Miracle-dz/UniFAR-FTUs huggingface dataset:
Habitat utilization and prey selection of the kestrel Falco tinnunculus in relation to small mammal abundance

The study examined habitat utilization and prey selection by the kestrel Falco tinnunculus in an area of cultivated farmland in Italy, along with field estimates of small mammal abundance. Kestrel males were radiotagged and ranging behaviour and diet were recorded. Kestrels actively selected grasslands both during flight and perching hunting, and most predations were registered in this habitat. The occurrence of small mammals in the diet was significantly different from what was estimated from trapping, indicating that kestrels behaved as selective predators, since microtines were eaten in a greater proportion than their abundance. Microtus savii was preferred more than the common vole Microtus arvalis, whereas soricids were negatively selected. Nevertheless, common voles represented the main component of the kestrels' food niche. Reproductive success was correlated with small mammal availability. This study revealed that the high density of kestrels within the study area is supported by steady grassland management.
Research Digest

If there is one brain region that has been promoted as the “centre” for emotion in recent years, it is the amygdala. This focus has been primarily because of a comprehensive series of findings begun from the work of LeDoux, and it has led to something of a reification of this brain structure. LeDoux (1996) himself has always been careful to point out that his work focuses only on one emotion (fear) and, indeed, only one aspect of fear (its memorial role in fear conditioning), but this appears not to have stopped others from assuming that the amygdala is where emotion happens. The regular activation of the amygdala in functional imaging investigations of emotion has confirmed this view. There have been others (notably Panksepp, 1998) who have pointed out that there is a range of other brain regions that appear to be engaged in emotion, that fear does not rely only on the amygdala, and, indeed, that electrical stimulation of many other brain areas produces even more intense fearful responses. Perhaps, it has been argued, the amygdala is involved only in the memorial aspects of fear, and other subcortical structures are central for the subjective experience of fear. However, this conclusion has been derived largely from work on animals and has awaited the systematic evaluation of subjective experience in humans. Because investigating subjective affective states remains (strangely enough) of low priority for many emotion researchers, we have waited for some time for a clear answer: this is now offered by the Anderson & Phelps and the Zald papers. Their data show that patients with amygdala damage—left, right, and bilateral—continue to experience subjective feelings of fear on a range of measures. It has taken emotion researchers a long time to do the first thing that a science of subjective experience (such as psychoanalysis) might have done on day one: ask the patient how he/she feels. Nevertheless, it is now clear that “the complexity and richness of human emotional life do not appear to be supported by the amygdala alone” (Anderson & Phelps, p. 717), and that “the human amygdala is neither necessary to consciously evaluate and report subjective emotional experiences, nor is it necessary for the more general subjective experience of affective states” (Zald, p. 113). There are many other brain regions that are known to play a role in emotional states, but we have yet to question what their precise role is in affective experience. We can now start the long process of establishing exactly what their contribution might be.
TEPLITS: A comprehensive Test Platform for Intelligent Transportation Systems

The introduction of Vehicle-to-Everything (V2X) communication has enormously extended the spectrum of Advanced Driver Assistance Systems (ADAS) in the past years. This development has come along with an increasing demand for test facilities. However, the number of new systems and interconnected nodes makes testing with real test vehicles costly and time consuming. For this reason virtual test drives have risen as a promising pre-filter for the final testing in real test facilities. To be effective and have a high validity, these virtual test drives need to be as close to reality as possible. Especially for connected safety-critical applications, such as platooning, all components (environment, traffic, vehicle dynamics, sensor systems, positioning and communication) must to be modeled accurately. In the work at hand, a simulation framework based on the middleware platform Robot Operating System (ROS) coupled with the vehicle dynamics simulator CarMaker is extended by the Global Navigation Satellite System (GNSS) simulator Spirent. A proof of concept is offered in terms of a simple performance evaluation of Cooperative Positioning (CP). CP allows vehicles to share raw GNSS measurements with their neighbors by means of V2X communications to increase availability, integrity and accuracy of their positioning. The proof of concept focuses on the latter and shows that it can be considerably enhanced by means of CP.
Morphological and physiological differences of the auditory system in three related bushcrickets (Orthoptera: Phaneropteridae, Poecilimon)

Abstract. The auditory system of three closely related bushcrickets was investigated with respect to morphological and physiological differences. The size of the acoustic vesicle in the prothorax cavity and the size of the acoustic spiracle were compared to differences in auditory tuning of the tympanic nerve and differences in the directionality. The results indicate that a small auditory vesicle and auditory spiracle provide reduced sensitivity in the high frequency range (above 10—15 kHz), but increase sensitivity at low frequencies (below 10 kHz). The directionality of the hearing system deteriorates at frequencies between 10 and 25 kHz in species with a small spiracle and trachea. The evolutionary implications of these differences of the auditory systems are discussed. They are considered to be influenced more by ecological factors than bioacoustical ones.
Instrumentation for Motor Imagery-based Brain Computer Interfaces relying on dry electrodes: a functional analysis

