Miracle-dz/UniFAR-FTUs huggingface dataset:
SEP Protons in GEO Measured With the ESA MultiFunctional Spectrometer

The multifunctional spectrometer (MFS) is a new radiation monitor that together with component technology test bed makes the European Space Agency Alphasat Environment and Effects Facility—Technology Demonstration Payload 8 (AEEF-TDP8). The two units are hosted in the X panel of the Alphasat satellite in orbit since July 2013. MFS is an instrument specifically designed to characterize the space radiation environment in geostationary orbit. The mission lifetime of AEEF/TDP8 will be at least three years and TDP8 is expected to be acquiring scientific data during the whole period. Before launch, MFS was submitted to proton and electron beam tests at the Paul Scherrer Institute in Switzerland in 2010. The main purpose was the validation and calibration of the MFS protoflight model together with the estimation of particle energy resolution and identification capability. A full Geant4 simulation with computer-aided design geometry exported to geometry description markup language description the MFS in-flight configuration was built. Ground test results were validated with Geant4 simulation. The measurements of MFS proton channels and MFS proton response functions are validated using comparisons with INTErnational Gamma-Ray Astrophysics Laboratory/INTEGRAL Radiation Environment Monitor data during the solar energetic particle event of January 2014. In addition, an artificial neural network (ANN) unfolding method was developed in order to unfold MFS data. Comparisons show that the derived ANN Alphasat/MFS fluxes are in remarkable agreement with INTEGRAL/IREM proton fluxes.
Achieving Scalable and Reliable Non-Intrusive Failure Reproduction in Distributed Systems by Enhancing the Event Chaining Approach

Achieving Scalable and Reliable Non-Intrusive Failure Reproduction in Distributed Systems by Enhancing the Event Chaining Approach Xiang Ren Master of Applied Science The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto 2018 Complex and unforeseen failures in distributed systems must be diagnosed and replicated so developers can understand the underlying problem and verify the resolution. Unfortunately, failure reproduction is unpredictable and time-consuming, often leading to costly
A phylogeny of Xanthopygina (Insecta, Coleoptera) reveals major lineages and the origin of myrmecophily

Xanthopygina is a group of colourful, neotropical rove beetles (Staphylinidae) comprising 28 genera and more than 350 species. While many genera are found on rotting fruits, carrion, dung and mushrooms, several taxa have evolved associations with social insects. Previous phylogenetic analyses have used only a subset of genera and were based solely on molecular data. In this paper, we performed Bayesian and maximum likelihood phylogenetic analyses of all known genera, including three potentially new genera, based on molecular (4,797 bp) and morphological (91) characters. Our results reaffirmed the monophyly of the subtribe and divided it into eight major lineages: the Elmas, Gastrisus, Isanopus, Ocyolinus, Plociopterus, Smilax, Trigonopselaphus and Xanthopygus groups. We hypothesized that myrmecophily evolved once in the common ancestor of the Smilax group, and that sphecophily possibly evolved twice, in the Trigonopselaphus and Xanthopygus groups.
Metcalfe's law and log-period power laws in the cryptocurrencies market

Abstract In this paper the authors investigate the statistical properties of some cryptocurrencies by using three layers of analysis: alpha-stable distributions, Metcalfe’s law and the bubble behaviour through the LPPL modelling. The results show, in the medium to long-run, the validity of Metcalfe's law (the value of a network is proportional to the square of the number of connected users of the system) for the evaluation of cryptocurrencies; however, in the short-run, the validity of Metcalfe’s law for Bitcoin is questionable. According to the bidirectional causality between the price and the network size, the expected price increase is a driver for more investors to join the Bitcoin network, which may lead in the end to a super-exponential price growth, possibly due to a herding behaviour of investors. The authors then used LPPL models to capture the behaviour of cryptocurrencies exchange rates during an endogenous bubble and to predict the most probable time of the regime switching. The main conclusion of this paper is that Metcalfe’s law may be valid in the long-run, however in the short-run, on various data regimes, its validity is highly debatable.
A Model Parent's Group for Enhancing Aggressive Children's Social Competence

ABSTRACT Preadolescent children's aggressive behaviors are related to maladjustment in their later adult lives. A major factor influencing the continuity of aggressive behaviors is the family environment. This paper presents a family dynamic oriented group work that integrates concepts of co-parenting and bidirectionality. The goal of the group was to enhance aggressive children's social competence by promoting positive interactions within the family. The six-week group covered topics such as identifying parenting styles, supporting parental alliances, fostering mutuality among parents and their children, making demands on children, and responding to children's needs and negative emotions. Several themes emerged in the group process. These themes included parents (1) having insufficient time to be with their children or a busy lifestyle, (2) having little confidence in parenting, and (3) losing patience/getting angry. Pre-post single group tests showed that aggressive children's social competence was improved four weeks after the group ended.
Low-Frequency Fatigue at Different Muscle Length Following Intermittent Eccentric Drop Jumps in 12—14 Year-Old Boys

