On Infinite Time Performance of Nonlinear Model Predictive Controllers

This paper addresses the problem of infinite time performance of model predictive controllers applied to constrained nonlinear systems. The total performance is compared with a finite horizon optimal cost to reveal performance limits of closed-loop model predictive control systems. Based on the Principle of Optimality, an upper and a lower bound of the ratio between the total performance and the finite horizon optimal cost are obtained explicitly expressed by the optimization horizon. The results also illustrate, from viewpoint of performance, how model predictive controllers approaches to infinite optimal controllers as the optimization horizon increases.

Predictive molecular classifiers in colorectal cancer

The introduction of predictive molecular markers has radically enhanced the identification of which patients may benefit from a given treatment. Despite recent controversies, KRAS mutation is currently the most recognized molecular predictive marker in colorectal cancer (CRC), predicting efficacy of anti-epidermal growth factor receptor (anti-EGFR) antibodies. However, other relevant markers have been reported and claimed to identify patients that will benefit from anti-EGFR therapies. This group of markers includes BRAF mutations, PI3KCA mutations, and loss of PTEN expression. Similarly, molecular markers for cytotoxic agents' efficacy also may predict outcome in patients with CRC. This review aims to summarize the most important predictive molecular classifiers in patients with CRC and further discuss any inconsistent or conflicting findings for these molecular classifiers.

Prognostic and predictive markers in colorectal cancer - The role of new genomic technologies

Colorectal cancer (CRC) is one of the most frequently occurring malignancies worldwide, and the second leading cause of cancer related death in the Western World. Although early stage disease is curable by surgical resection alone, one half of patients with CRC will present with metastatic disease at some stage in the course of their disease. The most active drug in the treatment of CRC is 5-fluorouracil (5-FU) which is used in both the adjuvant and advanced settings. The use of adjuvant therapy is of proven benefit in Stage III CRC, however, its role in Stage II disease is less clear. There is therefore a need to identify those patients with early stage disease who will develop recurrent disease, and who would therefore benefit most from adjuvant treatment. In the advanced setting, the use of irinotecan and oxaliplatin in combination with 5-FU has proven beneficial, with yet further improvements in survival reported with the addition of new targeted agents such as bevacizamab. Despite this, a significant number of patients with advanced disease do not derive any benefit from the chemotherapy they receive, highlighting a need for the development of molecular or genomic markers predictive of response to these chemotherapeutic agents. This review will evaluate the recent advances in pharmacogenomics in CRC, in particular the development of predictive markers of response to chemotherapy. The successful identification of these markers of response will herald an era of personalised treatment, reducing treatment-related toxicity and improving outcome of patients with CRC. -cr 2007 Bentham Science Publishers Ltd.

Predictive Value of Depressive Symptoms for All-Cause Mortality: Findings From the PRIME Belfast Study Examining the Role of Inflammation and Cardiovascular Risk Markers

OBJECTIVES: To improve understanding about the potential underlying biological mechanisms in the link between depression and all-cause mortality and to investigate the role that inflammatory and other cardiovascular risk factors may play in the relationship between depressive symptoms and mortality.

METHODS: Depression and blood-based biological markers were assessed in the Belfast PRIME prospective cohort study (N = 2389 men, aged 50-59 years) in which participants were followed up for 18 years. Depression was measured using the 10-item Welsh Pure Depression Inventory. Inflammation markers (C-reactive protein [CRP], neopterin, interleukin [IL]-1 receptor antagonist [IL-1Ra], and IL-18) and cardiovascular-specific risk factors (N-terminal pro-b-type natriuretic peptide, midregion pro-atrial natriuretic peptide, midregion pro-adrenomedullin, C-terminal pro-endothelin-1 [CT-proET]) were obtained at baseline. We used Cox proportional hazards modeling to examine the association between depression and biological measures in relation to all-cause mortality and explore the mediating effects.

