Affective Man-Machine Interface: Unveiling human emotions through biosignals

As is known for centuries, humans exhibit an electrical profile. This profile is altered through various psychological and physiological processes, which can be measured through biosignals; e.g., electromyography (EMG) and electrodermal activity (EDA). These biosignals can reveal our emotions and, as such, can serve as an advanced man-machine interface (MMI) for empathic consumer products. However, such a MMI requires the correct classification of biosignals to emotion classes. This chapter starts with an introduction on biosignals for emotion detection. Next, a state-of-the-art review is presented on automatic emotion classification. Moreover, guidelines are presented for affective MMI. Subsequently, a research is presented that explores the use of EDA and three facial EMG signals to determine neutral, positive, negative, and mixed emotions, using recordings of 21 people. A range of techniques is tested, which resulted in a generic framework for automated emotion classification with up to 61.31% correct classification of the four emotion classes, without the need of personal profiles. Among various other directives for future research, the results emphasize the need for parallel processing of multiple biosignals

Post-Operative Pain After Knee Arthroscopy and Related Factors

The aim of this study was to explore the intensity of post-arthroscopy knee pain during the first 24 hours, and to study the influence of pre-operative pain, tourniquet time and amount of surgical trauma on post-arthroscopy pain. In 78 male patients that underwent elective arthroscopic menisectomy or diagnostic arthroscopy of the knee, preoperative and post-operative pain were registered using the Visual Analogue Scale. Variance for repeated measures and for independent observations was analysed. Supplementary analgesia was required for 23% of the patients, more often in the recovery room and between 2 and 8 hours postoperatively. Of all factors analyzed, only time was statistically significant in determining the level of post-operative pain. Supplementary analgesia was required only in patients that underwent operative arthroscopy, and more often in patients with tourniquet time of more than 40 minutes. In conclusions, post-operative time is the most significant factor related to the post-arthroscopy knee pain

Revealing Real-Time Emotional Responses: a Personalized Assessment based on Heartbeat Dynamics

Emotion recognition through computational modeling and analysis of physiological signals has been widely investigated in the last decade. Most of the proposed emotion recognition systems require relatively long-time series of multivariate records and do not provide accurate real-time characterizations using short-time series. To overcome these limitations, we propose a novel personalized probabilistic framework able to characterize the emotional state of a subject through the analysis of heartbeat dynamics exclusively. The study includes thirty subjects presented with a set of standardized images gathered from the international affective picture system, alternating levels of arousal and valence. Due to the intrinsic nonlinearity and nonstationarity of the RR interval series, a specific point-process model was devised for instantaneous identification considering autoregressive nonlinearities up to the third-order according to the Wiener-Volterra representation, thus tracking very fast stimulus-response changes. Features from the instantaneous spectrum and bispectrum, as well as the dominant Lyapunov exponent, were extracted and considered as input features to a support vector machine for classification. Results, estimating emotions each 10 seconds, achieve an overall accuracy in recognizing four emotional states based on the circumplex model of affect of 79.29%, with 79.15% on the valence axis, and 83.55% on the arousal axis

Integrated motor drives: state of the art and future trends

With increased need for high power density, high efficiency and high temperature capabilities in Aerospace and Automotive applications, Integrated Motor Drives (IMD) offers a potential solution. However, close physical integration of the converter and the machine may also lead to an increase in components temperature. This requires careful mechanical, structural and thermal analysis; and design of the IMD system. This paper reviews existing IMD technologies and their thermal effects on the IMD system. The effects of the power electronics (PE) position on the IMD system and its respective thermal management concepts are also investigated. The challenges faced in designing and manufacturing of an IMD along with the mechanical and structural impacts of close physical integration is also discussed and potential solutions are provided. Potential converter topologies for an IMD like the Matrix converter, 2-level Bridge, 3-level NPC and Multiphase full bridge converters are also reviewed. Wide band gap devices like SiC and GaN and their packaging in power modules for IMDs are also discussed. Power modules components and packaging technologies are also presented

Testing a global standard for quantifying species recovery and assessing conservation impact

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a “Green List of Species” (now the IUCN Green Status of Species). A draft Green Status framework for assessing species’ progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species’ viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species’ recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard

Testing a global standard for quantifying species recovery and assessing conservation impact.

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a "Green List of Species" (now the IUCN Green Status of Species). A draft Green Status framework for assessing species' progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species' viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species' recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard

Motion of an artificial satellite inside a resisting atmosphere

Brouwer and Hori solved the problem of the motion of an artificial satellite inside a resisting atmosphere, considering the atmospheric density d expressed by the relation d = ∂-αr or d = exp (-αr). In this article an ameliorated solution is given in the same problem with the hypothesis d = ∂-α(r-ρ{variant}), where α is a constant positive coefficient; ρ{variant} is the terrestrial radius on the vector radius r of the satellite; and ∂ = 2.71828 is the basis of the natural logarithms. © 1966

The effect of group size, reproductive condition, and time period on sexual segregation patterns in three vespertilionid bat species

Sexual segregation is widespread across the animal kingdom, yet there is limited consensus on the factors that shape this behavioural phenomenon. Many of the existing theories are based on study species with high levels of sexual size dimorphism. Insights from studies on species with minimal sexual size dimorphism, such as vespertilionid bats, provide an opportunity to study the factors associated with segregation irrespective of body size effects. Using long-term data pooled from multiple bat box monitoring schemes across the U.K., we investigated segregation patterns in maternity roosts of three vespertilionid bat species, Bechstein’s bats, Myotis bechsteinii, Natterer’s bats, M. nattereri, and brown long-eared bats, Plecotus auritus. We used the Sexual Segregation and Aggregation Statistic (SSAS) to evaluate temporal trends of sexual segregation of roosts over the reproductive period (divided into pre-parturition, lactation, and post-lactation periods). Additionally, we used generalised linear mixed models and beta regression models to investigate the effect of group size on segregation patterns. Our results showed that the size of the maternity group was an important covariate of inter- and intra-sexual segregation, with males and non-breeding females typically segregated from large maternity groups across all three periods. Additionally, we demonstrate that reproductive condition and period influence segregation patterns, with breeding females segregated from non-breeding females and males during the lactation period. Although sexual segregation may be caused by multiple mechanisms, our results show that group size, female reproductive condition, and time period are key factors associated with segregation within bat roosts. These findings make a valuable contribution to the understanding of inter- and intra-sexual segregation in vespertilionid bats and complement existing research on segregation in other mammalian taxa, providing further evidence that sexual size dimorphism is not a prerequisite for sexual segregation

Using Bio-inspired Intelligence for Web Opinion Mining

This work proposes a bio-inspired based methodology in order to extract and evaluate user’s web texts / posts. To validate the methodology, a dataset is constructed using real data arising from Greek fora. The obtained results are compared with a commonly used machine learning technique (decision trees- C4.5 algorithm). The bio-inspired algorithm (namely the hybrid PSO/ACO2 algorithm) achieved average classification accuracy 90.59 % in a 10 fold cross validation experiment, outperforming the C4.5 algorithm (83.66%). The proposed methodology could be easily integrated with a decision support system providing services in the fields of e-commerce or e-government in order to help merchants acquire customer satisfaction or public administrators capture common understanding