Thermodynamic constraints on the assembly and diversity of microbial ecosystems are different near to and far from equilibrium

Non-equilibrium thermodynamics has long been an area of substantial interest to ecologists because most fundamental biological processes, such as protein synthesis and respiration, are inherently energy-consuming. However, most of this interest has focused on developing coarse ecosystem-level maximisation principles, providing little insight into underlying mechanisms that lead to such emergent constraints. Microbial communities are a natural system to decipher this mechanistic basis because their interactions in the form of substrate consumption, metabolite production, and cross-feeding can be described explicitly in thermodynamic terms. Previous work has considered how thermodynamic constraints impact competition between pairs of species, but restrained from analysing how this manifests in complex dynamical systems. To address this gap, we develop a thermodynamic microbial community model with fully reversible reaction kinetics, which allows direct consideration of free-energy dissipation. This also allows species to interact via products rather than just substrates, increasing the dynamical complexity, and allowing a more nuanced classification of interaction types to emerge. Using this model, we find that community diversity increases with substrate lability, because greater free-energy availability allows for faster generation of niches. Thus, more niches are generated in the time frame of community establishment, leading to higher final species diversity. We also find that allowing species to make use of near-to-equilibrium reactions increases diversity in a low free-energy regime. In such a regime, two new thermodynamic interaction types that we identify here reach comparable strengths to the conventional (competition and facilitation) types, emphasising the key role that thermodynamics plays in community dynamics. Our results suggest that accounting for realistic thermodynamic constraints is vital for understanding the dynamics of real-world microbial communities.

The Applicability of Augmented Reality Technologies for Evaluating Learning Activities

a new trend in the development of immersive technologies has become augmented reality (AR), which is in demand due to its property to implement visual objects to enrich the learning content. The paper is devoted to the study of the applicability of AR technologies for evaluating learning activi-ties since there is a problem of inconsistency of teaching approaches with tools that lead to biased results. This led to the development of the “AR Quiz” application that contains interaction types such as touch-based, voice, input field, gaze and gesture that stimulate activities. In combination with 10 other forms of assessment materials, its application field has expanded and the tasks for students have diversified. The present study provides the calculation of validity and reliability coefficients of the assessment materials contained in the “AR Quiz” application that reflects the suitability of indicators for the purpose, accuracy and stability of measurements. The paper reveals positive attitudes of expert teachers and students towards the use of AR when evaluating learning activities. Along with integration map of compliance of AR interaction types with assessment materials, the paper provides recommendations for teachers on evaluating learning activities based on AR.

The role of indirect effects in coevolution as mutualism transitions into antagonism

Species interactions have evolved from antagonistic to mutualistic and back several times throughout life's history. Yet, it is unclear how changes in the type of interaction between species alter the coevolutionary dynamics of entire communities. This is a pressing matter, as transitions from mutualisms to antagonisms may be becoming more common with human-induced global change. Here, we combine network and evolutionary theory to simulate how shifts in interaction types alter the coevolution of empirical communities. We show that as mutualistic networks shift to antagonistic, selection imposed by direct partners begins to outweigh that imposed by indirect partners. This weakening of indirect effects is associated with communities losing their tight integration of traits and increasing their rate of adaptation. The above changes are more pronounced when specialist consumers are the first species to switch to antagonism. A shift in the outcome of species' interactions may therefore reverberate across communities and alter the direction and speed of coevolution.

Understanding the Relationship between Interactions and Outcomes in Human-in-the-Loop Machine Learning

Human-in-the-loop Machine Learning (HIL-ML) is a widely adopted paradigm for instilling human knowledge in autonomous agents. Many design choices influence the efficiency and effectiveness of such interactive learning processes, particularly the interaction type through which the human teacher may provide feedback. While different interaction types (demonstrations, preferences, etc.) have been proposed and evaluated in the HIL-ML literature, there has been little discussion of how these compare or how they should be selected to best address a particular learning problem. In this survey, we propose an organizing principle for HIL-ML that provides a way to analyze the effects of interaction types on human performance and training data. We also identify open problems in understanding the effects of interaction types.

Performance inheritance and combining ability of spring barley accessions

Purpose and objectives. To establish the gene interaction types in the performance inheritance, to evaluate the combining abilities and effects of genes for this trait in spring barley accessions. Materials and methods. We investigated 75 F1 spring barley hybrid combinations derived from crossing 25 female forms with three male ones (chaffy and naked). Crossing was conducted in accordance with topcross design. F1 seeds and parents were sown with a cassette breeding planter SKS-6A. Grain pea was the forecrop. The plot area was 0.20 m2. The interrow distance was 0.20 m; the inter-plot tracks were of 0.50 m. Crossings were performed in two replications. Plants were harvested manually, with roots. For structural analysis, 20 typical plants were chosen from each F1 hybrid population, and the performance inheritance was determined by dominance degree (hp). The obtained data were grouped and gene interaction types were determined as per G.M. Beil and R.E. Atkins’s classification. Using two-factor analysis of variance in STATISTICA 10, we found significant differences between the GCA and SCA variances for the performance and evaluated the combining ability effects. Results and discussion. In 2019–2020, the features of 22 spring barley cultivars and three lines were described in terms of the gene interaction types in the performance inheritance and combining ability. On this basis, the prospects of biotype selections were evaluated. In the arid conditions of 2019, F1 only showed positive over dominance, while in favorable 2020 the inheritance types varied from positive to negative overdominance. In the two years, the general combining ability was high in female cultivars Khors and Troian. The male components did not show consistently high GCA for the both years. Hybrids between accessions with a high GCA and accessions with a lower or intermediate GCA may be promising in breeding due appearance of positive transgressions in the offspring. In 2019, the SCA effects were significantly strong in female forms Troian, Datcha, Gladys, Grace, Gatunok, Modern, and Herkules and in male forms Ahrarii and Scrabble. Conclusions. The study found that the gene interaction types in the spring barley performance inheritance depended on cross combinations and growing conditions. In unfavorable 2019, F1 only showed positive overdominance (heterosis), while in favorable 2020, positive overdominance, positive dominance and intermediate inheritance were observed. In 2019–2020, the high GCA was seen in female cultivars Khors and Troian. The strong SCA effects were noticed in female components Troian, Datcha, Gladys, Grace, Gatunok, Modern, and Herkules and male forms Agrarii and Scrabble. The hybrid combinations with the maximum probability of producing transgressive segregants have been selected