Total Number Of Detections Research Articles

When enough is enough: Optimising monitoring effort for large-scale wolf population size estimation in the Italian Alps.

The ongoing expansion of wolf (Canis lupus) populations in Europe has led to a growing demand for up-to-date abundance estimates. Non-invasive genetic sampling (NGS) is now widely used to monitor wolves, as it allows individual identification and abundance estimation without physically capturing individuals. However, NGS is resource-intensive, partly due to the elusive behaviour and wide distribution of wolves, as well as the cost of DNA analyses. Optimisation of sampling strategies is therefore a requirement for the long-term sustainability of wolf monitoring programs. Using data from the 2020-2021 Italian Alpine wolf monitoring, we investigate how (i) reducing the number of samples genotyped, (ii) reducing the number of transects, and (iii) reducing the number of repetitions of each search transect impacted spatial capture-recapture population size estimates. Our study revealed that a 25% reduction in the number of transects or, alternatively, a 50% reduction in the maximum number of repetitions yielded abundance estimates comparable to those obtained using the entire dataset. These modifications would result in a 2046 km reduction in total transect length and 19,628 km reduction in total distance searched. Further reducing the number of transects resulted in up to 15% lower and up to 17% less precise abundance estimates. Reducing only the number of genotyped samples led to higher (5%) and less precise (20%) abundance estimates. Randomly subsampling genotyped samples reduced the number of detections per individual, whereas subsampling search transects resulted in a less pronounced decrease in both the total number of detections and individuals detected. Our work shows how it is possible to optimise wolf monitoring by reducing search effort while maintaining the quality of abundance estimates, by adopting a modelling framework that uses a first survey dataset. We further provide general guidelines on how to optimise sampling effort when using spatial capture-recapture in large-scale monitoring programmes.

A Complementary Fusion-Based Multimodal Non-Destructive Testing and Evaluation Using Phased-Array Ultrasonic and Pulsed Thermography on a Composite Structure.

Combinative methodologies have the potential to address the drawbacks of unimodal non-destructive testing and evaluation (NDT & E) when inspecting multilayer structures. The aim of this study is to investigate the integration of information gathered via phased-array ultrasonic testing (PAUT) and pulsed thermography (PT), addressing the challenges posed by surface-level anomalies in PAUT and the limited deep penetration in PT. A center-of-mass-based registration method was proposed to align shapeless inspection results in consecutive insertions. Subsequently, the aligned inspection images were merged using complementary techniques, including maximum, weighted-averaging, depth-driven combination (DDC), and wavelet decomposition. The results indicated that although individual inspections may have lower mean absolute error (MAE) ratings than fused images, the use of complementary fusion improved defect identification in the total number of detections across numerous layers of the structure. Detection errors are analyzed, and a tendency to overestimate defect sizes is revealed with individual inspection methods. This study concludes that complementary fusion provides a more comprehensive understanding of overall defect detection throughout the thickness, highlighting the importance of leveraging multiple modalities for improved inspection outcomes in structural analysis.

Swimming behaviour of Atlantic salmon kelts migrating past a hydropower plant dam: Effects of hydraulics and dam operations

Hydropower plants commonly impede the downstream migration of Atlantic salmon (Salmo salar) kelts. Thus, understanding the effects of hydraulic conditions on kelt behaviour and passage performance at dams is crucial for developing effective mitigation measures. In this study, we investigated the influence of hydraulic conditions on kelt passage performance and swimming behaviour at a Norwegian hydropower plant. We combined biological data from 48 kelts collected via acoustic telemetry with hydraulic data modelled using computational fluid dynamics. We assessed kelt passage performance using metrics such as time-to-pass, total number of detections, and total number of detections per day. Additionally, we analysed swimming depths and speeds in relation to the hydraulic conditions created by different dam operating conditions. We found that the dam operation schedule impacted the kelts' ability to find a route past the dam. Though kelts could have passed the dam throughout the study period via a submerged pipe at the dam (which had seemingly sufficient discharge for the kelts to find), 98 % of the kelts instead waited for a spill gate to open partway through the study period. The swimming depth analysis indicated diel variation, with kelts swimming nearer to the water surface during the night. We found that swimming speed increased with increasing kelt body length, particularly under high turbulence kinetic energy and during the day. Furthermore, kelts swam faster as water velocity increased, but slowed down again as turbulence intensity increased. Our findings reveal the effects of hydraulic conditions and dam operations on the migration behaviour of Atlantic salmon kelts. This provides valuable insights for developing strategies to optimise dam operations and improve fish passage performance, including the need to spill enough water to increase passage success and will contribute to sustainable management of Atlantic salmon populations in regulated rivers.

