Bimodal Ones Research Articles

Hybrid Onion Layered System for the Analysis of Collective Subjectivity in Social Networks

This research aims to analyze the Digital Social Networks (DSN) behavior, constructed from the network’s relationships, interactions, and expressions of users’ private states through collective subjectivity. For this purpose, an onion-ring system called COSSOL has been built in a case study for Twitter, following a hybrid approach to integrate Machine Learning classifiers and structural metrics from Computational Linguistics and Computational Sociology disciplines, respectively. The paper designs two experimentation scenarios divided into cases of collective subjectivity analysis for Colombia under different levels of communities’ granularity. The first case validates the system by performing a cointegration test on the metrics of each construct for the onion rings’ communities. The results show that some communities better propagate their subjective expressions against the disclosed topic when they have a higher network density and a common polarity. Moreover, the most stable communities in polarity towards a topic are those whose members are highly connected. Conversely, communities with a higher centrality index in a subset of members do not exhibit stability in collective subjectivity towards a topic disclosed in that community. The second case validates the model with a series of Social Network Analysis (SNA) metrics with a polarity layer to describe the second onion ring subcommunities and their temporal variation through community recalculation. The results show no polar distributions similar to the bimodal ones representing consensus in the values of the common Thinking Acting and Feeling (TAF) forms. In addition, general negative sentiment is identified for the ten most representative nodes of the subcommunities analyzed.

Discrimination of benign and malignant solid breast masses using deep residual learning-based bimodal computer-aided diagnosis system

One of the most common breast cancer mammographic manifestation is solid mass. If the information obtained from mammography is inadequate, complementary modalities such as ultrasound imaging are used to achieve additional information. Although interest in the combination of information from different modalities is increasing, it is an extremely challenging task. In this regard, a computer-aided diagnosis (CAD) system can be an efficient solution to overcome these difficulties. However, most of the studies have focused on the development of mono-modal CAD systems, and a few existing bimodal ones rely on the extracted hand-crafted features of mammograms and sonograms. In order to meet these challenges, this paper proposes a novel bimodal deep residual learning model. It consists of the following major steps. First, the informative representation for each input image is separately constructed. Second, in order to construct the high-level joint representation of every two input images and effectively explore complementary information among them, the representation layers of them are fused. Third, all of these joint representations are fused to obtain the final common representation of the input images for the mass. Finally, the recognition result is obtained based on information extracted from all input images. The augmentation strategy was applied to enlarge the collected dataset for this study. Best recognition results on the sensitivity, specificity, F1-score, area under ROC curve, and accuracy metrics of 0.898, 0.938, 0.916, 0.964, and 0.917, respectively, are achieved by our model. Extensive experiments demonstrate the effectiveness and superiority of the proposed model over other state-of-the-art models.

Effect of bimodal powder blends on part density and melt pool fluctuation in laser powder bed fusion

The final part density in laser powder bed fusion is influenced by the powder particle size distribution. Too fine powders are not spreadable, and too coarse powders cause porosity. Powder blends, especially bimodal ones, can exhibit higher packing densities and changes in flowability compared to their monomodal constituents. These properties can influence final part density. Therefore, the influence of bimodal powder on final part density was investigated. Two gas atomized 316L (1.4404) powders with a D50 of 20.3 µm and 60.3 µm were blended at weight ratios of 3:1, 1:1, and 1:3, and the original and blended powders were processed. The results show that the final part porosity increases almost linearly with an increasing volume fraction of coarse powder. Furthermore, the final part density is independent of powder bulk density and flowability. Measurements of the top surface show that an increase of part porosity by coarse powder is caused by an increase in melt pool fluctuation, which in turn causes irregular solidified scan tracks. Additionally, the results show that the powder segregation during coating is stronger for the bimodal powder; however, no influence of the segregation on the part density could be found.

