Task partitioning in swarms of robots: an adaptive method for strategy selection

Task partitioning is the decomposition of a task into two or more sub-tasks that can be tackled separately. Task partitioning can be observed in many species of social insects, as it is often an advantageous way of organizing the work of a group of individuals. Potential advantages of task partitioning are, among others: reduction of interference between workers, exploitation of individuals?? skills and specializations, energy efficiency, and higher parallelism. Even though swarms of robots can benefit from task partitioning in the same way as social insects do, only few works in swarm robotics are dedicated to this subject. In this paper, we study the case in which a swarm of robots has to tackle a task that can be partitioned into a sequence of two sub-tasks. We propose a method that allows the individual robots in the swarm to decide whether to partition the given task or not. The method is self-organized, relies on the experience of each individual, and does not require explicit communication between robots. We evaluate the method in simulation experiments, using foraging as testbed. We study cases in which task partitioning is preferable and cases in which it is not. We show that the proposed method leads to good performance of the swarm in both cases, by employing task partitioning only when it is advantageous. We also show that the swarm is able to react to changes in the environmental conditions by adapting the behavior on-line. Scalability experiments show that the proposed method performs well across all the tested group sizes.     

The effect of various hypoglycaemic sulphonylureas on the cardiotoxicity of glycosides and arrhythmogenic activity due to myocardial ischaemia

The effects of different sulphonylureas on the electrical cardiac activity were studied in 145 rabbits and in 103 rats as well as in 278 digitalis-treated, non-smoker non-insulin-dependent diabetics on the same therapy at least during the previous three months. In rabbits and rats glibenclamide (0.0032-100 mumol. kg-1) decreased, while tolbutamide and carbutamide (0.008-1000 mumol. kg-1) increased strophantidin toxicity and myocardial ischaemia induced transitory ventricular fibrillation dose-dependently. The differences between the dose-response curve of glibenclamide and those of tolbutamide or carbutamide were significant. In digitalized non-insulin-dependent diabetics, multifocal ectopic ventricular beats could be observed in none among the 80 glibenclamide-treated diabetics, while in 12 cases of the 71 tolbutamide and in 10 cases of the 61 carbutamide treated diabetics. Two of the 66 non-insulin-dependent diabetics receiving only diet and 7 of the 278 age and sex matched, non-smoker, metabolically healthy patients had multifocal ectopic ventricular beats. No significant difference could be found between the therapeutical groups. It was concluded that instead of tolbutamide, glibenclamide must be preferred in digitalis-treated diabetics, when metabolic control is not satisfactorily achieved by diet and regime alone.     

Soil and root nutrient chemistry structure root-associated fungal assemblages in temperate forests

Root-associated fungi (RAF) link nutrient fluxes between soil and roots and thus play important roles in ecosystem functioning. To enhance our understanding of the factors that control RAF, we fitted statistical models to explain variation in RAF community structure using data from 150 temperate forest sites covering a broad range of environmental conditions and chemical root traits. We found that variation in RAF communities was related to both root traits (e.g., cations, carbohydrates, NO₃⁻) and soil properties (pH, cations, moisture, C/N). The identified drivers were the combined result of distinct response patterns of fungal taxa (determined at the rank of orders) to biotic and abiotic factors. Our results support that RAF community variation is related to evolutionary adaptedness of fungal lineages and consequently, drivers of RAF communities are context-dependent.     

Dormancy and germination: making every seed count in restoration

From 50 to 90% of wild plant species worldwide produce seeds that are dormant upon maturity, with specific dormancy traits driven by species' occurrence geography, growth form, and genetic factors. While dormancy is a beneficial adaptation for intact natural systems, it can limit plant recruitment in restoration scenarios because seeds may take several seasons to lose dormancy and consequently show low or erratic germination. During this time, seed predation, weed competition, soil erosion, and seed viability loss can lead to plant re‐establishment failure. Understanding and considering seed dormancy and germination traits in restoration planning are thus critical to ensuring effective seed management and seed use efficiency. There are five known dormancy classes (physiological, physical, combinational, morphological, and morphophysiological), each requiring specific cues to alleviate dormancy and enable germination. The dormancy status of a seed can be determined through a series of simple steps that account for initial seed quality and assess germination across a range of environmental conditions. In this article, we outline the steps of the dormancy classification process and the various corresponding methodologies for ex situ dormancy alleviation. We also highlight the importance of record‐keeping and reporting of seed accession information (e.g. geographic coordinates of the seed collection location, cleaning and quality information, storage conditions, and dormancy testing data) to ensure that these factors are adequately considered in restoration planning.     

Can S-LCA methodology support responsible sourcing of raw materials in EU policy context?

Purpose

Access, affordability and sustainability of raw material supply chains are crucial to the sustainable development of the European Union (EU) for both society and economy. The study investigates whether and how the social life cycle assessment (S-LCA) methodology can support responsible sourcing of raw materials in Europe. The potential of social indicators already available in an S-LCA database is tested for the development of new metrics to monitor social risks in raw material industries at EU policy level.

Methods

The Product Social Impact Life Cycle Assessment (PSILCA) database was identified as a data and indicators source to assess social risks in raw material industries in EU-28 and extra-EU countries. Six raw material country sectors in the scope of the European policy on raw materials were identified and aggregated among those available in PSILCA. The selection of indicators for the assessment was based on the RACER (Relevance, Acceptance, Credibility, Ease, Robustness) analysis, leading to the proposal of 9 social impact categories. An S-LCA of the selected raw material industries was, thus, performed for the EU-28 region, followed by a contribution analysis to detect direct and indirect impacts and investigate related supply chains. Finally, the social performance of raw material sectors in EU-28 was compared with that of six extra-EU countries.

Results and discussion

Considering the overall social risks in raw material industries, “Corruption”, “Fair salary”, “Health and safety” and “Freedom of association and collective bargaining” emerged as the most significant categories both in EU and extra-EU. EU-28 shows an above-average performance where the only exception is represented by the mining and quarrying sector. An investigation of the most contributing processes to social impact categories for EU-28 led to the identification of important risks originating in the supply chain and in extra-EU areas. Therefore, the S-LCA methodology confirmed the potential of a life cycle perspective to detect burdens shifting and trade-offs. However, only a limited view on the sectoral social performance could be obtained from the research due to a lack of social data.

Conclusions

The S-LCA methodology and indicators appear appropriate to perform an initial social sustainability screening, thus enabling the identification of hotspots in raw material supply chains and the prioritization of areas of action in EU policies. Further methodological developments in the S-LCA field are necessary to make the approach proposed in the paper fully adequate to support EU policies on raw materials.