Miracle-dz/UniFAR-FTUs huggingface dataset:
A QoS-aware, Proactive Tasks Offloading Model for Pervasive Applications

Edge Computing (EC) is a promising paradigm that provides multiple computation and analytics capabilities close to data sources while alleviating the drawbacks of centralized systems. Nonetheless, due to the limited computational resources of EC nodes and the expectation of ensuring high levels of QoS during tasks execution, innovative task management approaches are required. In this paper, we propose a distributed and intelligent decision-making scheme for tasks scheduling at the edge, considering multiple criteria/parameters. We enhance the behavior of EC nodes making them capable of securing high QoS levels during their functioning. Every EC node systematically evaluates the probability of violating the desired QoS levels and proactively decides some tasks to be offloaded when the aforementioned condition stands true. We present, describe and evaluate the proposed scheme through multiple experimental scenarios revealing its performance and the benefits of the envisioned monitoring mechanism, when serving processing requests in very dynamic environments like the EC.
COSMIC-RAY POSITRONS FROM MILLISECOND PULSARS

Observations by the Fermi Large Area Telescope of γ-ray millisecond pulsar (MSP) light curves imply copious pair production in their magnetospheres, and not exclusively in those of younger pulsars. Such pair cascades may be a primary source of Galactic electrons and positrons, contributing to the observed enhancement in positron flux above ∼10 GeV. Fermi has also uncovered many new MSPs, impacting Galactic stellar population models. We investigate the contribution of Galactic MSPs to the flux of terrestrial cosmic-ray electrons and positrons. Our population synthesis code predicts the source properties of present-day MSPs. We simulate their pair spectra invoking an offset-dipole magnetic field. We also consider positrons and electrons that have been further accelerated to energies of several TeV by strong intrabinary shocks in black widow (BW) and redback (RB) systems. Since MSPs are not surrounded by pulsar wind nebulae or supernova shells, we assume that the pairs freely escape and undergo losses only in the intergalactic medium. We compute the transported pair spectra at Earth, following their diffusion and energy loss through the Galaxy. The predicted particle flux increases for non-zero offsets of the magnetic polar caps. Pair cascades from the magnetospheres of MSPs are only modest contributors around a few tens of GeV to the lepton fluxes measured by the Alpha Magnetic Spectrometer, PAMELA, and Fermi, after which this component cuts off. The contribution by BWs and RBs may, however, reach levels of a few tens of percent at tens of TeV, depending on model parameters.
A geometry without angles: the case for a functional geometry of spatial prepositions

This thesis develops the view that the semantics of spatial prepositions are more fully realised within a framework of functionality, incorporating knowledge of the world, than within the spatial, geometrical framework more often used to analyse prepositions. It is argued that previous approaches which support full specification of lexical entries through the use of polysemy and prototype notions are not satisfactory or psychologically valid. It will also be shown that the minimal specification Classical approaches fail to account for all uses of the locatives described. It is suggested that minimal specification of lexical entries can be achieved by means of functional controls that can provide a more psychologically valid account of the semantics of spatial prepositions. Functional geometric control relations of fContainment, fSupport and fSuperiority are proposed for IN, ON and OVER respectively. These focus on the importance of location control in prepositional choice. It is argued that such controls underlie the use of spatial prepositions. The controls are suggested to be inherently dynamic and state that the relatum object is some way able to control the location of the referent object. For example, the use of the preposition IN is guided by the principle of fContainment which operates on the basic premise that the relatum (y) controls the location of the referent (x) such that when y moves there will be a correlated movement in x (or uncorrelated movement within the convex hull of y) by virtue of some degree of enclosure. The control relation that guides the use of OVER is fSuperiority and it operates on the basic premise that x threatens to come into contact with y as a consequence of gravitational force. Finally, the use of the preposition ON is suggested to be guided by notions of fSupport which operates on the premise that the relatum protects the referent from the force of gravity.
Virtual Sport Event Activities During Pandemic

The main objective of this study is to analyse the experiences of visitors and participants in accessing the virtual exhibition at the VR Duathlon Series TOBA 2020, which was taken place on September 26, 2020, at a location around Lake Toba, North Sumatra. This sports event is routinely held every year in different locations. However, it was carried out online during this pandemic to implement several activities such as exhibition information, competition activities, and tourism through virtual media. This research on virtual exhibitions completed using quantitative methods of analysing virtual reality from virtual reality application at sports events—the quantitative methods used by surveying 102 participants who accessed the virtual exhibition at the sporting event. This study stated that the completeness of the information regarding competition and tourism activities and the visual appearance of the environment from the virtual exhibition had a considerable influence on participants who accessed the virtual exhibition. The participants who access the virtual exhibition shown a desire to visit the event location after accessing the online virtual exhibition. This result answers the question that the application of virtual reality in sports events can provide a different experience for participants accustomed to attending events offline but need a more realistic virtual appearance to simulate the environment where the event took place as a visual and tourism attraction.
Properties of Q-ball dark matter: moving away from flat directions