Size-segregated Characteristics and Formation Mechanisms of Water-soluble Inorganic Ions during Different Seasons in Heshan of Guangdong, China

To identify the characteristics, sources, and formation mechanisms of aerosol particles during pollution episodes in the Pearl River Delta, 24 sets of size-segregated samples were collected in Heshan during July 2014 and January 2015 using a 10-stage Micro-Orifice Uniform Deposit Impactor (MOUDI), and nine ions, viz., Na+, NH4+, K+, Mg2+, Ca2+, Cl–, NO2–, NO3–, and SO42–, were investigated. The Na+, Mg2+, and Ca2+ were mainly distributed in the coarse particles, and were mainly from soil, dust, and sea salt. The fine-mode K+ during winter was mostly generated by biomass burning. The coarse-mode Cl– originated from sea salt, whereas the fine-mode Cl– resulted from the conversion of NH4Cl to the particle phase. Both the SO42– and the NO3– exhibited unimodal distributions during winter but bimodal ones during summer. The coarse-mode SO42– and NO3– arose from sea salt and heterogeneous reactions, respectively. An increase in the nitrogen oxidation ratio (NOR) and a decrease in the sulfur oxidation ratio (SOR) were observed on polluted days, with the highest values occurring in the 0.56–1 µm particle size fraction. The formation of NO3– was chiefly related toµ homogeneous gas-phase reactions during winter and nocturnal heterogeneous reactions involving N2O5 during summer, whereas the formation of SO42– was driven by gas-phase oxidation in the 0.056–0.32 µm size range and aqueous oxidation in the 0.56–3.2 µm range. Additionally, the SOR and the NO2 concentration displayed a positive correlation in the 0.056–1.8 µm particle size fraction, indicating that the potential formation of SO42– via aqueous reactions was accelerated by NO2.

Statistical Model of Motor-Evoked Potentials.

Motor-evoked potentials (MEPs) are widely used for biomarkers and dose individualization in transcranial stimulation. The large variability of MEPs requires sophisticated methods of analysis to extract information fast and correctly. Development and testing of such methods relies on the availability for realistic models of MEP generation, which are presently lacking. This paper presents a statistical model that can simulate long sequences of individualized MEP amplitude data with properties matching experimental observations. The MEP model includes three sources of trial-to-trial variability: excitability fluctuations, variability in the neural and muscular pathways, and physiological and measurement noise. It also generates virtual human subject data from statistics of population variability. All parameters are extracted as statistical distributions from experimental data from the literature. The model exhibits previously described features, such as stimulus-intensity-dependent MEP amplitude distributions, including bimodal ones. The model can generate long sequences of test data for individual subjects with specified parameters or for subjects from a virtual population. The presented MEP model is the most detailed to date and can be used for the development and implementation of dosing and biomarker estimation algorithms for transcranial stimulation.

Fish thermoregulation and the promotion of cellular antimicrobial defenses

Despite being ectotherms, reptiles have an ability to thermoregulate which is enhanced by adopting a variety of behavioural mechanisms. Different behavioural postures, the use of retreat sites and selection of microhabitats enable reptiles to maintain their core body temperatures (Tb) above that of ambient temperatures (Ta) in winter or below Ta maximum in summer. This study describes the daily activity patterns of leopard tortoises (Stigmochelys pardalis) in relation to Tb and Ta, and the extent to which leopard tortoises can manipulate their Tb in response to seasonal changes in Ta. Ten and nine leopard tortoises were radio-tracked in 2002 and 2003, respectively and cloacal Tb and behaviours observed. Core Tbs were measured using Thermocron iButtons™ surgically implanted into the body cavities of 4 and 5 adult telemetered tortoises for summer and winter 2003, respectively. There were seasonal differences in the extent to which certain behaviours were practiced and the time of day that these occurred. Leopard tortoises generally had unimodal activity patterns in winter and bimodal ones in summer. In winter tortoises were active at lower Tbs, and at lower Ta, than in summer. Tortoises maintained their core Tb well below Ta minimum profiles in summer and well above these in winter. Core Tb closely followed the increase in Ta minimum profiles in the mornings, however tortoises exhibited an extended thermal lag when Ta minimum profiles cooled overnight. By using different behavioural mechanisms in summer and winter, leopard tortoises maintained their core Tb at different levels compared with Ta minimum and maximum profiles. Consequently although they are ectotherms, they maintained their core Tb independent of Ta.

