Assessing the potential economic benefits to farmers from various GM crops becoming available in the European Union by 2025: results from an expert survey

This paper reports on a study that identified a range of crop-trait combinations that are: agronomically suited to the EU; provide advantages to arable farmers and consumers; and are either already available in international markets, or advancing along the development pipeline and likely to become available by 2025. An expert stakeholder panel was recruited and asked for their views, using the Delphi approach, on the impact of these crop-traits on enterprise competitiveness, through changes to yields, production costs and product prices. In terms of input traits, there was consensus that traits such as herbicide tolerant/insect resistant (HT/IR) maize, HT sugar beet and HT soya bean would provide positive benefits for farmers. Output-side traits such as winter-sown rape with reduced saturated fats, were seen as offering benefits to consumers, but were either likely to be restricted to niche markets, or offer relatively modest price premia to farmers growing them. Our analysis of the financial impact of the adoption of GM crops more widely in the EU, showed that the competitiveness of the agricultural sector could well be improved by this. However, such improvements would be relatively small-scale in that large-scale national natural advantages from either economic or environmental conditions is unlikely to be overturned

A framework for identifying suitable cases for using market-based approaches in industrial data acquisition

This is the author accepted manuscript. The final version is available from the Library and Information Statistics Unit, Loughborough University via http://dx.doi.org/ https://idimc.files.wordpress.com/2015/09/idimc2014_proceedings1.pdfVarious researchers have suggested concepts for the application of market-based techniques for data management and data acquisition. However, very few concepts have successfully been implemented and shown a positive practical impact. This can partially be attributed to the lack of existing techniques in identifying appropriate scenarios. Using knowledge from existing successful market implementations in data acquisition, data management and related areas, this paper aims to close this gap. It develops a framework for identifying scenarios applicable for a market-based data acquisition approach. It finds that a heterogeneous environment with distributed decision-making based on partial information combined with assumptions about the users knowledge about the data he is using, can give a good indication for the application of market-based data acquisition approaches. The developed framework is applied towards two sample scenarios

The quality of life and cost utility of home nocturnal and conventional in-center hemodialysis

The quality of life and cost utility of home nocturnal and conventional in-center hemodialysis.BackgroundHome nocturnal hemodialysis is an intensive form of hemodialysis, where patients perform their treatments at home for about 7hours approximately 6 nights a week. Compared with in-center conventional hemodialysis, home nocturnal hemodialysis has been shown to improve physiologic parameters and reduce health care costs; however, the effects on quality of life and cost utility are less clear. We hypothesized that individuals performing home nocturnal hemodialysis would have a higher quality of life and superior cost utility than in-center hemodialysis patients.MethodsHome nocturnal hemodialysis patients and a demographically similar group of in-center hemodialysis patients from a hospital without a home hemodialysis program underwent computer-assisted interviews to assess their utility score for current health by the standard gamble method.ResultsNineteen in-center hemodialysis and 24 home nocturnal hemodialysis patients were interviewed. Mean annual costs for home nocturnal hemodialysis were about $10,000 lower for home nocturnal hemodialysis ($55,139 ±$7651 for home nocturnal hemodialysis vs.$66,367 ±$17,502 for in-center hemodialysis, P = 0.03). Home nocturnal hemodialysis was associated with a higher utility score than in-center hemodialysis (0.77 ± 0.23 vs. 0.53 ± 0.35, P = 0.03). The cost utility for home nocturnal hemodialysis was$71,443/quality-adjusted life-year (QALY), while for in-center hemodialysis it was $125,845/QALY. Home nocturnal hemodialysis was the dominant strategy, with an incremental cost-effectiveness ratio (ICER) of -$45,932. The 95% CI for the ICER, and 2500 bootstrap iterations of the ICER all fell below the cost-effectiveness ceiling of $50,000. The net monetary benefit of home nocturnal hemodialysis ranged from$11,227 to $35,669.ConclusionHome nocturnal hemodialysis is associated with a higher quality of life and a superior cost utility when compared to in-center hemodialysis

Femoral Neck Angle Impacts Hip Disorder and Surgical Intervention: A Patient-Specific 3D Printed Analysis

The purpose of this study is to investigate the femoral neck angulation for prediction of the complication associated with dynamic hip screw (DHS) surgery and hip deformity. Three sample patients' MRI images were selected to calculate the femoral neck angles. A total of six femur head geometries were reconstructed and three dimensional (3D) models printed. The calculation of neck angles was done in both computer models and 3D-printed models. Our results showed that 3D-printed models achieved high accuracy and provided the physical measurements, when compared to the computer models could not confirm. Neck angulations related to uncomplicated DHS surgery ranged between 129{\deg}-139{\deg}, and non-deformity of normal neck angles ranged between 120{\deg}-135{\deg}. Our study indicated that patient-specific 3D printed femoral head models provide useful information for medical education and assist DHS surgery. Further research based on a large sample size is necessary