BreathFinder: A Method for Non-Invasive Isolation of Respiratory Cycles Utilizing the Thoracic Respiratory Inductance Plethysmography Signal.

The field of automatic respiratory analysis focuses mainly on breath detection on signals such as audio recordings, or nasal flow measurement, which suffer from issues with background noise and other disturbances. Here we introduce a novel algorithm designed to isolate individual respiratory cycles on a thoracic respiratory inductance plethysmography signal using the non-invasive signal of the respiratory inductance plethysmography belts. The algorithm locates breaths using signal processing and statistical methods on the thoracic respiratory inductance plethysmography belt and enables the analysis of sleep data on an individual breath level. The algorithm was evaluated against a cohort of 31 participants, both healthy and diagnosed with obstructive sleep apnea. The dataset consisted of 13 female and 18 male participants between the ages of 20 and 69. The algorithm was evaluated on 7.3 hours of hand-annotated data from the cohort, or 8782 individual breaths in total. The algorithm was specifically evaluated on a dataset containing many sleep-disordered breathing events to confirm that it did not suffer in terms of accuracy when detecting breaths in the presence of sleep-disordered breathing. The algorithm was also evaluated across many participants, and we found that its accuracy was consistent across people. Source code for the algorithm was made public via an open-source Python library. The proposed algorithm achieved an estimated 94% accuracy when detecting breaths in respiratory signals while producing false positives that amount to only 5% of the total number of detections. The accuracy was not affected by the presence of respiratory related events, such as obstructive apneas or snoring. This work presents an automatic respiratory cycle algorithm suitable for use as an analytical tool for research based on individual breaths in sleep recordings that include respiratory inductance plethysmography.

E-APK: Energy pattern detection in decompiled android applications

Energy efficiency is a non-functional requirement that developers must consider, particularly when building software for battery-operated devices like mobile ones: a long-lasting battery is an essential requirement for an enjoyable user experience. In previous studies, it has been shown that many mobile applications include inefficiencies that cause battery to be drained faster than necessary. Some of these inefficiencies result from software patterns that have been catalogued, and for which more energy-efficient alternatives are also known. The existing catalogues, however, assume as a fundamental requirement that one has access to the source code of an application in order to be able to analyse it. This requirement makes independent energy analysis challenging, or even impossible, e.g. for a mobile user or, most significantly, an App Store trying to provide information on how efficient an application being submitted for publication is. We study the viability of looking for known energy patterns in applications by decompiling them and analysing the resulting code. For this, we decompiled and analysed 420 open-source applications by extending an existing tool, which is now capable of transparently decompiling and analysing android applications. With the collected data, we performed a comparative study of the presence of four energy patterns between the source code and the decompiled code. We performed two types of analysis: (i) comparing the total number of energy pattern detections; (ii) comparing the similarity between energy pattern detections. When comparing the total number of detections in source code against decompiled code, we found that 79.29% of the applications reported the same number of energy pattern detections. To test the similarity between source code and APKs, we calculated, for each application, a similarity score based on our four implemented detectors. Of all applications, 35.76% achieved a perfect similarity score of 4, and 89.40% got a score of 3 or more out of 4. Furthermore, only two applications got a score of 0. When viewed in tandem, the results of the two analyses we performed point in a promising direction. They provide initial evidence that static analysis techniques, typically used in source code, can be a viable method to inspect APKs when access to source code is restricted, and further research in this area is worthwhile.

