Sparse modeling using orthogonal forward regression with PRESS statistic and regularization

The paper introduces an efficient construction algorithm for obtaining sparse linear-in-the-weights regression models based on an approach of directly optimizing model generalization capability. This is achieved by utilizing the delete-1 cross validation concept and the associated leave-one-out test error also known as the predicted residual sums of squares (PRESS) statistic, without resorting to any other validation data set for model evaluation in the model construction process. Computational efficiency is ensured using an orthogonal forward regression, but the algorithm incrementally minimizes the PRESS statistic instead of the usual sum of the squared training errors. A local regularization method can naturally be incorporated into the model selection procedure to further enforce model sparsity. The proposed algorithm is fully automatic, and the user is not required to specify any criterion to terminate the model construction procedure. Comparisons with some of the existing state-of-art modeling methods are given, and several examples are included to demonstrate the ability of the proposed algorithm to effectively construct sparse models that generalize well.

A robust nonlinear identification algorithm using PRESS statistic and forward regression

This letter introduces a new robust nonlinear identification algorithm using the Predicted REsidual Sums of Squares (PRESS) statistic and for-ward regression. The major contribution is to compute the PRESS statistic within a framework of a forward orthogonalization process and hence construct a model with a good generalization property. Based on the properties of the PRESS statistic the proposed algorithm can achieve a fully automated procedure without resort to any other validation data set for iterative model evaluation.

Automatic nonlinear predictive model-construction algorithm using forward regression and the PRESS statistic

An automatic nonlinear predictive model-construction algorithm is introduced based on forward regression and the predicted-residual-sums-of-squares (PRESS) statistic. The proposed algorithm is based on the fundamental concept of evaluating a model's generalisation capability through crossvalidation. This is achieved by using the PRESS statistic as a cost function to optimise model structure. In particular, the proposed algorithm is developed with the aim of achieving computational efficiency, such that the computational effort, which would usually be extensive in the computation of the PRESS statistic, is reduced or minimised. The computation of PRESS is simplified by avoiding a matrix inversion through the use of the orthogonalisation procedure inherent in forward regression, and is further reduced significantly by the introduction of a forward-recursive formula. Based on the properties of the PRESS statistic, the proposed algorithm can achieve a fully automated procedure without resort to any other validation data set for iterative model evaluation. Numerical examples are used to demonstrate the efficacy of the algorithm.

Marker placement to describe the wrist movements during activities of daily living in cyclical tasks

Objective. To describe the wrist kinematics during movement through free range of motion and activities of daily living using a cyclical task. Design. The wrist angles were initially calculated in a calibration trial and then in two selected activities of daily living (jar opening and carton pouring). Background. Existing studies which describe the wrist movement do not address the specific application of daily activities. Moreover, the data presented from subject to subject may differ simply because of the non-cyclical nature of the upper limbs movements. Methods. The coordinates of external markers attached to bone references on the forearm and dorsal side of the hand were obtained using an optical motion capture system. The wrist angles were derived from free motion trials and successively calculated in four healthy subjects for two specific cyclical daily activities (opening a jar and pouring from a carton). Results. The free motions trial highlighted the interaction between the wrist angles. Both the jar opening and the carton pouring activity showed a repetitive pattern for the three angles within the cycle length. In the jar-opening task, the standard deviation for the whole population was 10.8degrees for flexion-extension, 5.3degrees for radial-ulnar deviation and 10.4degrees for pronation-supination. In the carton-pouring task, the standard deviation for the whole population was 16.0degrees for flexion-extension, 3.4degrees for radial-ulnar deviation and 10.7degrees for pro nation-supination. Conclusion. Wrist kinematics in healthy subjects can be successfully described by the rotations about the axes of marker-defined coordinates systems during free range of motion and daily activities using cyclical tasks.

A double-blind, placebo-controlled, cross-over study to establish the bifidogenic effect of a very-long-chain inulin extracted from globe artichoke (Cynara scolymus) in healthy human subjects

There is growing interest in the use of inulins as substrates for the selective growth of beneficial gut bacteria such as bifidobacteria and lactobacilli because recent studies have established that their prebiotic effect is linked to several health benefits. In the present study, the impact of a very-long-chain inulin (VLCI), derived from globe artichoke (Cynara scolymus), on the human intestinal microbiota compared with maltodextrin was determined. A double-blind, cross-over study was carried out in thirty-two healthy adults who were randomised into two groups and consumed 10 g/d of either VLCI or maltodextrin, for two 3-week study periods, separated by a 3-week washout period. Numbers of faecal bifidobacteria and lactobacilli were significantly higher upon VLCI ingestion compared with the placebo. Additionally, levels of Atopobium group significantly increased, while Bacteroides–Prevotella numbers were significantly reduced. No significant changes in faecal SCFA concentrations were observed. There were no adverse gastrointestinal symptoms apart from a significant increase in mild and moderate bloating upon VLCI ingestion. These observations were also confirmed by in vitro gas production measurements. In conclusion, daily consumption of VLCI extracted from globe artichoke exerted a pronounced prebiotic effect on the human faecal microbiota composition and was well tolerated by all volunteers.

