Oral fingolimod for relapsing-remitting multiple sclerosis

Background: Most people with multiple sclerosis have the relapsing-remitting type. Objective/methods: The objective was to evaluate two clinical trials of fingolimod in relapsing multiple sclerosis. Results: FREEDOMS (FTY720 Research Evaluation Effects of Daily Oral therapy in Multiple Sclerosis), a Phase III placebo-controlled trial, showed that fingolimod (0.5 or 1.25 mg) reduced the relapse rate and disability in multiple sclerosis, compared to placebo. Fingolimod (0.5 or 1.25 mg) has been compared to interferon β-1a in a Phase III clinical trial (TRANSFORMS; Trial Assessing Injectable Interferon versus FTY720 Oral in Relapsing-Remitting Multiple Sclerosis) and shown to be more efficacious than interferon β-1a in reducing relapse rates. However, fingolimod did increase the risk of infections and skin cancers. Conclusions: Only the lower dose of fingolimod (0.5 mg), which possibly has less toxicity, should be considered for prevention of relapses in relapsing-remitting multiple sclerosis.

Does the p38 MAP kinase inhibitor pamapimod have potential for the treatment of rheumatoid arthritis?

Background: Methotrexate alone or in combination with other agents is the standard treatment for moderate-to-severe rheumatoid arthritis. As the biological agents are expensive, they are not usually used until methotrexate has failed to give a good response. Thus, there is scope for the development of cheaper drugs that can be used instead of methotrexate or in addition to methotrexate. Objectives/methods: Pamapimod is a p38α inhibitor being developed for use in the treatment of rheumatoid arthritis. The objective was to evaluate the recent clinical trials of pamapimod in subjects with rheumatoid arthritis. Results: There is no clear cut evidence that pamapimod alone or in the presence of methotrexate is efficacious in subjects with rheumatoid arthritis, but it does cause adverse effects. Conclusion: It is unlikely that pamapimod will be useful in the treatment of rheumatoid arthritis.

Resolvin inflammation with pain

Background: Inflammation and pain coexist in conditions such as arthritis, inflammatory bowel disease, and lower back pain. The drugs currently used to treat the combination of inflammation and pain all have disadvantages. Thus, new drugs and new approaches are needed to treat inflammation with pain. The resolvins are considered to be part of the natural resolving mechanism for inflammation, and have been shown to prevent inflammation in animal models. Objectives/methods: To evaluate a paper suggesting that the resolvins RvE1 and RvD1 attenuate inflammatory pain in animal models. Results: RvE1 has been shown to attenuate inflammation and, to a lesser extent, pain in animal models. Limited results are presented of the effectiveness of RvD1 against inflammatory pain. Conclusion: Drugs that mimic or potentiate the effects of the resolvins may be useful for the treatment of some inflammation with pain.

Application of reinforcement learning in an open railway access market price negotiation

In an open railway access market price negotiation, it is feasible to achieve higher cost recovery by applying the principles of price discrimination. The price negotiation can be modeled as an optimization problem of revenue intake. In this paper, we present the pricing negotiation based on reinforcement learning model. A negotiated-price setting technique based on agent learning is introduced, and the feasible applications of the proposed method for open railway access market simulation are discussed.

The conflict resolution in connected railway junctions

Purpose of study: Traffic conflicts occur when trains on different routes approach a converging junction in a railway network at the same time. To prevent collisions, a right-of-way assignment is needed to control the order in which the trains should pass the junction. Such control action inevitably requires the braking and/or stopping of trains, which lengthens their travelling times and leads to delays. Train delays cause a loss of punctuality and hence directly affect the quality of service. It is therefore important to minimise the delays by devising a suitable right-of-way assignment. One of the major difficulties in attaining the optimal right-of-way assignment is that the number of feasible assignments increases dramatically with the number of trains. Connected-junctions further complicate the problem. Exhaustive search for the optimal solution is time-consuming and infeasible for area control (multi-junction). Even with the more intelligent deterministic optimisation method revealed in [1], the computation demand is still considerable, which hinders real-time control. In practice, as suggested in [2], the optimality may be traded off by shorter computation time, and heuristic searches provide alternatives for this optimisation problem.

