Comparative seasonal acclimatization of food and energy consumption in adjacent populations of common spiny mice (Acomys cahirinus)

Animals inhabiting environments with low productivity and food availability commonly have reduced energy demands and increased digestive efficiencies. The dry matter intake (DMI), apparent digestible dry matter (ADDM), digestible efficiency (DE) and digestible energy intake (DEI) of two populations of common spiny mouse Acomys cahirinus were compared during both winter and summer under conditions of simulated water stress. Mice were captured from the north- and south-facing slopes (NFS and SFS) of the same canyon that represent mesic and xeric habitats, respectively. Measured variables were also compared between F-1 mice that had been born to either NFS or SFS mice, and raised in the laboratory. SFS mice were able to assimilate energy more efficiently than NFS mice during the summer. By comparison, NFS mice were able to assimilate more energy during the winter. During winter, NFS mice assimilated more energy at low levels of water stress, whereas SFS mice assimilated more energy at higher levels. Differences were also apparent in F-1 mice. It is therefore suggested that local climatic conditions can impose physiological adaptations that are retained in succeeding generations, creating unique meta-populations.

Genomic instability in Chinese hamster cells after exposure to X rays or alpha particles of different mean linear energy transfer

Evidence has accumulated that radiation induces a transmissible persistent destabilization of the genome, which mag. result in effects arising in the progeny of irradiated but surviving cells. An enhanced death rate among the progeny of cells surviving irradiation persists for many generations in the form of a reduced plating efficiency. Such delayed reproductive death is correlated with an increased occurrence of micronuclei. Since it has been suggested that radiation-induced chromosomal instability might depend on the radiation quality, we investigated the effects of alpha particles of different LET by looking at the frequency of delayed micronuclei in Chinese hamster V79 cells after cytochalasin-induced block of cell division, A dose-dependent increase in the frequency of micronuclei was found in cells assayed 1 week postirradiation or later. Also, there was a persistent increase in the frequency of dicentrics in surviving irradiated cells, Moreover, we found an increased micronucleus frequency in all of the 30 clones isolated from individual cells which had been irradiated with doses equivalent to either one, two or three alpha-particle traversals per cell nucleus, We conclude that the target for genomic instability in Chinese hamster cells must be larger than the cell nucleus. (C) 1997 by Radiation Research Society

Distributed Adaptive Learning Framework for Wide Area Monitoring of Power Systems Integrated with Distributed Generations

This paper presents a preliminary study of developing a novel distributed adaptive real-time learning framework for wide area monitoring of power systems integrated with distributed generations using synchrophasor technology. The framework comprises distributed agents (synchrophasors) for autonomous local condition monitoring and fault detection, and a central unit for generating global view for situation awareness and decision making. Key technologies that can be integrated into this hierarchical distributed learning scheme are discussed to enable real-time information extraction and knowledge discovery for decision making, without explicitly accumulating and storing all raw data by the central unit. Based on this, the configuration of a wide area monitoring system of power systems using synchrophasor technology, and the functionalities for locally installed open-phasor-measurement-units (OpenPMUs) and a central unit are presented. Initial results on anti-islanding protection using the proposed approach are given to illustrate the effectiveness.

Loss-of-Main Monitoring and Detection for Distributed Generations Using Dynamic Principal Component Analysis

In this paper, our previous work on Principal Component Analysis (PCA) based fault detection method is extended to the dynamic monitoring and detection of loss-of-main in power systems using wide-area synchrophasor measurements. In the previous work, a static PCA model was built and verified to be capable of detecting and extracting system faulty events; however the false alarm rate is high. To address this problem, this paper uses a well-known ‘time lag shift’ method to include dynamic behavior of the PCA model based on the synchronized measurements from Phasor Measurement Units (PMU), which is named as the Dynamic Principal Component Analysis (DPCA). Compared with the static PCA approach as well as the traditional passive mechanisms of loss-of-main detection, the proposed DPCA procedure describes how the synchrophasors are linearly
auto- and cross-correlated, based on conducting the singular value decomposition on the augmented time lagged synchrophasor matrix. Similar to the static PCA method, two statistics, namely T2 and Q with confidence limits are calculated to form intuitive charts for engineers or operators to monitor the loss-of-main situation in real time. The effectiveness of the proposed methodology is evaluated on the loss-of-main monitoring of a real system, where the historic data are recorded from PMUs installed in several locations in the UK/Ireland power system.