A human volunteer study to assess the impact of confectionery sweeteners on the gut microbiota composition.

Sweeteners are being sourced to lower the energetic value of confectionery including chocolates. Some, especially non-digestible carbohydrates, may possess other benefits for human health upon their fermentation by the colonic microbiota. The present study assessed non-digestible carbohydrate sweeteners, selected for use in low-energy chocolates, for their ability to beneficially modulate faecal bacterial profiles in human volunteers. Forty volunteers consumed a test chocolate (low-energy or experimental chocolate) containing 22·8 g of maltitol (MTL), MTL and polydextrose (PDX), or MTL and resistant starch for fourteen consecutive days. The dose of the test chocolates was doubled every 2 weeks over a 6-week period. Numbers of faecal bifidobacteria significantly increased with all the three test treatments. Chocolate containing the PDX blend also significantly increased faecal lactobacilli (P = 0·00 001) after the 6 weeks. The PDX blend also showed significant increases in faecal propionate and butyrate (P = 0·002 and 0·006, respectively). All the test chocolates were well tolerated with no significant change in bowel habit or intestinal symptoms even at a daily dose of 45·6 g of non-digestible carbohydrate sweetener. This is of importance not only for giving manufacturers a sugar replacement that can reduce energetic content, but also for providing a well-tolerated means of delivering high levels of non-digestible carbohydrates into the colon, bringing about improvements in the biomarkers of gut health.

Simulating the impacts of global warming on wheat in China using a large area crop model

Temperature is one of the most prominent environmental factors that determine plant growth, devel- opment, and yield. Cool and moist conditions are most favorable for wheat. Wheat is likely to be highly vulnerable to further warming because currently the temperature is already close to or above optimum. In this study, the impacts of warming and extreme high temperature stress on wheat yield over China were investigated by using the general large area model (GLAM) for annual crops. The results showed that each 1±C rise in daily mean temperature would reduce the average wheat yield in China by about 4.6%{5.7% mainly due to the shorter growth duration, except for a small increase in yield at some grid cells. When the maximum temperature exceeded 30.5±C, the simulated grain-set fraction declined from 1 at 30.5±C to close to 0 at about 36±C. When the total grain-set was lower than the critical fractional grain-set (0.575{0.6), harvest index and potential grain yield were reduced. In order to reduce the negative impacts of warming, it is crucial to take serious actions to adapt to the climate change, for example, by shifting sowing date, adjusting crop distribution and structure, breeding heat-resistant varieties, and improving the monitoring, forecasting, and early warning of extreme climate events.

Climatic and oceanic associations with daily rainfall extremes over southern Africa

Changes in climate variability and, in particular, changes in extreme climate events are likely to be of far more significance for environmentally vulnerable regions than changes in the mean state. It is generally accepted that sea-surface temperatures (SSTs) play an important role in modulating rainfall variability. Consequently, SSTs can be prescribed in global and regional climate modelling in order to study the physical mechanisms behind rainfall and its extremes. Using a satellite-based daily rainfall historical data set, this paper describes the main patterns of rainfall variability over southern Africa, identifies the dates when extreme rainfall occurs within these patterns, and shows the effect of resolution in trying to identify the location and intensity of SST anomalies associated with these extremes in the Atlantic and southwest Indian Ocean. Derived from a Principal Component Analysis (PCA), the results also suggest that, for the spatial pattern accounting for the highest amount of variability, extremes extracted at a higher spatial resolution do give a clearer indication regarding the location and intensity of anomalous SST regions. As the amount of variability explained by each spatial pattern defined by the PCA decreases, it would appear that extremes extracted at a lower resolution give a clearer indication of anomalous SST regions.

Robots with a gentle touch: advances in assistive robotics and prosthetics

As healthcare costs rise and an aging population makes an increased demand on services, so new techniques must be introduced to promote an individuals independence and provide these services. Robots can now be designed so they can alter their dynamic properties changing from stiff to flaccid, or from giving no resistance to movement, to damping any large and sudden movements. This has some strong implications in health care in particular for rehabilitation where a robot must work in conjunction with an individual, and might guiding or assist a persons arm movements, or might be commanded to perform some set of autonomous actions. This paper presents the state-of-the-art of rehabilitation robots with examples from prosthetics, aids for daily living and physiotherapy. In all these situations there is the potential for the interaction to be non-passive with a resulting potential for the human/machine/environment combination to become unstable. To understand this instability we must develop better models of the human motor system and fit these models with realistic parameters. This paper concludes with a discussion of this problem and overviews some human models that can be used to facilitate the design of the human/machine interfaces.