Coast control of train movement with genetic algorithms

Railway service is now the major transportation means in most of the countries around the world. With the increasing population and expanding commercial and industrial activities, a high quality of railway service is the most desirable. We present an application of genetic algorithms (GA) to search for the appropriate coasting point(s) and investigate the possible improvement on fitness of genes. Single and multiple coasting point control with simple GA are developed to attain the solutions and their corresponding train movement is examined. The multiple coasting point control with hierarchical genetic algorithm (HGA) is then proposed to integrate the determination of the number of coasting points.

Coasting control of train operation by genetic algorithm

Balancing between the provision of high quality of service and running within a tight budget is one of the biggest challenges for most metro railway operators around the world. Conventionally, one possible approach for the operator to adjust the time schedule is to alter the stop time at stations, if other system constraints, such as traction equipment characteristic, are not taken into account. Yet it is not an effective, flexible and economical method because the run-time of a train simply cannot be extended without limitation, and a balance between run-time and energy consumption has to be maintained. Modification or installation of a new signalling system not only increases the capital cost, but also affects the normal train service. Therefore, in order to procure a more effective, flexible and economical means to improve the quality of service, optimisation of train performance by coasting point identification has become more attractive and popular. However, identifying the necessary starting points for coasting under the constraints of current service conditions is no simple task because train movement is attributed by a large number of factors, most of which are non-linear and inter-dependent. This paper presents an application of genetic algorithms (GA) to search for the appropriate coasting points and investigates the possible improvement on computation time and fitness of genes.

Generation evolution in GA application on railway traffic control

This paper presents a Genetic Algorithms (GA) approach to resolve traffic conflicts at a railway junction. The formulation of the problem for the suitable application of GA will be discussed and three neighborhoods have been proposed for generation evolution. The performance of the GA is evaluated by computer simulation. This study paves the way for more applications of artificial intelligence techniques on a rather conservative industry.

Railway junction conflict resolution by local search method

This study investigates the application of local search methods on the railway junction traffic conflict-resolution problem, with the objective of attaining a quick and reasonable solution. A procedure based on local search relies on finding a better solution than the current one by a search in the neighbourhood of the current one. The structure of neighbourhood is therefore very important to an efficient local search procedure. In this paper, the formulation of the structure of the solution, which is the right-of-way sequence assignment, is first described. Two new neighbourhood definitions are then proposed and the performance of the corresponding local search procedures is evaluated by simulation. It has been shown that they provide similar results but they can be used to handle different traffic conditions and system requirements.

Patterns, heuristics for architectural design support: making use of evolutionary modelling in design

Software used by architectural and industrial designers – has moved from becoming a tool for drafting, towards use in verification, simulation, project management and project sharing remotely. In more advanced models, parameters for the designed object can be adjusted so a family of variations can be produced rapidly. With advances in computer aided design technology, numerous design options can now be generated and analyzed in real time. However the use of digital tools to support design as an activity is still at an early stage and has largely been limited in functionality with regard to the design process. To date, major CAD vendors have not developed an integrated tool that is able to both leverage specialized design knowledge from various discipline domains (known as expert knowledge systems) and support the creation of design alternatives that satisfy different forms of constraints. We propose that evolutionary computing and machine learning be linked with parametric design techniques to record and respond to a designer’s own way of working and design history. It is expected that this will lead to results that impact on future work on design support systems-(ergonomics and interface) as well as implicit constraint and problem definition for problems that are difficult to quantify.

A Heuristic algorithm for fixed train runtime

This paper proposes a train movement model with fixed runtime that can be employed to find feasible control strategies for a single train along an inter-city railway line. The objective of the model is to minimize arrival delays at each station along railway lines. However, train movement is a typical nonlinear problem for complex running environments and different requirements. A heuristic algorithm is developed to solve the problem in this paper and the simulation results show that the train could overcome the disturbance from train delay and coordinates the operation strategies to sure punctual arrival of trains at the destination. The developed algorithm can also be used to evaluate the running reliability of trains in scheduled timetables.

