Design, implementation and interpretation of in vitro batchculture experiments to assess enteric methane mitigation in ruminants—a review

In vitro fermentation techniques (IVFT) have been widely used to evaluate the nutritivevalue of feeds for ruminants and in the last decade to assess the effect of different nutritionalstrategies on methane (CH4) production. However, many technical factors may influencethe results obtained. The present review has been prepared by the ‘Global Network’ FACCE-JPI international research consortium to provide a critical evaluation of the main factorsthat need to be considered when designing, conducting and interpreting IVFT experimentsthat investigate nutritional strategies to mitigate CH4emission from ruminants. Given theincreasing and wide-scale use of IVFT, there is a need to critically review reports in the lit-erature and establish what criteria are essential to the establishment and implementationof in vitro techniques. Key aspects considered include: i) donor animal species and numberof animal used, ii) diet fed to donor animals, iii) collection and processing of rumen fluidas inoculum, iv) choice of substrate and incubation buffer, v) incubation procedures andCH4measurements, vi) headspace gas composition and vii) comparability of in vitro andin vivo measurements. Based on an evaluation of experimental evidence, a set of techni-cal recommendations are presented to harmonize IVFT for feed evaluation, assessment ofrumen function and CH4production.

Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

Background Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers (“biomarkers”) of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10–20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2–10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research.

A fast adaptive tunable RBF network for nonstationary systems

This paper describes a novel on-line learning approach for radial basis function (RBF) neural network. Based on an RBF network with individually tunable nodes and a fixed small model size, the weight vector is adjusted using the multi-innovation recursive least square algorithm on-line. When the residual error of the RBF network becomes large despite of the weight adaptation, an insignificant node with little contribution to the overall system is replaced by a new node. Structural parameters of the new node are optimized by proposed fast algorithms in order to significantly improve the modeling performance. The proposed scheme describes a novel, flexible, and fast way for on-line system identification problems. Simulation results show that the proposed approach can significantly outperform existing ones for nonstationary systems in particular.

A review on the combination of binary classifiers in multiclass problems

Several real problems involve the classification of data into categories or classes. Given a data set containing data whose classes are known, Machine Learning algorithms can be employed for the induction of a classifier able to predict the class of new data from the same domain, performing the desired discrimination. Some learning techniques are originally conceived for the solution of problems with only two classes, also named binary classification problems. However, many problems require the discrimination of examples into more than two categories or classes. This paper presents a survey on the main strategies for the generalization of binary classifiers to problems with more than two classes, known as multiclass classification problems. The focus is on strategies that decompose the original multiclass problem into multiple binary subtasks, whose outputs are combined to obtain the final prediction.

HIERARCHICAL DECOMPOSITION OF MULTICLASS PROBLEMS

Several popular Machine Learning techniques are originally designed for the solution of two-class problems. However, several classification problems have more than two classes. One approach to deal with multiclass problems using binary classifiers is to decompose the multiclass problem into multiple binary sub-problems disposed in a binary tree. This approach requires a binary partition of the classes for each node of the tree, which defines the tree structure. This paper presents two algorithms to determine the tree structure taking into account information collected from the used dataset. This approach allows the tree structure to be determined automatically for any multiclass dataset.

Adhesion as a tool for in-built nanotechnology design in cementitious materials

Confined water, such as those molecules in nanolayers of 2-3 nm in length, plays an important role in the adhesion of hydrophilic materials, mainly in cementitious ones. In this study, the effects of water containing kosmotropic substances on adhesion, known for their ability of enhancing the hydrogen bond (H-bond) network of confined water, were evaluated using mechanical strength tests. Indeed, to link adhesion provided by water confined in nanolayers to a macro-response of the cementitious samples, such as the bending strength, requires the evaluation of local water H-bond network configuration in the presence of kosmotropes, considering their influences on the extent and the strength of H-bonds. Among the kosmotropes, trimethylamine and sucrose provided a 50% increase in bending strength compared to the reference samples, the latter just using water as an adhesive, whereas trehalose was responsible for reducing the bending strength to a value close to the samples without any adhesive. The results attained opened up perspectives regarding exploring the confined water behavior which naturally occurs throughout the hydration process in cement-based materials.

