Perception of biological motion in point-light displays by jumping spiders

Over the last 50 years, point-light displays have been successfully used to explore how animals respond to dynamic visual stimuli—specifically, differentiation of the biological from the non-biological. These stimuli are designed to preserve movement patterns while minimizing static detail, with single dots representing each of the main joints of a moving animal. Imposed by their internal skeleton, vertebrate movements follow a specific semi-rigid dynamic pattern, termed “biological-motion”, which can be used to distinguish animate from inanimate objects. Although biological motion detection has not been studied in invertebrates, rigid exoskeletons force many species to also follow semi-rigid movement principles. Due to their highly developed visual system and complex visual behaviors, we investigated the capability of jumping spiders to discriminate biological from non-biological motion using point-light display stimuli. By constraining spiders so that they could rotate but not move directionally, we simultaneously presented two point-light display stimuli with specific dynamic traits and registered their preference by observing which pattern they turned towards. Jumping spiders clearly demonstrated the ability to discriminate between stimuli. However, spiders showed no preference when both stimuli presented patterns with semi-rigid movements, results that are directly comparable to responses in vertebrate systems. This represents the first demonstration of biological motion recognition in an invertebrate, posing crucial questions about the evolutionary history of this ability and complex visual processing in non-vertebrate systems.

The dynamics of organizational reputation and status: momentum and volatility

PurposeOrganizational reputation and status are similar yet distinct constructs, serving as signals conveying information about an organization and its products and thus constituting audiences' perceptions about the organization. However, compared to status, reputation tends to change more dynamically over time. In this study, the authors argue that the dynamic traits of reputation – particularly, its momentum and volatility – may serve as additional signals and/or noises, influencing potential exchange partners' perception about the organization and thereby determining its status.Design/methodology/approachThe authors test our hypotheses in the context of the US venture capital firms between 1990 and 2010. The authors collected 8,793 firm-year observations of 1,186 VC firms and used the Arellano–Bover/Blundell–Bond dynamic panel estimation method to estimate their model.FindingsThe authors’ findings show that reputation momentum has a positive effect on status, whereas reputation volatility does not have a significant direct effect. However, the authors found that volatility has indirect effects on status, serving as a noise weakening the signaling effects of reputation and its momentum.Originality/valueThis paper contributes to the literature on organizational reputation and status by suggesting the importance of considering the dynamic traits of organizational reputation, which are indeed the crucial factors that distinguish reputation from status. Also, this study provides managerial implications for the organizations that aim to enhance their status through managing their reputation.

A Multi-Tier Streaming Analytics Model of 0-Day Ransomware Detection Using Machine Learning

Desktop and portable platform-based information systems become the most tempting target of crypto and locker ransomware attacks during the last decades. Hence, researchers have developed anti-ransomware tools to assist the Windows platform at thwarting ransomware attacks, protecting the information, preserving the users’ privacy, and securing the inter-related information systems through the Internet. Furthermore, they utilized machine learning to devote useful anti-ransomware tools that detect sophisticated versions. However, such anti-ransomware tools remain sub-optimal in efficacy, partial to analyzing ransomware traits, inactive to learn significant and imbalanced data streams, limited to attributing the versions’ ancestor families, and indecisive about fusing the multi-descent versions. In this paper, we propose a hybrid machine learner model, which is a multi-tiered streaming analytics model that classifies various ransomware versions of 14 families by learning 24 static and dynamic traits. The proposed model classifies ransomware versions to their ancestor families numerally and fuses those of multi-descent families statistically. Thus, it classifies ransomware versions among 40K corpora of ransomware, malware, and good-ware versions through both semi-realistic and realistic environments. The supremacy of this ransomware streaming analytics model among competitive anti-ransomware technologies is proven experimentally and justified critically with the average of 97% classification accuracy, 2.4% mistake rate, and 0.34% miss rate under comparative and realistic test.

