Integrating understandability in the evaluation of consumer health search engines

In this paper we propose a method that integrates the no- tion of understandability, as a factor of document relevance, into the evaluation of information retrieval systems for con- sumer health search. We consider the gain-discount evaluation framework (RBP, nDCG, ERR) and propose two understandability-based variants (uRBP) of rank biased precision, characterised by an estimation of understandability based on document readability and by different models of how readability influences user understanding of document content. The proposed uRBP measures are empirically contrasted to RBP by comparing system rankings obtained with each measure. The findings suggest that considering understandability along with topicality in the evaluation of in- formation retrieval systems lead to different claims about systems effectiveness than considering topicality alone.

Rad51 supports triple negative breast cancer metastasis

In contrast to extensive studies on familial breast cancer, it is currently unclear whether defects in DNA double strand break (DSB) repair genes play a role in sporadic breast cancer development and progression. We performed analysis of immunohistochemistry in an independent cohort of 235 were sporadic breast tumours. This analysis suggested that RAD51 expression is increased during breast cancer progression and metastasis and an oncogenic role for RAD51 when deregulated. Subsequent knockdown of RAD51 repressed cancer cell migration in vitro and reduced primary tumor growth in a syngeneic mouse model in vivo. Loss of RAD51 also inhibited associated metastasis not only in syngeneic mice but human xenografts and changed the metastatic gene expression profile of cancer cells, consistent with inhibition of distant metastasis. This demonstrates for the first time a new function of RAD51 that may underlie the proclivity of patients with RAD51 overexpression to develop distant metastasis. RAD51 is a potential biomarker and attractive drug target for metastatic triple negative breast cancer, with the capability to extend the survival of patients, which is less than 6 months.

Making decisions about antibiotic use in the Australian primary healthcare sector

Introduction Australia is contributing to the global problem of antimicrobial resistance with one of the highest rates of antibiotic use amongst OECD countries. Data from the Australian primary healthcare sector suggests unnecessary antibiotics were prescribed for conditions that will resolve without it. If left unchecked, this will result in more resistant micro-organisms, against which antibiotics will be useless. There is a lack of understanding about what is influencing decisions to use antibiotics – what factors influences general practitioners (GPs) to prescribe antibiotics, consumers to seek antibiotics, and pharmacists to fill old antibiotic prescriptions? It is also not clear how these individuals trade-off between the possible benefits that antibiotics may provide in the immediate/short term, against the longer term societal risk of antimicrobial resistance. Method This project will investigate (a) what factors drive decisions to use antibiotics for GPs, pharmacists and consumers, and (b) how these individuals discount the future. Factors will be gleaned from published literature and from a qualitative phase using semi-structured interviews, to inform the development of Discrete Choice Experiments (DCEs). Three DCEs will be constructed – one for each group of interest – to allow investigation of which factors are more important in influencing (a) GPs to prescribe antibiotics, (b) consumers to seek antibiotics, and (c) pharmacists to fill legally valid but old or repeat prescriptions of antibiotics. Regression analysis will be conducted to understand the relative importance of these factors. A Time Trade Off exercise will be developed to investigate how these individuals discount the future, and whether GPs and pharmacists display the same extent of discounting the future, as consumers. Expected Results Findings from the DCEs will provide an insight into which factors are more important in driving decision making in antibiotic use for GPs, pharmacists and consumers. Findings from the Time Trade Off exercise will show what individuals are willing to trade for preserving the miracle of antibiotics. Conclusion The emergence of antibiotic resistance is inevitable. This research will expand on what is currently known about influencing desired behaviour change in antibiotic use, in the fight against antibiotic resistance. Real World Implications Research findings will contribute to existing national programs to bring about a reduction in inappropriate use of antibiotic in Australia. Specifically, influencing (1) how key messages and public health campaigns are crafted to increase health literacy, and (2) clinical education and empowerment of GPs and pharmacists to play a more responsive role as stewards of antibiotic use in the community.

Left on the side of the road? A review of deterrence-based theoretical developments in road safety

Deterrence-based initiatives form a cornerstone of many road safety countermeasures. This approach is informed by Classical Deterrence Theory, which proposes that individuals will be deterred from committing offences if they fear the perceived consequences of the act, especially the perceived certainty, severity and swiftness of sanctions. While deterrence-based countermeasures have proven effective in reducing a range of illegal driving behaviours known to cause crashes such as speeding and drink driving, the exact level of exposure, and how the process works, remains unknown. As a result the current study involved a systematic review of the literature to identify theoretical advancements within deterrence theory that has informed evidence-based practice. Studies that reported on perceptual deterrence between 1950 and June 2015 were searched in electronic databases including PsychINFO and ScienceDirect, both within road safety and non-road safety fields. This review indicated that scientific efforts to understand deterrence processes for road safety were most intense during the 1970s and 1980s. This era produced competing theories that postulated both legal and non-legal factors can influence offending behaviours. Since this time, little theoretical progression has been made in the road safety arena, apart from Stafford and Warr's (1993) reconceptualisation of deterrence that illuminated the important issue of punishment avoidance. In contrast, the broader field of criminology has continued to advance theoretical knowledge by investigating a range of individual difference-based factors proposed to influence deterrent processes, including: moral inhibition, social bonding, self-control, tendencies to discount the future, etc. However, this scientific knowledge has not been directed towards identifying how to best utilise deterrence mechanisms to improve road safety. This paper will highlight the implications of this lack of progression and provide direction for future research.