Low frequency fatigue (LFF) in 12—14 year-old adolescent boys (n = 10) doing 75 eccentric jumps performed every20 s from a platform 80 cm high was investigated.Thus the aim of this study was to find out if LFF manifests itself in the muscles of boys aged 12—14 years doing 75 dropjumps performed every 20 s at angles of 90˚ and 135˚ from a platform 80 cm high. The results of the research have shownthat doing 75 eccentric jumps performed every 20 s calls forth LFF in the muscles of boys that is particularly strong anddisappears more slowly at a shorter length of the muscle exercised. Thus, the hypothesis as to the sarcomeric origin ofLFF in the muscles of boys and men has been confirmed. Besides, the muscles of men of mature age are more resistantto LFF than those of boys. This fact, as well as a more acute pain brought about in the muscles of boys, indicates thatthe muscles of boys are less resistant to mechanical damage than those of men of mature age.It is maintained that as a result of the eccentric exercise performed, some portion of the weak sarcomeres gets tornand then the strong sarcomeres, i.e. the ones that develop contraction force have to work at a shorter muscle length.When muscle contraction length is short the sensitiveness of miofibrillas to Ca 2+ decreases. It is rather unexpectedthough that 24 h after the end of the exercise the force developed by electrostimulation at low frequencies (20 Hz) issmaller (p < 0.05), as compared to the initial force registered at a shorter muscle length. Since after the exercise therewas also a decrease in the force developed at a shorter muscle length in particular, the sarcomeres are believed tohave been damaged during eccentric exercise.Keywords: electrical stimulation, force, age, muscle damage, stretch-shortening exercise.
A high electrical performance of DG-MOSFET transistors in 4H-SiC and 6H-SiC 130 nm technology by BSIM3v3 model

Abstract In this paper, the electrical performance of double gate DG-MOSFET transistors in 4H-SiC and 6H-SiC technologies have been studied by BSIM3v3 model. In which the I–V and gm–V characteristics and subthreshold operation of the DGMOSFET have been investigated for two models (series and parallel) based on equivalent electronic circuits and the results so obtained are compared with the single gate SG-MOSFET, using 130 nm technology and OrCAD PSpice software. The electrical characterization of DG-MOSFETs transistors have shown that they operate under a low voltage less than 1.2 V and low power for both models like the SG-MOSFET transistor, especially the series DG-MOSFET transistor is characterized by an ultra low power. The different transistors are characterized by an ultra low OFF leakage current of pA order, very high ON/OFF ratio of and high subthreshold slope of order 0.1 V/dec for the transistors in 6H-SiC and 4H-SiC respectively. These transistors also proved higher transconductance efficiency, especially the parallel DG-MOSFET transistor.
Graphs and Colorings for Answer Set Programming with Preferences

The integration of preferences into answer set programming constitutes an important practical device for distinguishing certain preferred answer sets from non-preferred ones. To this end, we elaborate upon rule dependency graphs and their colorings for characterizing different preference handling strategies found in the literature. We start from a characterization of (three types of) preferred answer sets in terms of totally colored dependency graphs. In particular, we demonstrate that this approach allows us to capture all three approaches to preferences in a uniform setting by means of the concept of a height function. In turn, we exemplarily develop an operational characterization of preferred answer sets in terms of operators on partial colorings for one particular strategy. In analogy to the notion of a derivation in proof theory, our operational characterization is expressed as a (non-deterministically formed) sequence of colorings, gradually turning an uncolored graph into a totally colored one.
Location-Based Flooding Techniques for Vehicular Emergency Messaging

This paper analyzes the scalability of message flooding protocols in networks with various node densities, which can be expected in vehicular scenarios. Vehicle safety applications require reliable delivery of warning messages to nearby and approaching vehicles. Due to potentially large distances and shadowing, the delivery protocol must forward messages over multiple hops, thereby increasing network congestion and packet collisions. In addition to application-layer backoff delay and duplicate message suppression mechanisms, location-based backoff techniques have been proposed for vehicular networks. We propose a new hybrid method of location-based and counterbased method, and study several variants through simulations. Our preliminary results in the various density scenarios indicate that the proposed hybrid methods outperform conventional backoff delay techniques and adaptively operate in extremely congested network condition
A novel 77-GHz radar frontend with 19-GHz signal distribution on RF-PCB substrate