Characterization of rainstorm modes along the upper mainstream of Yangtze River during 2003–2016

ABSTRACTAccurate knowledge of extrveme rainfall mode (time distribution) is crucial for many fields, such as hydraulic structure design, flood control and reservoir operation. The rainstorm modes along the upper mainstream of Yangtze River (UMYR) during 2003–2016 were investigated by fuzzy mode identification method, linear regression and Mann–Kendall test. Results show that unimodal rainstorms are more frequently seen than bimodal ones, and those with late peaks are dominant along UMYR. Moreover, rainstorms tend to centre on downstream UMYR. Trend analysis reveals moderate decreases in regional mean rainstorm frequency and amount, but an increase in regional mean peak intensity. Unimodal rainstorms with early peaks and bimodal rainstorms with early and late peaks have increased significantly. However, unimodal rainstorms with late peaks and bimodal rainstorms with middle and late peaks show decreases. Spatially, decreases in rainstorm frequency, amount and peak intensity are found in downstream, while peak intensity shows an increasing trend in the upper UMYR. Along the river reach, mean rainstorm levels are generally below 100 mm. In comparison to bimodal rainstorms, unimodal rainstorms are more intense, and those with middle peaks are considered most intense with mean levels of peak intensity generally ranging from 25 to 50 mm h−1. For other rainstorm modes, the mean levels of peak intensity are generally below 25 mm h−1. Finally, we found there is a potential change in the dominant rainstorm mode in downstream UMYR, where unimodal rainstorms with early peaks have become the prevalent local rainstorm mode in recent years, replacing unimodal rainstorms with late peaks.

A New Regression Model for Bounded Responses

Aim of this contribution is to propose a new regression model for continuous variables bounded to the unit interval (e.g. proportions) based on the flexible beta (FB) distribution. The latter is a special mixture of two betas, which greatly extends the shapes of the beta distribution mainly in terms of asymmetry, bimodality and heavy tail behaviour. Its special mixture structure ensures good theoretical properties, such as strong identifiability and likelihood boundedness, quite uncommon for mixture models. Moreover, it makes the model computationally very tractable also within the Bayesian framework here adopted. At the same time, the FB regression model displays easiness of interpretation as well as remarkable fitting capacity for a variety of data patterns, including unimodal and bimodal ones, heavy tails and presence of outliers. Indeed, simulation studies and applications to real datasets show a general better performance of the FB regression model with respect to competing ones, namely the beta (Ferrari and Cribari-Neto, 2004) and the beta rectangular (Bayes et al., 2012), in terms of precision of estimates, goodness of fit and posterior predictive intervals.

Rapid learning of visual ensembles.

We recently demonstrated that observers are capable of encoding not only summary statistics, such as mean and variance of stimulus ensembles, but also the shape of the ensembles. Here, for the first time, we show the learning dynamics of this process, investigate the possible priors for the distribution shape, and demonstrate that observers are able to learn more complex distributions, such as bimodal ones. We used speeding and slowing of response times between trials (intertrial priming) in visual search for an oddly oriented line to assess internal models of distractor distributions. Experiment 1 demonstrates that two repetitions are sufficient for enabling learning of the shape of uniform distractor distributions. In Experiment 2, we compared Gaussian and uniform distractor distributions, finding that following only two repetitions Gaussian distributions are represented differently than uniform ones. Experiment 3 further showed that when distractor distributions are bimodal (with a 30° distance between two uniform intervals), observers initially treat them as uniform, and only with further repetitions do they begin to treat the distributions as bimodal. In sum, observers do not have strong initial priors for distribution shapes and quickly learn simple ones but have the ability to adjust their representations to more complex feature distributions as information accumulates with further repetitions of the same distractor distribution.

