Animal group forces resulting from predator avoidance and competition minimization

A new model to explain animal spacing, based on a trade-off between foraging efficiency and predation risk, is derived from biological principles. The model is able to explain not only the general tendency for animal groups to form, but some of the attributes of real groups. These include the independence of mean animal spacing from group population, the observed variation of animal spacing with resource availability and also with the probability of predation, and the decline in group stability with group size. The appearance of "neutral zones" within which animals are not motivated to adjust their relative positions is also explained. The model assumes that animals try to minimize a cost potential combining the loss of intake rate due to foraging interference and the risk from exposure to predators. The cost potential describes a hypothetical field giving rise to apparent attractive and repulsive forces between animals. Biologically based functions are given for the decline in interference cost and increase in the cost of predation risk with increasing animal separation. Predation risk is calculated from the probabilities of predator attack and predator detection as they vary with distance. Using example functions for these probabilities and foraging interference, we calculate the minimum cost potential for regular lattice arrangements of animals before generalizing to finite-sized groups and random arrangements of animals, showing optimal geometries in each case and describing how potentials vary with animal spacing. (C) 1999 Academic Press.</p>

Beamforming and interference cancellation schemes for D2D communications

We investigate device-to-device (D2D) communication underlaying cellular networks with M-antenna base stations. We consider both beamforming (BF) and interference cancellation (IC) strategies under quantized channel state information (CSI), as well as, perfect CSI. We derive tight closed-form approximations of the ergodic achievable rate which hold for arbitrary transmit power, location of users and number of antennas. Based on these approximations, we derive insightful asymptotic expressions for three special cases namely high signal-to-noise (SNR), weak interference, and large M. In particular, we show that in the high SNR regime a ceiling effect exists which depends on the received signal-to-interference ratio and the number of antennas. Moreover, the achievable rate scales logarithmically with M. The ergodic achievable rate is shown to scale logarithmically with SNR and the antenna number in the weak interference case. When the BS is equipped with large number of antennas, we find that the ergodic achievable rate under quantized CSI reaches a saturated value, whilst it scales as log2M under perfect CSI.

Secure Multiple Amplify-and-Forward Relaying with Co-Channel Interference

We investigate the impact of co-channel interference on the security performance of multiple amplify-and-forward (AF) relaying networks, where N intermediate AF relays assist the data transmission from the source to the destination. The relays are corrupted by multiple co-channel interferers, and the information transmitted from the relays to destination can be overheard by the eavesdropper. In order to deal with the interference and wiretap, the best out of N relays is selected for security enhancement. To this end, we derive a novel lower bound on the secrecy outage probability (SOP), which is then utilized to present two best relay selection criteria, based on the instantaneous and statistical channel information of the interfering links. For these criteria and the conventional maxmin criterion, we quantify the impact of co-channel interference and relay selection by deriving the lower bound on the SOP. Furthermore, we derive the asymptotic SOP for each criterion, to explicitly reveal the impact of transmit power allocation among interferers on the secrecy performance, which offers valuable insights into practical design. We demonstrate that all selection criteria achieve full secrecy diversity order N, while the proposed in this paper two criteria outperform the conventional max-min scheme. 

The Holocene British and Irish ancient woodland fossil beetle fauna: implications for forest history, biodiversity and faunal colonisation

This paper presents a new review of our knowledge of the ancient forest beetle fauna from Holocene archaeological and palaeoecological sites in Great Britain and Ireland. It examines the colonisation, dispersal and decline of beetle species, highlighting the scale and nature of human activities in the shaping of the landscape of the British Isles. In particular, the paper discusses effects upon the insect fauna, and examines in detail the fossil record from the Humberhead Levels, eastern England. It discusses the local extirpation of up to 40 species in Britain and 15 species in Ireland. An evaluation of the timing of extirpations is made, suggesting that many species in Britain disappear from the fossil record between c. 3000 cal BC and 1000 cal BC (c. 5000-3000 cal BP), although some taxa may well have survived until considerably later. In Ireland, there are two distinct trends, with a group of species which seem to be absent after c. 2000 cal BC (c. 4000 cal BP) and a further group which survives until at least as late as the medieval period. The final clearance of the Irish landscape over the last few hundred years was so dramatic, however, that some species which are not especially unusual in a British context were decimated. Reasons behind the extirpation of taxa are examined in detail, and include a combination of forest clearance and human activities, isolation of populations, lack of temporal continuity of habitats, edaphic and competition factors affecting distribution of host trees (particularly pine), lack of forest fires and a decline in open forest systems. The role of climate change in extirpations is also evaluated. Consideration is given to the significance of these specialised ancient forest inhabitants in Ireland in the absence of an early Holocene land-bridge which suggests that colonisation was aided by other mechanisms, such as human activities and wood-rafting. Finally, the paper discusses the Continental origins of the British and Irish fauna and its hosts and the role played by European glacial refugia.

Does Gender Matter? Women Business Angels and the Supply of Entrepreneurial Finance

There is a substantial literature on the relationship between gender and access to finance. However, most studies have been concerned with access to debt finance. More recently, the focus of this research has broadened to examine women and venture capital. This article extends the focus further by examining the role of women in the business angel market, which is more important than the formal venture capital market in terms of both the number of ventures supported and total capital flows. Based on a detailed analysis of business angels in the U.K., the study concludes that women investors who are active in the market differ from their male counterparts in only limited respects. Future research into women business angels, and the possible existence of gender differences, needs to be based on more fully elaborated standpoint epistemologies that focus on the experience of the woman angel investor per se, and center on the examination of the role of homophily, social capital, networking, and competition in investment behavior.

Gene selection by cooperative competition clustering

Clustering analysis of data from DNA microarray hybridization studies is an essential task for identifying biologically relevant groups of genes. Attribute cluster algorithm (ACA) has provided an attractive way to group and select meaningful genes. However, ACA needs much prior knowledge about the genes to set the number of clusters. In practical applications, if the number of clusters is misspecified, the performance of the ACA will deteriorate rapidly. In fact, it is a very demanding to do that because of our little knowledge. We propose the Cooperative Competition Cluster Algorithm (CCCA) in this paper. In the algorithm, we assume that both cooperation and competition exist simultaneously between clusters in the process of clustering. By using this principle of Cooperative Competition, the number of clusters can be found in the process of clustering. Experimental results on a synthetic and gene expression data are demonstrated. The results show that CCCA can choose the number of clusters automatically and get excellent performance with respect to other competing methods.