Boundary and internal conditions for adjoint fluid-flow problems

The ever-increasing robustness and reliability of flow-simulation methods have consolidated CFD as a major tool in virtually all branches of fluid mechanics. Traditionally, those methods have played a crucial role in the analysis of flow physics. In more recent years, though, the subject has broadened considerably, with the development of optimization and inverse design applications. Since then, the search for efficient ways to evaluate flow-sensitivity gradients has received the attention of numerous researchers. In this scenario, the adjoint method has emerged as, quite possibly, the most powerful tool for the job, which heightens the need for a clear understanding of its conceptual basis. Yet, some of its underlying aspects are still subject to debate in the literature, despite all the research that has been carried out on the method. Such is the case with the adjoint boundary and internal conditions, in particular. The present work aims to shed more light on that topic, with emphasis on the need for an internal shock condition. By following the path of previous authors, the quasi-1D Euler problem is used as a vehicle to explore those concepts. The results clearly indicate that the behavior of the adjoint solution through a shock wave ultimately depends upon the nature of the objective functional.

Praktiska effekter av begreppsförvirring för en databas konceptuella design : En fallstudie om databas- och begreppsmodellering

Company X develops a laboratory information system (LIS) called System Y. The informationsystem has a two-tier database architecture consisting of a production database and a historicaldatabase. A database constitutes the backbone of a IS, which makes the design of the databasevery important. A poorly designed database can cause major problems within an organization.The two databases in System Y are poorly modeled, particularly the historical database. Thecause of the poor modeling was unclear concepts. The unclear concepts have remained in thedatabase and in the company organization and caused a general confusion of concepts. The splitdatabase architecture itself has evolved into a bottleneck and is the cause of many problemsduring the development of System Y.Company X investigates the possibility of integrating the historical database with the productiondatabase. The goal of our thesis is to conduct a consequence analysis of such integration andwhat the effects would be on System Y, and to create a new design for the integrated database.We will also examine and describe the practical effects of confusion of concepts for a databaseconceptual design.To achieve the goal of the thesis, five different method steps have been performed: a preliminarystudy of the organization, a change analysis, a consequence analysis and an investigation of theconceptual design of the database. These method steps have helped identify changes necessaryfor the organization, a new design proposal for an integrated database, the impact of theproposed design and a number of effects of confusion for the database.

Improved Road Design for Future Maintenance - Analysis of Road Barrier Repair Costs

The cost of a road construction over its service life is a function of the design, quality of construction, maintenance strategies and maintenance operations. Unfortunately, designers often neglect a very important aspect which is the possibility to perform future maintenance activities. The focus is mainly on other aspects such as investment costs, traffic safety, aesthetic appearance, regional development and environmental effects. This licentiate thesis is a part of a Ph.D. project entitled “Road Design for lower maintenance costs” that aims to examine how the life-cycle costs can be optimized by selection of appropriate geometrical designs for the roads and their components. The result is expected to give a basis for a new method used in the road planning and design process using life-cycle cost analysis with particular emphasis on road maintenance. The project started with a review of literature with the intention to study conditions causing increased needs for road maintenance, the efforts made by the road authorities to satisfy those needs and the improvement potential by consideration of maintenance aspects during planning and design. An investigation was carried out to identify the problems which obstruct due consideration of maintenance aspects during the road planning and design process. This investigation focused mainly on the road planning and design process at the Swedish Road Administration. However, the road planning and design process in Denmark, Finland and Norway were also roughly evaluated to gain a broader knowledge about the research subject. The investigation was carried out in two phases: data collection and data analysis. Data was collected by semi-structured interviews with expert actors involved in planning, design and maintenance and by a review of design-related documents. Data analyses were carried out using a method called “Change Analysis”. This investigation revealed a complex combination of problems which result in inadequate consideration of maintenance aspects. Several urgent needs for changes to eliminate these problems were identified. Another study was carried out to develop a model for calculation of the repair costs for damages of different road barrier types and to analyse how factors such as road type, speed limits, barrier types, barrier placement, type of road section, alignment and seasonal effects affect the barrier damages and the associated repair costs. This study was carried out using a method called the “Case Study Research Method”. Data was collected from 1087 barrier repairs in two regional offices of the Swedish Road Administration, the Central Region and the Western Region. A table was established for both regions containing the repair cost per vehicle kilometre for different combinations of barrier types, road types and speed limits. This table can be used by the designers in the calculation of the life-cycle costs for different road barrier types.