The functional analysis of a novel instrumentation for Brain-Computer Interfaces (BCI) is carried out. This consists of a wireless wearable helmet with only 8 dry electrodes. The brain signals to be measured through an electroencephalography are related to the sensorimotor cortex. The final aim is to distinguish between different motor imagery tasks. Furthermore, this analysis also takes into account the discrimination between two executed movements. Features are extracted from the brain signals by means of a Common Spatial Pattern algorithm. Then, two different classifiers are employed to process the brain signals, namely the Random Forest, and the Support Vector Machine with Gaussian kernel. Their performance was compared in terms of classification accuracy and the best accuracy resulted equal to about 80% when distinguishing between left and right imagined movement, classified by means of the Random Forest. The results of this study aim at giving a contribution to the building of wearable BCIs for daily life applications.
Eddy Current Phase Gradient and Its Identification of Conductive Material Defects

In this paper, the phase gradient is taken as the characteristic quantity of defect testing signal by using the phase spectrum analysis method of spatial domain, and the phase gradient of testing signal is extracted by using the digital phase- sensitive demodulation technology to detect and classify different types of defects in the plate metal sample. Dual air core coil eddy current sensor and 1-10kHz multi-frequency excitation signal are used to identify surface defects, lower surface defects and internal defects of the sample. The experimental results show that this experimental system can effectively detect defects, and visual detection results can be obtained through phase spectrum analysis of spatial domain. The phase gradient is used as the characteristic quantity to effectively suppress the influence of lift-off effect, making the detection results more accurate.
Sweet Corn (Zea mays) Cultivar Sensitivity to Mesotrione*

Field studies were conducted in 1999 and 2000 at Simcoe, Ridgetown, and Exeter, Ontario, to evaluate the tolerance of nine sweet corn cultivars to mesotrione, applied preemergence (PRE) at 140 and 280 g ai/ha and postemergence (POST) at 100 and 200 g ai/ha. Urea ammonium nitrate fertilizer (28%) at 2.5% (v/v) and crop oil concentrate at 1% (v/v) were added to POST applications of mesotrione only. All cultivars were tolerant to mesotrione applied PRE. There was no injury, or reductions in plant height or yield with PRE applications of mesotrione at any location in either year. POST applications of mesotrione, particularly at 200 g/ha, caused significant phytotoxicity to ‘Calico Belle’ and ‘Del Monte 2038’. Other cultivars also showed phytotoxic symptoms; however, this injury was much reduced and did not occur at all locations each year. Sweet corn injury by mesotrione increased as rate increased. Del Monte 2038 also had significantly reduced plant height and yields. Other cultivars had no plant height or yield reductions because of POST applications of mesotrione. Nomenclature: Mesotrione; sweet corn, Zea mays L. Additional index words: Crop injury, plant height, triketone. Abbreviations: DAP, days after planting; DAT, days after treatment; HPPD, p-hydroxy-phenylpyruvate dioxygenase; OM, organic matter; PRE, preemergence; POST, postemergence; SU, sulfonylurea.
28 GHz-Band Experimental Trial at 283 km/h Using the Shinkansen for 5G Evolution

To enhance 5G (5G Evolution) further, more stable high bit-rate transmission using high SHF bands including 28 GHz or EHF bands is provided even in high-mobility environments such as in high-speed trains. However, in future 5G use cases in the Shinkansen, a dynamic changes in the beam direction and a greater Doppler frequency shift may cause performance degradation in 28 GHz-band transmission. Thus, we conduct a 28-GHz band 5G experimental trial on an actual Shinkansen that runs at a maximum speed of 283 km/h. This paper introduces the world’s first 28 GHzband 5G experimental system used in a 5G experimental trial in the Shinkansen travelling over 200 km/h. We detail the experimental configuration in which three base stations are deployed along the Tokaido Shinkansen railway with a mobile station located in the train. This paper also presents the downlink transmission performance measured in such a high-mobility environment. The experimental trial can achieve throughput exceeding 1.0 Gbps and consecutive handovers among the three BSs.
Generalized Gaussian Noise Distribution Enabled Sparse Representation Model for Bearing Fault Diagnosis