Prompt Detection of Fast Optical Bursts with the Vera C. Rubin Observatory

The transient optical sky has remained largely unexplored on very short timescales. While there have been some experiments searching for optical transients from minutes to years, none have had the capability to distinguish millisecond fast optical bursts (FOBs). Such very fast transients could be the optical counterparts of fast radio bursts, the prompt emission from γ-ray bursts, or other previously unknown phenomena. Here, we investigate a novel approach to the serendipitous detection of FOBs, which relies on searching for anomalous spatial images. In particular, due to their short duration, the seeing-distorted images of FOBs should look characteristically different than those of steady sources in a standard optical exposure of finite duration. We apply this idea to simulated observations with the Vera C. Rubin Observatory, produced by tracing individual photons through a turbulent atmosphere, and down through the optics and camera of the Rubin telescope. We compare these simulated images to steady-source star simulations in 15 s integrations, the nominal Rubin exposure time. We report the classification accuracy results of a neural network classifier for distinguishing FOBs from steady sources. From this classifier, we derive constraints in duration–intensity parameter space for unambiguously identifying FOBs in Rubin observations. We conclude with estimates of the total number of detections of FOB counterparts to FRBs expected during the 10 yr Rubin Legacy Survey of Space and Time.

Research on the application of neural network based external location element settlement method in object location of geographic information

BackgroundGeographical information about human settlements is necessary to facilitate humanitarian aid, recognize the location of real-world objects, support local development and improve disaster resilience in settlements. Although deep learning is employed in object location in settlements, these models have computational complexity and less detection accuracy. Hence they require further development with regards to precision in object location from geographic data. ObjectiveTo efficiently identify the object location in Chinese settlements from geographic information, we proposed Artificial Neural Network (ANN) optimized by Red Fox (RF) optimization (ANN-RF) model in this research. MethodsThe multi-resolution Geographic information data was collected from Tongzhou District, Beijing, China. ANN applies the measures of length, area, distance and direction to recognize object location from this data. An RF algorithm is used to optimize the weight vector of the ANN architecture to improve the efficiency of the ANN architecture. The parameters such as precision, recall, F1-score, number of correct detections, overall actual matches and the total number of detections were computed for the proposed model. ResultsThe precision rate and F1-score for the proposed ANN based RF optimization are about 98.9% and 97.5% which are higher than that of conventional models. ConclusionThe proposed ANN-RF model shows promising results in detecting object location in settlements from geographic information.

Large Interferometer For Exoplanets (LIFE)

Context.One of the long-term goals of exoplanet science is the atmospheric characterization of dozens of small exoplanets in order to understand their diversity and search for habitable worlds and potential biosignatures. Achieving this goal requires a space mission of sufficient scale that can spatially separate the signals from exoplanets and their host stars and thus directly scrutinize the exoplanets and their atmospheres.Aims.We seek to quantify the exoplanet detection performance of a space-based mid-infrared (MIR) nulling interferometer that measures the thermal emission of exoplanets. We study the impact of various parameters and compare the performance with that of large single-aperture mission concepts that detect exoplanets in reflected light.Methods.We have developed an instrument simulator that considers all major astrophysical noise sources and coupled it with Monte Carlo simulations of a synthetic exoplanet population around main-sequence stars within 20 pc of the Sun. This allows us to quantify the number (and types) of exoplanets that our mission concept could detect. Considering single visits only, we discuss two different scenarios for distributing 2.5 yr of an initial search phase among the stellar targets. Different apertures sizes and wavelength ranges are investigated.Results.An interferometer consisting of four 2 m apertures working in the 4–18.5 μ.m wavelength range with a total instrument throughput of 5% could detect up to ≈550 exoplanets with radii between 0.5 and 6R⊕with an integratedS/N≥ 7. At least ≈160 of the detected exoplanets have radii ≤1.5R⊕. Depending on the observing scenario, ≈25–45 rocky exoplanets (objects with radii between 0.5 and 1.5R⊕) orbiting within the empirical habitable zone (eHZ) of their host stars are among the detections. With four 3.5 m apertures, the total number of detections can increase to up to ≈770, including ≈60–80 rocky eHZ planets. With four times 1 m apertures, the maximum detection yield is ≈315 exoplanets, including ≤20 rocky eHZ planets. The vast majority of small, temperate exoplanets are detected around M dwarfs. The impact of changing the wavelength range to 3–20 μm or 6–17 μm on the detection yield is negligible.Conclusions.A large space-based MIR nulling interferometer will be able to directly detect hundreds of small, nearby exoplanets, tens of which would be habitable world candidates. This shows that such a mission can compete with large single-aperture reflected light missions. Further increasing the number of habitable world candidates, in particular around solar-type stars, appears possible via the implementation of a multi-visit strategy during the search phase. The high median S/N of most of the detected planets will allow for first estimates of their radii and effective temperatures and will help prioritize the targets for a second mission phase to obtain high-S/N thermal emission spectra, leveraging the superior diagnostic power of the MIR regime compared to shorter wavelengths.