Identifying GM crops for future cultivation in the EU through a Delphi forecasting exercise

This paper reports on a Delphi forecasting exercise carried out to identify crop traits that could feasibly be introduced to the advantage of arable farmers, and for the general benefit of the public, in EU member states. An expert stakeholder panel was recruited and asked for opinions on scenarios concerning the availability of GM events, and also scenarios that envisage novel crops developed using advanced technology not classified as GM. In a second round of consultation, panel members commented anonymously on opinions elicited in the first phase. Results indicate that crops with input traits most likely to become available in the EU before 2025 are HTIR maize, HT sugarbeet and HT soybean; these are already widely adopted outside Europe. The crops with output traits most likely to become available and offering benefits to consumers are winter-sown varieties of rape with reduced saturated fats, spring varieties of which are already available outside EU (notably Canadian Canola)

Predicting Hidden Links in Supply Networks

Manufacturing companies often lack visibility of the procurement interdependencies between the suppliers within their supply network. However, knowledge of these interdependencies is useful to plan for potential operational disruptions. In this paper, we develop the Supply Network Link Predictor (SNLP) method to infer supplier interdependencies using the manufacturer’s incomplete knowledge of the network. SNLP uses topological data to extract relational features from the known network to train a classifier for predicting potential links. Using a test case from the automotive industry, four features are extracted: (i) number of existing supplier links, (ii) overlaps between supplier product portfolios, (iii) product outsourcing associations, and (iv) likelihood of buyers purchasing from two suppliers together. Naïve Bayes and Logistic Regression are then employed to predict whether these features can help predict interdependencies between two suppliers. Our results show that these features can indeed be used to predict interdependencies in the network and that predictive accuracy is maximized by (i) and (iii). The findings give rise to the exciting possibility of using data analytics for improving supply chain visibility. We then proceed to discuss to what extent such approaches can be adopted and their limitations, highlighting next steps for future work in this area

An industrial data recommender system to solve the problem of data overload

This is the author accepted manuscript. The final version is available from 23rd European Conference on Information Systems (ECIS 2015) via https://balsa.man.poznan.pl/indico/event/44/contribution/203Getting the right data to the right decision-maker is a significant problem for many industrial companies. One of the main reasons is an overload of data. With the increasing amounts of industrial data this problem is becoming a bigger problem in the future. In order to address this challenge we propose the use of an Industrial Data Recommender System (IDRS). An IDRS recommends additional data to append to the data the decision-maker is currently working with, using techniques from the recommender systems domain like content-based and collaborative filtering. Using industrial cases we found that an IDRS is capable of suggesting useful information to the decision-maker. This additional information should help them to improve their decision-making.Boein

An evidence-based review on the likely economic and environmental impact of genetically modified cereals and oilseeds for UK agriculture

An evidence-based review of the potential impact that the introduction of genetically-modified (GM) cereal and oilseed crops could have for the UK was carried out. The inter-disciplinary research project addressed the key research questions using scenarios for the uptake, or not, of GM technologies. This was followed by an extensive literature review, stakeholder consultation and financial modelling. The world area of canola, oilseed rape (OSR) low in both erucic acid in the oil and glucosinolates in the meal, was 34M ha in 2012 of which 27% was GM; Canada is the lead producer but it is also grown in the USA, Australia and Chile. Farm level effects of adopting GM OSR include: lower production costs; higher yields and profits; and ease of farm management. Growing GM OSR instead of conventional OSR reduces both herbicide usage and environmental impact. Some 170M ha of maize was grown in the world in 2011 of which 28% was GM; the main producers are the USA, China and Brazil. Spain is the main EU producer of GM maize although it is also grown widely in Portugal. Insect resistant (IR) and herbicide tolerant (HT) are the GM maize traits currently available commercially. Farm level benefits of adopting GM maize are lower costs of production through reduced use of pesticides and higher profits. GM maize adoption results in less pesticide usage than on conventional counterpart crops leading to less residues in food and animal feed and allowing increasing diversity of bees and other pollinators. In the EU, well-tried coexistence measures for growing GM crops in the proximity of conventional crops have avoided gene flow issues. Scientific evidence so far seems to indicate that there has been no environmental damage from growing GM crops. They may possibly even be beneficial to the environment as they result in less pesticides and herbicides being applied and improved carbon sequestration from less tillage. A review of work on GM cereals relevant for the UK found input trait work on: herbicide and pathogen tolerance; abiotic stress such as from drought or salinity; and yield traits under different field conditions. For output traits, work has mainly focussed on modifying the nutritional components of cereals and in connection with various enzymes, diagnostics and vaccines. Scrutiny of applications submitted for field trial testing of GM cereals found around 9000 applications in the USA, 15 in Australia and 10 in the EU since 1996. There have also been many patent applications and granted patents for GM cereals in the USA for both input and output traits;an indication of the scale of such work is the fact that in a 6 week period in the spring of 2013, 12 patents were granted relating to GM cereals. A dynamic financial model has enabled us to better understand and examine the likely performance of Bt maize and HT OSR for the south of the UK, if cultivation is permitted in the future. It was found that for continuous growing of Bt maize and HT OSR, unless there was pest pressure for the former and weed pressure for the latter, the seed premia and likely coexistence costs for a buffer zone between other crops would reduce the financial returns for the GM crops compared with their conventional counterparts. When modelling HT OSR in a four crop rotation, it was found that gross margins increased significantly at the higher levels of such pest or weed pressure, particularly for farm businesses with larger fields where coexistence costs would be scaled down. The impact of the supply of UK-produced GM crops on the wider supply chain was examined through an extensive literature review and widespread stakeholder consultation with the feed supply chain. The animal feed sector would benefit from cheaper supplies of raw materials if GM crops were grown and, in the future, they might also benefit from crops with enhanced nutritional profile (such as having higher protein levels) becoming available. This would also be beneficial to livestock producers enabling lower production costs and higher margins. Whilst coexistence measures would result in increased costs, it is unlikely that these would cause substantial changes in the feed chain structure. Retailers were not concerned about a future increase in the amount of animal feed coming from GM crops. To conclude, we (the project team) feel that the adoption of currently available and appropriate GM crops in the UK in the years ahead would benefit farmers, consumers and the feed chain without causing environmental damage. Furthermore, unless British farmers are allowed to grow GM crops in the future, the competitiveness of farming in the UK is likely to decline relative to that globally

