Small wars and insurgencies in theory and practice, 1500-1850

In early modern times, warfare in Europe took on many diverse and overlapping forms. Our modern notions of ‘regular’ and ‘irregular’ warfare, of ‘major war’ and ‘small war’, have their roots in much greater diversity than such binary notions allow for. While insurgencies go back to time immemorial, they have become conceptually fused with ‘small wars’. This is a term first used to denote special operations, often carried out by military companies formed from special ethnic groups and then recruited into larger armies. In its Spanish form, guerrilla, the term ‘small war’ came to stand for an ideologically-motivated insurgency against the state authorities or occupying forces of another power. There is much overlap between the phenomena of irregular warfare in the sense of special operations alongside regular operations, and irregular warfare of insurgents against the regular forces of a state. This book demonstrates how long the two phenomena were in flux and fed on each other, from the raiding operations of the 16th century to the ‘small wars’ or special operations conducted by special units in the 19th century, which existed alongside and could merge with a popular insurgency. This book is based on a special issue of the journal Small Wars & Insurgencies.

An approximate dynamic programming approach for improving accuracy of lossy data compression by Bloom filters

Bloom filters are a data structure for storing data in a compressed form. They offer excellent space and time efficiency at the cost of some loss of accuracy (so-called lossy compression). This work presents a yes-no Bloom filter, which as a data structure consisting of two parts: the yes-filter which is a standard Bloom filter and the no-filter which is another Bloom filter whose purpose is to represent those objects that were recognised incorrectly by the yes-filter (that is, to recognise the false positives of the yes-filter). By querying the no-filter after an object has been recognised by the yes-filter, we get a chance of rejecting it, which improves the accuracy of data recognition in comparison with the standard Bloom filter of the same total length. A further increase in accuracy is possible if one chooses objects to include in the no-filter so that the no-filter recognises as many as possible false positives but no true positives, thus producing the most accurate yes-no Bloom filter among all yes-no Bloom filters. This paper studies how optimization techniques can be used to maximize the number of false positives recognised by the no-filter, with the constraint being that it should recognise no true positives. To achieve this aim, an Integer Linear Program (ILP) is proposed for the optimal selection of false positives. In practice the problem size is normally large leading to intractable optimal solution. Considering the similarity of the ILP with the Multidimensional Knapsack Problem, an Approximate Dynamic Programming (ADP) model is developed making use of a reduced ILP for the value function approximation. Numerical results show the ADP model works best comparing with a number of heuristics as well as the CPLEX built-in solver (B&B), and this is what can be recommended for use in yes-no Bloom filters. In a wider context of the study of lossy compression algorithms, our researchis an example showing how the arsenal of optimization methods can be applied to improving the accuracy of compressed data.

Can milk proteins be a useful tool in the management of cardiometabolic health? An updated review of human intervention trials

The prevalence of cardiometabolic diseases is a significant public health burden worldwide. Emerging evidence supports the inverse association between greater dairy consumption and reduced risk of cardiometabolic diseases. Dairy proteins may have in important role in the favourable impact of dairy on human health such as blood pressure (BP) control, blood lipid and glucose control. The purpose of this review is to update and critically evaluate the evidence on the impacts of casein and whey protein in relation to metabolic function. Evidence from acute clinical studies assessing postprandial responses to milk protein ingestion suggests benefits on vascular function independent of BP, as well as improvement in glycaemic homeostasis. Chronic interventions have been less conclusive, with some showing benefits and others indicating a lack of improvement in vascular function. During chronic consumption BP appears to be lowered and both dyslipidaemia and hyperglacaemia seems to be controlled. Limited number of trials investigated the effects of dairy proteins on oxidative stress and inflammation. The beneficial changes in cardiometabolic homeostasis are likely mediated through improvements in insulin resistance, however to gain more detailed understanding on the underlying mechanism of milk proteins warrants further research. The incorporation of meals enriched with dairy protein in the habitual diet may result in the beneficial effects on cardiometabolic health. Nevertheless, future well-designed, controlled studies are needed to investigate the relative effects of both casein and whey protein on BP, vascular function, glucose homeostasis and inflammation.