Improved sensitivity for space domain awareness observations with the murchison widefield array

Our previously reported survey of the Low Earth Orbit (LEO) environment using the Murchison Widefield Array (MWA) detected over 70 unique Resident Space Objects (RSOs) over multiple passes, from 20 h of observations in passive radar mode. In this paper, we extend this work by demonstrating two methods that improve the detection sensitivity of the system. The first method, called shift-stacking, increases the statistical significance of faint RSO signals through the spatially coherent integration of the reflected signal along the RSO’s trajectory across the sky. This method was tested on the observations used during our previous blind survey, and we obtained a 75% increase in the total number of detections. The second method re-focuses the MWA to the near-field RSO’s position (post-observation), by applying a complex phase correction to each visibility to account for the curved wave-front. The method was tested successfully on an MWA extended array observation of an ISS pass. However, the method is currently limited by signal de-coherence on the long-baselines (due to the hardware constraints of the current correlator). We discuss the sensitivity improvement for RSO detections we expect from the MWA Phase 3 correlator upgrade. We conclude the paper by briefly commenting on future dedicated Space Domain Awareness (SDA) systems that will incorporate MWA technologies.

663. Two (Plus) Birds, One Stone: The Rapid, Comprehensive, Non-invasive Detection of Co-Pathogens of Critical Importance Using A Plasma-based Microbial Cell-free DNA Next-generation Sequencing Test

BackgroundImmunocompromised (IC) patients are at risk for infections by a spectrum of invasive pathogens. The overlap in presentation makes it challenging to differentiate among infectious etiologies and critical co-infections (CI) may remain undiagnosed. Open-ended, comprehensive assessment of infection through microbial cell-free DNA (mcfDNA) next-generation sequencing (NGS) of plasma offers the potential for the rapid identification of multiple co-infecting pathogens of critical importance (CI-POCI) with one test.MethodsKarius TestTM (KT) results from patients who underwent clinical testing from December 2016 to April 2021 were reviewed for detections of two or more CI-POCI including parasites, fungi (Pneumocystis jirovecii, Trichosporon sp, endemic mycoses, Aspergillus sp., Mucorales, Non-Aspergillus/Non-Mucorales molds), mycobacteria, Legionella sp., Nocardia sp. and Listeria. KT, developed and validated in Karius’ CLIA certified/CAP accredited lab, detects mcfDNA from plasma. McfDNA is extracted, NGS performed, human sequences removed and remaining sequences aligned to a curated pathogen database of > 1500 organisms. Organisms present above a statistical threshold are reported and quantified. For > 85% of tests the time to result reporting is the next day from sample receipt.ResultsKT detected CI of two or more POCI in 59 samples (75% adults, 25% children). The most common partnering co-pathogens of critical importance were Aspergillus sp (38), Mucorales (17) and PJP (14); the most common combinations were two or more distinct Aspergillus sp (14) followed by an Aspergillus sp and a Mucorales (12). There were 17 samples with the detection of three or more CI-POCI (29%). Figure 1. Chord Plot of Co-infections with Pathogens of Critical Importance The outer circle sections represent Karius Test detections belonging to different taxonomic groups. The length of each circle section is proportional to the total number of detections of a taxon belonging to that group. The chords connecting a pair of circle sections are proportional to the number of times two taxa from those groups were observed together, weighted by the total number of taxa detected.ConclusionPlasma mcfDNA NGS offers a rapid, comprehensive non-invasive means of detecting CI-POCI in IC patients with one test. Although rare, co-infections with POCI can greatly increase mortality. The KT can provide important insights into pathogen-pathogen interactions in complex hosts and help optimize therapy.Disclosures Matthew Smollin, PharmD, Karius, Inc. (Employee) Martin S. Lindner, PhD, Karius, Inc. (Consultant) Nicholas R. Degner, MD, MPH, MS, Karius Inc. (Employee, Shareholder) Ricardo Castillo-Galvan, MD MPH, Karius Inc. (Consultant) Jose Alexander, MD, D(ABMM), FCCM, CIC, SM, MB(ASCP), BCMAS, Karius (Employee) Ann Macintyre, DO, Karius, Inc. (Employee) Bradley Perkins, MD, Karius, Inc. (Employee) Asim A. Ahmed, MD, Karius, Inc. (Employee) Aparna Arun, MD, Karius (Employee)