Analytical discrete stacking sequence optimization of rectangular composite plates subjected to buckling and FPF constraints

A special type of new discrete design variables is introduced in order to find optimal stacking sequences for laminated structures. Using the proposed new design variables, we demonstrate how to find analytical (i.e. without any numerical optimization algorithm) optimal solutions for laminates made of plies having three different fibre orientations: 0◦, ±45◦, 90◦. It is proved that the definition of design variables enables us to distinguish two types of optimal solutions, i.e. unimodal and bimodal ones. The form of optimal stacking sequences affects the multiplicity (bimodal problems) or uniqueness (unimodal problems) of the solutions. The decoding procedure between membrane and flexural design variables is also proposed. The results demonstrate the effectiveness, simplicity and advantages of the use of design variables, especially in the sense of the accuracy, repeatability of results and convergence of the method.

Bifurcation analysis of a self-organizing signaling system for eukaryotic chemotaxis

Phosphatidylinositol 3,4,5-trisphosphate (\(\hbox {PIP}_3\)) is a membrane lipid that works as a directional compass in migrating cells. Remarkably, \(\hbox {PIP}_3\) shows both transient patterns and oscillatory patterns on the membrane, depending on experimental conditions (Arai et al. in Proc Natl Acad Sci 107:12399–12404, 2010). Here, we analyzed a reaction–diffusion model of the phosphatidylinositol signaling system that gives rise to transient pattern formation. Numerical bifurcation analysis showed that equilibrium solutions can be classified into uniform, unimodal and bimodal ones, among which the first and the second are stable for some parameter regions. We found that transient patterns of \(\hbox {PIP}_3\) can be explained by the “ghost” after unimodal solutions disappear at a fold bifurcation. We further reduced the original PDEs to five-variable ODEs, considering only local and global concentrations. The bifurcation analysis of the reduced ODEs supports the above observation. Finally, we propose that trajectories of such transient patterns are determined by the phase space structure of the dynamical system.

Ostwald ripening of supported Pt nanoclusters with initial size-selected distributions

The use of a laser ablation cluster source made it recently possible to study Ostwald ripening of supported Pt nanoclusters with atomic control of the initial size distributions, such as Pt68 or Pt22+Pt68 (K. Wettergren et al., Nano Lett. (2014)). Monodispersed clusters were found to be more stable compared to the bimodal ones and to those with wide polydisperse initial size distribution. To clarify the results of the experiments, we present here the corresponding kinetic Monte Carlo simulations of Ostwald ripening with emphasis on the role of the initial size distribution with control at the atomic level.

Some Skew-Symmetric Distributions Which Include the Bimodal Ones

The class of skew-symmetric distributions has received much attention in recent years. In this article, we introduce two distributions which can capture the skew-symmetric unimodal (e.g., skew-Laplace, skew-normal) and the skew-symmetric bimodal ones systematically. Their natural generalizations of the skew-Laplace and the skew-normal distributions provide greater flexibility in modeling real data distributions. These models also avoid the identifiability problems of using mixtures to fit bimodal data. The stochastic representations that provide the random number generation algorithms are presented. The explicit forms of the central moments indicated that the proposed distributions have wide ranges of the skewness and kurtosis measures.

Thermoregulation in leopard tortoises in the Nama-Karoo: The importance of behaviour and core body temperatures

Despite being ectotherms, reptiles have an ability to thermoregulate which is enhanced by adopting a variety of behavioural mechanisms. Different behavioural postures, the use of retreat sites and selection of microhabitats enable reptiles to maintain their core body temperatures (Tb) above that of ambient temperatures (Ta) in winter or below Ta maximum in summer. This study describes the daily activity patterns of leopard tortoises (Stigmochelys pardalis) in relation to Tb and Ta, and the extent to which leopard tortoises can manipulate their Tb in response to seasonal changes in Ta. Ten and nine leopard tortoises were radio-tracked in 2002 and 2003, respectively and cloacal Tb and behaviours observed. Core Tbs were measured using Thermocron iButtons™ surgically implanted into the body cavities of 4 and 5 adult telemetered tortoises for summer and winter 2003, respectively. There were seasonal differences in the extent to which certain behaviours were practiced and the time of day that these occurred. Leopard tortoises generally had unimodal activity patterns in winter and bimodal ones in summer. In winter tortoises were active at lower Tbs, and at lower Ta, than in summer. Tortoises maintained their core Tb well below Ta minimum profiles in summer and well above these in winter. Core Tb closely followed the increase in Ta minimum profiles in the mornings, however tortoises exhibited an extended thermal lag when Ta minimum profiles cooled overnight. By using different behavioural mechanisms in summer and winter, leopard tortoises maintained their core Tb at different levels compared with Ta minimum and maximum profiles. Consequently although they are ectotherms, they maintained their core Tb independent of Ta.