An explorable public transcriptomics compendium for eukaryotic microalgae

Eukaryotic microalgae dominate primary photosynthetic productivity in fluctuating nutrient-rich environments, including coastal, estuarine and polar regions, where competition and complexity are presumably adaptive and dynamic traits. Numerous genomes and transcriptomes of these species have been carefully sequenced, providing an unprecedented view into the vast genetic repertoires and the diverse transcriptional programs operating inside these organisms. Here we collected, re-mapped, quantified and clustered publicly available transcriptome data for ten different eukaryotic microalgae in order to develop new insights into their molecular systems biology, as well as to provide a large new resource of integrated information to facilitate the efforts of others to further compare and contextualize the results of individual and new experiments within and between species. This is summarized herein and provided for public use by the eukaryotic microalgae research community.

Dynamic Analysis and Structure Soil Interaction of Retaining Wall Using ETABS

Retaining systems are widely used international for serving numerous functions in structures and infrastructures. The seismic response of forms of walls that assist a single soil layer has been examined with the aid of some of researchers in the past. The design of preserving partitions in seismic areas poses a complex problem. The conventional layout method usually contains calculation of an element of safety in opposition to sliding, overturning and bearing ability failure. Retaining partitions have suffered damages under beyond earthquakes. Typically the analyses do not bear in mind the retained soil’s interplay with the wall, which takes location at some point of dynamic conditions. The situations of separation of wall (at some point of interactions) over again trade the dynamic traits of the assumed wall-soil interplay that needs to be addressed. Our study conducts the retaining wall beneath static in addition to seismic situations about above components.

Walking like an ant: a quantitative and experimental approach to understanding locomotor mimicry in the jumping spider Myrmarachne formicaria

Protective mimicry, in which a palatable species avoids predation by being mistaken for an unpalatable model, is a remarkable example of adaptive evolution. These complex interactions between mimics, models and predators can explain similarities between organisms beyond the often-mechanistic constraints typically invoked in studies of convergent evolution. However, quantitative studies of protective mimicry typically focus on static traits (e.g. colour and shape) rather than on dynamic traits like locomotion. Here, we use high-speed cameras and behavioural experiments to investigate the role of locomotor behaviour in mimicry by the ant-mimicking jumping spider Myrmarachne formicaria , comparing its movement to that of ants and non-mimicking spiders. Contrary to previous suggestions, we find mimics walk using all eight legs, raising their forelegs like ant antennae only when stationary. Mimics exhibited winding trajectories (typical wavelength = 5–10 body lengths), which resemble the winding patterns of ants specifically engaged in pheromone-trail following, although mimics walked on chemically inert surfaces. Mimics also make characteristically short (approx. 100 ms) pauses. Our analysis suggests that this makes mimics appear ant-like to observers with slow visual systems. Finally, behavioural experiments with predatory spiders yield results consistent with the protective mimicry hypothesis. These findings highlight the importance of dynamic behaviours and observer perception in mimicry.

E-Index for Differentiating Complex Dynamic Traits

While it is a daunting challenge in current biology to understand how the underlying network of genes regulates complex dynamic traits, functional mapping, a tool for mapping quantitative trait loci (QTLs) and single nucleotide polymorphisms (SNPs), has been applied in a variety of cases to tackle this challenge. Though useful and powerful, functional mapping performs well only when one or more model parameters are clearly responsible for the developmental trajectory, typically being a logistic curve. Moreover, it does not work when the curves are more complex than that, especially when they are not monotonic. To overcome this inadaptability, we therefore propose a mathematical-biological concept and measurement,E-index (earliness-index), which cumulatively measures the earliness degree to which a variable (or a dynamic trait) increases or decreases its value. Theoretical proofs and simulation studies show thatE-index is more general than functional mapping and can be applied to any complex dynamic traits, including those with logistic curves and those with nonmonotonic curves. Meanwhile,E-index vector is proposed as well to capture more subtle differences of developmental patterns.