or kurtosis. The new distribution is a generalization of the LN distribution. For the new proposal, its main properties are studied and the process of estimation of the parameters involved in the model is carried out from a classical perspective using the maximum likelihood method. An important feature of this distribution is the non-singularity of the Fisher information matrix, which guarantees the use of asymptotic theory to study the properties of the parameter estimators. A Monte Carlo type simulation study is carried out to evaluate the properties of the estimators and finally, an illustration is presented with a set of data related to the concentration of nickel in soil samples, allowing to show that the proposed distribution fits extremely well in certain situations.

The bimodal and unimodal seasonal cycles of surface Chlorophyll-a (Chl-a) concentration (SCC) are ubiquitous in the mid-latitude oceans. The nutrient and light are regarded as two key factors affecting such seasonal differences. However, our quantitative knowledge of distinguishing these two factors is still inadequate in mid-latitude regions where they limit primary productivity simultaneously. It hinders the full understanding of the underlying mechanisms of seasonal blooms. In this study, the bimodal and unimodal variations of SCC in the Kuroshio Extension (KE) region have been investigated, with a special focus on the emergence latitudes of the secondary peak, i.e., the phytoplankton fall bloom. Based on satellite observations, we have found that the SCC bloom emerges in spring and fall in the northern region, and that spring (fall) bloom starts later (earlier) as the latitude gets higher. In the southern part of KE, by contrast, the SCC tends to peak in late winter or early spring with its bloom time delaying gradually with increasing latitude. A regression model regarding the role of the nutrient and light has been proposed to reconstruct the seasonal variations of the observed SCC, and the relative contributions of the two factors have been assessed quantitatively. It is shown that the regression model has reasonably captured the seasonal variations of SCC in terms of the bimodal/unimodal feature as well as the time of occurrence. Specifically, we have found the boundary between bimodality and unimodality areas moves northward as KE flows eastward, which corresponds to the equivalent contribution of the nutrient and light to the SCC variation and the eastward-decreasing nutrient at the same latitude. Moreover, we have used the model to explore the lag effect of light on regulating the seasonal cycle of SCC, which is associated with the light-heating process, the resultant ocean vertical stratification and the nutrient deficiency, the time interval between the growth rate and SCC, as well as light attenuation within the mixed layer. In the context of global warming, our study has provided insights into the switch pattern between bimodality and unimodality of SCC in mid-latitude oceans.

This paper documents the bimodality of momentum stocks: both high- and low-momentum stocks have nontrivial probabilities for both high and low returns. The bimodality makes the momentum strategy fundamentally risky and can cause a large loss. To alleviate the bimodality and improve return predictability, this paper develops a novel cross-sectional prediction model via machine learning. By reclassifying stocks based on their predicted financial performance, the model significantly outperforms off-the-shelf machine learning models. Tested on the U.S. market, a value-weighted long-short portfolio earns a monthly alpha of 2.4% (t-statistic = 6.63) when regressed against the Fama–French five factors plus the momentum and short-term reversal factors. This paper was accepted by Kay Giesecke, finance. [ABSTRACT FROM AUTHOR]

This study investigates the short‐term transition process between the Kuroshio Extension (KE) stable and unstable states (bimodality) based on eddy energetics analysis. The local dynamic mechanisms modulating the KE transitions are revealed by exploring the eddy kinetic energy (EKE) variability. During the stable‐to‐unstable transitions (low‐to‐high EKE level; SU), baroclinic instability is the major source of EKE growth. As the negative sea surface height anomaly (SSHa) signal propagates westward near the KE domain, the KE jet downstream (150°E–155°E) slows down at first but its upstream (140°E–145°E) remains fast. The great upstream vertical shear is conducive to the strong regional baroclinic instability. The difference in velocity between the KE upstream and downstream leads to the positive velocity anomaly and the strengthening of vertical velocity shears in the midstream (145°E–150°E). Hence, the baroclinic instability in the KE upstream and midstream facilitates the growth of EKE, thereby inducing the KE path to transform from a stable into an unstable state. During the unstable‐to‐stable transitions (high‐to‐low EKE level; US), the combination of advection and eddy wind work plays a key role in reducing EKE. With the positive SSHa signal arriving at the south of the KE axis, the KE jet speeds up. In this situation, more EKE is advected, especially from the KE midstream, into the downstream where wind dissipation takes effect. When most eddies are consumed, the KE path becomes more stable. Plain Language Summary: The Kuroshio is a strong northerly current on the western boundary of the North Pacific, connecting with the North Equatorial Current to the south and the Kuroshio Extension (KE) to the north. The KE region is one of the most powerful regions of eddy activity in the world, and its eddy intensity presents two remarkable states (weak and strong), which indicates the decadal KE dynamic bimodality (stable and unstable states). Numerous previous studies investigated such a KE bimodality from a low‐frequency variability perspective. In the present study, we mainly focus on the short‐term transition process (STP) between the KE bimodality. The STP is triggered by sea surface height anomaly (SSHa) associated with the westward‐propagating Rossby wave, originating in the Pacific Decadal Oscillation. When the SSHa approaches the KE domain, the KE jet undergoes a great change. Furthermore, the enhanced baroclinic instability facilitates the KE transforming from a stable to an unstable state. On the contrary, the combination of horizontal advection and wind dissipation is responsible for the unstable‐to‐stable process. Key Points: The local processes of the Kuroshio Extension (KE) transitions are triggered by sea surface height anomaly signals associated with the westward‐propagating Rossby waveThe enhancement of baroclinic instability is responsible for the KE path stable‐to‐unstable transitionsThe combination of intensified advection and wind dissipation enables the KE to convert from an unstable state into a stable state [ABSTRACT FROM AUTHOR]

