873 resultados para Box Butte Experiment farm


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News from Iowa’s Center for Agricultural Safety and Health (I-CASH)

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News from Iowa’s Center for Agricultural Safety and Health (I-CASH)

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News from Iowa’s Center for Agricultural Safety and Health (I-CASH)

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The function of silk web decorations in orb weaving spiders has been debated for decades. The most accepted hypothesized functions are that web decorations I) provide camouflage against predators, 2) are an advertisement for vertebrates to avoid web damage, or 3) increase the attraction of prey to the web. Most studies have focused on only a few genera, Argiope being the most common. In this study, I evaluated the prey attraction hypothesis of silk decorations for a species of a poorly studied genus in this topic, Micrathena sexpinosa Hahn 1822. I used a web-choice experiment in which I presented empty or web-bearing frames at the end of a tunnel to stingless bees (Tetragonisca angustula). This frame-choice experiment consisted of the following comparisons: decorated web vs. empty frame, decorated web vs. undecorated web, and undecorated web vs. empty frame. Webs with decoration intercepted significantly more bees than empty frames and undecorated webs. Therefore, the decorations of Micrathena sexpinosa might play a role in increasing foraging success.

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Culverts are common means to convey flow through the roadway system for small streams. In general, larger flows and road embankment heights entail the use of multibarrel culverts (a.k.a. multi-box) culverts. Box culverts are generally designed to handle events with a 50-year return period, and therefore convey considerably lower flows much of the time. While there are no issues with conveying high flows, many multi-box culverts in Iowa pose a significant problem related to sedimentation. The highly erosive Iowa soils can easily lead to the situation that some of the barrels can silt-in early after their construction, becoming partially filled with sediment in few years. Silting can reduce considerably the capacity of the culvert to handle larger flow events. Phase I of this Iowa Highway Research Board project (TR-545) led to an innovative solution for preventing sedimentation. The solution was comprehensively investigated through laboratory experiments and numerical modeling aimed at screening design alternatives and testing their hydraulic and sediment conveyance performance. Following this study phase, the Technical Advisory Committee suggested to implement the recommended sediment mitigation design to a field site. The site selected for implementation was a 3-box culvert crossing Willow Creek on IA Hwy 1W in Iowa City. The culvert was constructed in 1981 and the first cleanup was needed in 2000. Phase II of the TR 545 entailed the monitoring of the site with and without the selfcleaning sedimentation structure in place (similarly with the study conducted in laboratory). The first monitoring stage (Sept 2010 to December 2012) was aimed at providing a baseline for the operation of the as-designed culvert. In order to support Phase II research, a cleanup of the IA Hwy 1W culvert was conducted in September 2011. Subsequently, a monitoring program was initiated to document the sedimentation produced by individual and multiple storms propagating through the culvert. The first two years of monitoring showed inception of the sedimentation in the first spring following the cleanup. Sedimentation continued to increase throughout the monitoring program following the depositional patterns observed in the laboratory tests and those documented in the pre-cleaning surveys. The second part of Phase II of the study was aimed at monitoring the constructed self-cleaning structure. Since its construction in December 2012, the culvert site was continuously monitored through systematic observations. The evidence garnered in this phase of the study demonstrates the good performance of the self-cleaning structure in mitigating the sediment deposition at culverts. Besides their beneficial role in sediment mitigation, the designed self-cleaning structures maintain a clean and clear area upstream the culvert, keep a healthy flow through the central barrel offering hydraulic and aquatic habitat similar with that in the undisturbed stream reaches upstream and downstream the culvert. It can be concluded that the proposed self-cleaning structural solution “streamlines” the area upstream the culvert in a way that secures the safety of the culvert structure at high flows while producing much less disturbance in the stream behavior compared with the current constructive approaches.

