Polymer-drug conjugates: current status and future trends

Polymer conjugates are nano-sized, multicomponent constructs already in the clinic as anticancer compounds, both as single agents or as elements of combinations. They have the potential to improve pharmacological therapy of a variety of solid tumors. Polymer-drug conjugation promotes passive tumor targeting by the enhanced permeability and retention (EPR) effect and allows for lysosomotropic drug delivery following endocytic capture. In the first part of this review, we analyze the promising results arising from clinical trials of polymer-bound chemotherapy. The experience gained on these studies provides the basis for the development of a more sophisticated second-generation of polymer conjugates. However, many challenges still lay ahead providing scope to develop and refine this field. The "technology platform'' of polymer therapeutics allows the development of both new and exciting polymeric materials, the incorporation of novel bioactive agents and combinations thereof to address recent advances in drug therapy. The rational design of polymer drug conjugates is expected to realize the true potential of these "nanomedicines".

Cognitive behaviour therapy for psychosis: current evidence and future directions

The past decade has seen considerable growth in the evidence base of cognitive behavioural therapy for psychosis. Consistent reports of moderate effect sizes have led to such interventions being recommended as part of routine clinical practice. Most of this evidence is based on a generic form of CBT for psychosis applied to a heterogeneous group. An increase in the effectiveness of cognitive behavioural interventions may require new protocols. Such therapeutic developments should be based on the theoretical understanding of the psychological processes associated with specific forms of psychotic presentation. The current evidence base of CBT for psychosis is reviewed, and barriers that have held back the development of this research are discussed.

Cognitive therapy for anxiety disorders: current status and future directions.

This paper reviews recent theoretical, conceptual and practice developments in cognitive-behaviour therapy (CBT) for anxiety disorders. The empirical status of CBT for anxiety disorders is reviewed and recent advances in the field are outlined. Challenges for the future development of CBT for the anxiety disorders are examined in relation to the efficacy, effectiveness and cost-effectiveness of the approach. It is concluded that the major challenge currently facing CBT for anxiety disorders in the UK is how to meet the increased demand for provision whilst maintaining high levels of efficacy and effectiveness. It is suggested that the creation of an evidence base for the dissemination of CBT needs to become a priority for empirical investigation in order effectively to expand the provision of CBT for anxiety disorders.

Predicting fault inflow in iterative software development processes: an industrial evaluation

This paper addresses the need for accurate predictions on the fault inflow, i.e. the number of faults found in the consecutive project weeks, in highly iterative processes. In such processes, in contrast to waterfall-like processes, fault repair and development of new features run almost in parallel. Given accurate predictions on fault inflow, managers could dynamically re-allocate resources between these different tasks in a more adequate way. Furthermore, managers could react with process improvements when the expected fault inflow is higher than desired. This study suggests software reliability growth models (SRGMs) for predicting fault inflow. Originally developed for traditional processes, the performance of these models in highly iterative processes is investigated. Additionally, a simple linear model is developed and compared to the SRGMs. The paper provides results from applying these models on fault data from three different industrial projects. One of the key findings of this study is that some SRGMs are applicable for predicting fault inflow in highly iterative processes. Moreover, the results show that the simple linear model represents a valid alternative to the SRGMs, as it provides reasonably accurate predictions and performs better in many cases.

Hybrid fault detection and isolation in an heater bank of an HVAC system

In this work a hybrid technique that includes probabilistic and optimization based methods is presented. The method is applied, both in simulation and by means of real-time experiments, to the heating unit of a Heating, Ventilation Air Conditioning (HVAC) system. It is shown that the addition of the probabilistic approach improves the fault diagnosis accuracy.

Multiple-model fault tolerant control of terminal unites of HVAC Systems

In this work, a fault-tolerant control scheme is applied to a air handling unit of a heating, ventilation and air-conditioning system. Using the multiple-model approach it is possible to identify faults and to control the system under faulty and normal conditions in an effective way. Using well known techniques to model and control the process, this work focuses on the importance of the cost function in the fault detection and its influence on the reconfigurable controller. Experimental results show how the control of the terminal unit is affected in the presence a fault, and how the recuperation and reconfiguration of the control action is able to deal with the effects of faults.

Historical and current machine intelligence

In this article, we provide an initial insight into the study of MI and what it means for a machine to be intelligent. We discuss how MI has progressed to date and consider future scenarios in a realistic and logical way as much as possible. To do this, we unravel one of the major stumbling blocks to the study of MI, which is the field that has become widely known as "artificial intelligence"

Fault tolerance of Mobius cubes under two forbidden fault set models

An n-dimensional Mobius cube, 0MQ(n) or 1MQ(n), is a variation of n-dimensional cube Q(n) which possesses many attractive properties such as significantly smaller communication delay and stronger graph-embedding capabilities. In some practical situations, the fault tolerance of a distributed memory multiprocessor system can be measured more precisely by the connectivity of the underlying graph under forbidden fault set models. This article addresses the connectivity of 0MQ(n)/1MQ(n), under two typical forbidden fault set models. We first prove that the connectivity of 0MQ(n)/1MQ(n) is 2n - 2 when the fault set does not contain the neighborhood of any vertex as a subset. We then prove that the connectivity of 0MQ(n)/1MQ(n) is 3n - 5 provided that the neighborhood of any vertex as well as that of any edge cannot fail simultaneously These results demonstrate that 0MQ(n)/1MQ(n) has the same connectivity as Q(n) under either of the previous assumptions.