How fishing cats Prionailurus viverrinus Bennett, 1833 fish: describing a felid’s strategy to hunt aquatic prey

The fishing cat’s persistence in a ‘semi-aquatic niche’ suggests the evolution of a successful hunting strategy. We describe it for the first time by analysing 197 camera-trap video-clips, collected from a participatory-science initiative, within an ethogram framework. The cats spent ∼52% of the time sitting and waiting for prey (fishes) to come nearer and took limited attempts to hunt (3.89%) in deeper waters (in which the upper portions of the cat’s body were submerged), where its hunting success was found to be 42.86%. In shallow waters, it adopted a predominantly active mode of hunting (∼96%) to flush out prey.

The Identification of Non-Driving Activities with Associated Implication on the Take-Over Process

In conditionally automated driving, the engagement of non-driving activities (NDAs) can be regarded as the main factor that affects the driver’s take-over performance, the investigation of which is of great importance to the design of an intelligent human–machine interface for a safe and smooth control transition. This paper introduces a 3D convolutional neural network-based system to recognize six types of driver behaviour (four types of NDAs and two types of driving activities) through two video feeds based on head and hand movement. Based on the interaction of driver and object, the selected NDAs are divided into active mode and passive mode. The proposed recognition system achieves 85.87% accuracy for the classification of six activities. The impact of NDAs on the perspective of the driver’s situation awareness and take-over quality in terms of both activity type and interaction mode is further investigated. The results show that at a similar level of achieved maximum lateral error, the engagement of NDAs demands more time for drivers to accomplish the control transition, especially for the active mode NDAs engagement, which is more mentally demanding and reduces drivers’ sensitiveness to the driving situation change. Moreover, the haptic feedback torque from the steering wheel could help to reduce the time of the transition process, which can be regarded as a productive assistance system for the take-over process.

Radar imaging complex with SAR and ASR for aerospace vechicle

The subject of this study in the article is the algorithms for radio monitoring of the Earth in various views from aerospace transport. The goal is to design a structural diagram of a radio complex that can operate simultaneously in two modes: modified antenna aperture synthesis (SAR) and aperture synthesis (RAS), in accordance with algorithms synthesized using the maximum likelihood method. The modified SAR mode allows obtaining high-resolution radio images in the observation angle range ±(20°...50°) from the direction to the nadir. A method for combining a modified PCA algorithm is used, which differs from the classical imaging algorithm by the possibility of obtaining a higher spatial resolution, the payment for this is the complication of the signal processing algorithm associated with the implementation of decorrelating filters that expand the spectrum of received signals in each receiving path, and the RAS mode, which allows imaging using passive or active radar principles. The passive RAS mode provides for the imaging in the observation angle range of ±20° from the nadir based on the results of processing signals of its own broadband radio-thermal radiation, and active mode – in the same observation angle range, but using the broadband noise signal of the backlight. An important result in the formation of a radio image in the specified viewing area when using the active mode of the RAS is that the images are close in physical content, namely, proportional to the specific effective reflection surface of the underlying surface. Additionally, a distinctive feature of the synthesized algorithms is the use of wideband probing signals and, accordingly, the same input paths of receivers, which makes it possible to increase the signal-to-noise ratio of the output effect. Conclusions. The scientific novelty of the results obtained is as follows: a structural diagram of the radio complex was developed on the basis of algorithms synthesized using the maximum likelihood method. For the formation of a radio image in the radio complex, a combination of SAR and RAS (with two modes of operation) is implemented. This implementation is important, since it allows obtaining high-resolution images in the observation angle range of ±50° from the direction to the nadir. It is advisable to place the complex on airplanes, helicopters and spacecraft (preferably those that move in low orbits)

A Near-Zero Power Triboelectric Wake-Up System for Autonomous Beaufort Scale of Wind Force Monitoring

