Miracle-dz/UniFAR-FTUs huggingface dataset:
Nested diets: a novel pattern of individual-level resource use

Many generalist populations may actually be composed of relatively specialist individuals. This ‘individual specialization’ may have important ecological and evolutionary implications. Although this phenomenon has been documented in more than one hundred taxa, it is still unclear how individuals within a population actually partition resources. Here we applied several methods based on network theory to investigate the intrapopulation patterns of resource use in the gracile mouse opossum Gracilinanus microtarsus. We found evidence of significant individual specialization in this species and that the diets of specialists are nested within the diets of generalists. This novel pattern is consistent with a recently proposed model of optimal foraging and implies strong asymmetry in the interactions among individuals of a population.
Nonprofit organizations at the crossroads of offline and online fundraising in the digital era: The influence of the volume of target beneficiaries on the success of donation-based crowdfunding through digital platforms

The purpose of this research consists of exploring the extent to which the volume of target beneficiaries — explaining the success of offline fundraising campaigns for charitable causes — may influence as well the success of donation-based crowdfunding (DCF) campaigns promoted through digital platforms. First, the literature on the influence of the volume of potential beneficiaries on the success of offline fundraising campaigns for charitable causes is reviewed. Second, hypotheses are proposed linking the determinants identified in the literature to DCF campaigns. Thirdly, their explanatory capacity is measured through quantitative analysis based upon a database of 360 campaigns fostered by nonprofits via Microdonaciones, a donation-based crowdfunding digital platform, for the period 2012–2017. Logistic regression analysis is used to test the hypotheses proposed. Results confirm that donation-based crowdfunding campaigns for charitable causes promoted through digital platforms and resulting successful, tend to be small and limited concerning the volume of potential beneficiaries intended to be assisted.
Clinical effect of low level laser therapy on healing of recurrent aphthous ulcer and oral ulceration in Behcet ’ s disease

Background: As the exact etiology of recurrent aphthous ulcer (RAU) remains unknown, therapeutic measures are challenging and difficult. Low level laser therapy use in based on the concept that certain doses of specific wavelength can turn on or off certain cellular components or functions as well as aid in healing and reducing pain and swelling of oral lesions. The aim of this study was to evaluate the clinical effect of low energy Gallium-Arsenide semiconductor diode laser, 904 nm, on the healing process of recurrent aphthous ulceration and oral ulceration in Behcet’s disease. Patients and Methods: This study was performed on 47 patients, age range 12-58 years, with RAU lesions irradiated by laser into two doses (in alternative day), and divided into Control group: RAU patients without any treatment. Group one: RAU in Behcet’s disease irradiated with 1.5 Joule laser. Group two: RAU only, irradiated with 1.5 Joule laser. The results obtained account for duration of lesions, size measurement, pain symptoms, and presence of erythema in three visits. Results: It was shown that no difference in the healing process of RAU and oral ulcer in Behcet’s disease when compared with the control group after low level laser therapy, however when the lesion is less than 24 hours old, it was healed faster than control group. In addition to that, pain symptoms disappear soon after laser therapy, or it regains in low intensity. In RAU, healing process was reduced to a couple of days in initial stage of ulcer, however, a non significant clinical difference was observed on healing process of RAU and oral ulceration in Behcet’s disease after LLLT in comparison with non treated RAU lesions. There was no statistical significant difference on healing process of RAU and oral ulceration in Behcet’s disease after LLLT. Pain disappears soon after LLLT and this is temporary which recur in the next visit but in milder form. Conclusion: Dose and other parameters at which low level laser therapy (LLLT) is implemented influence effectiveness of the therapy
UMAP: Urban mobility analysis platform to harvest car sharing data

Car sharing is nowadays a popular means of transport in smart cities. In particular, the free-floating paradigm lets the customers look for available cars, book one, and then start and stop the rental at their will, within a specific area. This is done thanks to a smartphone app, which contacts a web-based backend to exchange information. In this paper we present UMAP, a platform to harvest the data freely made available on the web by these backends and to extract driving habits in cities. We design UMAP with two specific purposes. Firsty UMAP fetches data from car sharing platforms in real time. Secondly, it processes the data to extract advanced information about driving patterns and user's habits. To extract information, UMAP augments the data available from the car sharing platforms with mapping and direction information fetched from other web platforms. This information is stored in a data lake where historical series are built, and later analyzed using analytics modules easy to design and customize. We prove the flexibility of UMAP by presenting a case of study for the city of Turin. We collect car sharing usage data for over 50 days to characterize both the temporal and spatial properties of rentals, and to characterize customers' habits in using the service, which we contrast with public transportation alternatives. Results provide insights about the driving style and needs, which are useful for smart city planners, and prove the feasibility of our approach.
An analysis of improved Nyquist pulses based on Pearson distance

