The basic ingredients of the North Atlantic Storm Track. Part II: Sea surface temperatures

The impact of North Atlantic SST patterns on the storm track is investigated using a hierarchy of GCM simulations using idealized (aquaplanet) and “semirealistic” boundary conditions in the atmospheric component (HadAM3) of the third climate configuration of the Met Office Unified Model (HadCM3). This framework enables the mechanisms determining the tropospheric response to North Atlantic SST patterns to be examined, both in isolation and in combination with continental-scale landmasses and orography. In isolation, a “Gulf Stream” SST pattern acts to strengthen the downstream storm track while a “North Atlantic Drift” SST pattern weakens it. These changes are consistent with changes in the extratropical SST gradient and near-surface baroclinicity, and each storm-track response is associated with a consistent change in the tropospheric jet structure. Locally enhanced near-surface horizontal wind convergence is found over the warm side of strengthened SST gradients associated with ascending air and increased precipitation, consistent with previous studies. When the combined SST pattern is introduced into the semirealistic framework (including the “North American” continent and the “Rocky Mountains”), the results suggest that the topographically generated southwest–northeast tilt in the North Atlantic storm track is enhanced. In particular, the Gulf Stream shifts the storm track south in the western Atlantic whereas the strong high-latitude SST gradient in the northeastern Atlantic enhances the storm track there.

Commodity currency: an alternative route to currency union

Proposals have been made for a common currency for East Asia, but the countries preparing to participate need to be in a state of economic convergence. We show that at least six countries of East Asia already satisfy this condition. There also needs to be a mechanism by which the new currency relates to other reserve currencies. We demonstrate that a numéraire could be defined solely from the actual worldwide consumption of food and energy per capita, linked to fiat currencies via world market prices. We show that real resource prices are stable in real terms, and likely to remain so. Furthermore, the link from energy prices to food commodity prices is permanent, arising from energy inputs in agriculture, food processing and distribu-tion. Calibration of currency value using a yardstick such as our SI numéraire offers an unbiased measure of the con-sistently stable cost of subsistence in the face of volatile currency exchange rates. This has the advantage that the par-ticipating countries need only agree to currency governance based on a common standards institution, a much less on-erous form of agreement than would be required in the creation of a common central bank.

Random prism: an alternative to random forests

Ensemble learning techniques generate multiple classifiers, so called base classifiers, whose combined classification results are used in order to increase the overall classification accuracy. In most ensemble classifiers the base classifiers are based on the Top Down Induction of Decision Trees (TDIDT) approach. However, an alternative approach for the induction of rule based classifiers is the Prism family of algorithms. Prism algorithms produce modular classification rules that do not necessarily fit into a decision tree structure. Prism classification rulesets achieve a comparable and sometimes higher classification accuracy compared with decision tree classifiers, if the data is noisy and large. Yet Prism still suffers from overfitting on noisy and large datasets. In practice ensemble techniques tend to reduce the overfitting, however there exists no ensemble learner for modular classification rule inducers such as the Prism family of algorithms. This article describes the first development of an ensemble learner based on the Prism family of algorithms in order to enhance Prism’s classification accuracy by reducing overfitting.

A novel alternative to cryopreservation for the short-term storage of stem cells for use in cell therapy using alginate encapsulation

Efficient transport of stem/progenitor cells without affecting their survival and function is a key factor in any practical cell-based therapy. However, the current approach using liquid nitrogen for the transfer of stem cells requires a short delivery time window is technically challenging and financially expensive. The present study aims to use semipermeable alginate hydrogels (crosslinked by strontium) to encapsulate, store, and release stem cells, to replace the conventional cryopreservation method for the transport of therapeutic cells within world-wide distribution time frame. Human mesenchymal stem cell (hMSC) and mouse embryonic stem cells (mESCs) were successfully stored inside alginate hydrogels for 5 days under ambient conditions in an air-tight environment (sealed cryovial). Cell viability, of the cells extracted from alginate gel, gave 74% (mESC) and 80% (hMSC) survival rates, which compared favorably to cryopreservation. More importantly, the subsequent proliferation rate and detection of common stem cell markers (both in mRNA and protein level) from hMSCs and mESCs retrieved from alginate hydrogels were also comparable to (if not better than) results gained following cryopreservation. In conclusion, this new and simple application of alginate hydrogel encapsulation may offer a cheap and robust alternative to cryopreservation for the transport and storage of stem cells for both clinical and research purposes.