Road Design for Future Maintenance : Life-cycle Cost Analyses for Road Barriers

The cost of a road construction over its service life is a function of design, quality of construction as well as maintenance strategies and operations. An optimal life-cycle cost for a road requires evaluations of the above mentioned components. Unfortunately, road designers often neglect a very important aspect, namely, the possibility to perform future maintenance activities. Focus is mainly directed towards other aspects such as investment costs, traffic safety, aesthetic appearance, regional development and environmental effects. This doctoral thesis presents the results of a research project aimed to increase consideration of road maintenance aspects in the planning and design process. The following subgoals were established: Identify the obstacles that prevent adequate consideration of future maintenance during the road planning and design process; and Examine optimisation of life-cycle costs as an approach towards increased efficiency during the road planning and design process. The research project started with a literature review aimed at evaluating the extent to which maintenance aspects are considered during road planning and design as an improvement potential for maintenance efficiency. Efforts made by road authorities to increase efficiency, especially maintenance efficiency, were evaluated. The results indicated that all the evaluated efforts had one thing in common, namely ignorance of the interrelationship between geometrical road design and maintenance as an effective tool to increase maintenance efficiency. Focus has mainly been on improving operating practises and maintenance procedures. This fact might also explain why some efforts to increase maintenance efficiency have been less successful. An investigation was conducted to identify the problems and difficulties, which obstruct due consideration of maintainability during the road planning and design process. A method called “Change Analysis” was used to analyse data collected during interviews with experts in road design and maintenance. The study indicated a complex combination of problems which result in inadequate consideration of maintenance aspects when planning and designing roads. The identified problems were classified into six categories: insufficient consulting, insufficient knowledge, regulations and specifications without consideration of maintenance aspects, insufficient planning and design activities, inadequate organisation and demands from other authorities. Several urgent needs for changes to eliminate these problems were identified. One of the problems identified in the above mentioned study as an obstacle for due consideration of maintenance aspects during road design was the absence of a model for calculating life-cycle costs for roads. Because of this lack of knowledge, the research project focused on implementing a new approach for calculating and analysing life-cycle costs for roads with emphasis on the relationship between road design and road maintainability. Road barriers were chosen as an example. The ambition is to develop this approach to cover other road components at a later stage. A study was conducted to quantify repair rates for barriers and associated repair costs as one of the major maintenance costs for road barriers. A method called “Case Study Research Method” was used to analyse the effect of several factors on barrier repairs costs, such as barrier type, road type, posted speed and seasonal effect. The analyses were based on documented data associated with 1625 repairs conducted in four different geographical regions in Sweden during 2006. A model for calculation of average repair costs per vehicle kilometres was created. Significant differences in the barrier repair costs were found between the studied barrier types. In another study, the injuries associated with road barrier collisions and the corresponding influencing factors were analysed. The analyses in this study were based on documented data from actual barrier collisions between 2005 and 2008 in Sweden. The result was used to calculate the cost for injuries associated with barrier collisions as a part of the socio-economic cost for road barriers. The results showed significant differences in the number of injuries associated with collisions with different barrier types. To calculate and analyse life-cycle costs for road barriers a new approach was developed based on a method called “Activity-based Life-cycle Costing”. By modelling uncertainties, the presented approach gives a possibility to identify and analyse factors crucial for optimising life-cycle costs. The study showed a great potential to increase road maintenance efficiency through road design. It also showed that road components with low investment costs might not be the best choice when including maintenance and socio-economic aspects. The difficulties and problems faced during the collection of data for calculating life-cycle costs for road barriers indicated a great need for improving current data collecting and archiving procedures. The research focused on Swedish road planning and design. However, the conclusions can be applied to other Nordic countries, where weather conditions and road design practices are similar. The general methodological approaches used in this research project may be applied also to other studies.

From the road network database to a graph for localization purposes

The problems of finding best facility locations require complete and accurate road network with the corresponding population data in a specific area. However the data obtained in road network databases usually do not fit in this usage. In this paper we propose our procedure of converting the road network database to a road graph which could be used in localization problems. The road network data come from the National road data base in Sweden. The graph derived is cleaned, and reduced to a suitable level for localization problems. The population points are also processed in ordered to match with that graph. The reduction of the graph is done maintaining most of the accuracy for distance measures in the network.

