CL-ACP: a parallel combination of CNN and LSTM anticancer peptide recognition model

Background Anticancer peptides are defence substances with innate immune functions that can selectively act on cancer cells without harming normal cells and many studies have been conducted to identify anticancer peptides. In this paper, we introduce the anticancer peptide secondary structures as additional features and propose an effective computational model, CL-ACP, that uses a combined network and attention mechanism to predict anticancer peptides. Results The CL-ACP model uses secondary structures and original sequences of anticancer peptides to construct the feature space. The long short-term memory and convolutional neural network are used to extract the contextual dependence and local correlations of the feature space. Furthermore, a multi-head self-attention mechanism is used to strengthen the anticancer peptide sequences. Finally, three categories of feature information are classified by cascading. CL-ACP was validated using two types of datasets, anticancer peptide datasets and antimicrobial peptide datasets, on which it achieved good results compared to previous methods. CL-ACP achieved the highest AUC values of 0.935 and 0.972 on the anticancer peptide and antimicrobial peptide datasets, respectively. Conclusions CL-ACP can effectively recognize antimicrobial peptides, especially anticancer peptides, and the parallel combined neural network structure of CL-ACP does not require complex feature design and high time cost. It is suitable for application as a useful tool in antimicrobial peptide design.

Modeling Daily Partner Violence and Substance Use Based upon Couple’s Reporting

While agent-based models (ABMs) have successfully modeled violence and women’s decision-making, they relied upon studies of her daily reports of violence and household environment; these models were not based upon descriptions of his emotions and perceptions. The purpose of this study was to improve our understanding of the triggers of violent events within violent relationships through agent-based modeling by including men’s perceptions and emotions. An agent-based model was created of couples with history of violence based upon results of a study involving multiple time series of partner violence, including couples’ daily reports of their emotions and perceptions. To explore factors that may alter model results, seven continuous variable parameters were created based upon significant ( p ≤ .05) but discrepant (opposite directions) in prior studies. To assess the potential impact that influencing factors such as random stress as well as his and her feelings and behaviors could have on violence and stalking, the impact of these factors was also assessed. Results found that, at baseline, which included no extremes in variable parameters, no violence emerged. One prior-day→same-day relationship (HerConcern→HerConcern) was particularly important in this ABM. Men’s and women’s drug use and refraining from arguments had little impact on any outcome, but his and her alcohol use, his sense of insult and her violence all had significant effects. In fact, women’s alcohol use interacted with other influencing variables and was a source of atypical patterns. In conclusion, incorporating men’s perceptions into an ABM of partner violence resulted in important differences compared with ABMs based solely on women’s input. Not only were women’s daily concerns about the effect of violence on children was critical to results, but this ABM demonstrated the complexity of partner violence in response to influences as illustrated by contextual dependence, interaction effects and synergy.

Linking the FTO obesity rs1421085 variant circuitry to cellular, metabolic, and organismal phenotypes in vivo

Variants in FTO have the strongest association with obesity; however, it is still unclear how those noncoding variants mechanistically affect whole-body physiology. We engineered a deletion of the rs1421085 conserved cis-regulatory module (CRM) in mice and confirmed in vivo that the CRM modulates Irx3 and Irx5 gene expression and mitochondrial function in adipocytes. The CRM affects molecular and cellular phenotypes in an adipose depot–dependent manner and affects organismal phenotypes that are relevant for obesity, including decreased high-fat diet–induced weight gain, decreased whole-body fat mass, and decreased skin fat thickness. Last, we connected the CRM to a genetically determined effect on steroid patterns in males that was dependent on nutritional challenge and conserved across mice and humans. Together, our data establish cross-species conservation of the rs1421085 regulatory circuitry at the molecular, cellular, metabolic, and organismal level, revealing previously unknown contextual dependence of the variant’s action.