Gauge-mediated models of supersymmetry-breaking imply that stable Q-balls can form in the early universe and act as dark matter. All stable Q-balls in the MSSM are associated with one or more flat directions. We show that while Q-balls are produced from the fragmentation of a flat direction condensate, they quickly evolve to a ground state that is slightly away from this flat direction. In this process a (B+L)-ball can become electrically charged. This is a novel form of charge acquisition with important ramifications for the experimental search for Q-ball dark matter.
Controlled growth variation for the detuning of AlGaInP-based microcavity light emitting diodes

Visible top emitting microcavity light emitting diodes have been fabricated. The structure consists of two AlGaAs-AlAs Bragg reflectors surrounding an AlGaInP cavity with three GaInP quantum wells. The extraction efficiency of these structures can be maximized optimising the detuning between the quantum well emission and the cavity mode wavelength. We have grown a structure with parabolic profiles of thickness for the reflector layers only: the cavity mode wavelength was continuously shifted by 60 nm over the wafer. We measured a maximum of external quantum efficiency of 1.2% corresponding to a detuning of -12 nm in good agreement with analytical simulations. This result enabled us to estimate an internal quantum efficiency of 50% at a current density of 20 A/cm/sup 2/.
Structural Relationships between Cognitive Achievement and Learning-Related Factors among South Korean Adolescents

This study aimed to differentiate between middle and high school students by investigating the structural relationships between academic self-efficacy, academic stress, learning motivation, and learning strategies—the learning-related factors of South Korean adolescents’ learning achievements. We obtained relevant information for 4051 middle school students and 4242 high school students from the Gyeonggi Institute of Education’s three-year panel data study (2016–2018). The results showed direct and indirect influential relationships between academic self-efficacy, academic stress, learning motivation, and learning strategy. Results of the analysis conducted by separating the structural equation model into middle and high school student groups showed that both models met the goodness-of-fit indices criteria; the difference between middle and high school student group models was significant. Hence, to promote academic achievement among middle and high school students, differential assistance is needed. Middle school students should be assisted so that they have a good command of learning strategy after reducing academic stress by increasing academic self-efficacy. For high school students, management of academic stress by increasing academic self-efficacy is the most important aspect.
Deflections of Nanowires with Consideration of Surface Effects

The elementary beam model is modified to include the surface effects and used to analyze the deflections of nanowires under different boundary conditions. The results show that compared to deflections of nanowires without consideration of surface effects, the surface effects can enlarge or reduce deflections of nanowires, and nanowire buckling occurs under certain conditions. This study might be helpful for design of nanowire-based nanoelectromechanical systems.
Revisiting -Reciprocal Distance Re-Ranking for Skeleton-Based Person Re-Identification

Person re-identification (re-ID) as a retrieval task often utilizes a re-ranking model to improve performance. Existing re-ranking methods are typically designed for conventional person re-ID with RGB images, while skeleton representation re-ranking for skeleton-based person re-ID still remains to be explored. To fill this gap, we revisit the <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula>-reciprocal distance re-ranking model in this letter, and propose a generic re-ranking method that exploits the salient skeleton features to perform <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula>-reciprocal distance encoding for skeleton-based person re-ID re-ranking. In particular, we devise the skeleton sequence pooling to aggregate the most salient features of skeletons within a sequence, and combine both original Euclidean distance and <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula>-reciprocal distance to re-rank the skeleton sequence representations for person re-ID. Furthermore, we propose the context-based Rank-1 voting that jointly exploits the initial ranking list and re-ranking list to vote for the top candidate to enhance the Rank-1 matching. Extensive experiments on three public benchmarks demonstrate that our approach can effectively re-rank different state-of-the-art skeleton representations and significantly improve their person re-ID performance.
Revisiting the Multidimensional Work Motivation Scale (MWMS)

ABSTRACT This multi-sample study (5 samples) revisited the content and factor structure of the Multidimensional Work Motivation Scale (MWMS) through exploratory structural equation modelling. Specifically, the operational representation of, and the relations between, the types of behavioural regulation were investigated as was their relation to theoretical outcomes. Results suggest the removal of three problematic items and show that work motivation, as measured by the MWMS, is best represented by a factor structure reflecting autonomous motivation, introjected and external regulation as well as amotivation. Furthermore, introjected regulation is more strongly represented by its avoidance subscale, whereas the two types of external regulation (material and social) are not distinguishable. Lastly, autonomous motivation is linked to optimal employee functioning (e.g., vigor/vitality, satisfaction, lower turnover intention). The two controlled types of regulation have differentiated relations with performance, but are both linked to poor employee health and turnover intention, with (avoidance) introjected regulation being a particularly important predictor. By revisiting the content of the MWMS and cross-validating its structure in five samples, this study provides an empirically adequate representation of the types of regulation and their outcomes. Suggestions for future research aimed at improving the content of the MWMS are also offered.
Magnetic effects induced by sp impurities and defects in nonmagnetic sp materials