Maximising umami taste in meat using natural ingredients: effects on chemistry, sensory perception and hedonic liking in young and old consumers

BACKGROUND: Umami taste in foods is elicited predominantly by the presence of glutamic acid and 5’-ribonucleotides, which act synergistically. This study aimed to use natural ingredients to maximise umami taste of a meat formulation and determine effects on liking of older consumers. METHODS: Cooked meat products with added natural ingredients (yeast extract, mycoscent, shiitake extract, tomato puree, soy sauce and soy bean paste) or monosodium glutamate (MSG) were prepared and compared to a control sample analytically (umami compounds), sensorially (sensory profile) and hedonically (liking by younger and older volunteers). Taste detection thresholds of sodium chloride and MSG of volunteers were collected. RESULTS: Four of the seven cooked meat products developed had a significantly higher content of umami-contributing compounds compared to the control. All products, except those containing MSG or tomato puree, were scored (by trained sensory panel) perceptually significantly higher in umami and / or salty taste compared to the control. Consumer tests showed a correlation of liking by the older cohort with perceived saltiness (ρ=0.76). CONCLUSION: The addition of natural umami-containing ingredients during the cooking of meat can provide enhanced umami and salty taste characteristics, this can lead to increased liking by some consumers, particularly those with raised taste detection thresholds.

Random Prism: a noise-tolerant alternative to Random Forests

Ensemble learning can be used to increase the overall classification accuracy of a classifier by generating multiple base classifiers and combining their classification results. A frequently used family of base classifiers for ensemble learning are decision trees. However, alternative approaches can potentially be used, such as the Prism family of algorithms that also induces classification rules. Compared with decision trees, Prism algorithms generate modular classification rules that cannot necessarily be represented in the form of a decision tree. Prism algorithms produce a similar classification accuracy compared with decision trees. However, in some cases, for example, if there is noise in the training and test data, Prism algorithms can outperform decision trees by achieving a higher classification accuracy. However, Prism still tends to overfit on noisy data; hence, ensemble learners have been adopted in this work to reduce the overfitting. This paper describes the development of an ensemble learner using a member of the Prism family as the base classifier to reduce the overfitting of Prism algorithms on noisy datasets. The developed ensemble classifier is compared with a stand-alone Prism classifier in terms of classification accuracy and resistance to noise.

Mechanism for synchronized motion between two humans in mutual tapping experiments: Transition from alternative mode to synchronization mode

We performed mutual tapping experiments between two humans to investigate the conditions required for synchronized motion. A transition from an alternative mode to a synchronization mode was discovered under the same conditions when a subject changed from a reactive mode to an anticipation mode in single tapping experiments. Experimental results suggest that the cycle time for each tapping motion is tuned by a proportional control that is based on synchronization errors and cycle time errors. As the tapping frequency increases, the mathematical model based on the feedback control in the sensory-motor closed loop predicts a discrete mode transition as the gain factors of the proportional control decease. The conditions of the synchronization were shown as a consequence of the coupled dynamics based on the subsequent feedback loop in the sensory-motor system.

An alternative approach to investigating lead-lag relationships between stock and stock index futures markets

In the absence of market frictions, the cost-of-carry model of stock index futures pricing predicts that returns on the underlying stock index and the associated stock index futures contract will be perfectly contemporaneously correlated. Evidence suggests, however, that this prediction is violated with clear evidence that the stock index futures market leads the stock market. It is argued that traditional tests, which assume that the underlying data generating process is constant, might be prone to overstate the lead-lag relationship. Using a new test for lead-lag relationships based on cross correlations and cross bicorrelations it is found that, contrary to results from using the traditional methodology, periods where the futures market leads the cash market are few and far between and when any lead-lag relationship is detected, it does not last long. Overall, the results are consistent with the prediction of the standard cost-of-carry model and market efficiency.

Portmanteau model diagnostics and tests for nonlinearity: a comparative Monte Carlo study of two alternative methods

This paper employs an extensive Monte Carlo study to test the size and power of the BDS and close return methods of testing for departures from independent and identical distribution. It is found that the finite sample properties of the BDS test are far superior and that the close return method cannot be recommended as a model diagnostic. Neither test can be reliably used for very small samples, while the close return test has low power even at large sample sizes