Sparse representation (SR) theory gets great development in recent years for bearing fault diagnosis. Many scholars focus on constructing proper regularization terms, while few of them notice that the noise assumption is also quite important. Because in the actual engineering signal, the noise does not necessarily obey a single Gaussian distribution, while it is usually assumed so in the traditional SR model. Therefore in this paper, we propose a new SR model, which fits the noise in signal with a generalized Gaussian distribution (0 ≤q ≤2) and also assumes the coefficient obeys a hyper-Laplacian distribution (0 ≤ p ≤ 1). Thus this new SR model is marked as a generalized Gaussian noise distribution enabled the sparse representation model (GGSR). It has a flexible form because the parameters q and p can be adjusted to fit the true noise and coefficient distributions. Then the solving algorithm of the model is also developed based on the ADMM algorithm. Finally, the denoising performance of GGSR is verified by a series of simulation and engineering experiments. It shows that the GGSR model is effective in extracting impulses from the noisy signal.
PREDATION AND COMPETITION: THE IMPACT OF FISHERIES ON MARINE-MAMMAL POPULATIONS OVER THE NEXT ONE HUNDRED YEARS

Abstract We discuss the potential for commercial fisheries to adversely impact ≥1 population of marine mammal by the end of the 21st century. To a large degree, patterns over the last 50 years regarding human population growth, success and failure in marine-fisheries management, and life history and status information on marine mammals are the basis for 6 predictions. First, annual worldwide landings of fish and shellfish by the end of the 21st century will be less than 80 million tons. Second, virtually all of the predictions regarding species composition and energy flow within a marine community, based on models developed to date with incomplete information on species abundance, food habits, genetic effects of fishing, and variability of predator food habits, will prove wrong on a decadal or longer time scale. Third, the most common type of competitive interaction between marine mammals and commercial fisheries will be that in which commercial fisheries adversely affect a marine-mammal population by depleting localized food resources without necessarily overfishing the target species of fish (or shellfish). Because of this, the number of extant populations and species richness of marine mammals will be reduced by the end of the 21st century, and coastal populations and species will be affected more negatively than will noncoastal species. Fifth, predator control programs designed to reduce local populations of marine mammals will be common without changes in existing forms of fishery management. Finally, protein from marine mammals will become a more important component of the human diet than it currently is.
An FPGA-based multi-frequency EIT system with reference signal measurement

Multi-frequency electrical impedance tomography (MFEIT) has been rapidly developed, from theory to application, in the biomedical imaging. Compared with the traditional electrical impedance tomography (EIT), MFEIT provided more information for physiological status analysis or pathological diagnosis. In this work, a MFEIT system based on FPGA is designed, which includes the following new characteristics. First, a high-accuracy multi-frequency current source with adjustable output frequency and amplitude as well as high output impedance is designed based on the combination of a classic current mirror and a differential topology, which demonstrates stable performance in high frequencies. Second, a reference measurement circuit is developed for the calibration of phase measurement data, through which the amplitude data and phase data can be more accurately measured. Furthermore, the low-pass filters of system have been designed based on the Butterworth filter theory to realize the flattest frequency response in the passband. A series of systematic tests are performed on the MFEIT system, including filter testing, amplitude and phase signal-to-noise ratio (SNR) measurements, channel consistency and measurement repeatability verification. Finally, the flatness analysis of the system frequency response and the load dependency discussion are performed respectively. In all, the maximum amplitude SNR and phase SNR of the boundary measurements are 71.55dB and 64.12dB respectively. The frequency response curve at low loads is almost flat across the entire bandwidth between 20Hz and 1MHz. Although the frequency response deteriorates when the magnitude of load is as high as kΩ, it remains flat in the frequency range of 200Hz-100kHz. The evaluation results indicate that the system has good performance over a wide frequency band, and achieves a relatively high SNR.
MORAN EFFECT ON NONLINEAR POPULATION PROCESSES

I investigate the efficacy of the Moran effect as applied to natural population processes. The Moran effect, the correlated density-independent disturbances that bring independently oscillating local populations into synchrony, was originally conceived as an attribute of a linear model system. However, it applies only approximately to natural populations, as they are inherently nonlinear in their density-dependent structure, given that no animal has an unlimited reproductive capacity. The degree of approximation, as measured by the degree of correlation among populations involved, is shown to depend, given the density-dependent structure, on the variances of the random disturbances. In particular, if the unperturbed density-dependent process converges to an equilibrium density, approximation is good when the variances are equal among the populations involved and comparatively small, but it worsens as the variances and their differences increase. For those processes that do not converge, when unperturbed, but exhibit bounded oscillations, the degree of approximation tends to deteriorate considerably, or may practically collapse, even if the disturbances are not large in variance. A sample correlation coefficient is often spurious if the observed population processes to be correlated are highly autocorrelated and limited in length. To detect spuriousness, the density-independent disturbances must somehow be estimated from the data. Three methods (moving-average, linear regression, and nonlinear regression) are considered, and their merits and demerits are discussed. Results of the present investigation are summarized with respect to the interpretations (or diagnoses) of sample cross-correlation functions.
A Destination Prediction Model for Individual Passengers in Urban Rail Transit