Beaufort scale of wind force monitoring is the basic content of meteorological monitoring, which is an important means to ensure the safety of production and life by timely warning of natural disasters. As there is a limited battery life for sensors, determining how to reduce power consumption and extend system life is still an urgent problem. In this work, a near-zero power triboelectric wake-up system for autonomous Beaufort scale of wind force monitoring is proposed, in which a rotary TENG is used to convert wind energy into a stored electric energy capacitor. When the capacitor voltage accumulates to the threshold voltage of a transistor, it turns on as an electronic switch and the system wakes up. In active mode, the Beaufort scale of wind force can be judged according to the electric energy and the signal is sent out wirelessly. In standby mode, when there is no wind, the power consumption of the system is only 14 nW. When the wind scale reaches or exceeds light air, the system can switch to active mode within one second and accurately judge the Beaufort scale of wind force within 10 s. This work provided a triboelectric sensor-based wake-up system with ultralow static power consumption, which has great prospects for unattended environmental monitoring, hurricane warning, and big data acquisition.

Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit

Background: Using machine learning to combine wrist accelerometer (ACM) and electrodermal activity (EDA) has been shown effective to detect primarily and secondarily generalized tonic-clonic seizures, here termed as convulsive seizures (CS). A prospective study was conducted for the FDA clearance of an ACM and EDA-based CS-detection device based on a predefined machine learning algorithm. Here we present its performance on pediatric and adult patients in epilepsy monitoring units (EMUs).Methods: Patients diagnosed with epilepsy participated in a prospective multi-center clinical study. Three board-certified neurologists independently labeled CS from video-EEG. The Detection Algorithm was evaluated in terms of Sensitivity and false alarm rate per 24 h-worn (FAR) on all the data and on only periods of rest. Performance were analyzed also applying the Detection Algorithm offline, with a less sensitive but more specific parameters configuration (“Active mode”).Results: Data from 152 patients (429 days) were used for performance evaluation (85 pediatric aged 6–20 years, and 67 adult aged 21–63 years). Thirty-six patients (18 pediatric) experienced a total of 66 CS (35 pediatric). The Sensitivity (corrected for clustered data) was 0.92, with a 95% confidence interval (CI) of [0.85-1.00] for the pediatric population, not significantly different (p > 0.05) from the adult population's Sensitivity (0.94, CI: [0.89–1.00]). The FAR on the pediatric population was 1.26 (CI: [0.87–1.73]), higher (p < 0.001) than in the adult population (0.57, CI: [0.36–0.81]). Using the Active mode, the FAR decreased by 68% while reducing Sensitivity to 0.95 across the population. During rest periods, the FAR's were 0 for all patients, lower than during activity periods (p < 0.001).Conclusions: Performance complies with FDA's requirements of a lower bound of CI for Sensitivity higher than 0.7 and of a FAR lower than 2, for both age groups. The pediatric FAR was higher than the adult FAR, likely due to higher pediatric activity. The high Sensitivity and precision (having no false alarms) during sleep might help mitigate SUDEP risk by summoning caregiver intervention. The Active mode may be advantageous for some patients, reducing the impact of the FAR on daily life. Future work will examine the performance and usability outside of EMUs.

Phase stable swept-source optical coherence tomography with active mode-locking laser for contrast enhancements of retinal angiography

Swept-source optical coherence tomography (SS-OCT) is an attractive high-speed imaging technique for retinal angiography. However, conventional swept lasers vary the cavity length of the laser mechanically to tune the output wavelength. This causes sweep-timing jitter and hence low phase stability in OCT angiography. Here, we improve an earlier phase-stabilized, akinetic, SS-OCT angiography (OCTA) method by introducing coherent averaging. We develop an active mode-locking (AML) laser as a high phase-stable akinetic swept source for the OCTA system. The phase stability of the improved system was analyzed, and the effects of coherent averaging were validated using a retina phantom. The effectiveness of the coherent averaging method was further confirmed by comparing coherently and conventionally averaged en face images of human retinal vasculature for their contrast-to-noise ratio, signal-to-noise ratio, and vasculature connectivity. The contrast-to-noise ratio was approximately 1.3 times larger when applying the coherent averaging method in the human retinal experiment. Our coherent averaging method with the high phase-stability AML laser source for OCTA provides a valuable tool for studying healthy and diseased retinas.