Presence-absence versus abundance data for monitoring threatened species

Effective detection of population trend is crucial for managing threatened species. Little theory exists, however, to assist managers in choosing the most cost-effective monitoring techniques for diagnosing trend. We present a framework for determining the optimal monitoring strategy by simulating a manager collecting data on a declining species, the Chestnut-rumped Hylacola (Hylacola pyrrhopygia parkeri), to determine whether the species should be listed under the IUCN (World Conservation Union) Red List. We compared the efficiencies of two strategies for detecting trend, abundance, and presence-absence surveys, underfinancial constraints. One might expect the abundance surveys to be superior under all circumstances because more information is collected at each site. Nevertheless, the presence-absence data can be collected at more sites because the surveyor is not obliged to spend a fixed amount of time at each site. The optimal strategy for monitoring was very dependent on the budget available. Under some circumstances, presence-absence surveys outperformed abundance surveys for diagnosing the IUCN Red List categories cost-effectively. Abundance surveys were best if the species was expected to be recorded more than 16 times/year; otherwise, presence-absence surveys were best. The relationship between the strategies we investigated is likely to be relevant for many comparisons of presence-absence or abundance data. Managers of any cryptic or low-density species who hope to maximize their success of estimating trend should find an application for our results.

Induced visual illusions and gamma oscillations in human primary visual cortex

Using magnetoencephalography, we studied the spatiotemporal properties of cortical responses in terms of event-related synchronization and event-related desynchronization to a range of stripe patterns in subjects with no neurological disorders. These stripes are known for their tendency to induce a range of abnormal sensations, such as illusions, nausea, dizziness, headache and attacks of pattern-sensitive epilepsy. The optimal stimulus must have specific physical properties, and maximum abnormalities occur at specific spatial frequency and contrast. Despite individual differences in the severity of discomfort experienced, psychophysical studies have shown that most observers experience some degree of visual anomaly on viewing such patterns. In a separate experiment, subjects reported the incidence of illusions and discomfort to each pattern. We found maximal cortical power in the gamma range (30-60 Hz) confined to the region of the primary visual cortex in response to patterns of 2-4 cycles per degree, peaking at 3 cycles per degree. This coincides with the peak of mean illusions and discomfort, also maximal for patterns of 2-4 cycles per degree. We show that gamma band activity in V1 is a narrow band function of spatial frequency. We hypothesize that the intrinsic properties of gamma oscillations may underlie visual discomfort and play a role in the onset of seizures.

Coarse threat images reveal theta oscillations in the amygdala: a magnetoencephalography study

Neurocognitive models propose a specialized neural system for processing threat-related information, in which the amygdala plays a key role in the analysis of threat cues. fMRI research indicates that the amygdala is sensitive to coarse visual threat relevant information—for example, low spatial frequency (LSF) fearful faces. However, fMRI cannot determine the temporal or spectral characteristics of neural responses. Consequently, we used magnetoencephalography to explore spatiotemporal patterns of activity in the amygdala and cortical regions with blurry (LSF) and normal angry, fearful, and neutral faces. Results demonstrated differences in amygdala activity between LSF threat-related and LSF neutral faces (50-250 msec after face onset). These differences were evident in the theta range (4-8 Hz) and were accompanied by power changes within visual and frontal regions. Our results support the view that the amygdala is involved in the early processing of coarse threat related information and that theta is important in integrating activity within emotion-processing networks.

Multimodal characterisation of sensorimotor oscillations

The studies in this project have investigated the ongoing neuronal network oscillatory activity found in the sensorimotor cortex using two modalities: magnetoencephalography (MEG) and in vitro slice recordings. The results have established that ongoing sensorimotor oscillations span the mu and beta frequency region both in vitro and in MEG recordings, with distinct frequency profiles for each recorded laminae in vitro, while MI and SI show less difference in humans. In addition, these studies show that connections between MI and SI modulate the ongoing neuronal network activity in these areas. The stimulation studies indicate that specific frequencies of stimulation affect the ongoing activity in the sensorimotor cortex. The continuous theta burst stimulation (cTBS) study demonstrates that cTBS predominantly enhances the power of the local ongoing activity. The stimulation studies in this project show limited comparison between modalities, which is informative of the role of connectivity in these effects. However, independently these studies provide novel information on the mechanisms on sensorimotor oscillatory interaction. The pharmacological studies reveal that GABAergic modulation with zolpidem changes the neuronal oscillatory network activity in both healthy and pathological MI. Zolpidem enhances the power of ongoing oscillatory activity in both sensorimotor laminae and in healthy subjects. In contrast, zolpidem attenuates the “abnormal” beta oscillatory activity in the affected hemisphere in Parkinsonian patients, while restoring the hemispheric beta power ratio and frequency variability and thereby improving motor symptomatology. Finally we show that independent signals from MI laminae can be integrated in silico to resemble the aggregate MEG MI oscillatory signals. This highlights the usefulness of combining these two methods when elucidating neuronal network oscillations in the sensorimotor cortex and any interventions.