Urban rail transit, as an important part of public transportation, plays an important role in solving the problems of large urban public traffic flow and road congestion. Real-time estimation of the destination of each individual passenger who has entered a metro station but remains in the system is of great significance for real-time passenger tracking, service recommendation, and other related applications. Traditional technology is mainly using statistical and probabilistic methods to predict user's destination, which are based on the travel information of individual passengers. However, individual passenger travel is not only affected by itself, but also affected by group travel, and other contextual factors, especially when individual users have a small amount of history travel information. Therefore, these methods cannot get best results for the prediction of destination. This paper proposes a method called as DCM based on multi-nominal logit model with highly explanatory. DCM extracts three types of features, including group features, individual features, and context features, then feed these features to a multi-nominal logit model to predict the destinations of individual passengers. We tested our method based on real data over two months in Shenzhen, China which is collected by automatic toll system, and the result shows that our method is superior to existing methods.
Single-Frequency kHz-Linewidth 1070 nm Laser Based on Yb:YAG Derived Silica Fiber

A kHz-linewidth single-frequency laser at 1070 nm was demonstrated based on homemade heavily Yb3+-doped Yb:YAG-derived silica fiber (YDSF), which was fabricated by molten-core fabrication method. Stable single-longitudinal-mode (SLM) lasing operation was achieved by adopting ring cavity configuration, where a piece of un-pumped polarization maintaining Yb3+-doped fiber (PM-YDF) was utilized as a saturable absorber (SA). A maximum output power of the stable single longitudinal mode continuous wave laser up to 40 mW was obtained with a pump power of 542 mW at 976 nm. The optical signal-to-noise ratio (OSNR) was ~60 dB, and the laser linewidth was measured to be less than 4.3 kHz, which is limited by the measurement setup. The fluctuation of center wavelength of the laser was less than 0.1 pm within 10 min. Wavelength tuning from 1069.99 to 1070.42 nm was achieved by controlling the temperature of the fiber Bragg grating (FBG).
Parasitic Location Logging: Estimating Users’ Location from Context of Passersby

People often turn off location logging when the batteries of their smartphones get low, to reduce the phone’s power consumption and prolong its operation. Here, we propose an innovative data sharing scheme called as the Parasitic Location Logging (PLL). PLL can acquire location of such users, what we call parasitic users, without invoking any location functionalities by the GPS and Bluetooth low energy (BLE) sensors of their smartphones. PLL estimates parasitic users’ location and trajectory by relying on other users who pass by the parasitic user, what we call host users, as evidence that they are located in close proximity. The results of field experiments showed that PLL dramatically decreases battery consumption of parasitic users’ smartphones and that the position of parasitic users can be identified accurately. Moreover, the battery consumption of PLL was rigorously evaluated in a laboratory setting to demonstrate its benefit. An agent simulation evaluating the proposed calculation algorithm under various conditions in realistic environments validated the robustness of PLL.
Joint Radar-Communication Strategies for Autonomous Vehicles: Combining Two Key Automotive Technologies

Self-driving cars constantly assess their environment to choose routes, comply with traffic regulations, and avoid hazards. To that aim, such vehicles are equipped with wireless communications transceivers as well as multiple sensors, including automotive radars. The fact that autonomous vehicles implement both radar and communications motivates designing these functionalities in a joint manner. Such dualfunction radar-communications (DFRC) designs are the focus of a large body of recent work. These approaches can lead to substantial gains in size, cost, power consumption, robustness, and performance, especially when both radar and communications operate in the same range, which is the case in vehicular applications.
Novel Substrate Integrated Waveguide Architectures for Microfluidic Biosensing and Environmental Detection

This paper presents two novel substrate integrated waveguide (SIW) sensing-elements for microfluidic biosensing and environmental detection. The first proposed structure is a SIW interferometer for biological liquids characterization. The operation principle of the latter is based on the variation of the effective dielectric constant of a sensitive branch due to the introduction of aqueous solutions into a sensitive region of a total volume of ~1 µL. To achieve a destructive interference, the signal division and combination have been carried out using microstrip Wilkinson power dividers. The sensitive characteristics of the device have been tested by measuring two buffer solutions; Phosphate-buffered saline (PBS) and Roswell Park Memorial Institute medium (RPMI). In regards to the second proposed device, it consists of an H-plane SIW-based horn antenna demonstrated for relative humidity (RH) sensing. The sensitive characteristics of the proposed antenna without the use of a sensitive layer were tested in the range of 25%–75% RH. The combination of antenna and sensor functions in a single substrate integrated device offers multiple advantages and enables the development of simple, compact and cost-effective sensors. Passive RFID sensing is also possible with this technique without resorting to the use of additional sensors.