Reaching population immunity against COVID‐19 is proving difficult even in countries with high vaccination levels. Thus, it is critical to identify limits of control and effective measures against future outbreaks. The effects of nonpharmaceutical interventions (NPIs) and vaccination strategies are analyzed with a detailed community‐specific agent‐based model (ABM). The authors demonstrate that the threshold for population immunity is not a unique number, but depends on the vaccination strategy. Prioritizing highly interactive people diminishes the risk for an infection wave, while prioritizing the elderly minimizes fatalities when vaccinations are low. Control over COVID‐19 outbreaks requires adaptive combination of NPIs and targeted vaccination, exemplified for Germany for January–September 2021. Bimodality emerges from the heterogeneity and stochasticity of community‐specific human–human interactions and infection networks, which can render the effects of limited NPIs uncertain. The authors' simulation platform can process and analyze dynamic COVID‐19 epidemiological situations in diverse communities worldwide to predict pathways to population immunity even with limited vaccination. [ABSTRACT FROM AUTHOR]

We use natural language processing (NLP) to retrieve location data for cheilostome bryozoan species (text-mined occurrences (TMO)) in an automated procedure. We compare these results with data combined from two major public databases (DB): the Ocean Biodiversity Information System (OBIS), and the Global Biodiversity Information Facility (GBIF). Using DB and TMO data separately and in combination, we present latitudinal species richness curves using standard estimators (Chao2 and the Jackknife) and range-through approaches. Our combined DB and TMO species richness curves quantitatively document a bimodal global latitudinal diversity gradient for extant cheilostomes for the first time, with peaks in the temperate zones. A total of 79% of the georeferenced species we retrieved from TMO (N = 1,408) and DB (N = 4,549) are non-overlapping. Despite clear indications that global location data compiled for cheilostomes should be improved with concerted effort, our study supports the view that many marine latitudinal species richness patterns deviate from the canonical latitudinal diversity gradient (LDG). Moreover, combining online biodiversity databases with automated information retrieval from the published literature is a promising avenue for expanding taxon-location datasets. [ABSTRACT FROM AUTHOR]

Stem growth responses to soil and atmospheric drought are critical to forecasting the tree carbon sink strength. Yet, responses of drought-prone forests remain uncertain despite global aridification trends. Stem diameter variations at an hourly resolution were monitored in five Mediterranean tree species from a mesic and a xeric site for 6 and 12 years. Stem growth and dehydration responses to soil (REW) and atmospheric (VPD) drought were explored at different timescales. Annually, growth was determined by the number of growing days and hours. Seasonally, growth was bimodal (autumn growth ≈ 8%-18% of annual growth), varying among species and sites across the hydrometeorological space, while dehydration consistently responded to REW. Sub-daily, substantial growth occurred during daytime, with nighttime-to-daytime ratios ranging between 1.2 and 3.5 (Arbutus unedo ≈ Quercus faginea < Quercus ilex < Pinus halepensis in the mesic site, and Juniperus thurifera < P. halepensis in the xeric site). Overall, time windows favourable for growth were limited by soil (rather than atmospheric) drought, modulating annual and seasonal growth in Mediterranean species, and stems maintained non-negligible growth during daytime. These patterns contrast with observations from wetter or cooler biomes, demonstrating the growth plasticity of drought-prone species to more arid climate conditions., (© 2024 The Author(s). Plant, Cell & Environment published by John Wiley & Sons Ltd.)