Influence of (1,3‐phenylene)bis(3‐methyl‐1‐phenyl pentylidene)dilithium initiator concentration on the modality of polybutadiene

AbstractThe strong influence of (1,3‐phenylene)bis(3‐methyl‐1‐phenyl pentylidene)dilithium initiator (DLI) concentration on the modality of polybutadiene (PBd) in the presence of lithium s‐butoxide (s‐BuOLi) in benzene, at room temperature, has been studied. The quality of DLI has been evaluated by gas chromatography‐mass spectrometry (GC‐MS) and 1H NMR. Keeping s‐BuOLi/C‐Li ratio (R) close to unity, at relatively high DLI concentrations (C > 7 × 10−4 M), monomodal high 1,4‐PBds with polydispersity index less than 1.07 were obtained, whereas bimodal ones at lower concentrations (C < 6 × 10−4 M). The effect of C‐Li concentration on the modality of PBd has been evaluated using size exclusion chromatography on samples taken during and at the end of the polymerization. Viscosity observations have also been used to further support the results. The bimodality of PBd has been attributed to partially terminated difunctional species because of the inevitable presence of protic impurities in the polymerization solution, although high vacuum technique was used, which becomes more significant at low initiator concentrations. Moreover, the strong influence of s‐BuOLi on the microstructure of PBd has been demonstrated by 1H NMR. © 2012 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2013

Short-term memory for auditory and visual durations: evidence for selective interference effects

The present study sought to determine the format in which visual, auditory and auditory-visual durations ranging from 400 to 600ms are encoded and maintained in short-term memory, using suppression conditions. Participants compared two stimulus durations separated by an interval of 8s. During this time, they performed either an articulatory suppression task, a visuospatial tracking task or no specific task at all (control condition). The results showed that the articulatory suppression task decreased recognition performance for auditory durations but not for visual or bimodal ones, whereas the visuospatial task decreased recognition performance for visual durations but not for auditory or bimodal ones. These findings support the modality-specific account of short-term memory for durations.

Microstrain Analysis of Titanium Aluminides

The aeronautic and automotive industries have shown a renewed interest in TiAl based alloys. The main reasons for such an interest are their low density (~3,8g/cm3), a good stiffness and a high strength for temperatures up to 750°C. However, these alloys exhibit, in their polycrystalline form, a poor ductility at room temperature with widely scattered values. The aim of this study is therefore to characterise their mechanical behaviour with a multiscale methodology, coupling microstructure analysis and strain field measurements. This methodology employs orientation imaging microscopy as well as digital imaging correlation techniques with an intragranular step size of a few micrometers. Two chemical compositions (47 at. % Al and 48 at. % Al) and two processing routes (casting and powder metallurgy) are studied. Thus, four different types of final microstructures are considered, from fully lamellar Ti3Al (a2) + TiAl (g) microstructure to bimodal ones composed of two-phase (a2+g) lamellar grains and monolithic g grains. Firstly, the microstructure is characterised crystallographically and morphologically. This allows the identification of a representative volume element (RVE) inside the analysed volume. Then, uniaxial mechanical tests are performed for each microstructure, and the strain fields are analysed with a multiscale approach, which determines the spatial distribution of the strain field heterogeneity with respect to the different microstructures.

