47 research outputs found
What to bid and when to stop
No full textNegotiation is an important activity in human society, and is studied by various disciplines, ranging from economics and game theory, to electronic commerce, social psychology, and artificial intelligence. Traditionally, negotiation is a necessary, but also time-consuming and expensive activity. Therefore, in the last decades there has been a large interest in the automation of negotiation, for example in the setting of e-commerce. This interest is fueled by the promise of automated agents eventually being able to negotiate on behalf of human negotiators.Every year, automated negotiation agents are improving in various ways, and there is now a large body of negotiation strategies available, all with their unique strengths and weaknesses. For example, some agents are able to predict the opponent's preferences very well, while others focus more on having a sophisticated bidding strategy. The problem however, is that there is little incremental improvement in agent design, as the agents are tested in varying negotiation settings, using a diverse set of performance measures. This makes it very difficult to meaningfully compare the agents, let alone their underlying techniques. As a result, we lack a reliable way to pinpoint the most effective components in a negotiating agent.There are two major advantages of distinguishing between the different components of a negotiating agent's strategy: first, it allows the study of the behavior and performance of the components in isolation. For example, it becomes possible to compare the preference learning component of all agents, and to identify the best among them. Second, we can proceed to mix and match different components to create new negotiation strategies., e.g.: replacing the preference learning technique of an agent and then examining whether this makes a difference. Such a procedure enables us to combine the individual components to systematically explore the space of possible negotiation strategies.To develop a compositional approach to evaluate and combine the components, we identify structure in most agent designs by introducing the BOA architecture, in which we can develop and integrate the different components of a negotiating agent. We identify three main components of a general negotiation strategy; namely a bidding strategy (B), possibly an opponent model (O), and an acceptance strategy (A). The bidding strategy considers what concessions it deems appropriate given its own preferences, and takes the opponent into account by using an opponent model. The acceptance strategy decides whether offers proposed by the opponent should be accepted.The BOA architecture is integrated into a generic negotiation environment called Genius, which is a software environment for designing and evaluating negotiation strategies. To explore the negotiation strategy space of the negotiation research community, we amend the Genius repository with various existing agents and scenarios from literature. Additionally, we organize a yearly international negotiation competition (ANAC) to harvest even more strategies and scenarios. ANAC also acts as an evaluation tool for negotiation strategies, and encourages the design of negotiation strategies and scenarios.We re-implement agents from literature and ANAC and decouple them to fit into the BOA architecture without introducing any changes in their behavior. For each of the three components, we manage to find and analyze the best ones for specific cases, as described below. We show that the BOA framework leads to significant improvements in agent design by wining ANAC 2013, which had 19 participating teams from 8 international institutions, with an agent that is designed using the BOA framework and is informed by a preliminary analysis of the different components.In every negotiation, one of the negotiating parties must accept an offer to reach an agreement. Therefore, it is important that a negotiator employs a proficient mechanism to decide under which conditions to accept. When contemplating whether to accept an offer, the agent is faced with the acceptance dilemma: accepting the offer may be suboptimal, as better offers may still be presented before time runs out. On the other hand, accepting too late may prevent an agreement from being reached, resulting in a break off with no gain for either party. We classify and compare state-of-the-art generic acceptance conditions. We propose new acceptance strategies and we demonstrate that they outperform the other conditions. We also provide insight into why some conditions work better than others and investigate correlations between the properties of the negotiation scenario and the efficacy of acceptance conditions.Later, we adopt a more principled approach by applying optimal stopping theory to calculate the optimal decision on the acceptance of an offer. We approach the decision of whether to accept as a sequential decision problem, by modeling the bids received as a stochastic process. We determine the optimal acceptance policies for particular opponent classes and we present an approach to estimate the expected range of offers when the type of opponent is unknown. We show that the proposed approach is able to find the optimal time to accept, and improves upon all existing acceptance strategies.Another principal component of a negotiating agent's strategy is its ability to take the opponent's preferences into account. The quality of an opponent model can be measured in two different ways. One is to use the agent's performance as a benchmark for the model's quality. We evaluate and compare the performance of a selection of state-of-the-art opponent modeling techniques in negotiation. We provide an overview of the factors influencing the quality of a model and we analyze how the performance of opponent models depends on the negotiation setting. We identify a class of simple and surprisingly effective opponent modeling techniques that did not receive much previous attention in literature.The other way to measure the quality of an opponent model is to directly evaluate its accuracy by using similarity measures. We review all methods to measure the accuracy of an opponent model and we then analyze how changes in accuracy translate into performance differences. Moreover, we pinpoint the best predictors for good performance. This leads to new insights concerning how to construct an opponent model, and what we need to measure when optimizing performance.Finally, we take two different approaches to gain more insight into effective