Modern telecommunications require high data rates and very good quality of service. The improved Nyquist pulses outperform the standard RC pulse in terms of error probability when sampled with a time offset. An analysis of these novel pulses in terms of performance and similarity in shape based on Pearson distance between the vectors that contain the samples of the impulse response and frequency characteristic has been carried out. The most performing pulses show a smaller value of Pearson distance with respect to the standard ‘raised cosine’ pulse. The Pearson distance diminishes for higher values of the excess bandwidth.
Optimal patrol strategies against attacker's persistent attack with multiple resources

In recent years, terrorist organizations' activates are various (e.g., igniting a bomb, shooting). Thus, it is difficult to predict the target which will be attacked and how to implement attacks by attackers. Although security agencies may have some knowledge of adversaries, potential targets can't be covered by sufficient security resources all the time due to limited security resources. There are generally two forms of attacks. One is instantaneous attack such as igniting a bomb. The other is persistent attack like shooting and knife attack. Most studies assumed that the site of the deploying resources is completely protected, but ignored the attacker's attack ability will exceed defender's defense ability in the case of persistent attacks. An example of the typical persistent attack is a terrorist attack happening in Kunming, China on March 1, 2014, which caused large losses. In this paper, we first explore the attacker's persistent attack with multiple resources like Kunming attack and make four contributions: 1) A new Stackelberg game model to formulate the problem for attacker's persistent attack with multiple resources; 2) A novel algorithm to compute the optimal mixed patrol strategy for the defender; 3) A modified double-oracle algorithm to further scale up the algorithm; and 4) Extensive experiments to show solution quality and scalability of proposed algorithms.
Deep Learning and Reconfigurable Platforms in the Internet of Things: Challenges and Opportunities in Algorithms and Hardware

As the Internet of Things (IoT) continues its run as one of the most popular technology buzzwords of today, the discussion really turns from how the massive data sets are collected to how value can be derived from them, i.e., how to extract knowledge out of such (big) data. IoT devices are used in an ever-growing number of application domains (see Figure 1), ranging from sports gadgets (e.g., Fitbits and Apple Watches) or more serious medical devices (e.g., pacemakers and biochips) to smart homes, cities, and self-driving cars, to predictive maintenance in missioncritical systems (e.g., in nuclear power plants or airplanes). Such applications introduce endless possibilities for better understanding, learning, and informedly acting (i.e., situational awareness and actionable information in government lingo). Although rapid expansion of devices and sensors brings terrific opportunities for taking advantage of terabytes of machine data, the mind-boggling task of understanding growth of data remains and heavily relies on artificial intelligence and machine learning [1], [2].
26 Investigating Fragility in Plant – Frugivore Networks : A Case Study of the Atlantic Forest in Brazil

Mutualistic interactions among free-living species, such as in pollination and seed dispersal by animals, have been a major factor in the evolution of flowering plants and animals. The recent disruption of these interactions caused by human activities may bring about a considerable loss of biodiversity (Buchmann and Nabhan, 1996; Jordano, 2000; Herrera, 2002; Fontaine et al., 2006). An important characteristic of mutualistic interactions among free-living species is that exclusive, pairwise interactions are rare (Thompson, 2005). In contrast, in a given ecological community, each species interacts with a few to dozens of mutualistic partners (Jordano, 1987). As a result, at the community level, mutualistic interactions often emerge as web-like systems (Jordano, 1987; Jordano et al., 2003). Web-like systems such as food webs, the Internet and human social interactions are traditionally described as graphs or networks (reviewed by Albert and Barabási, 2002). Recently, the notion of complex networks has emerged as a key concept for understanding mutualistic interactions among species in a given community (Olesen and Jordano, 2002; Bascompte et al., 2003; Jordano et al., 2003; Vazquez and Aizen, 2004; Guimarães et al., 2006). Indeed, by applying the network approach, several consistent patterns in the structure of mutualistic ecological interactions have been described, including high heterogeneity in the degree of specialization (Jordano et al., 2003), strong asymmetrical specialization among partners (Bascompte et al., 2003; Vazquez and Aizen, 2004; Guimarães et al., 2006) and an allometric relationship between number of interactions and species richness (Bascompte et al., 2003). The description of structural patterns of plant–animal networks allows inferences to be made about the robustness of ecological interactions to disturbances (e.g. Jordano et al., 2003). In addition, the network approach
A Multi-Sensor and Parallel Processing SoC for Miniaturized Medical Instrumentation