Identifying Periodic Variable Stars and Eclipsing Binary Systems with Long-term Las Cumbres Observatory Photometric Monitoring of ZTF J0139+5245

Abstract We present the results of our search for variable stars using the long-term Las Cumbres Observatory (LCO) monitoring of white dwarf ZTF J0139+5245 with the two 1.0 m telescope nodes located at McDonald Observatory using the Sinistro imaging instrument. In this search, we find 38 variable sources, of which 27 are newly discovered or newly classified (71%) based on comparisons with previously published catalogs, thereby increasing the number of detections in the field of view under consideration by a factor of ≈2.5. We find that the improved photometric precision per exposure due to longer exposure time for LCO images combined with the greater time sampling of LCO photometry enables us to increase the total number of detections in this field of view. Each LCO image covers a field of view of 26′ × 26′ and observes a region close to the Galactic plane (b = −9.°4) abundant in stars with an average stellar density of ≈8 arcmin−2. We perform aperture photometry and Fourier analysis on over 2000 stars across 1560 LCO images spanning 537 days to find 28 candidate BY Draconis variables, three candidate eclipsing binaries of type EA, and seven candidate eclipsing binaries of type EW. In assigning preliminary classifications to our detections, we demonstrate the applicability of the Gaia color–magnitude diagram as a powerful classification tool for variable-star studies.

A Bayesian Filter for Multi-View 3D Multi-Object Tracking With Occlusion Handling.

This paper proposes an online multi-camera multi-object tracker that only requires monocular detector training, independent of the multi-camera configurations, allowing seamless extension/deletion of cameras without retraining effort. The proposed algorithm has a linear complexity in the total number of detections across the cameras, and hence scales gracefully with the number of cameras. It operates in the 3D world frame, and provides 3D trajectory estimates of the objects. The key innovation is a high fidelity yet tractable 3D occlusion model, amenable to optimal Bayesian multi-view multi-object filtering, which seamlessly integrates, into a single Bayesian recursion, the sub-tasks of track management, state estimation, clutter rejection, and occlusion/misdetection handling. The proposed algorithm is evaluated on the latest WILDTRACKS dataset, and demonstrated to work in very crowded scenes on a new dataset.

Comparing the efficacy and cost-effectiveness of sampling methods for estimating population abundance and density of a recovering carnivore: the European pine marten (Martes martes)

Many methods are available to gather data on wildlife population parameters, such as population abundance and density, yet few have been compared or validated. We compared the efficacy of three survey methods (live trapping, hair tubes and scats) for estimating abundance and population density of the European pine marten (Martes martes) in Galloway Forest, Scotland. We evaluated these methods by, firstly, comparing the accuracy of the population estimate derived from each method, and, secondly, comparing the financial cost of each method. Molecular analysis of samples from all three methods was used to determine sex and individual genotype. Population abundance estimates were derived from capture-recapture programme Capwire. The non-invasive methods (hair tubes and scats combined) detected 81% of known individuals, although hair tubes and scats performed poorly alone, detecting 48% and 52% of individuals, respectively. Live trapping was the individual method that detected the most individuals (77%). Hair tubes were the most expensive method, both in financial cost and personnel hours, whilst scat sampling was the cheapest method. There was a highly significant association between the sex of the animal and the total number of detections by method. The population abundance estimate from all methods combined was 32 (95% CI 31–35) and the population density estimate was 0.27 martens/km2. This study indicates that a combined sampling approach comprising hair tubes and scats maximises the number of detections and provides a viable alternative to invasive live trapping.

An algorithm based on logistic regression with data fusion in wireless sensor networks

A decision fusion rule using the total number of detections reported by the local sensors for hypothesis testing and the total number of detections that report “1” to the fusion center (FC) is studied for a wireless sensor network (WSN) with distributed sensors. A logistic regression fusion rule (LRFR) is formulated. We propose the logistic regression fusion algorithm (LRFA), in which we train the coefficients of the LRFR, and then use the LRFR to make a global decision about the presence/absence of the target. Both the fixed and variable numbers of decisions received by the FC are examined. The fusion rule of K out of N and the counting rule are compared with the LRFR. The LRFA does not depend on the signal model and the priori knowledge of the local sensors’ detection probabilities and false alarm rate. The numerical simulations are conducted, and the results show that the LRFR improves the performance of the system with low computational complexity.