Extended Phase Unwrapping Max-Flow/Min-Cut Algorithm for Multibaseline SAR Interferograms Using a Two-Stage Programming Approach

Multi-baseline (MB) phase unwrapping (PU) is a key step of MB synthetic aperture radar (SAR) interferometry (InSAR). Compared with the traditional single-baseline (SB) PU, MB PU is applicable to the area where topography varies violently without obeying the phase continuity assumption. A two-stage programming MB PU approach (TSPA) proposed by H. Yu. builds the link between SB and MB PUs, so many existing classical SB PU methods can be transplanted into the MB domain. In this paper, an extended PU max-flow/min-cut (PUMA) algorithm for MB InSAR using the TSPA, referred to as TSPA-PUMA, is proposed, consisting of a two-stage programming procedure. In stage 1, phase gradients are estimated based on Chinese remainder theorem (CRT). In stage 2, a Markov random field (MRF) model of PUMA is designed for modeling local contextual dependence based on the phase gradients obtained by stage 1. Subsequently, the energy of the MRF model is minimized by graph cuts techniques. The experiment results illustrate that the TSPA-PUMA method can drastically enhance the accuracy of the original PUMA method in the rugged area, and is more efficient than the original TSPA method. In addition, the noise robustness of TSPA-PUMA can be improved through adding more interferograms with different baseline lengths.

Staat und Zivilgesellschaft

The relationship between the state and civil society can be characterised as complex, disharmonious and dynamic. The complexity results from the historical conditions of its origin and the different ways of thinking, grasping and structuring the relationship. The relationship is disharmonious because although it can theoretically be thought of as equal, this equality, in fact, hardly exists. The relationship is dynamic because it is in a permanent state of tension between the path dependencies of the history of ideas, and therefore can and must be constantly rethought. This anthology attempts to grasp and illuminate the relationship between the state and civil society in all its complexity by paying special attention to the contextual dependence of the genesis of this complicated relationship. With the emergence of the modern state based on sovereignty, the state entered into opposition with civil society. Modern political theory has devoted much of its energy to reflecting this antagonism and bridging the gap between the two. With contributions by Nelson Chacón, Julian Dörr, Christopher Gohl, Oliver Hidalgo, Heinz Kleger, Alexander Kruska, Antoine Lévy, Andreas Nix, Edwin QuirogaMolano and Michael Zantke.

INSULT AS A HIGHLY TRAUMATIC SITUATION FOR A PERSONALITY

The article presents the results of a theoretical study dedicated to situation of insult that causes serious consequences for the human psyche. Insult is a negative impact of an emotional nature that degrades a person. In the scholarly literature it is considered to be a premeditated, intentional, purposeful type of emotional abuse. Insult is of latent nature; it does not result in actual physical insult for the victim’s body, but often precedes or accompanies other forms of abuse (physical, sexual). This feature of insult complicates the study of this phenomenon significantly. Insult is a stressor of high intensity; it threats the psychological well-being and integrity of a personality. Humiliation, especially systematic, affects a person’s self-esteem negatively, contributes to its victimisation and social isolation. The main characteristics of the insult such as anthropogenicity, activity, awareness, contextual dependence are given. This article presents analysis of differences of the insult from the other, passive, and sometimes unconscious by the aggressor type of emotional abuse – from neglect. Features of experiencing of insult by people of different ages and in various relationships (parent-child, partner, professional) are noted. Particular attention is paid to the study of the psychological consequences of insult, including posttraumatic stress, some mental disorders and significant damage to a person’s self-esteem, his self-image.

Machine Learning for Smart Tourism and Retail

The unprecedented growth in the amount and variety of data we can store about the behaviour of customers has been parallel to the popularization and development of machine learning algorithms. This confluence of factors has created the opportunity of understanding customer behaviour and preferences in ways that were undreamt of in the past. In this chapter, the authors study the possibilities of different state-of-the-art machine learning algorithms for retail and smart tourism applications, which are domains that share common characteristics, such as contextual dependence and the kind of data that can be used to understand customers. They explore how supervised, unsupervised, and recommender systems can be used to profile, segment, and create value for customers.