A Scalable High Throughput Firewall in FPGA

High end network security applications demand high speed operation and large rule set support. Packet classification is the core functionality that demands high throughput in such applications. This paper proposes a packet classification architecture to meet such high throughput. We have implemented a Firewall with this architecture in reconflgurable hardware. We propose an extension to Distributed Crossproducting of Field Labels (DCFL) technique to achieve scalable and high performance architecture. The implemented Firewall takes advantage of inherent structure and redundancy of rule set by using our DCFL Extended (DCFLE) algorithm. The use of DCFLE algorithm results in both speed and area improvement when it is implemented in hardware. Although we restrict ourselves to standard 5-tuple matching, the architecture supports additional fields. High throughput classification invariably uses Ternary Content Addressable Memory (TCAM) for prefix matching, though TCAM fares poorly in terms of area and power efficiency. Use of TCAM for port range matching is expensive, as the range to prefix conversion results in large number of prefixes leading to storage inefficiency. Extended TCAM (ETCAM) is fast and the most storage efficient solution for range matching. We present for the first time a reconfigurable hardware implementation of ETCAM. We have implemented our Firewall as an embedded system on Virtex-II Pro FPGA based platform, running Linux with the packet classification in hardware. The Firewall was tested in real time with 1 Gbps Ethernet link and 128 sample rules. The packet classification hardware uses a quarter of logic resources and slightly over one third of memory resources of XC2VP30 FPGA. It achieves a maximum classification throughput of 50 million packet/s corresponding to 16 Gbps link rate for the worst case packet size. The Firewall rule update involves only memory re-initialization in software without any hardware change.

A Scalable High Throughput Firewall in FPGA

High end network security applications demand high speed operation and large rule set support. Packet classification is the core functionality that demands high throughput in such applications. This paper proposes a packet classification architecture to meet such high throughput. We have Implemented a Firewall with this architecture in reconfigurable hardware. We propose an extension to Distributed Crossproducting of Field Labels (DCFL) technique to achieve scalable and high performance architecture. The implemented Firewall takes advantage of inherent structure and redundancy of rule set by using, our DCFL Extended (DCFLE) algorithm. The use of DCFLE algorithm results In both speed and area Improvement when It is Implemented in hardware. Although we restrict ourselves to standard 5-tuple matching, the architecture supports additional fields.High throughput classification Invariably uses Ternary Content Addressable Memory (TCAM) for prefix matching, though TCAM fares poorly In terms of area and power efficiency. Use of TCAM for port range matching is expensive, as the range to prefix conversion results in large number of prefixes leading to storage inefficiency. Extended TCAM (ETCAM) is fast and the most storage efficient solution for range matching. We present for the first time a reconfigurable hardware Implementation of ETCAM. We have implemented our Firewall as an embedded system on Virtex-II Pro FPGA based platform, running Linux with the packet classification in hardware. The Firewall was tested in real time with 1 Gbps Ethernet link and 128 sample rules. The packet classification hardware uses a quarter of logic resources and slightly over one third of memory resources of XC2VP30 FPGA. It achieves a maximum classification throughput of 50 million packet/s corresponding to 16 Gbps link rate for file worst case packet size. The Firewall rule update Involves only memory re-initialiization in software without any hardware change.

Sediment concentration prediction and statistical evaluation for annual load estimation

We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.

Sequential allocation in clinical trials

Suppose two treatments with binary responses are available for patients with some disease and that each patient will receive one of the two treatments. In this paper we consider the interests of patients both within and outside a trial using a Bayesian bandit approach and conclude that equal allocation is not appropriate for either group of patients. It is suggested that Gittins indices should be used (using an approach called dynamic discounting by choosing the discount rate based on the number of future patients in the trial) if the disease is rare, and the least failures rule if the disease is common. Some analytical and simulation results are provided.

A contemporary assessment of land condition in the Northern Gulf region of Queensland

A framework using assessments of soil condition, pasture composition and woodland density was applied to describe 14 grazing land types as being in A (100% of original carrying capacity), B (75%), C (45%) or D (20%) condition. We assessed the condition of 260 sites, principally along public and some station roads, to provide a benchmark for current land condition. Land types were also assigned relative grazing values between 10 (best) and 0, reflecting soil fertility and potential biomass production. The method identifies particular, 'at-risk' land types for priority investment of resources, while the rationale behind assessments might point to management interventions to improve the condition of those land types. Across all land types, 47% of sites were in A condition, 34% in B condition, 17% in C condition and only 2% in D condition. Seventy-five percent of land types with grazing values >5 were in A or B condition, compared with 88% for those with grazing values ?5. For Georgetown granites, only 27% of sites were in A or B condition, with values for other land types being: alluvials 59%, black soils 64% and red duplex soils 57%, suggesting that improving management of these land types is a priority issue. On land types with high grazing value, the major discounting factor was pasture composition (72% of sites discounted), while increasing woodland density was the main discount (73% of sites discounted) on low grazing value land types.