Critical success factors of project management for Brunei construction projects : improving project performance

The problem of delays in the construction industry is a global phenomenon and the construction industry in Brunei Darussalam is no exception. The goal of all parties involved in construction projects – owners, contractors, engineers and consultants in either the public or private sector is to successfully complete the project on schedule, within planned budget, with the highest quality and in the safest manner. Construction projects are frequently influenced by either success factors that help project parties reach their goal as planned, or delay factors that stifle or postpone project completion. The purpose of this research is to identify success and delay factors which can help project parties reach their intended goals with greater efficiency. This research extracted seven of the most important success factors according to the literature and seven of the most important delay factors identified by project parties, and then examined correlations between them to determine which were the most influential in preventing project delays. This research uses a comprehensive literature review to design and conduct a survey to investigate success and delay factors and then obtain a consensus of expert opinion using the Delphi methodology to rank the most needed critical success factors for Brunei construction projects. A specific survey was distributed to owners, contractors and engineers to examine the most critical delay factors. A general survey was distributed to examine the correlation between the identified delay factors and the seven most important critical success factors selected. A consensus of expert opinion using the Delphi methodology was used to rank the most needed critical success factors for Brunei building construction. Data was collected and evaluated by statistical methods to identify the most significant causes of delay and to measure the strength and direction of the relationship between critical success factors and delay factors in order to examine project parties’ evaluation of projects’ critical success and delay factors, and to evaluate the influence of critical success factors on critical delay factors. A relative importance index has been used to determine the relative importance of the various causes of delays. A one and two-way analysis of variance (ANOVA) has been used to examine how the group or groups evaluated the influence of the critical success factors in avoiding or preventing each of the delay factors, and which success factors were perceived as most influential in avoiding or preventing critical delay factors. Finally the Delphi method, using consensus from an expert panel, was employed to identify the seven most critical success factors used to avoid the delay factors, and thereby improve project performance.

Listening to voices of self : digital journaling among gifted young adolescents

The lives of gifted young adolescents are often subject to adult-generated and expert narratives that can impact a developing sense of self. However, opportunities for gifted young adolescents to represent themselves as informants can emerge through digital forms of qualitative research. This paper reports on the value of digital writing of journal entries, delivered by email to a researcher over several months, as an alternative to face-to-face interviews. Journaling methods combined with techniques of 'listening for voices' can support young adolescents in generating their own multi-vocal narratives of self. This method capturing self-narratives in email form has the potential to produce rich understandings of individual young adolescents' self-constructions.

Mentor educators’ understandings of mentoring preservice primary teachers

Mentors are significant in shaping a preservice teacher’s practices. Developing common understandings about effective mentoring practices can assist the mentoring process. What are mentor educators’ practical ideas towards implementing a mentoring program? This mixed-method study involves surveys, questionnaires, and audio-taped focus group meetings on 14 mentor educators’ views on mentoring preservice primary teachers. This research aims to understand mentor educators’ motivations for mentoring, their views about what makes a good mentor, benefits for mentors, and issues or concerns for mentors and the mentoring process. It also focuses on determining professional development for mentors and troubleshooting potential problems. Findings revealed that these mentor educators were motivated into developing mentoring programs as a way to: (1) influence the quality of preservice teacher education (2) provide personal and professional development in mentoring, and (3) support mentors and the mentoring process within school settings. Outlining what makes a good mentor and benefits for mentors were consistent with the literature. However, these expert mentors also provided potential solutions (e.g., university support and professional development ideas) on issues such as knowing the mentee’s level of development and expectations, building a professional relationship prior to placement and the mentor’s dual role as confidant and assessor.

APROMORE : an advanced process model repository

Business process models are becoming available in large numbers due to their popular use in many industrial applications such as enterprise and quality engineering projects. On the one hand, this raises a challenge as to their proper management: How can it be ensured that the proper process model is always available to the interested stakeholder? On the other hand, the richness of a large set of process models also offers opportunities, for example with respect to the re-use of existing model parts for new models. This paper describes the functionalities and architecture of an advanced process model repository, named APROMORE. This tool brings together a rich set of features for the analysis, management and usage of large sets of process models, drawing from state-of-the art research in the field of process modeling. A prototype of the platform is presented in this paper, demonstrating its feasibility, as well as an outlook on the further development of APROMORE.