Incremental Trust in Grid Computing

This paper describes a comparative simulation study of some incremental trust and reputation algorithms for handling behavioural trust in large distributed systems, such as those based on the Grid paradigm. Two types of reputation algorithm (based on discrete and Bayesian evaluation of ratings) and two ways of combining direct trust and reputation (discrete combination and combination based on fuzzy logic) are considered. The various combinations of these methods are evaluated from the point of view of their ability to respond to changes in behaviour and the ease with which suitable parameters for the algorithms can be found in the context of Grid computing systems.

Intensity and directionality of bat echolocation signals

The paper reviews current knowledge of intensity and directionality of bat echolocation signals. Recent studies have revealed that echolocating bats can be much louder than previously believed. Bats previously dubbed “whispering” can emit calls with source levels up to 110 dB SPL at 10 cm and the louder open space hunting bats have been recorded at above 135 dB SPL. This implies that maximum emitted intensities are generally 30 dB or more above initial estimates. Bats' dynamic control of acoustic features also includes the intensity and directionality of their sonar calls. Aerial hawking bats will increase signal directionality in the field along with intensity thus increasing sonar range. During the last phase of prey pursuit, vespertilionid bats broaden their echolocation beam considerably, probably to counter evasive maneuvers of eared prey. We highlight how multiple call parameters (frequency, duration, intensity, and directionality of echolocation signals) in unison define the search volume probed by bats and in turn how bats perceive their surroundings. Small changes to individual parameters can, in combination, drastically change the bat's perception, facilitating successful navigation and food acquisition across a vast range of ecological niches. To better understand the function of echolocation in the natural habitat it is critical to determine multiple acoustic features of the echolocation calls. The combined (interactive) effects, not only of frequency and time parameters, but also of intensity and directionality, define the bat's view of its acoustic scene

Open-source workflow approaches to passive acoustic monitoring of bats

The work was funded by grants to PTM from Carlsberg Semper Ardens Research Projects and the Independent Research Fund Denmark.The affordability, storage and power capacity of compact modern recording hardware have evolved passive acoustic monitoring (PAM) of animals and soundscapes into a non-invasive, cost-effective tool for research and ecological management particularly useful for bats and toothed whales that orient and forage using ultrasonic echolocation. The use of PAM at large scales hinges on effective automated detectors and species classifiers which, combined with distance sampling approaches, have enabled species abundance estimation of toothed whales. But standardized, user-friendly and open access automated detection and classification workflows are in demand for this key conservation metric to be realized for bats. We used the PAMGuard toolbox including its new deep learning classification module to test the performance of four open-source workflows for automated analyses of acoustic datasets from bats. Each workflow used a different initial detection algorithm followed by the same deep learning classification algorithm and was evaluated against the performance of an expert manual analyst. Workflow performance depended strongly on the signal-to-noise ratio and detection algorithm used: the full deep learning workflow had the best classification accuracy (≤67%) but was computationally too slow for practical large-scale bat PAM. Workflows using PAMGuard's detection module or triggers onboard an SM4BAT or AudioMoth accurately classified up to 47%, 59% and 34%, respectively, of calls to species. Not all workflows included noise sampling critical to estimating changes in detection probability over time, a vital parameter for abundance estimation. The workflow using PAMGuard's detection module was 40 times faster than the full deep learning workflow and missed as few calls (recall for both ~0.6), thus balancing computational speed and performance. We show that complete acoustic detection and classification workflows for bat PAM data can be efficiently automated using open-source software such as PAMGuard and exemplify how detection choices, whether pre- or post-deployment, hardware or software-driven, affect the performance of deep learning classification and the downstream ecological information that can be extracted from acoustic recordings. In particular, understanding and quantifying detection/classification accuracy and the probability of detection are key to avoid introducing biases that may ultimately affect the quality of data for ecological management.Publisher PDFPeer reviewe

Resting Metabolic Rate Does Not Change in Response to Different Types of Training in Subjects with Type 2 Diabetes

Background and objectivesAmbiguous results have been reported regarding the effects of training on resting metabolic rate (RMR), and the importance of training type and intensity is unclear. Moreover, studies in subjects with type 2 diabetes (T2D) are sparse. In this study, we evaluated the effects of interval and continuous training on RMR in subjects with T2D. Furthermore, we explored the determinants for training-induced alterations in RMR.MethodsData from two studies, both including T2D subjects, were encompassed in this manuscript. Study 1 was a randomized, crossover study where subjects (n = 14) completed three, 2-week interventions [control, continuous walking training (CWT), interval-walking training (IWT)] separated by washout periods. Training included 10 supervised treadmill sessions, 60 min/session. CWT was performed at moderate walking speed [aiming for 73% of walking peak oxygen uptake (VO2peak)], while IWT was performed as alternating 3-min repetitions at slow (54% VO2peak) and fast (89% VO2peak) walking speed. Study 2 was a single-arm training intervention study where subjects (n = 23) were prescribed 12 weeks of free-living IWT (at least 3 sessions/week, 30 min/session). Before and after interventions, RMR, physical fitness, body composition, and glycemic control parameters were assessed.ResultsNo overall intervention-induced changes in RMR were seen across the studies, but considerable inter-individual differences in RMR changes were seen in Study 2. At baseline, total body mass (TBM), fat-free mass (FFM), and fat mass were all associated with RMR. Changes in RMR were associated with changes in TBM and fat mass, and subjects who decreased body mass and fat mass also decreased their RMR. No associations were seen between changes in physical fitness, glycemic control, or FFM and changes in RMR.ConclusionNeither short-term continuous or interval-type training, nor longer term interval training affects RMR in subjects with T2D when no overall changes in body composition are seen. If training occurs concomitant with a reduction in fat mass, however, RMR is decreased.Clinical Trials Registration (www.ClinicalTrials.gov)NCT02320526 and NCT02089477

