Victimization

Not all groups are equally likely to be subject to acts of aggression; specific subgroups are more likely to be victimized. For example, youth who identify as a sexual minority are more likely to be victims of traditional forms of bullying than their heterosexual friends. There has been less research, however, on population subgroups and the likelihood of becoming a victim of cyber aggression. In exploring this topic, this chapter examines several questions including, “How important is the amount of time spent online as an intermediate variable in predicting whether an individual will become a victim of cyber aggression?” and “Does sexual orientation impact the likelihood of being a victim of cyberaggression above and beyond the amount of time spent online?” Multivariate statistical methods and survey data from the Pew Research Center for the year 2014 was used in this analysis.

LENNA (Learning Emotions Neural Network Assisted): An Empathic Chatbot Designed to Study the Simulation of Emotions in a Bot and Their Analysis in a Conversation

Currently, most chatbots are unable to detect the emotional state of the interlocutor and respond according to the interlocutor’s emotional state. Over the last few years, there has been growing interest in empathic chatbots. In other disciplines aside from artificial intelligence, e.g., in medicine, there is growing interest in the study and simulation of human emotions. However, there is a fundamental issue that is not commonly addressed, and it is the design of protocols for quantitatively evaluating an empathic chatbot by utilizing the analysis of the conversation between the bot and an interlocutor. This study is motivated by the aforementioned scenarios and by the lack of methods for assessing the performance of an empathic bot; thus, a chatbot with the ability to recognize the emotions of its interlocutor is needed. The main novelty of this study is the protocol with which it is possible to analyze the conversations between a chatbot and an interlocutor, regardless of whether the latter is a person or another chatbot. For this purpose, we have designed a minimally viable prototype of an empathic chatbot, named LENNA, for evaluating the usefulness of the proposed protocol. The proposed approach uses Shannon entropy to measure the changes in the emotional state experienced by the chatbot during a conversation, applying sentiment analysis techniques to the analysis of the conversation. Once the simulation experiments were performed, the conversations were analyzed by applying multivariate statistical methods and Fourier analysis. We show the usefulness of the proposed methodology for evaluating the emotional state of LENNA during conversations, which could be useful in the evaluation of other empathic chatbots.

Main directions of the study of plant invasions in Russia

This article is focused on the analysis of major approaches to plant invasion research used by Russian researchers. They fall within three main groups: 1. Conventional approaches to floristic analysis based on the Russian scientific tradition of floristic research, 2. Approaches focused on the study of the fraction of invasive flora, making blacklists and regional Black books, 3. New comprehensive approaches based on a synthesis of methods used in botany, geo-information technology and population genetics. Multivariate statistical methods allow for the visualization of various data, including those on alien species group structures in various regions. They make it possible to identify boundaries of ecological niches occupied by plants in respect to climate-and-environmental or ecological variables. An assessment of current statistical interdependence between alien plant characteristics and scores of factors limiting their dissemination facilitates the making of predictive models of plant invasion. Examples of multivariate statistical methods used in invasion biology were analyzed, along with different approaches to the study of the variability of alien species. Alien and invasive fractions of the flora of the Trans-Siberian Railway were analyzed not by administrative units but by natural biomes. This approach allowed us to assess the correlation between the number of invasive species with different natural-climatic and floristic characteristics of biomes. The publication of "Black Books" of various administrative subjects of Russia according to a unified methodology allowed us to make an inventory of invasive species over the vast territory of the country. The experience gained by Russian researchers may be further used for developing universal approaches to plant invasion research.

Application of Multivariate Statistical Methods and Water Quality Index for the Evaluation of Surface Water Quality in the Cunas River Basin, Peru

Watershed management requires information that allows the intervention of possible sources that affect aquatic systems. Surface water quality in the Cunas river basin (Peru) was evaluated using multivariate statistical methods and the CCME-WQI water quality index. Twenty-seven sampling sites were established in the Cunas River and nine sites in the tributary river. Water samples were collected in two contrasting climatic seasons and the CCME-WQI was determined based on physicochemical and bacteriological parameters. The PCA generated three PC with a cumulative explained variation of 78.28 %. The generalised linear model showed strong significant positive relationships (p < 0.001) of E. coli with Fe, nitrate, Cu and TDS, and a strong significant negative relationship (p < 0.001) with pH. Overall, the CCME-WQI showed the water bodies in the upper reaches of the Cunas River as good water quality (87.07), in the middle reaches as favourable water quality (67.65) and in the lower reaches as poor water quality (34.86). In the tributary, the CCME-WQI showed the water bodies as having good water quality (82.34).