An agent-based approach for energy-efficient sensor networks in logistics

As part of the fourth industrial revolution, logistics processes are augmented with connected information systems to improve their reliability and sustainability. Above all, customers can analyse process data obtained from the networked logistics operations to reduce costs and increase margins. The logistics of managing liquid goods is particularly challenging due to the strict transport temperature requirements involving monitoring via sensors attached to containers. However, these sensors transmit much redundant information that, at times, does not provide additional value to the customer, while consuming the limited energy stored in the sensor batteries. This paper aims to explore and study alternative approaches for location tracking and state monitoring in the context of liquid goods logistics. This problem is addressed by using a combination of data-driven sensing and agent-based modelling techniques. The simulation results show that the longest life span of batteries is achieved when most sensors are put into sleep mode yielding an increase of ×21.7 and ×3.7 for two typical routing scenarios. However, to allow for situations in which high quality sensor data is required to make decisions, agents need to be made aware of the life cycle phase of individual containers. Key contributions include (1) an agent-based approach for modelling the dynamics of liquid goods logistics to enable monitoring and detect inefficiencies (2) the development and analysis of three sensor usage strategies for reducing the energy consumption, and (3) an evaluation of the trade-offs between energy consumption and location tracking precision for timely decision making in resource constrained monitoring systems

Regression of left ventricular mass following conversion from conventional hemodialysis to thrice weekly in-centre nocturnal hemodialysis

<p>Abstract</p> <p>Background</p> <p>Increased left ventricular mass (LVM) is associated with adverse outcomes in patients receiving chronic hemodialysis. Among patients receiving conventional hemodialysis (CHD, 3×/week, 4 hrs/session), we evaluated whether dialysis intensification with in-centre nocturnal hemodialysis (INHD, 3×/week, 7-8 hrs/session in the dialysis unit) was associated with regression of LVM.</p> <p>Methods</p> <p>We conducted a retrospective cohort study of CHD recipients who converted to INHD and received INHD for at least 6 months. LVM on the first echocardiogram performed at least 6 months post-conversion was compared to LVM pre-conversion. In a secondary analysis, we examined echocardiograms performed at least 12 months after starting INHD. The effect of conversion to INHD on LVM over time was also evaluated using a longitudinal analysis that incorporated all LVM data on patients with 2 or more echocardiograms.</p> <p>Results</p> <p>Thirty-seven patients were eligible for the primary analysis. Mean age at conversion was 49 ± 12 yrs and 30% were women. Mean pre-conversion LVM was 219 ± 66 g and following conversion, LVM declined by 32 ± 58 g (p = 0.002). Among patients whose follow-up echocardiogram occurred at least 12 months following conversion, LVM declined by 40 ± 56 g (p = 0.0004). The rate of change of LVM decreased significantly from 0.4 g/yr before conversion, to -11.7 g/yr following conversion to INHD (p < 0.0001).</p> <p>Conclusion</p> <p>Conversion to INHD is associated with a significant regression in LVM, which may portend a more favourable cardiovascular outcome. Our preliminary findings support the need for randomized controlled trials to definitively evaluate the cardiovascular effects of INHD.</p