RESULTS: During follow-up, 418 participants died. Higher levels of depressive symptoms were associated with higher levels of CRP, IL-1Ra, and CT-proET. After adjustment for socioeconomic and life-style risk factors, depressive symptoms were significantly associated with all-cause mortality (hazard ratio = 1.10 per scale unit, 95% confidence interval = 1.04-1.16). This association was partly explained by CRP (7.3%) suggesting a minimal mediation effect. IL-1Ra, N-terminal pro-b-type natriuretic peptide, midregion pro-atrial natriuretic peptide, midregion pro-adrenomedullin, and CT-proET contributed marginally to the association between depression and subsequent mortality.

CONCLUSIONS: Inflammatory and cardiovascular risk markers are associated with depression and with increased mortality. However, depression and biological measures show additive effects rather than a pattern of meditation of biological factors in the association between depression and mortality.

Preoperative radial artery volume flow is predictive of arteriovenous fistula outcomes

Objective: Guidelines recommend the creation of a wrist radiocephalic arteriovenous fistula (RAVF) as initial hemodialysis vascular access. This study explored the potential of preoperative ultrasound vessel measurements to predict AVF failure to mature (FTM) in a cohort of patients with end-stage renal disease in Northern Ireland

.Methods: A retrospective analysis was performed of all patients who had preoperative ultrasound mapping of upper limb blood vessels carried out from August 2011 to December 2014 and whose AVF reached a functional outcome by March 2015.

Results: There were 152 patients (97% white) who had ultrasound mapping andan AVF functional outcome recorded; 80 (54%) had an upper arm AVF created, and 69 (46%) had a RAVF formed. Logistic regression revealed that female gender (odds ratio [OR], 2.5; 95% confidence interval [CI], 1.12-5.55; P = .025), minimum venous diameter (OR, 0.6; 95% CI, 0.39-0.95; P = .029), and RAVF (OR, 0.4; 95% CI, 0.18-0.89; P = .026) were associated with FTM. On subgroup analysis of the RAVF group, RAVFs with an arterial volume flow <50 mL/min were seven times as likely to fail as RAVFs with higher volume flows (OR, 7.0; 95% CI, 2.35-20.87; P < .001).

Conclusions: In this cohort, a radial artery flow rate <50 mL/min was associated with a sevenfold increased risk of FTM in RAVF, which to our knowledge has not been previously reported in the literature. Preoperative ultrasound mapping adds objective assessment in the clinical prediction of AVF FTM.

Does subjective rating reflect behavioural coding? Personality in 2 month-old dog puppies: An open-field test and adjective-based questionnaire

A number of studies have recently investigated personality traits in non-human species, with the dog gaining popularity as a subject species for research in this area. Recent research has shown the consistency of personality traits across both context and time for adult dogs, both when using questionnaire based methods of investigation and behavioural analyses of the dogs' behaviour. However, only a few studies have assessed the correspondence between these two methods, with results varying considerably across studies. Furthermore, most studies have focused on adult dogs, despite the fact that an understanding of personality traits in young puppies may be important for research focusing on the genetic basis of personality traits. In the current study, we sought to evaluate the correspondence between a questionnaire based method and the in depth analyses of the behaviour of 2-month old puppies in an open-field test in which a number of both social and non-social stimuli were presented to the subjects. We further evaluated consistency of traits over time by re-testing a subset of puppies. The correspondence between methods was high and test-retest consistency (for the main trait) was also good using both evaluation methods. Results showed clear factors referring to the two main personality traits 'extroversion,' (i.e. the enthusiastic, exuberant approach to the stimuli) and 'neuroticism,' (i.e. the more cautious and fearful approach to the stimuli), potentially similar to the shyness-boldness dimension found in previous studies. Furthermore, both methods identified an 'amicability' dimension, expressing the positive interactions the pups directed at the humans stranger, and a 'reservedness' dimension which identified pups who largely chose not to interact with the stimuli, and were defined as quiet and not nosey in the questionnaire.

Learning about probability from text and tables: Do color coding and labeling through an interactive-user interface help?