Road network and GPS tracking with data processing and quality assessment

GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: reliability, data processing and the related application. This thesis aims to study the GPS tracking form the methodological, technical and practical aspects. It first evaluates the reliability of GPS based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost. The results show that the geographical positioning is reliable. Velocity is slightly underestimated, whereas altitude measurements are unreliable.Post processing techniques with auxiliary information is found necessary and important when solving the inaccuracy of GPS data. The densities of the road network influence the finding of optimal locations. The influence will stabilize at a certain level and do not deteriorate when the node density is higher.

Student Thesis Level: Master’s Thesis in Business Administration Corporate Social Responsibility (CSR) networking : A case study on why members join CSR network and why are they sharing their knowledge

Purpose – This research focuses on finding the reasons, why members from different sectors join a cross-sector/multi-stakeholder CSR network and what motivates them to share (or not to share) their knowledge of CSR and their best practices. Design/methodology/approach – Semi-structured interviews were conducted with members of the largest cross-sector CSR network in Sweden. The sample base of 15 people was chosen to be able to represent a wider variety of members from each participating sectors. As well as the CEO of the intermediary organization was interviewed. The interviews were conducted via email and telephone. Findings – The findings include several reasons linked to the business case of CSR such as stakeholder pressure, competitive advantage, legitimacy and reputation as well as new reasons like the importance of CSR, and the access of further knowledge in the field. Further reasons are in line with members wanting to join a network, such as access to contact or having personal contacts. As to why members are sharing their CSR knowledge, the findings indicate to inspire others, to show CSR commitment, to be visible, it leads to business opportunity and the access of others knowledge, and because it was requested. Reasons for not sharing their knowledge would be the lack of opportunity, lack of time and the lack of experience to do so. Originality/value – The research contributes to existing studies, which focused on Corporate Social Responsibility and cross-sector networking as well as to inter-organizational knowledge sharing in the field of CSR.

How does data quality in a network affect heuristic solutions?

To have good data quality with high complexity is often seen to be important. Intuition says that the higher accuracy and complexity the data have the better the analytic solutions becomes if it is possible to handle the increasing computing time. However, for most of the practical computational problems, high complexity data means that computational times become too long or that heuristics used to solve the problem have difficulties to reach good solutions. This is even further stressed when the size of the combinatorial problem increases. Consequently, we often need a simplified data to deal with complex combinatorial problems. In this study we stress the question of how the complexity and accuracy in a network affect the quality of the heuristic solutions for different sizes of the combinatorial problem. We evaluate this question by applying the commonly used p-median model, which is used to find optimal locations in a network of p supply points that serve n demand points. To evaluate this, we vary both the accuracy (the number of nodes) of the network and the size of the combinatorial problem (p). The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 supply points we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000 (which is aggregated from the 1.5 million nodes). To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when the accuracy in the road network increase and the combinatorial problem (low p) is simple. When the combinatorial problem is complex (large p) the improvements of increasing the accuracy in the road network are much larger. The results also show that choice of the best accuracy of the network depends on the complexity of the combinatorial (varying p) problem.

Using Multi-Objective Optimization To Maximize Multiple Benefits For Sustainable Drainage Design

For many years, drainage design was mainly about providing sufficient network capacity. This traditional approach had been successful with the aid of computer software and technical guidance. However, the drainage design criteria had been evolving due to rapid population growth, urbanisation, climate change and increasing sustainability awareness. Sustainable drainage systems that bring benefits in addition to water management have been recommended as better alternatives to conventional pipes and storages. Although the concepts and good practice guidance had already been communicated to decision makers and public for years, network capacity still remains a key design focus in many circumstances while the additional benefits are generally considered secondary only. Yet, the picture is changing. The industry begins to realise that delivering multiple benefits should be given the top priority while the drainage service can be considered a secondary benefit instead. The shift in focus means the industry has to adapt to new design challenges. New guidance and computer software are needed to assist decision makers. For this purpose, we developed a new decision support system. The system consists of two main components – a multi-criteria evaluation framework for drainage systems and a multi-objective optimisation tool. Users can systematically quantify the performance, life-cycle costs and benefits of different drainage systems using the evaluation framework. The optimisation tool can assist users to determine combinations of design parameters such as the sizes, order and type of drainage components that maximise multiple benefits. In this paper, we will focus on the optimisation component of the decision support framework. The optimisation problem formation, parameters and general configuration will be discussed. We will also look at the sensitivity of individual variables and the benchmark results obtained using common multi-objective optimisation algorithms. The work described here is the output of an EngD project funded by EPSRC and XP Solutions.