A multimodal perspective on the composition of cortical oscillations:frontiers in human neuroscience

An expanding corpus of research details the relationship between functional magnetic resonance imaging (fMRI) measures and neuronal network oscillations. Typically, integratedelectroencephalography(EEG) and fMRI,orparallel magnetoencephalography (MEG) and fMRI are used to draw inference about the consanguinity of BOLD and electrical measurements. However, there is a relative dearth of information about the relationship between E/MEG and the focal networks from which these signals emanate. Consequently, the genesis and composition of E/MEG oscillations requires further clarification. Here we aim to contribute to understanding through a series of parallel measurements of primary motor cortex (M1) oscillations, using human MEG and in-vitro rodent local field potentials. We compare spontaneous activity in the ~10Hz mu and 15-30Hz beta frequency ranges and compare MEG signals with independent and integrated layers III and V(LIII/LV) from in vitro recordings. We explore the mechanisms of oscillatory generation, using specific pharmacological modulation with the GABA-A alpha-1 subunit modulator zolpidem. Finally, to determine the contribution of cortico-cortical connectivity, we recorded in-vitro M1, during an incision to sever lateral connections between M1 and S1 cortices. We demonstrate that frequency distribution of MEG signals appear have closer statistically similarity with signals from integrated rather than independent LIII/LV laminae. GABAergic modulation in both modalities elicited comparable changes in the power of the beta band. Finally, cortico-cortical connectivity in sensorimotor cortex (SMC) appears to directly influence the power of the mu rhythm in LIII. These findings suggest that the MEG signal is an amalgam of outputs from LIII and LV, that multiple frequencies can arise from the same cortical area and that in vitro and MEG M1 oscillations are driven by comparable mechanisms. Finally, corticocortical connectivity is reflected in the power of the SMC mu rhythm. © 2013 Ronnqvist, Mcallister, Woodhall, Stanford and Hall.

Power tapping function in near infra-red region based on 45° tilted fiber gratings

We report an efficient power tapping device working in near infra-red (800 nm) wavelength region based on UV-in- scribed 45° tilted fiber grating (45°-TFG) structure. Five 45°-TFGs were UV-inscribed in hydrogenated PS750 fiber using a custom-designed phase mask with different grating lengths of 3 mm, 5 mm, 9 mm, 12 mm and 15 mm, showing polarization dependent losses (PDLs) of 1 dB, 3 dB, 7 dB, 10 dB and 13 dB, respectively. The power side-tapping efficiency is clearly depending on the grating strength. It has been identified that the power tapping efficiency increases with the grating strength and deceases along the grating length. The side-tapped power profile has also been examined in azimuthal direction, showing a near-Gaussian distribution. These experimental results clearly demonstrated that 45°- TFGs may be used as in-fiber power tapping devices for applications requiring in-line signal monitoring.

Signal Processing under Active Monitoring

This paper describes a method of signal preprocessing under active monitoring. Suppose we want to solve the inverse problem of getting the response of a medium to one powerful signal, which is equivalent to obtaining the transmission function of the medium, but do not have an opportunity to conduct such an experiment (it might be too expensive or harmful for the environment). Practically the problem can be reduced to obtaining the transmission function of the medium. In this case we can conduct a series of experiments of relatively low power and superpose the response signals. However, this method is conjugated with considerable loss of information (especially in the high frequency domain) due to fluctuations of the phase, the frequency and the starting time of each individual experiment. The preprocessing technique presented in this paper allows us to substantially restore the response of the medium and consequently to find a better estimate for the transmission function. This technique is based on expanding the initial signal into the system of orthogonal functions.