The effect of ground leases on house prices in Helsinki

One imperfection in housing markets is imperfect knowledge about legal interests such as ground leases. Both actual reduced legal interest as well as uncertainty surrounding rights and future lease payments for houses constructed on leased land may affect prices relative to houses built on freehold land. We use regression analysis of sales prices of condominium transactions in Helsinki to examine the effect ground leases have on house prices. We find that prices on condominiums constructed on leased lots are discounted at least 5 %, on average. In addition, we see that the announcement of potentially large increases in base rents upon renewal contributes to the discount.

Factors affecting farmland prices in Finland

The purpose of the study was to analyse factors affecting the differences in land prices between regions. The key issue was to find out the policy effects on farmland prices. In addition to comprehensive literature review, a theoretical analysis as well as modern panel and spatial econometric techniques were utilized. The study clearly pointed out the importance of taking into account the possible spatial dependence. The data were exceptionally large, comprising more than 6 000 observations. Thus, it allowed a thorough econometric estimation including the possibility to take into account the spatial nature of the data. This study supports the view that there are many other factors that affect farmland prices besides pure agricultural returns. It was also found that the support clearly affects land prices. However, rather than assuming the discount rates for support and market returns to be similar, the rough analysis refers to the discount rate for support being a little lower. If this were true it would indicate that farmers rely more on support income than market returns. The results support the view presented in literature that land values are more responsive to government payments when these payments are perceived to be permanent. An important result of this study is that the structural differences between regions and the structural change in agriculture seemed to have a considerable role in affecting land prices. Firstly, the present structure affects the competition in the land market: the more dense farms are in the region the more there are potential buyers, and the land price increases. Secondly, the change in farm structure (especially in animal husbandry) connected to the policy changes that increase area-based support affects land prices. The effect comes from two sources. Growing farms need more land for the manure, and the proportion of retiring farmers may be lower. The introduction of the manure density variable proved to be an efficient way to aggregate the otherwise very difficult task of taking into account the environmental pressure caused by structural change in animal husbandry. Finally, infrastructure also has a very important role in determining the price level of agricultural land. If other industries are prospering in the surrounding area, agricultural viability also seems to improve. The non-farm opportunities offered to farm families make continuing and developing farming more tempting.

Essays on socially optimal phosphorus policies in crop production

Phosphorus is a nutrient needed in crop production. While boosting crop yields it may also accelerate eutrophication in the surface waters receiving the phosphorus runoff. The privately optimal level of phosphorus use is determined by the input and output prices, and the crop response to phosphorus. Socially optimal use also takes into account the impact of phosphorus runoff on water quality. Increased eutrophication decreases the economic value of surface waters by Deteriorating fish stocks, curtailing the potential for recreational activities and by increasing the probabilities of mass algae blooms. In this dissertation, the optimal use of phosphorus is modelled as a dynamic optimization problem. The potentially plant available phosphorus accumulated in soil is treated as a dynamic state variable, the control variable being the annual phosphorus fertilization. For crop response to phosphorus, the state variable is more important than the annual fertilization. The level of this state variable is also a key determinant of the runoff of dissolved, reactive phosphorus. Also the loss of particulate phosphorus due to erosion is considered in the thesis, as well as its mitigation by constructing vegetative buffers. The dynamic model is applied for crop production on clay soils. At the steady state, the analysis focuses on the effects of prices, damage parameterization, discount rate and soil phosphorus carryover capacity on optimal steady state phosphorus use. The economic instruments needed to sustain the social optimum are also analyzed. According to the results the economic incentives should be conditioned on soil phosphorus values directly, rather than on annual phosphorus applications. The results also emphasize the substantial effects the differences in varying discount rates of the farmer and the social planner have on optimal instruments. The thesis analyzes the optimal soil phosphorus paths from its alternative initial levels. It also examines how erosion susceptibility of a parcel affects these optimal paths. The results underline the significance of the prevailing soil phosphorus status on optimal fertilization levels. With very high initial soil phosphorus levels, both the privately and socially optimal phosphorus application levels are close to zero as the state variable is driven towards its steady state. The soil phosphorus processes are slow. Therefore, depleting high phosphorus soils may take decades. The thesis also presents a methodologically interesting phenomenon in problems of maximizing the flow of discounted payoffs. When both the benefits and damages are related to the same state variable, the steady state solution may have an interesting property, under very general conditions: The tail of the payoffs of the privately optimal path as well as the steady state may provide a higher social welfare than the respective tail of the socially optimal path. The result is formalized and an applied to the created framework of optimal phosphorus use.