Effect of ecological momentary assessment, goal-setting and personalized phone-calls on adherence to interval walking training using the InterWalk application among patients with type 2 diabetes-A pilot randomized controlled trial

<div><p>Objectives</p><p>The objective was to investigate the feasibility and usability of electronic momentary assessment, goal-setting and personalized phone-calls on adherence to a 12-week self-conducted interval walking training (IWT) program, delivered by the InterWalk smartphone among patients with type 2 diabetes (T2D).</p><p>Methods</p><p>In a two-arm pilot randomized controlled trial (Denmark, March 2014 to February 2015), patients with T2D (18–80 years with a Body Mass Index of 18 and 40 kg/m2) were randomly allocated to 12 weeks of IWT with (experimental) or without additional support (control). The primary outcome was the difference between groups in accumulated time of interval walking training across 12 weeks. All patients were encouraged to use the InterWalk application to perform IWT for ≥90 minute/week. Patients in the experimental group made individual goals regarding lifestyle change. Once a week inquiries about exercise adherence was made using an ecological momentary assessment (EMA). In case of consistent self-reported non-adherence, the patients would receive a phone-call inquiring about the reason for non-adherence. The control group did not receive additional support. Information about training adherence was assessed objectively. Usability of the EMA was assessed based on response rates and self-reported satisfaction after 12-weeks.</p><p>Results</p><p>Thirty-seven patients with T2D (66 years, 65% female, hemoglobin 1Ac 50.3 mmol/mol) where included (n = 18 and n = 19 in experimental and control group, respectively). The retention rate was 83%. The experimental group accumulated [95%CI] 345 [-7, 698] minutes of IWT more than the control group. The response rate for the text-messages was 83% (68% for males and 90% for females). Forty-one percent of the experimental and 25% of the control group were very satisfied with their participation.</p><p>Conclusion</p><p>The combination inquiry about adherence using EMA, goal-setting with the possibility of follow-up phone calls are considered feasible interventions to attain training adherence when using the InterWalk app during a 12-week period in patients with T2D. Some uncertainty about the effect size of adherence remains.</p><p>Trial registration</p><p>Clinicaltrials.gov <a href="https://clinicaltrials.gov/ct2/show/NCT02089477" target="_blank">NCT02089477</a></p></div

A 2.6-gram sound and movement tag for studying the acoustic scene and kinematics of echolocating bats

This study was supported by the Carlsberg Foundation via a Semper Ardens grant, ONR, N00014-17-1- 2736; AFOSR FA9550-14-1-0398, and NSF NCS-FO:1734744 and a Human Frontiers Science Program Long-Term Fellowship to AS. These experiments were approved by The Danish Council for Experiments on Animals under permit number: 2016-15-0201-00989 and by the Johns Hopkins University Animal Care and Use Committee under protocol number BA17A107. We thank Uwe Firzlaff and Lutz Wiegrebe for their help.1. To study sensorimotor behaviour in wild animals, it is necessary to synchronously record the sensory inputs available to the animal, and its movements. To do this, we have developed a biologging device that can record the primary sensory information and the associated movements during foraging and navigating in echolocating bats. 2. This 2.6 -gram tag records the sonar calls and echoes from an ultrasonic microphone, while simultaneously sampling fine-scale movement in three dimensions from wideband accelerometers and magnetometers. In this study, we tested the tag on an European noctula (Nyctalus noctula) during target approaches and on four big brown bats (Eptesicus fuscus) during prey interception in a flight room. 3. We show that the tag records both the outgoing calls and echoes returning from objects at biologically relevant distances. Inertial sensor data enables the detection of behavioural events such as flying, turning, and resting. In addition, individual wing-beats can be tracked and synchronized to the bat's sound emissions to study the coordination of different motor events. 4. By recording the primary acoustic flow of bats concomitant with associated behaviours on a very fine time-scale, this type of biologging method will foster a deeper understanding of how sensory inputs guide feeding behaviours in the wild.PostprintPeer reviewe

International Circumpolar Surveillance System for Invasive Pneumococcal Disease, 1999–2005

Disease rates are high among indigenous persons in Arctic countries, and PCV7 has resulted in decreased rates in North American children

Active Control of Acoustic Field-of-View in a Biosonar System

Echolocating bats can actively change the area scanned by their biosonar sensory system (“field of view”), and they do so according to the complexity of the environment and depending on the distance to the target