The objectives of this study were to evaluate the effect of supplemental premilking stimulation, provided after manual stimulation, by means of high-frequency pulsation without reduction of the vacuum in the pulsation chamber on milking performance, teat tissue condition, udder health, and well-being in dairy cows. In a randomized controlled trial, Holstein cows (n = 491) from 1 commercial dairy farm with a thrice-per-day milking schedule were assigned to treatment and control groups over a 64-d period. Treatments consisted of a maximum of 20 s of pulsation stimulation at a pulsation rate of 100 (SPS100) or 300 (SPS300) cycles per minute and a pulsation ratio of 25:75, which were applied after completion of manual premilking stimulation upon milking unit attachment. Cows in the control group (CON) received only traditional premilking stimulation by manual forestripping for 6 s, and wiping. Milking characteristics were measured with on-farm milk flow meters. Milking machine-induced short-term (swelling at teat base, firmness at teat end, and teat discoloration) and long-term (teat-end callosity) changes to the teat tissue were assessed manually and visually. Composite milk samples were analyzed for somatic cell counts. Cow hind-leg activity was assessed with 3-dimensional accelerometers. Fecal 11,17-dioxoandrostanes (11,17-DOAs; a group of cortisol metabolites) were determined on wk 4 and 8 to assess the well-being of the cows. Generalized linear mixed models were used to study the effect of treatments on the outcome variables milk yield/milking and milking unit-on time. We observed no meaningful differences among groups for milk yield or milking unit-on time. Least squares means and their 95% confidence intervals (95% CI) for cows in the SPS100, SPS300, and CON groups were 13.9 (13.3-14.5), 14.0 (13.4-14.6), and 13.9 (13.3-14.6) kg for milk yield and 218 (212-224), 218 (211-224), and 218 (212-224) s for milking unit-on time, respectively. Compared with cows in the CON group, the odds (95% CI) of short-term changes were 1.30 (0.95-1.78) for the SPS100 group and 1.50 (1.10-2.05) for the SPS300 group. The odds of long-term changes were 0.94 (0.67-1.34) for cows in the SPS100 group and 0.71 (0.49-1.04) for cows in the SPS300 group. We observed no differences in SCC. In reference to the CON group, the hazard ratio (95% CI) in SPS100 and SPS300, respectively, were 0.35 (0.13-0.98) and 1.22 (0.57-2.64) for clinical mastitis, and 0.34 (0.12-0.95) and 1.28 (0.60-2.73) for culling. The least squares means (95% CI) of hind-leg activity during milking were 8.3 (6.5-10.5), 10.6 (8.1-13.7), and 9.1 (7.2-11.6) movements per milking for the SPS100, SPS300, and CON groups, respectively. The least squares means (95% CI) of fecal 11,17-DOAs concentration (ng/g) at the first and second test days, respectively, were 31.1 (28.1-34.2) and 22.3 (19.2-25.4) for the SPS100 group, 26.4 (23.4-29.4) and 25.2 (22.0-28.4) for the SPS300 group, and 24.8 (21.8-27.9) and 25.0 (21.7-28.3) for the CON group. We conclude that applying supplemental stimulation after manual stimulation through the high-frequency pulsation system tested here did not impart additional benefits to the milk harvesting process, teat tissue condition, somatic cell count, or the well-being of the animals., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Abstract Reaching population immunity against COVID‐19 is proving difficult even in countries with high vaccination levels. Thus, it is critical to identify limits of control and effective measures against future outbreaks. The effects of nonpharmaceutical interventions (NPIs) and vaccination strategies are analyzed with a detailed community‐specific agent‐based model (ABM). The authors demonstrate that the threshold for population immunity is not a unique number, but depends on the vaccination strategy. Prioritizing highly interactive people diminishes the risk for an infection wave, while prioritizing the elderly minimizes fatalities when vaccinations are low. Control over COVID‐19 outbreaks requires adaptive combination of NPIs and targeted vaccination, exemplified for Germany for January–September 2021. Bimodality emerges from the heterogeneity and stochasticity of community‐specific human–human interactions and infection networks, which can render the effects of limited NPIs uncertain. The authors' simulation platform can process and analyze dynamic COVID‐19 epidemiological situations in diverse communities worldwide to predict pathways to population immunity even with limited vaccination.

Fine-grained strata deposited on the Eastern Siberian craton are predominantly considered to mainly consist of Neoproterozoic sandstones. Clastic rocks near the unconformity border of the Ediacaran and the Riphean are represented by sandstone and siltstone layers with thicknesses of several tens of meters, belonging to the Nepa, Tira, and Byuk horizons in the Nepa–Botuoba region. These Neoproterozoic sandstones have features characteristic of aeolianites formed under the action of high wind velocity in the Ediacaran period. Sandstone samples near the Riphean–Ediacaran boundary were collected from five deep wells and characterized for granulometry and mineral composition using optical microscopy, XRD, SEM, and ICP-MS techniques. These sandstones have a high proportion of quartz (60–98%) with minor amounts of feldspars, carbonate, and sulfate cements. Thin sections of the sandy rocks feature bimodal distributions of the grains throughout many sections, with large well-rounded quartz grains being several orders of magnitude greater than the silt matrix grains. The monomineralic quartz rocks have an overgrowth of quartz grains. These rocks can be petroleum reservoirs with good porosity and permeability, but in most of the studied intervals, a high content of anhydrite and dolomite interstitial cement significantly reduces both. The porosity of the rocks is low, while the permeability is very low, which may be associated with a significant amount of clay and cement material. Aeolianites normally contain large amounts of bimodal quartz (due to its high stability and resistance to weathering) and possess the presence of heavy minerals.

A bimodal double log-normal distribution on the real line is proposed using the random sign mixture transform. Its associated statistical inferences are derived. Its parameters are estimated by the maximum likelihood method. The performance of the estimators and the corresponding confidence intervals is checked by simulation studies. Application of the proposed distribution to a real data set from a DNA microarray is presented.