We report <italic>VivoSoC</italic>, a system-on-chip realized in 130-nm CMOS for miniaturized medical instrumentation as used in mobile health devices or implantable telemetry systems for animal experiments. It features six neural stimulation channels and acquisition circuits for 9<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> electrode-based recordings, 4-channel/32-LED photoplethysmography (PPG), bioimpedance, and temperature. A 34-<inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula>/MHz quad-core processing unit with sophisticated data, power, and clock management techniques enables on-chip feature extraction, which can dramatically reduce transmission or storage data rates in a system—crucial for overall power consumption and exemplarily demonstrated on preliminary work on implantable PPG-based vital signs monitoring.
Word-of-Mouth, Observed Adoptions, and Anime Watching Decisions: The Role of the Personal versus the Community Network

We quantify the effects of others' adoptions and word-of-mouth (volume and valence) on consumers' product adoption decisions. We differentiate between the effects of word-of-mouth and observed adoptions from friends ("personal network") and the effects of word-of-mouth and observed adoptions from the whole community ("community network"). Understanding the relative importance of word-of-mouth and observed adoptions at each network level provides crucial guidance for companies regarding their information provision and platform design strategies. Our unique data come from an online anime (Japanese cartoon) platform containing individual-level data on users' networks, anime adoptions, forum posts, and ratings of animes. Our results reveal that both word-of-mouth (volume and valence) and observed adoptions from the community network have significant positive effects on individual users' anime watching decisions. Furthermore, this finding also holds true for word-of-mouth and observed adoptions coming from the personal network. Comparing the magnitudes of the effects of word-of-mouth and observed adoptions across both network levels, we find that word-of-mouth valence from the community network is the largest driver among the social learning forces we study. Thus our results show that word-of-mouth and observed adoptions provide unique and different information that individuals use in their anime watching decisions and that the community network is the primary source of information driving anime adoptions.
Metal–Insulator–Graphene Diode Mixer Based on CVD Graphene-on-Glass

In this letter, we present for the first time a mixer circuit based on Metal–Insulator–Graphene (MIG) diodes fabricated with large-scale monolayer graphene grown by chemical vapor deposition. A small-signal model extracted from the diode physical structure is used together with a large-signal model extracted from the dc characteristics of the MIG diode to build a down-conversion mixer. The measured conversion loss at a local oscillator power (<inline-formula> <tex-math notation="LaTeX">${P}_{\text {LO}}$ </tex-math></inline-formula>) of 5 dBm is lower than 15 dB, while RF-to-IF isolation is 36 dB with an input return loss and RF-to-LO isolation better than 10 dB over the frequency band from 1.7–6 GHz. Promising mixer results in combination with the CVD-based process promote the MIG diode-based mixer to be used in low-power, low-cost, microwave, and millimeter-wave circuit applications.
Power distribution of parallel converters in islanded microgrid using virtual resistance droop control

This paper investigates the power distribution problem of multiple parallel inverters with different power ratings in microgrid. An improved droop control method based on virtual resistance is provided, which facilities the power distribution and restrain of circulating-current. The proposed approach can make the sharing of both active and reactive power of loads in microgrid in accordance with their capacity properly. The simulation with MATLAB/Simulink is conducted to validate effectiveness of the proposed control strategy.
The Application of Machine Learning Techniques on Channel Frequency Response Based Indoor Positioning in Dynamic Environments

Traditional IPS uses triangulation based on signal strength but its accuracy is impaired in non-line-of-sight (NLOS) situations. Among the available wireless technologies for indoor positioning, WiFi is a good candidate since it is supported by existing mobile devices and infrastructure indoors, and it can operate under both LOS and NLOS conditions. One of the cutting-edge WiFi-based localization techniques exploits time-reversal resonating strength (TRRS) of coherent channel frequency responses (CFR). The basic concept of CFR-based positioning is based on the similarity measure between the testing CFR and the pre-recorded CFR fingerprints. A common assumption in previous works is that the wireless channel is time invariant. In this paper, we study CFR-based positioning in a dynamic indoor environment. Using the collected channel response fingerprints for both LOS and NLOS scenarios, we exploit supervised machine learning techniques to enhance the processing speed while achieving high positioning accuracy under the effect of dynamic wireless channels.
Flickering in AGB stars: probing the nature of accreting companions

Binary companions to asymptotic giant branch (AGB) stars are an important aspect of their evolution. Few AGB companions have been detected, and in most cases it is difficult to distinguish between main-sequence and white dwarf companions. Detection of photometric flickering, a tracer of compact accretion discs around white dwarfs, can help identify the nature of these companions. In this work, we searched for flickering in four AGB stars suggested to have likely accreting companions. We found no signs for flickering in two targets: R Aqr and V1016 Cyg. Flickering was detected in the other two stars: Mira and Y Gem. We investigated the true nature of Mira’s companion using three different approaches. Our results for Mira strongly suggest that its companion is a white dwarf.
Effects of inverted vision on hand-pointing performance in altered gravity during parabolic flight