On Elastic Properties of Single-walled Carbon Nanotubes as Composite Reinforcing Fillers

As one of the fundamental prerequisites for composite material applications of single-walled carbon nanotubes, their mechanical properties as reinforcing fillers should be identified in the conventional manner of mechanics of composite materials. In particular, identification of elastic properties under axial tension and compression, i.e., initial Young's modulus and Poisson's ratio in terms of longitudinal straining will have a considerable influence on the estimation accuracy of the mechanical (including elastic) properties of carbon nanotube reinforced composites. In this article, elastic properties of unchiral (arm-chair and zig-zag) single-walled carbon nanotubes of different diameters under infinitesimal, small but finite, and large strain regions are numerically computed based on the definition of tube cross-sectional area which will be adopted in the composite materials communities. A classical molecular dynamics simulation using the well-verified Tersoff-type empirical potential for carbon and hydrocarbon molecules is employed. Contrary to what has been reported so far for the case of infinitesimal straining which has been conducted in this study as well, it has been shown that the elastic properties such as initial Young's modulus and Poisson's ratio of the nanotubes in a small but finite strain range should be more or less treated as chirality-dependent, diameter-dependent, and bi-modal ones. The Mooney—Rivlin constants of unchiral carbon nanotubes are also evaluated. From the present results, it is cautioned that the carbon nanotubes are not always stiff and strong when they are looked upon as reinforcing fibers or fillers of composite materials.

Chemiluminescent picture of diphenyleneiodonium‐inhibited NADPH oxidase: a bimodal process and its logistic–exponential model‐based description

A chemiluminescence (CL) study of diphenyleneiodonium-inhibited NADPH oxidase was performed on a cellular system containing neutrophils stimulated by phorbol myristate acetate, indicating a complex bimodal structure of CL processes corresponding to different stages of the inhibition. The complex structure of these processes was described by a superposition of two logistic-exponential (LE) models, characterizing these processes as bimodal ones. To determine the mechanistic foundation of the LE model-described processes, a generalized form of the second-order dynamic system of CL reactions, the solution to which corresponds to the LE model, was constructed. The diphenyleneiodonium effects on neutrophil NADPH oxidase were separated from the total bimodal CL of the whole measurement system by the use of difference CL processes. These difference processes were also found to be bimodal; thus, inhibitor-induced reduction of CL could be described by a second-order dynamic system. The rate constants and initial concentrations in this dynamic system were determined by the least squares method applied to numerical solutions approximating the difference processes. Using interrelations between the parameters of the dynamic system, cooperative effects in the inhibitor reactions with NADPH oxidase were found and described quantitatively. Other evidences of cooperativity were obtained from integral characteristics of the CL reduction process, i.e. dose-response and progress curves, determined by numerical integration of the LE models constituting the superposition. On this basis, it was also possible to detect a specific binding of the inhibitor to the enzyme. Finally, putative reaction mechanisms suggested by the model obtained were considered and compared with those known at present.

Milk flow traits in Mediterranean Italian Buffaloes

The aim of this study was to analyze the milk flow pattern in Italian Mediterranean Buffaloes in relation to parity and oxytocin administration. A total of 330 milk flow recorders were collected during morning and evening milkings by using an electronic milk flow meters (Lactocorder®). Milk flow curves were examined and subject were divided according milk flow pattern in: normal pattern, bimodal pattern and “double pattern”. Data were analysed by using ANOVA and Chi square test. Total milk yield per milking was significantly higher (P<0.01) in pluriparous and consistent with the average DIM of 205 days. No differences in milk yield and maximum milk flow were found between the oxytocin groups while both parameters were higher in bimodal and double pattern groups compared to normal milk flow pattern. Lag time was higher (P<0.01) in oxytocin treated group and in normal vs the other two pattern groups. Length of main milking phase was higher in pluriparous, oxytocin treated group (P<0.01) and in bimodal vs the normal one (P<0.05) while double pattern showed the highest value (P<0.01). Percentage of bimodal milk flow was 13.7% while a double flow pattern was 12.4%. A higher percentage of double pattern was found in oxytocin treated buffaloes vs normal and bimodal ones (18.1% vs 8.1% and 7.5% respectively; P< 0.05) and in pluriparous vs primiparous (74.4% vs 25.6%; P< 0.05).