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News from Iowa’s Center for Agricultural Safety and Health (I-CASH)

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News from Iowa’s Center for Agricultural Safety and Health (I-CASH)

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News from Iowa’s Center for Agricultural Safety and Health (I-CASH)

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News from Iowa’s Center for Agricultural Safety and Health (I-CASH)

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Background: C-reactive protein (CRP) is associated with risk of coronary heart disease (CHD). Whether CRP is causally associated with CHD or merely a marker of underlying atherosclerosis is uncertain. Methods: We used a Mendelian randomisation design to investigate the causal relationship of CRP with CHD. We identified three genetic variants in the CRP locus (rs7553007, rs1130864 and rs1205) which influence CRP levels. We tested the three SNPs for association with CHD amongst 28,112 CHD cases and 100,823 controls. We then compared the observed relationship between the SNPs and CHD, with that predicted from the association of SNPs with CRP levels, and of CRP levels with CHD. Results: SNPs in the CRP locus were not associated with CHD: rs7553007, OR 0.98 (95% CI, 0.94-1.01); rs1130864, OR 1.00 (95% CI, 0.86-1.15); rs1205, OR 1.03 (95% CI, 0.99-1.07); combined OR for all three SNPs, 1.00 (95% CI, 0.97-1.02), per 20% lower CRP (figure). In contrast, the predicted OR for CHD from a 20% lower CRP level is 0.94 (95% CI, 0.94- 0.95), based on meta-analysis of observational studies. Conclusions: Though CRP variants are associated with CRP levels, and CRP levels with risk of CHD, we observed that CRP variants are not associated with CHD risk. Our Mendelian randomisation experiment strongly argues against a causal association of CRP with CHD.

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News from Iowa’s Center for Agricultural Safety and Health (I-CASH)