Ideas of Ulrich Beck in the Сontext of Modern Methodological Searches in World Sociology

The article reconstructed the system and method of the German sociologist Ulrich Beck. The importance of this work in the methodological situation in modern sociology is shown. This situation is due to changes in the social world and the fourth scientific revolution, which takes place in science in general. A significant part of the concepts included in the conceptual networks of various paradigms of modern sociology were formed during the second scientific revolution. In addition, sociologists, who investigate the Modernity, face the impact of unscientific circumstances, such as global threats, pressure of the ruling classes, and others. Ulrich Beck influenced world sociology with concepts of risk society, Second Modernity, cosmopolitanism. His critique of methodological nationalism is important. His call for overcoming “zombie concepts” remains valid. At the same time, the German sociologist, calling for a new utopia, saw the path to a cosmopolitan federation of states with divided sovereignty in establishing cooperation between capital, states, and civil society. He could not offer any real mechanisms for this cooperation. For progressive shifts in the problems of modernity, the synthesis of the ideas of the Second Modern, the sociology of creative Marxism, the world-systems analysis and ecological sociology can be useful. By this time, these traditions are divided by barriers of incomprehension and competition for intellectual novelty. In the theory of the Second Modern, the disadvantage is also a strong contextual dependence on the current political situation. U. Beck created his texts as comments to current processes. For ideological synthesis, it is necessary not only to recreate the course of thoughts of sociologists, but to present their ideas in the form of coherent concepts in the context of the requirements of a new methodological situation. The Second Modern and its characteristics such as Globalization can be considered as a stage in the development of the world capitalist system. The idea of a Risk Society can resonate with the development of Environmental Sociology. Criticism of neoliberalism in the sociology of creative Marxism can provide greater objectivity to the idea of cosmopolitanism. But for this, it is necessary to reconstruct the conceptual series of these research directions, their methodological guidelines in connection with the philosophical foundations of their metasociological knowledge.

Social capital dimensions, innovation, and technology in Europe: a case-studies meta-synthesis

This article aims to improve the understanding on how structural, relational, and cognitive dimensions of social capital influence innovation outcomes on interorganizational and intraorganizational networks. A meta-synthesis research design with eight selected qualitative case studies located in a European context were conducted. The patterns of causal relationships among the variables presented in the case studies were identified. The antecedents of social capital dimensions, the influence of the dimensions on reducing barrier or impediments for innovation and on the enhancement of enablers or facilitators of innovation outcomes, and the direct effects of social capital dimensions on innovation compose the resulting framework. Furthermore, differences between the influence of social capital dimensions on innovation and technology in interorganizational and intraorganizational setting in European companies were found. The meta-synthesis this research relies on another researcher’s insights and interpretation of data, being susceptible to their bias. Adopting qualitative case studies insights for getting to an analytical generalization reduces the deepness, richness, and contextual dependence of original authors’ findings. The findings could help organizations developing optimal conditions for the improvement of the likelihood of gathering innovation and technology and development outcomes from both interorganizational and intraorganizational networks. This article contributes for both innovation and technology development and social capital literature by proposing an integrated framework comprised of social capital antecedents and the role of social dimensions on reducing barriers or impediments, enhancing enablers or facilitators, and affecting innovation outcomes directly.

Beauty-in-averageness and its contextual modulations: A Bayesian statistical account

Understanding how humans perceive the likability of high-dimensional “objects” such as faces is an important problem in both cognitive science and AI/ML. Existing models of human preferences generally assume these preferences to be fixed. However, human assessment of facial attractiveness have been found to be highly context-dependent. Specifically, the classical Beauty-in-Averageness (BiA) effect, whereby a face blended from two original faces is judged to be more attractive than the originals, is significantly diminished or reversed when the original faces are recognizable, or when the morph is mixed-race/mixed gender and the attractiveness judgment is preceded by a race/gender categorization. This effect, dubbed Ugliness-in-Averageness (UiA), has previously been attributed to a disfluency account, which is both qualitative and clumsy in explaining BiA. We hypothesize, instead, that these contextual influences on face processing result from the dependence of attractiveness perception on an element of statistical typicality, and from an attentional mechanism that restricts face representation to a task-relevant subset of features, thus redefining typicality within that subspace. Furthermore, we propose a principled explanation of why statistically atypical objects are less likable: they incur greater encoding or processing cost associated with a greater prediction error, when the brain uses predictive coding to compare the actual stimulus properties with those expected from its associated categorical prototype. We use simulations to show our model provides a parsimonious, statistically grounded, and quantitative account of contextual dependence of attractiveness. We also validate our model using experimental data from a gender categorization task. Finally, we make model predictions for a proposed experiment that can disambiguate the previous disfluency account and our statistical typicality theory.