A Real-time Decision Support System Prototype for Management of a Power Block

This paper describes the basic tools for a real-time decision support system of a semiotic type on the example of the prototype for management and monitoring of a nuclear power block implemented on the basis of the tool complex G2+GDA using cognitive graphics and parallel processing. This work was supported by RFBR (project 02-07-90042).

Connection design without accurate LV feeder load data:an argument for LV monitoring

Since privatisation, maintenance of DNO LV feeder maximum demand information has gradually demised in some Utility Areas, and it is postulated that lack of knowledge about 11kV and LV electrical networks is resulting in a less economical and energy efficient Network as a whole. In an attempt to quantify the negative impact, this paper examines ten postulated new connection scenarios for a set of real LV load readings, in order to find the difference in design solutions when LV load readings were and were not known. The load profiles of the substations were examined in order to explore the utilisation profile. It was found that in 70% of the scenarios explored, significant cost differences were found. These cost differences varied by an average of 1000%, between schemes designed with and without load readings. Obviously, over designing a system and therefore operating more, underutilised transformers becomes less financially beneficial and less energy efficient. The paper concludes that new connection design is improved in terms of cost when carried out based on known LV load information and enhances the case for regular maximum feeder demand information and/or metering of LV feeders. © 2013 IEEE.

Rhythm makes the world go round:an MEG-TMS study on the role of right TPJ theta oscillations in embodied perspective taking

While some aspects of social processing are shared between humans and other species, some aspects are not. The former seems to apply to merely tracking another's visual perspective in the world (i.e., what a conspecific can or cannot perceive), while the latter applies to perspective taking in form of mentally “embodying” another's viewpoint. Our previous behavioural research had indicated that only perspective taking, but not tracking, relies on simulating a body schema rotation into another's viewpoint. In the current study we employed Magnetoencephalography (MEG) and revealed that this mechanism of mental body schema rotation is primarily linked to theta oscillations in a wider brain network of body-schema, somatosensory and motor-related areas, with the right posterior temporo-parietal junction (pTPJ) at its core. The latter was reflected by a convergence of theta oscillatory power in right pTPJ obtained by overlapping the separately localised effects of rotation demands (angular disparity effect), cognitive embodiment (posture congruence effect), and basic body schema involvement (posture relevance effect) during perspective taking in contrast to perspective tracking. In a subsequent experiment we interfered with right pTPJ processing using dual pulse Transcranial Magnetic Stimulation (dpTMS) and observed a significant reduction of embodied processing. We conclude that right TPJ is the crucial network hub for transforming the embodied self into another's viewpoint, body and/or mind, thus, substantiating how conflicting representations between self and other may be resolved and potentially highlighting the embodied origins of high-level social cognition in general.

DC power line communication based on power/signal dual modulation in phase shift full bridge converters

For intelligent DC distributed power systems, data communication plays a vital role in system control and device monitoring. To achieve communication in a cost effective way, power/signal dual modulation (PSDM), a method that integrates data transmission with power conversion, can be utilized. In this paper, an improved PSDM method using phase shift full bridge (PSFB) converter is proposed. This method introduces a phase control based freedom in the conventional PSFB control loop to realize communication using the same power conversion circuit. In this way, decoupled data modulation and power conversion are realized without extra wiring and coupling units, and thus the system structure is simplified. More importantly, the signal intensity can be regulated by the proposed perturbation depth, and so this method can adapt to different operating conditions. Application of the proposed method to a DC distributed power system composed of several PSFB converters is discussed. A 2kW prototype system with an embedded 5kbps communication link has been implemented, and the effectiveness of the method is verified by experimental results.

Real-time temperature estimation for power MOSFETs considering thermal ageing effects

This paper presents a novel real-time power-device temperature estimation method that monitors the power MOSFET's junction temperature shift arising from thermal aging effects and incorporates the updated electrothermal models of power modules into digital controllers. Currently, the real-time estimator is emerging as an important tool for active control of device junction temperature as well as online health monitoring for power electronic systems, but its thermal model fails to address the device's ongoing degradation. Because of a mismatch of coefficients of thermal expansion between layers of power devices, repetitive thermal cycling will cause cracks, voids, and even delamination within the device components, particularly in the solder and thermal grease layers. Consequently, the thermal resistance of power devices will increase, making it possible to use thermal resistance (and junction temperature) as key indicators for condition monitoring and control purposes. In this paper, the predicted device temperature via threshold voltage measurements is compared with the real-time estimated ones, and the difference is attributed to the aging of the device. The thermal models in digital controllers are frequently updated to correct the shift caused by thermal aging effects. Experimental results on three power MOSFETs confirm that the proposed methodologies are effective to incorporate the thermal aging effects in the power-device temperature estimator with good accuracy. The developed adaptive technologies can be applied to other power devices such as IGBTs and SiC MOSFETs, and have significant economic implications.

