Agricultural biomass as provisioning ecosystem service: quantification of energy flows

Agro-ecosystems supply provisioning, regulating and cultural services to human society. This study focuses on the agro-ecosystem provisioning services regarding the production of agricultural biomass. These services strongly respond to the socio-economic demands of human beings, and are characterised by an injection of energy in the ecosystems production cycle which is often exceeding the ecological capacity of the ecosystem, i.e. the overall ability of the ecosystem to produce goods and services linked to its bio-physical structure and processes that take place during the agricultural production. Agricultural production is identified as ecosystem service in widely recognised ecosystem service frameworks, but currently there is no clear agreement within the scientific and policy communities on how the ecological-socio-economic flow linked to this provisioning service should be assessed, beyond a mere accounting of yields. This study attempts to provide a new insight to this issue by proposing an approach based on the energy budget, which takes into consideration the energy needed by the ecosystem to supply the service. The approach is based on the concepts of Energy Return on Investment (EROI) and Net Energy Balance (NEB), and considers different bio-physical structures and processes of agroecosystems. The work is structured in three parts: the first aims at estimating inputs (machinery, seeds, fertilizers, irrigation, labour) in energy terms; the second at estimating biomass output in energy terms; the third to compare actual agricultural production with three reference scenarios encompassing a range of human input (no input – low input –high input scenarios). Results show that in general terms cereal and grassland systems have the largest energy gains (both in terms of EROI and NEB). Such systems are characterised by a lower economic value of their output compared to other producing systems such as fruits, which have lower energy gains but a higher embodied energy, which is recognized in the market as valuable. Comparison of actual production systems with the high input scenario confirms that current production in Europe is already highly intensive, and that increasing the energy input would not improve the efficiency of the conversion of such additional energy into biomass. Overall, the proposed approach seems a useful tool to identify which are the factors in the agricultural production process that could be modified to improve the energy efficiency in agricultural systems and the sustainability of their production. This study can be considered as a first step in the assessment of the total energy balance of the agro-ecosystem. In fact it deals with the quantification of energy regarding human inputs and the corresponding output and further analysis should address crucial issues such as the quality of the energy and the embodied energy in the plant production, which will help to better understand the complexity of the agro-ecosystems

Exploring sociality and engagement in play through game-control distribution

Abstract This study explores how distributing the controls of a video game among multiple players affects the sociality and engagement experienced in game play. A video game was developed in which the distribution of game controls among the players could be varied, thereby affecting the abilities of the individual players to control the game. An experiment was set up in which eight groups of three players were asked to play the video game while the distribution of the game controls was increased in three steps. After each playing session, the players' experiences of sociality and engagement were assessed using questionnaires. The results showed that distributing game control among the players increased the level of experienced sociality and reduced the level of experienced control. The game in which the controls were partly distributed led to the highest levels of experienced engagement, because the game allowed social play while still giving the players a sense of autonomy. The implications for interaction design are discussed

REVISITING ANNA MOSCOWITZ\u27S KROSS\u27S CRITIQUE OF NEW YORK CITY\u27S WOMEN\u27S COURT: THE CONTINUED PROBLEM OF SOLVING THE PROBLEM OF PROSTITUTION WITH SPECIALIZED CRIMINAL COURTS

This article explores New York City\u27s non-traditional, judicially based response to prostitution. This article first recounts the history of New York City’s Women’s Court. It then examines the work of the Midtown Community Court, the “problem-solving court” established in 1993 to address criminal issues, like prostitution, in Midtown Manhattan. It also discusses the renewed concerns about sex work in New York and describe the movement, propelled by modern reformers, to address prostitution through specialty courts. It then contrasts the shared features and attributes of the Women’s Court and Midtown Court models. Finally, the article urges modern reformers to step back from the problem-solving court movement and their call for the creation of more such specialized criminal courts

mlplasmids : a user-friendly tool to predict plasmid- and chromosome-derived sequences for single species

Assembly of bacterial short-read whole-genome sequencing data frequently results in hundreds of contigs for which the origin, plasmid or chromosome, is unclear. Complete genomes resolved by long-read sequencing can be used to generate and label short-read contigs. These were used to train several popular machine learning methods to classify the origin of contigs from Enterococcus faecium, Klebsiella pneumoniae and Escherichia colt using pentamer frequencies. We selected support-vector machine (SVM) models as the best classifier for all three bacterial species (Fl-score E. faecium=0.92, F1-score K. pneumoniae=0.90, F1-score E. coli=0.76), which outperformed other existing plasmid prediction tools using a benchmarking set of isolates. We demonstrated the scalability of our models by accurately predicting the plasmidome of a large collection of 1644 E. faecium isolates and illustrate its applicability by predicting the location of antibiotic-resistance genes in all three species. The SVM classifiers are publicly available as an R package and graphical-user interface called 'mlplasmids'. We anticipate that this tool may significantly facilitate research on the dissemination of plasmids encoding antibiotic resistance and/or contributing to host adaptation.Peer reviewe