An accurate perception of the body and the environment is important for programming pointing accuracy and controlling motor action. The objective of this research effort was to assess the influence of gravity on these cognitive and sensorimotor processes. The integration of vestibular, visual, proprioceptive, and cognitive cues was investigated during a pointing task that required eye-hand coordination. Parabolic flights provide a unique environment to understand the specific role of gravity since both vestibular and proprioceptive inputs, as well as the gravitational reference, are altered during the various gravity levels obtained. Additionally, visual input can be altered using prisms that invert the visual scene. Six subjects participated in a within-subject experiment during the 61st ESA and 112th CNES parabolic flight campaigns. Seated subjects performed hand-pointing motions at randomly appearing dots on a 22-inch tactile display during 15 parabolas under three different gravity levels (0G, 1G, 1.8G) and two different visual conditions (normal, up-down inverted). Pointing latency (i.e. reaction time and duration of movement) and pointing accuracy (i.e. error between the target position and the actual hit) were recorded using custom-built software. Results show a statistically significant increase in reaction time and action time (i.e. decrease in performance), and a statistically significant upward shifting in the vertical pointing direction during up-down inverted vision with respect to normal vision. However, data did not reveal statistical significant differences in pointing performance between gravity levels. We discuss the significance of these results regarding the mechanisms of sensory integration for eye-hand coordination and briefly propose future research directions in this area.
Topography-Related Glacier Area Changes in Central Tianshan from 1989 to 2015 Derived from Landsat Images and ASTER GDEM Data

Studies have investigated the glacier projected area (2D Area) on a horizontal plane, which is much smaller than the glacier topographic surface extent (3D Area) in steep terrains. This study maps the glacier outline in Central Tianshan using Landsat images from four periods, i.e., 1989, 2002, 2007 and 2015, by an object-based classification approach, and analyzes the glacier 2D and 3D area changes related to topographic factors based on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global DEM data. This approach shows an accuracy of 90.8% for clean ice mapping. The derived clean ice outlines are in good agreement with the 2nd Chinese Glacier Inventory (CGI2) and the Global Land Ice Measurements from Space (GLIMS). The fields with a northern aspect receive the least surface solar radiation, leading to dominant existing glaciers. Glaciers are near evenly distributed in slope zones of 0° to 50° and have a mean slope angle of 28.8°, resulting in a 30.3% larger 3D area than the 2D area in 2015 in Central Tianshan. The glacier 2D area decreased by 404 km2 (−8.1%) between 1989 and 2015, while the 3D area declined by 516 km2 (−7.9%). The glacier 2D area showed a reduction of −1.8% between 1989 and 2002, −3.8% between 2002 and 2007, and −2.7% between 2007 and 2015, and these retreating rates closely responded to the variations of regional mean air temperature and precipitation. Topographically, most reductions occurred in elevation bands of 3000–4000 m and in slope zones of 10–20° and 40–50°, and in the eastern aspect fields. The northern Tekes River catchment had the largest shrinking rate of −17.0% (2D area), followed by the southern Karasu River (−14.2%) and Muzart River (−7.7%) catchments. In contrast, glaciers in the Kumerik/Aksu and Tailan River catchments in the Tuomuer region showed little change (−2%).
Machine learning in incident categorization automation

IT incident management process requires a correct categorization to attribute incident tickets to the right resolution group and obtain an operational system as quickly as possible, having the lowest possible impact on the business and costumers. In this work, we introduce a module to automatically categorize incident tickets, turning the responsible teams for incident management more productive. This module can be integrated as an extension into an incident ticket system (ITS), which contributes to reduce the time wasted on incident ticket route and reduce the amount of errors on incident categorization. To automate the classification, we use a support vector machine (SVM), obtaining an accuracy of 89%, approximately, on a dataset of real-world incident tickets.
RF Wide-Band Bandpass Filter With Dynamic In-Band Multi-Interference Suppression Capability

A class of RF multi-functional bandpass filter with multiple frequency-reconfigurable rejected bands that are embedded into its broad transmission frequency range is reported. This filter concept exploits an original tunable multi-band quasi-bandstop section as constituent block. In this manner, unprecedented levels of spectral adaptivity are obtained for its in-band notches. Among them: 1) independent control of center frequency and rejection level; 2) notch-combination capability to conform wider rejected bands and make their number dynamically selectable; and 3) generation of dual-band bandpass responses with adjustable bandwidth and inter-band transmission zeros. This results in controllable in-band stopbands with reconfigurable bandwidth, attenuation level, and filtering-profile type. The devised filter architecture, which is appropriate for dynamic multi-interference mitigation in broad-band RF receivers, is scalable to any number of arbitrary-order in-band notches. For proof-of-concept purposes, a UHF-band microstrip prototype with up to two tunable in-band second-order stopbands is manufactured and measured.