System-on-a-Chip (SOC) based environmental monitoring platform for the detection of hazardous materials

The purpose of this research is design considerations for environmental monitoring platforms for the detection of hazardous materials using System-on-a-Chip (SoC) design. Design considerations focus on improving key areas such as: (1) sampling methodology; (2) context awareness; and (3) sensor placement. These design considerations for environmental monitoring platforms using wireless sensor networks (WSN) is applied to the detection of methylmercury (MeHg) and environmental parameters affecting its formation (methylation) and deformation (demethylation). ^ The sampling methodology investigates a proof-of-concept for the monitoring of MeHg using three primary components: (1) chemical derivatization; (2) preconcentration using the purge-and-trap (P&T) method; and (3) sensing using Quartz Crystal Microbalance (QCM) sensors. This study focuses on the measurement of inorganic mercury (Hg) (e.g., Hg2+) and applies lessons learned to organic Hg (e.g., MeHg) detection. ^ Context awareness of a WSN and sampling strategies is enhanced by using spatial analysis techniques, namely geostatistical analysis (i.e., classical variography and ordinary point kriging), to help predict the phenomena of interest in unmonitored locations (i.e., locations without sensors). This aids in making more informed decisions on control of the WSN (e.g., communications strategy, power management, resource allocation, sampling rate and strategy, etc.). This methodology improves the precision of controllability by adding potentially significant information of unmonitored locations.^ There are two types of sensors that are investigated in this study for near-optimal placement in a WSN: (1) environmental (e.g., humidity, moisture, temperature, etc.) and (2) visual (e.g., camera) sensors. The near-optimal placement of environmental sensors is found utilizing a strategy which minimizes the variance of spatial analysis based on randomly chosen points representing the sensor locations. Spatial analysis is employed using geostatistical analysis and optimization occurs with Monte Carlo analysis. Visual sensor placement is accomplished for omnidirectional cameras operating in a WSN using an optimal placement metric (OPM) which is calculated for each grid point based on line-of-site (LOS) in a defined number of directions where known obstacles are taken into consideration. Optimal areas of camera placement are determined based on areas generating the largest OPMs. Statistical analysis is examined by using Monte Carlo analysis with varying number of obstacles and cameras in a defined space. ^

Optimum wireless power transmission for sensors embedded in concrete

Various nondestructive testing (NDT) technologies for construction and performance monitoring have been studied for decades. Recently, the rapid evolution of wireless sensor network (WSN) technologies has enabled the development of sensors that can be embedded in concrete to monitor the structural health of infrastructure. Such sensors can be buried inside concrete and they can collect and report valuable volumetric data related to the health of a structure during and/or after construction. Wireless embedded sensors monitoring system is also a promising solution for decreasing the high installation and maintenance cost of the conventional wire based monitoring systems. Wireless monitoring sensors need to operate for long time. However, sensor batteries have finite life-time. Therefore, in order to enable long operational life of wireless sensors, novel wireless powering methods, which can charge the sensors’ rechargeable batteries wirelessly, need to be developed. The optimization of RF wireless powering of sensors embedded in concrete is studied here. First, our analytical results focus on calculating the transmission loss and propagation loss of electromagnetic waves penetrating into plain concrete at different humidity conditions for various frequencies. This analysis specifically leads to the identification of an optimum frequency range within 20–80 MHz that is validated through full-wave electromagnetic simulations. Second, the effects of various reinforced bar configurations on the efficiency of wireless powering are investigated. Specifically, effects of the following factors are studied: rebar types, rebar period, rebar radius, depth inside concrete, and offset placement. This analysis leads to the identification of the 902–928 MHz ISM band as the optimum power transmission frequency range for sensors embedded in reinforced concrete, since antennas working in this band are less sensitive to the effects of varying humidity as well as rebar configurations. Finally, optimized rectennas are designed for receiving and/or harvesting power in order to charge the rechargeable batteries of the embedded sensors. Such optimized wireless powering systems exhibit significantly larger efficiencies than the efficiencies of conventional RF wireless powering systems for sensors embedded in plain or reinforced concrete.