bidding strategies. We present a new classification method for negotiation strategies, based on their pattern of concession making against different kinds of opponents. We apply this technique to classify some well-known negotiating strategies, and we formulate guidelines on how agents should bid in order to be successful, which gives insight into the bidding strategy space of negotiating agents. Furthermore, we apply optimal stopping theory again, this time to find the concessions that maximize utility for the bidder against particular opponents. We show there is an interesting connection between optimal bidding and optimal acceptance strategies, in the sense that they are mirrored versions of each other.Lastly, after analyzing all components separately, we put the pieces back together again. We take all BOA components accumulated so far, including the best ones, and combine them all together to explore the space of negotiation strategies.We compute the contribution of each component to the overall negotiation result, and we study the interaction between components. We find that combining the best agent components indeed makes the strongest agents. This shows that the component-based view of the BOA architecture not only provides a useful basis for developing negotiating agents but also provides a useful analytical tool. By varying the BOA components we are able to demonstrate the contribution of each component to the negotiation result, and thus analyze the significance of each. The bidding strategy is by far the most important to consider, followed by the acceptance conditions and finally followed by the opponent model.Our results validate the analytical approach of the BOA framework to first optimize the individual components, and then to recombine them into a negotiating agent
Ballynahone Bog - Atmospheric ammonia concentration survey: Impacts of a new poultry farm
No full textIntensive poultry farming are recognised as large emission sources of atmospheric ammonia (NH3) gas. In the summer of 2014, a poultry farm was constructed on the south-western edge of Ballynahone National Park, an Area of Special Scientific Interest (ASSI/SAC) and a Ramsar site. The sensitivity of peatland ecosystems to nitrogen deposition and the prevailing south-westerly wind in the area has led to concern that Ballynahone Bog may be adversely affected by NH3 emissions arising from the poultry livestock installation. A local-scale transect downwind of the poultry housing across the reserve and three other monitoring locations within the reserve were set up to help identify the effects of the poultry housing on NH3 emissions to the atmosphere. Monthly ammonia measurements were made before and after population of the new poultry housing. This report summarises the measurement period September 2014 – January 2018
Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
No full textApproaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups
Compartmentalized cross-linked enzymatic nano-aggregates (c-CLEnA) for efficient in-flow biocatalysis
No full textNano-sized enzyme aggregates, which preserve their catalytic activity are of great interest for flow processes, as these catalytic species show minimal diffusional issues, and are still sizeable enough to be effectively separated from the formed product. The realization of such catalysts is however far from trivial. The stable formation of a micro-to millimeter-sized enzyme aggregate is feasible via the formation of a cross-linked enzyme aggregate (CLEA); however, such a process leads to a rather broad size distribution, which is not always compatible with microflow conditions. Here, we present the design of a compartmentalized templated CLEA (c-CLEnA), inside the nano-cavity of bowl-shaped polymer vesicles, coined stomatocytes. Due to the enzyme preorganization and concentration in the cavity, cross-linking could be performed with substantially lower amount of cross-linking agents, which was highly beneficial for the residual enzyme activity. Our methodology is generally applicable, as demonstrated by using two different cross-linkers (glutaraldehyde and genipin). Moreover, c-CLEnA nanoreactors were designed with Candida antarctica Lipase B (CalB) and Porcine Liver Esterase (PLE), as well as a mixture of glucose oxidase (GOx) and horseradish peroxidase (HRP). Interestingly, when genipin was used as cross-linker, all enzymes preserved their initial activity. Furthermore, as proof of principle, we demonstrated the successful implementation of different c-CLEnAs in a flow reactor in which the c-CLEnA nanoreactors retained their full catalytic function even after ten runs. Such a c-CLEnA nanoreactor represents a significant step forward in the area of in-flow biocatalysis.BT/Biocatalysi
Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index
No full textObesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and similar to 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 x 10(-8)), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation
Novel Approach Identifies SNPs in SLC2A10 and KCNK9 with Evidence for Parent-of-Origin Effect on Body Mass Index
No full textThe phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ~4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity. © 2014 Hoggart et al
Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution
No full textWaist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10⁻⁹ to P = 1.8 × 10⁻⁴⁰) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10⁻³ to P = 1.2 × 10⁻¹³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions
Who provides care for people dying of cancer? A comparison of a rural and metropolitan cohort in a South Australian bereaved population study
No full textAuthor version under embargo for 12 months from publication. This is the peer reviewed version of the following article: [Burns, C.M., Dal Grande, E., Tieman, J.J., Abernethy, A.P. and Currow, D.C. (2015). Who provides care for people dying of cancer? A comparison of a rural and metropolitan cohort in a South Australian bereaved population study. Australian Journal of Rural Health, 23(1) pp. 24-31. ], which has been published in final form at [DOI:10.1111/ajr.12168]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Background: People in the rural and remote areas often have disparities in access to services and specific challenges when called upon to provide care. In order to plan and resource palliative care services, it is important to know what levels of service are available and what are the perceived unmet needs of caregivers for people at the end of life.