A novel radar frontend for 77 GHz mid-range-radar (MRR) and short-range-radar (SRR) applications is presented. The radar sensor makes use of a Colpitts oscillator, frequency multipliers, and a transceive (TRX) mixer. A single sensor contains up to four channels using antenna arrays for angular detection relative to the sensor. The characterization of the integrated circuit's parameters has been carried out using a two-channel sensor with waveguide (WG) transitions. A radar measurement scenario has been realized using a four-channel sensor with a differential antenna array. All sensors have been implemented on off-the-shelf printed circuit board (PCB) substrate.
Using Version Control Data to Evaluate the Impact of Software Tools: A Case Study of the Version Editor

Software tools can improve the quality and maintainability of software, but are expensive to acquire, deploy, and maintain, especially in large organizations. We explore how to quantify the effects of a software tool once it has been deployed in a development environment. We present an effort-analysis method that derives tool usage statistics and developer actions from a project's change history (version control system) and uses a novel effort estimation algorithm to quantify the effort savings attributable to tool usage. We apply this method to assess the impact of a software tool called VE, a version-sensitive editor used in Bell Labs. VE aids software developers in coping with the rampant use of certain preprocessor directives (similar to #if/#endif in C source files). Our analysis found that developers were approximately 40 percent more productive when using VE than when using standard text editors.
DIC Image Segmentation of Dense Cell Populations by Combining Deep Learning and Watershed

Image segmentation of dense cell populations acquired using label-free optical microscopy techniques is a challenging problem. In this paper, we propose a novel approach based on a combination of deep learning and the watershed transform to segment differential interference contrast (DIC) images with high accuracy. The main idea of our approach is to train a convolutional neural network to detect both cellular markers and cellular areas and, based on these predictions, to split the individual cells using the watershed transform. The approach was developed based on the images of dense HeLa cell populations included in the Cell Tracking Challenge database. Our approach was ranked the best in terms of segmentation, detection, as well as overall performance as evaluated on the challenge datasets.
Mixture models for optical flow computation

The computation of optical flow relies on merging information available over an image patch to form an estimate of 2-D image velocity at a point. This merging process raises many issues. These include the treatment of outliers in component velocity measurements and the modeling of multiple motions within a patch which arise from occlusion boundaries or transparency. A new approach for dealing with these issues is presented. It is based on the use of a probabilistic mixture model to explicitly represent multiple motions within a patch. A simple extension of the EM-algorithm is used to compute a maximum likelihood estimate for the various motion parameters. Preliminary experiments indicate that this approach is computationally efficient, and that it can provide robust estimates of the optical flow values in the presence of outliers and multiple motions. <<ETX>>
A brief review of cytotoxicity of nanoparticles on mesenchymal stem cells in regenerative medicine

Abstract Multipotent mesenchymal stem cells have shown great promise for application in regenerative medicine owing to their particular therapeutic effects, such as significant self-renewability, low immunogenicity, and ability to differentiate into a variety of specialized cells. However, there remain certain complicated and unavoidable problems that limit their further development and application. One of the challenges is to noninvasively monitor the delivery and biodistribution of transplanted stem cells during treatment without relying on behavioral endpoints or tissue histology, and it is important to explore the potential mechanisms to clarify how stem cells work in vivo. To solve these problems, various nanoparticles (NPs) and their corresponding imaging methods have been developed recently and have made great progress. In this review, we mainly discuss NPs used to label stem cells and their toxic effects on the latter, the imaging techniques to detect such NPs, and the current existing challenges in this field.
A Land Cover Refined Classification Method Based on the Fusion of LiDAR Data and UAV Image

Refined classification is one of the important research directions of remote sensing data classification. With the support of LiDAR data, the fusion of UAV image feature will be an effective mean to expand feature sets and improve classification category differentiation. After expanding the feature sets, there are high dimensional, massive data, small training samples and so on, which are important problems affecting the classification accuracy. Therefore, based on the DSM features obtained from LiDAR, this paper extracts the geometric features of the relevant space according to the neighborhood constraint rules, and proposes a SVM-DBN classification algorithm for small training samples after the fusion spectra, textures and other features. Using the small training samples classification of SVM, the algorithm predicts a large number of inexpensive unmarked samples on the basis of fewer training samples, uses the prediction results as prior-information training DBN and corrects the results of SVM prediction. The classification results show that the method has high overall precision and reliable results, which provide a new idea for the study of land cover refined classification.
Disentangling factors limiting diamondback moth, Plutella xylostella (L.), spatio‐temporal population abundance: A tool for pest forecasting