Learning from visual representations is enhanced when learners appropriately integrate corresponding visual and verbal information. This study examined the effects of two methods of promoting integration, color coding and labeling, on learning about probabilistic reasoning from a table and text. Undergraduate students (N = 98) were randomly assigned to learn about probabilistic reasoning from one of 4 computer-based lessons generated from a 2 (color coding/no color coding) by 2 (labeling/no labeling) between-subjects design. Learners added the labels or color coding at their own pace by clicking buttons in a computer-based lesson. Participants' eye movements were recorded while viewing the lesson. Labeling was beneficial for learning, but color coding was not. In addition, labeling, but not color coding, increased attention to important information in the table and time with the lesson. Both labeling and color coding increased looks between the text and corresponding information in the table. The findings provide support for the multimedia principle, and they suggest that providing labeling enhances learning about probabilistic reasoning from text and tables

Distributed coding for systems with cooperative diversity

O presente trabalho propõe-se a divulgar as mais significativas técnicas de esquemas cooperativos, de forma a ultrapassar alguns dos problemas dos sistemas móveis sem fios da próxima geração, estendendo a área de cobertura destes sistemas, assim como a sua capacidade e fiabilidade. O estudo de diversos esquemas cooperativos é efetuado em termos de capacidade e de taxa de erros, fazendo variar o número de relays e de antenas em cada elemento do sistema. Diversos algoritmos com aplicação em sistemas cooperativos são desenvolvidos e propostos ao longo desta tese, como códigos espaço-frequência aplicados de forma distribuída nos relays, para sistemas baseados na tecnologia OFDM e sob diversos cenários próximos da realidade. Os sistemas cooperativos são particularmente úteis em situações em que o caminho direto entre dois terminais não está acessível ou tem uma fraca qualidade de transmissão. Tendo este aspeto em consideração, e pretendendo ter a máxima eficiência espetral e máxima diversidade, um algoritmo com precodificação é também proposto para múltiplos relays, cada um equipado com uma ou duas antenas. A formulação matemática associada aos algoritmos propostos é apresentada, assim como a derivação da probabilidade de erro teórica. O desempenho dos sistemas assistidos por relays usando os algoritmos propostos é comparado em relação a outros esquemas cooperativos equivalentes e a esquemas não-cooperativos, considerando cenários com diferentes qualidades de canal, daí advindo importantes conclusões em relação a estes sistemas.

Spatial attention enhances object coding in local and distributed representations of the lateral occipital complex

The modulation of neural activity in visual cortex is thought to be a key mechanism of visual attention. The investigation of attentional modulation in high-level visual areas, however, is hampered by the lack of clear tuning or contrast response functions. In the present functional magnetic resonance imaging study we therefore systematically assessed how small voxel-wise biases in object preference across hundreds of voxels in the lateral occipital complex were affected when attention was directed to objects. We found that the strength of attentional modulation depended on a voxel's object preference in the absence of attention, a pattern indicative of an amplificatory mechanism. Our results show that such attentional modulation effectively increased the mutual information between voxel responses and object identity. Further, these local modulatory effects led to improved information-based object readout at the level of multi-voxel activation patterns and to an increased reproducibility of these patterns across repeated presentations. We conclude that attentional modulation enhances object coding in local and distributed object representations of the lateral occipital complex.

Face segregation and recognition by cortical multi-scale line and edge coding

Models of visual perception are based on image representations in cortical area V1 and higher areas which contain many cell layers for feature extraction. Basic simple, complex and end-stopped cells provide input for line, edge and keypoint detection. In this paper we present an improved method for multi-scale line/edge detection based on simple and complex cells. We illustrate the line/edge representation for object reconstruction, and we present models for multi-scale face (object) segregation and recognition that can be embedded into feedforward dorsal and ventral data streams (the “what” and “where” subsystems) with feedback streams from higher areas for obtaining translation, rotation and scale invariance.

Cortical object segregation and categorization by multi-scale line and edge coding

In this paper we present an improved scheme for line and edge detection in cortical area V1, based on responses of simple and complex cells, truly multi-scale with no free parameters. We illustrate the multi-scale representation for visual reconstruction, and show how object segregation can be achieved with coarse-to-finescale groupings. A two-level object categorization scenario is tested in which pre-categorization is based on coarse scales only, and final categorization on coarse plus fine scales. Processing schemes are discussed in the framework of a complete cortical architecture.