Purpose: To examine and compare urban and rural palliative care service availability and patterns of care from randomised, population-based surveys of caregivers of people at the end of life.
Methods: Survey responses on the death of ‘someone close’ from 23,588 interviews of South Australians conducted between 2001 and 2007 are analysed exploring palliative care service availability, caregiving provided, and characteristics of the deceased and caregivers.
Results: There was no difference in reported rates of accessing specialist palliative care services between rural and urban respondents (in unadjusted and adjusted analyses) nor did the proportion of people for whom cancer was their life-limiting illness. There was greater reliance on friends than first degree relatives in hands-on care provided at the end of life in rural settings. The rates of reported need for more support did not differ between urban and rural respondents for caregivers of people at the end of life.
Conclusion
Use of palliative care services was similar for rural and urban caregivers for someone close at the end of life with similar levels of met and unmet needs
Preoperative aerobic fitness and perioperative outcomes in patients undergoing cystectomy before and after implementation of a national lockdown
No full textBackground: Lower fitness is a predictor of adverse outcomes after radical cystectomy. Lockdown measures during the COVID-19 pandemic affected daily physical activity. We hypothesised that lockdown during the pandemic was associated with a reduction in preoperative aerobic fitness and an increase in postoperative complications in patients undergoing radical cystectomy. Methods: We reviewed routine preoperative cardiopulmonary exercise testing (CPET) data collected prior to the pandemic (September 2018 to March 2020) and after lockdown (March 2020 to July 2021) in patients undergoing radical cystectomy. Differences in CPET variables, Postoperative Morbidity Survey (POMS) data, and length of hospital stay were compared. Results: We identified 267 patients (85 pre-lockdown and 83 during lockdown) who underwent CPET and radical cystectomy. Patients undergoing radical cystectomy throughout lockdown had lower ventilatory anaerobic threshold (9.0 [7.9–10.9] vs 10.3 [9.1–12.3] ml kg−1 min−1; P=0.0002), peak oxygen uptake (15.5 [12.9–19.1] vs 17.5 [14.4–21.0] ml kg−1 min−1; P=0.015), and higher ventilatory equivalents for carbon dioxide (34.7 [31.4–38.5] vs 33.4 [30.5–36.5]; P=0.030) compared with pre-lockdown. Changes were more pronounced in males and those aged >65 yr. Patients undergoing radical cystectomy throughout lockdown had a higher proportion of day 5 POMS-defined morbidity (89% vs 75%, odds ratio [OR] 2.698, 95% confidence interval [CI] 1.143–6.653; P=0.019), specifically related to pulmonary complications (30% vs 13%, OR 2.900, 95% CI 1.368–6.194; P=0.007) and pain (27% vs 9%, OR 3.471, 95% CI 1.427–7.960; P=0.004), compared with pre-lockdown on univariate analysis. Conclusions: Lockdown measures in response to the COVID-19 pandemic were associated with a reduction in fitness and an increase in postoperative morbidity among patients undergoing radical cystectomy
Author Correction: Engineering transient dynamics of artificial cells by stochastic distribution of enzymes (Nature Communications, (2021), 12, 1, (6897), 10.1038/s41467-021-27229-0)
No full textIn this article the affiliation Institució Catalana de Recerca i Estudis Avançats (ICREA), Pg. Lluís Companys 23, 08010 Barcelona, Spain for Samuel Sanchez was missing. The original article has been corrected