A Comparison of Four Survey Methods for Detecting Fox Squirrels in the Southeastern United States

Fox squirrel Sciurus niger populations in the southeastern United States appear to have declined, and 3 (S. n. cinereus, S. n. shermani, and S. n. avicennia) of the 10 subspecies are currently listed with a conservation status of protection. Efforts to conserve and manage fox squirrels in the southeastern United States are constrained by difficulties in studying their populations because of low densities and low detectability. There is a need for an effective survey method to fill knowledge gaps on southeastern fox squirrel ecology. To address this need and to identify a cost-effective and reliable technique to survey and monitor southeastern fox squirrel populations, we compared four survey methods across seasons: live-trapping; camera-trapping; point counts; and line-transect surveys, in regard to whether a detection occurred at a survey point, the total number of detections at a survey point, and the total cost for each method. We assessed the effectiveness of capture and detection methods and the influence of seasonality using generalized linear mixed models. We found camera-trapping to be the most effective survey method for assessing the presence and distribution of southeastern fox squirrels. In total, camera-traps produced significantly more detections (n = 223) of fox squirrels than all other methods combined (n = 84), with most detections occurring in spring (n = 97) and the fewest in the autumn (n = 60). Furthermore, we detected fox squirrels at more survey points with camera-traps (73%) than all other methods (63%), and we identified 16% more individuals from camera-trap photographs than live-trapped. We recommend future monitoring of southeastern fox squirrels to be conducted using camera-trapping during the spring unless handling of animals is needed for other research purposes.

A Comparison of Four Survey Methods for Detecting Fox Squirrels in the Southeastern United States

Abstract Fox squirrel Sciurus niger populations in the southeastern United States appear to have declined, and 3 (S. n. cinereus, S. n. shermani, and S. n. avicennia) of the 10 subspecies are currently listed with a conservation status of protection. Efforts to conserve and manage fox squirrels in the southeastern United States are constrained by difficulties in studying their populations because of low densities and low detectability. There is a need for an effective survey method to fill knowledge gaps on southeastern fox squirrel ecology. To address this need and to identify a cost-effective and reliable technique to survey and monitor southeastern fox squirrel populations, we compared four survey methods across seasons: live-trapping; camera-trapping; point counts; and line-transect surveys, in regard to whether a detection occurred at a survey point, the total number of detections at a survey point, and the total cost for each method. We assessed the effectiveness of capture and detection methods and the influence of seasonality using generalized linear mixed models. We found camera-trapping to be the most effective survey method for assessing the presence and distribution of southeastern fox squirrels. In total, camera-traps produced significantly more detections (n = 223) of fox squirrels than all other methods combined (n = 84), with most detections occurring in spring (n = 97) and the fewest in the autumn (n = 60). Furthermore, we detected fox squirrels at more survey points with camera-traps (73%) than all other methods (63%), and we identified 16% more individuals from camera-trap photographs than live-trapped. We recommend future monitoring of southeastern fox squirrels to be conducted using camera-trapping during the spring unless handling of animals is needed for other research purposes.

Variability in the performance of the spectrogram correlation detector for North-east Pacific blue whale calls

Spectrogram correlation has been used successfully for automatic detection of baleen whale calls. However, applying this method consistently to long time series can be challenging. To illustrate the potential challenges of the automatic detection process, recordings collected in the Southern California Bight between 2007 and 2012 were used for detection of North-east Pacific blue whale (Balaenoptera musculus) B calls. The effects of the following factors were investigated: blue whale B call frequency shift and appropriate kernel modification, seasonal variability in call abundance, analyst variability and noise. Due to intra- and inter-annual changes in the call frequency of blue whale B calls, seasonal and annual adjustments to the call detection kernel were needed. To account for seasonal variability in call production, evaluation of the detector against ground truth data was performed at multiple times during the year. Analyst variability did not affect overall long-term trends in detection, but it had an impact on the total number of detections, as well as call rate estimation. Noise, particularly from shipping, was negatively correlated with detections at hourly time scales. A detailed analysis of variability in the performance of spectrogram correlation detectors should be performed when applying this method to long-term acoustic data-sets.

Oils ain’t oils: can truffle-infused food additives improve detection of rare and cryptic mycophagous mammals?