Data‐mining techniques play an important role in hyperparameter optimization of heterogeneous environmental factors and their relative contribution as determinants of incidences in insect pest ecological studies. A multidimensional field‐based surveillance was conducted in two seasons (24 months), July–June of each season (2015/2016 ‐ season 1 and 2016/2017 ‐ season 2) using sex‐pheromone‐baited traps and Thermocron i‐Buttons to identify key determinants of population abundance of diamondback moth, Plutella xylostella L. , across spatial horticultural hotspots of Botswana. The moth is a notorious global brassica pest. Pearson's product moment correlation matrix showed month of the year (M), mean temperature (Tmean) and maximum temperature (Tmax) as positively correlated (p < 0.001) to number of moths (N), while minimum temperature (Tmin), minimum relative humidity (RHmin), mean relative humidity (RHmean), maximum relative humidity (RHmax) and host plant (h) were negatively correlated (p < 0.001) to N. Using Waikato Environment for Knowledge Analysis (WEKA) data‐mining techniques, two models were developed: (a) M5P decision‐tree algorithm associated with nine linear models (LMs) and (b) principal component analysis (PCA) based on four principal components. Both approaches identified M as the major predictor of moth abundance, followed by h and farming region (R). However, R was a function of Tmax (positive auto‐correlation) and RHmax (negative auto‐correlation). These results provide simplified relative contribution of heterogeneous factors in influencing P. xylostella spatio‐temporal abundance, essential for early warning systems in pest management. This is an important component of sustainable pest management aimed at managing insect pests and minimizing pesticides abuse in brassica production systems.
Extrinsic Factors Influencing Internal Auditors’ Effectiveness in Jordanian Public Sector

This study focuses on the extrinsic factors, namely, top management support, complexity, independence, and internal audit department’s size that are out of internal auditors' control affecting their effectiveness in the Jordanian public sector. The current study also tries to improve understanding of the extrinsic factors affecting internal auditors’ ability to achieve the assigned goals in order to highlight internal auditors’ effectiveness. Resource-based and agency theories were used in developing the research model. Two sets of questionnaires were distributed among the financial managers and internal audit managers. The results reveal that top management support, independence, and the size of internal audit department play a significant and positive role on the effectiveness of internal auditors, whereas complexity of the task has been found to make a negative impact on the level of their performance. Given the significance of the public sector within the Jordanian economy, the findings are valuable for the internal audit function, regulators, and decision-makers in proposing new legislation and regulations of an internal audit function. Future studies may look into other factors that may restrict internal audit performance, such as organizational culture and pay satisfaction.
Flux-weakening control performance of partitioned stator switched flux PM machines

This paper firstly investigates the flux-weakening control performance of two types of new partitioned stator switched flux permanent magnet (PM) (PS-SFPM) machines and then proposes a novel mechanical flux-weakening technique. The PS-SFPM machine topologies, operation principles and flux weakening control methods are described. In addition, it is shown that by mechanically varying the relative position of two stators of the PS-SFPM machine, the PM flux-linkage can also be varied and hence it can provide improvement of the speed range and torque capability. The optimal relative mechanical angle is derived to enable the maximum torque capability and reduce or even avoid the flux-weakening current injected by the inverter. The proposed technique is verified by 2-dimensional (2D) finite element (FE) analyses and experiments on the prototype machines.
Energy Minimization in Internet-of-Things System Based on Rotary-Wing UAV

In this letter, we study unmanned aerial vehicle (UAV) enabled Internet-of-Things (IoT) system, where a rotary-wing UAV is employed to collect data from a set of IoT devices. By introducing the propulsion energy model for rotary-wing UAV, we aim to minimize the maximum energy consumption among all devices, while satisfying the UAV energy budget. The problem is formulated with a non-convex programming by jointly optimizing the communication scheduling and transmit power allocation for devices as well as the UAV trajectory. An efficient solution is proposed by applying the alternating optimization and successive convex approximation techniques. Simulation results show that the proposed solution can achieve significant gains over benchmark schemes for data collection over IoT system.
Carbon dots, a powerful non-toxic support for bioimaging by fluorescence nanoscopy and eradication of bacteria by photothermia

Carbon Dots (CDs) are innovative materials which have potential applications in many fields, including nanomedicine, energy and catalysis. Here CDs were produced by the alkali-assisted ultrasonic route and characterized by several techniques to determine their composition and properties. Fluorescence nanoscopy using single-molecule localization microscopy shows that they have very good photophysical properties and a remarkable blinking behaviour at 405 nm. Moreover, these CDs are a safe material, non-toxic towards different cell lines (cancer and non-cancer cells) even at very high concentration, reflecting an excellent biocompatibility. Photothermia, i.e. their heating capacity under laser irradiation, was evaluated at two wavelengths and at several power densities. The resulting temperature increment was high (5 < ΔT < 45 °C) and appropriate for biomedical applications. Bioimaging and photothermia were then performed on E. coli, a Gram(−) bacterium, incubated with CDs. Remarkably, by photothermia at 680 nm (0.3, 1 and 1.9 W cm−2) or 808 nm (1.9 W cm−2), CDs are able to eradicate bacteria in their exponential and stationary phases. Images obtained by 3D super-resolution microscopy clearly show the different CD distributions in surviving bacteria after mild photothermal treatment. These results confirm that CDs are multifunctional materials with a wide range of biomedical applications.