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Dans cette thèse, nous étudions les aspects comportementaux d'agents qui interagissent dans des systèmes de files d'attente à l'aide de modèles de simulation et de méthodologies expérimentales. Chaque période les clients doivent choisir un prestataire de servivce. L'objectif est d'analyser l'impact des décisions des clients et des prestataires sur la formation des files d'attente. Dans un premier cas nous considérons des clients ayant un certain degré d'aversion au risque. Sur la base de leur perception de l'attente moyenne et de la variabilité de cette attente, ils forment une estimation de la limite supérieure de l'attente chez chacun des prestataires. Chaque période, ils choisissent le prestataire pour lequel cette estimation est la plus basse. Nos résultats indiquent qu'il n'y a pas de relation monotone entre le degré d'aversion au risque et la performance globale. En effet, une population de clients ayant un degré d'aversion au risque intermédiaire encoure généralement une attente moyenne plus élevée qu'une population d'agents indifférents au risque ou très averses au risque. Ensuite, nous incorporons les décisions des prestataires en leur permettant d'ajuster leur capacité de service sur la base de leur perception de la fréquence moyenne d'arrivées. Les résultats montrent que le comportement des clients et les décisions des prestataires présentent une forte "dépendance au sentier". En outre, nous montrons que les décisions des prestataires font converger l'attente moyenne pondérée vers l'attente de référence du marché. Finalement, une expérience de laboratoire dans laquelle des sujets jouent le rôle de prestataire de service nous a permis de conclure que les délais d'installation et de démantèlement de capacité affectent de manière significative la performance et les décisions des sujets. En particulier, les décisions du prestataire, sont influencées par ses commandes en carnet, sa capacité de service actuellement disponible et les décisions d'ajustement de capacité qu'il a prises, mais pas encore implémentées. - Queuing is a fact of life that we witness daily. We all have had the experience of waiting in line for some reason and we also know that it is an annoying situation. As the adage says "time is money"; this is perhaps the best way of stating what queuing problems mean for customers. Human beings are not very tolerant, but they are even less so when having to wait in line for service. Banks, roads, post offices and restaurants are just some examples where people must wait for service. Studies of queuing phenomena have typically addressed the optimisation of performance measures (e.g. average waiting time, queue length and server utilisation rates) and the analysis of equilibrium solutions. The individual behaviour of the agents involved in queueing systems and their decision making process have received little attention. Although this work has been useful to improve the efficiency of many queueing systems, or to design new processes in social and physical systems, it has only provided us with a limited ability to explain the behaviour observed in many real queues. In this dissertation we differ from this traditional research by analysing how the agents involved in the system make decisions instead of focusing on optimising performance measures or analysing an equilibrium solution. This dissertation builds on and extends the framework proposed by van Ackere and Larsen (2004) and van Ackere et al. (2010). We focus on studying behavioural aspects in queueing systems and incorporate this still underdeveloped framework into the operations management field. In the first chapter of this thesis we provide a general introduction to the area, as well as an overview of the results. In Chapters 2 and 3, we use Cellular Automata (CA) to model service systems where captive interacting customers must decide each period which facility to join for service. They base this decision on their expectations of sojourn times. Each period, customers use new information (their most recent experience and that of their best performing neighbour) to form expectations of sojourn time at the different facilities. Customers update their expectations using an adaptive expectations process to combine their memory and their new information. We label "conservative" those customers who give more weight to their memory than to the xiv Summary new information. In contrast, when they give more weight to new information, we call them "reactive". In Chapter 2, we consider customers with different degree of risk-aversion who take into account uncertainty. They choose which facility to join based on an estimated upper-bound of the sojourn time which they compute using their perceptions of the average sojourn time and the level of uncertainty. We assume the same exogenous service capacity for all facilities, which remains constant throughout. We first analyse the collective behaviour generated by the customers' decisions. We show that the system achieves low weighted average sojourn times when the collective behaviour results in neighbourhoods of customers loyal to a facility and the customers are approximately equally split among all facilities. The lowest weighted average sojourn time is achieved when exactly the same number of customers patronises each facility, implying that they do not wish to switch facility. In this case, the system has achieved the Nash equilibrium. We show that there is a non-monotonic relationship between the degree of risk-aversion and system performance. Customers with an intermediate degree of riskaversion typically achieve higher sojourn times; in particular they rarely achieve the Nash equilibrium. Risk-neutral customers have the highest probability of achieving the Nash Equilibrium. Chapter 3 considers a service system similar to the previous one but with risk-neutral customers, and relaxes the assumption of exogenous service rates. In this sense, we model a queueing system with endogenous service rates by enabling managers to adjust the service capacity of the facilities. We assume that managers do so based on their perceptions of the arrival rates and use the same principle of adaptive expectations to model these perceptions. We consider service systems in which the managers' decisions take time to be implemented. Managers are characterised by a profile which is determined by the speed at which they update their perceptions, the speed at which they take decisions, and how coherent they are when accounting for their previous decisions still to be implemented when taking their next decision. We find that the managers' decisions exhibit a strong path-dependence: owing to the initial conditions of the model, the facilities of managers with identical profiles can evolve completely differently. In some cases the system becomes "locked-in" into a monopoly or duopoly situation. The competition between managers causes the weighted average sojourn time of the system to converge to the exogenous benchmark value which they use to estimate their desired capacity. Concerning the managers' profile, we found that the more conservative Summary xv a manager is regarding new information, the larger the market share his facility achieves. Additionally, the faster he takes decisions, the higher the probability that he achieves a monopoly position. In Chapter 4 we consider a one-server queueing system with non-captive customers. We carry out an experiment aimed at analysing the way human subjects, taking on the role of the manager, take decisions in a laboratory regarding the capacity of a service facility. We adapt the model proposed by van Ackere et al (2010). This model relaxes the assumption of a captive market and allows current customers to decide whether or not to use the facility. Additionally the facility also has potential customers who currently do not patronise it, but might consider doing so in the future. We identify three groups of subjects whose decisions cause similar behavioural patterns. These groups are labelled: gradual investors, lumpy investors, and random investor. Using an autocorrelation analysis of the subjects' decisions, we illustrate that these decisions are positively correlated to the decisions taken one period early. Subsequently we formulate a heuristic to model the decision rule considered by subjects in the laboratory. We found that this decision rule fits very well for those subjects who gradually adjust capacity, but it does not capture the behaviour of the subjects of the other two groups. In Chapter 5 we summarise the results and provide suggestions for further work. Our main contribution is the use of simulation and experimental methodologies to explain the collective behaviour generated by customers' and managers' decisions in queueing systems as well as the analysis of the individual behaviour of these agents. In this way, we differ from the typical literature related to queueing systems which focuses on optimising performance measures and the analysis of equilibrium solutions. Our work can be seen as a first step towards understanding the interaction between customer behaviour and the capacity adjustment process in queueing systems. This framework is still in its early stages and accordingly there is a large potential for further work that spans several research topics. Interesting extensions to this work include incorporating other characteristics of queueing systems which affect the customers' experience (e.g. balking, reneging and jockeying); providing customers and managers with additional information to take their decisions (e.g. service price, quality, customers' profile); analysing different decision rules and studying other characteristics which determine the profile of customers and managers.

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This issue review provides an update on the proposed sale of state land as defined in Senate File 2088, Government Reorganization and Efficiency Act, section 8.

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This book contains ten articles, originally published as circulars of the Iowa Agricultural Experiment Station dealing with the Iowa Agricultural farm crisis situation in 1932 and 1933.