We tested whether an artificial food additive, truffle oil, improved detection of mycophagous mammals when added to a standard bait type of peanut butter and rolled oats used with camera traps. Sixteen mammalian taxa were subsequently recorded, the most common being antechinus, bush rat (Rattus fuscipes), swamp wallaby (Wallabia bicolor) and long-nosed bandicoot (Perameles nasuta) as well as the long-nosed potoroo (Potorous tridactylus) and southern brown bandicoot (Isoodon obesulus). The only species for which detection rate was improved by the addition of truffle oil to standard bait was the ringtail possum (Pseudocheirus peregrinus), a species that has never been recorded eating fungi. In contrast, the total number of detections of all species at any given site was significantly higher, on average, using standard bait without truffle oil, as was the average number of detections of the partially mycophagous bush rat. Time to first detection of bush rats and swamp wallabies was significantly shorter using the standard bait type, compared with one with truffle oil added. Overall, the use of the truffle oil additive did not improve the chance or rate of detecting mycophagous mammals. To maximise the number of detections of mammals at camera traps the use of a standard bait type of peanut butter and rolled oats is recommended.

(Sub)millimetre interferometric imaging of a sample of COSMOS/AzTEC submillimetre galaxies

We used the PdBI to map a sample of 15 SMGs in the COSMOS field at the wavelength of 1.3 mm. The target SMGs were originally discovered in the JCMT/AzTEC 1.1 mm continuum survey at S/N=4-4.5. This paper presents, for the first time, interferometric millimetre-wavelength observations of these sources. The angular resolution of our observations, 1.8", allowed us to accurately determine the positions of the target SMGs. Using a detection threshold of S/N>4.5 regardless of multiwavelength counterpart association, and 4<S/N<=4.5 if a multiwavelength counterpart within 1.5" is also present, the total number of detections in our survey is 22. Three of our detected SMGs (AzTEC21, 27, and 28; which corresponds to 20%) are marginally resolved at our angular resolution, and these sources are found to have elongated or clumpy morphologies and/or multiple components. Using optical to NIR photometric redshifts, available spectroscopic redshifts, and redshifts estimated from the radio-to-submm spectral index we infer a median redshift of $\tilde{z}=3.20\pm0.25$ for our sample. To study the overall multiplicity and redshift distribution of flux-limited samples of SMGs we combined these sources with the 15 brightest AzTEC SMGs detected at 1.1 mm, AzTEC1-15, and studied previously. This constitutes a complete, flux- and S/N-limited 1.1-mm selected sample. We find that the median redshift for the 15 brightest AzTEC SMGs ($\tilde{z}=3.05\pm0.44$) is consistent with that for AzTEC16-30. This conforms to recent observational findings that SMGs do not exhibit any significant trend between the redshift and (sub)mm flux density. For the combined AzTEC1-30 sample we derive a median redshift of $\tilde{z}=3.17\pm0.27$, consistent with previous results based on mm-selected samples. We further infer that within the combined AzTEC1-30 sample $\sim25\pm9\%$ of sources separate into multiple components.

Fish Movements and Passage Through a Water Control Structure: River Stage and Floodplain Connectivity

The St. John's Bayou water control structure near New Madrid, MO, connects the main Mississippi River to two large backwater areas called the New Madrid Floodway and St. John's Bayou. While this area has been altered, the New Madrid Floodway and St. John's Bayou account for the only substantial portion of the historic Mississippi River floodplain that remains and provides the only critical connection between backwater/floodplain habitat and the river. Fish passage was evaluated during April–December 2010 using ultrasonic telemetry. Stationary receivers were placed strategically at five locations above and below the structure in St. John's Bayou, in the floodway and the outlet to the Mississippi River. A total of 100 individuals representing 14 species were tagged. Total number of detections during an 8-month period was 1 264 717. Fifteen individuals representing five species moved into the Mississippi and Ohio rivers; seven individuals returned to St. John's Bayou. Thirteen of the 14 species moved upstream through the structure. Of the 85 individuals that stayed in the bayou, 29 fish passed through the structure for a total of 92 passage events. The downstream : upstream passage was roughly 50:50. Passage was correlated with river rise, with frequency of passage being higher in spring, but passage occurred each month during the study. Copyright © 2015 John Wiley & Sons, Ltd.