Integrative multi-omics analysis of childhood aggressive behavior

This study introduces and illustrates the potential of an integrated multi-omics approach in investigating the underlying biology of complex traits such as childhood aggressive behavior. Using multivariate statistical methods, we integrated 45 polygenic scores (PGSs) based on genome-wide SNP data, 78,772 CpGs, and 90 metabolites for 645 twins (cases=42.0%, controls=58.0%). The single-omics models selected 31 PGSs, 1614 CpGs, and 90 metabolites, and the multi-omics biomarker panel comprised 44 PGSs, 746 CpGs, and 90 metabolites. The predictive accuracy in the test (N=277, cases=42.2%, controls=57.8%) and validation data (N=142 participants from a clinical cohort, cases=45.1%, controls=54.9%) ranged from 43.0% to 57.0% for the single- and multi-omics models. The average correlations across omics layers of omics traits selected for aggression in single-omics models ranged from 0.18 to 0.28. In the multi-omics model higher correlations were found and we describe five sets of correlational patterns with high absolute correlations (|r| ≥ 0.60) of aggression-related omics traits selected into the multi-omics model, providing novel biological insights.

Geochemical characterization of the Sutlegen bauxite deposit, SW Antalya

Purpose.The purpose is to determine geological and geochemical characteristics of the Sutlegen (Antalya, Turkey) bauxites, to identify the elements that played a major role in their formation. Methods. X-ray diffraction (XRD) mineral phase analysis, X-ray fluorescence (XRF) elemental analysis, plasma-mass spectrometry (ICP-MS), the petrographic and mineralogical analyses, and multivariate statistical methods were used. Findings. The major element content of the ore was determined as Al2O3 (60-35.2 wt%), SiO2 (39.5-0.2 wt%), Fe2O3 (48.4-19.5 wt%), TiO2 (36.9-16 wt%), and P2O5 (0.5-0.1 wt%). The Sutlegen region, which shows epirogenetic action with the uplift of the earth's crust, is generally rich in neritic carbonates. It was revealed that the bauxite ores have undergone moderate and strong laterization as a result of the deferruginization in the environment, and they were classified into four groups as lateritic, ferritic, kaolinitic, and bauxite. The increase in the aluminosilicate minerals, which were formed during the formation of bauxite in the environment was found to be directly proportional to the laterization processes. In this context, it was considered that the lateritic material that was firstly formed in the environment filled the cavities and pores of the karst-type limestones and sedimentary units in the region by superficial transfer phenomena. The bivariate diagrams of Log Cr vs. Log Ni revealed that the bauxite that formed in the region had an ultrabasic source. Originality. In literature, no scientific studies have been found on bauxite mineralization in the Sutlegen deposits that have been operated for a long period. Practical implications. In this context, the geochemical characteristics of bauxites revealed that the source of the laterization process in the region was the ultrabasic igneous rocks. The lateritic material moved by superficial transfer was accumulated on sandstone, claystone, siltstone, and limestone and in karstic cavities; then, it formed karstic bauxite (kaolinitic and bauxite) of different classifications due to the effect of metamorphism.

Peripheral areas and their distinctive characteristics: The case of Hungary

The delimitation and classification of peripheral settlements using multivariate statistical methods is presented in this article, with a case study of Hungary. A combination of four different methods provided the basis for the delimitation of settlements defined as peripheral. As significant overlapping was detected between the results of the different methods, peripheries – more than one-fifth of the Hungarian settlements – were identified in a common set of the results. The independence of the results from the applied methods points to the fact that peripherisation is multi-faceted, and the peripheries of Hungary are stable and well-discernible from other regions. After the identification of peripheral areas, we classified these settlements into groups based on their specific features. Multiple steps specifying the relevant variables resulted in selecting the most appropriate 10 indicators and these served as the basis for a hierarchical cluster analysis, through which 7 clusters (types of peripheries) were identified. Five of them comprised enough cases to detect the most important dimensions and specific features of the backwardness of these groups. These clusters demonstrated a spatial pattern and their socioeconomic and infrastructural features highlighted considerable disparities. These differences should be taken into consideration when development policies are applied at regional levels or below.