Leucocyte ascorbic acid levels failed to identify six of seven elderly patients shown to be deficient on an oral vitamin C saturation test. Compared to those with a normal saturation test, patients judged deficient had lower levels for triceps skinfold thickness, mean arm muscle circumference and Quetelet's index; there was a significant association with the habit of eating alone, and with a dietary intake of less than 30 mg of ascorbic acid daily (the recommended daily allowance in the U.K.). No significant difference was found in the values for haemoglobin, serum albumin or potassium concentrations between the two groups, and no association shown between a deficient saturation test and smoking, season, sublingual varicosities or an abnormal bleeding time.

estimates of the frequencies of keywords to compute a near optimal solution when the estimates are accurate, while at the same time maintaining a good worst-case competitive ratio in case the estimates are totally incorrect. This is motivated by real-world situations where search engines have stochastic

Assessing the reliability of complex technological systems such as communi-cation networks, transportation grids, and bridge networks is a difficult task. From a mathematical point of view, the problem of estimating network reli-ability belongs to the #P complexity class. As a consequence

, is both costly and unreliable.) The proposed measure, the association ratio, estimates word association norms directly from computer readable corpora, making it possible to estimate norms for tens of thousands of words

-based methods produce unreliable results. In this paper, we propose a novel hidden Markov random field (HMRF) model, which is a stochastic process generated by a MRF whose state sequence cannot be observed directly but which can be indirectly estimated through observations. Mathematically, it can be shown

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Motivated by navigation and tracking applications within sensor networks, we consider the problem of performing Kalman filtering with intermittent observations. When data travel along unreliable communication channels in a large, wireless, multihop sensor network, the effect of communication

, and middleware services. We introduce the influence field, which can be estimated from a network of binary sensors, as the basis for a novel classifier. A contribution of our work is that we do not assume a reliable network; on the contrary, we quantitatively analyze the effects of network unreliability

, it summarizes the key results of the Coda and Odyssey systems. Finally, it describes the research opportunities in five important topics relevant to mobile computing: caching metrics, semantic callbacks and validators, resource revocation, analysis of adaptation, and global estimation from local observations. 1

compute a local weighted least-squares estimate, which converges to the global maximum-likelihood solution. This scheme is robust to unreliable communication links. We show that it works in a network with dynamically changing topology, provided that the infinitely occurring communication graphs