This paper is a review of the state-of-the-art research concerning the first-principle simulation, synthesis, properties, and application prospects of a new class of magnetic materials obtained by doping nonmagnetic sp compounds (oxides, chalcogenides, and borides of nontransition sp elements) or nanostructures (carbon, BN, AIN, and MgO nanotubes) with nonmagnetic sp impurities or nanostructures involving structural vacancies or topological defects.
Synthesis of Silver, Gold, and Platinum Doped Zinc Oxide Nanoparticles by Pulsed Laser Ablation in Water

In this paper, we propose a simple two-step method for the synthesis of Ag, Au, and Pt-doped ZnO nanoparticles. The method is based on the fabrication of targets using the pulsed laser deposition (PLD) technique where thin layers of metals (Ag, Pt, Au) have been deposited on a metal-oxide bulk substrate (ZnO). Such formed structures were used as a target for the production of doped nanoparticles (ZnO: Ag, ZnO: Au, and ZnO: Pt) by laser ablation in water. The influence of Ag, Au, and Pt doping on the optical properties, structure and composition, sizing, and morphology was studied using UV-Visible (UV-Vis) and photoluminescence (PL) spectroscopies, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and transmission electron microscopy (TEM), respectively. The band-gap energy decreased to 3.06, 3.08, and 3.15 for silver, gold, and platinum-doped ZnO compared to the pure ZnO (3.2 eV). PL spectra showed a decrease in the recombination rate of the electrons and holes in the case of doped ZnO. SEM, TEM, and AFM images showed spherical-shaped nanoparticles with a relatively smooth surface. The XRD patterns confirm that Ag, Au, and Pt were well incorporated inside the ZnO lattice and maintained a hexagonal wurtzite structure. This work could provide a new way for synthesizing various doped materials.
Relation-Shape Convolutional Neural Network for Point Cloud Analysis

Point cloud analysis is very challenging, as the shape implied in irregular points is difficult to capture. In this paper, we propose RS-CNN, namely, Relation-Shape Convolutional Neural Network, which extends regular grid CNN to irregular configuration for point cloud analysis. The key to RS-CNN is learning from relation, i.e., the geometric topology constraint among points. Specifically, the convolutional weight for local point set is forced to learn a high-level relation expression from predefined geometric priors, between a sampled point from this point set and the others. In this way, an inductive local representation with explicit reasoning about the spatial layout of points can be obtained, which leads to much shape awareness and robustness. With this convolution as a basic operator, RS-CNN, a hierarchical architecture can be developed to achieve contextual shape-aware learning for point cloud analysis. Extensive experiments on challenging benchmarks across three tasks verify RS-CNN achieves the state of the arts.
Animal welfare index: an animal welfare evaluation of beef production farms in Ireland

ABSTRACT The study objective was to examine the animal welfare status of Irish beef production farms using an animal welfare index (AWI). Beef production farms (n = 105) including suckler calf-to-beef (n = 30), suckler calf/weaning/finishing (n = 63), dairy calf-to-beef (n = 12) were assessed during the winter housing period using the AWI. Fifty-one indicators were grouped into six categories: ‘locomotion’; six indicators, ‘social interactions’; eight indicators, ‘flooring’; four indicators, ‘environment’; nine indicators, ‘stockperson’; thirteen indicators and ‘husbandry management’ eleven indicators. Two indicators relating to the size of the farm and number of animals on the farm were also collected. The overall mean AWI percentage for the suckler calf-to-beef, suckler calf/weaning/finishing, dairy calf-to-beef farms were 70.3%, 71.9% and 66.6%, respectively. There was no difference (P > 0.05) in AWI between full-time and part-time farmers. This study demonstrated the application of the AWI for use in beef production systems.
Effect of Compactiﬁed Dimensions on the Ground State Energy of the Hydrogen Atom

The three-dimensional Hydrogen atom has been explored extensively, and a wavefunction and energy expression can be found in closed form. Little work, however, has been done with higherdimensional atoms. This discussion focuses on the effects of adding first one then two compactified dimensions to a Hydrogen atom. The metric of the 4-D Hydrogen atom is taken to be R3 × S1 while the 5-D metric is taken to be R3× S2. We first determine the form of the Laplacian operator in each space and use it to find the respective atomic potentials. The variational method is used to determine an upper bound on the ground state energy as a function of the size of the extra dimension(s). Equating the 4and 5-D variational energy functions with the experimentally confirmed 3-D Hydrogen atom ground state, an upper bound on the size the compactied dimension(s) must be in order to have not yet been detected is calculated.
Tumor-Specific Monomethyl Auristatin E (MMAE) Prodrug Nanoparticles for Safe and Effective Chemotherapy

A prodrug is bioreversible medication that is specifically converted to the active drugs by enzymes overexpressed in the tumor microenvironment, which can considerably reduce the chemotherapy-induced side effects. However, prodrug strategies usually have low antitumor efficacy compared to free drugs by delayed drug release. This is because they need time to be activated by enzymatic cleavage and they also cannot be fully recovered to the active drugs. Therefore, highly potent anticancer drug should be considered to expect a sufficient antitumor efficacy. Herein, we propose tumor-specific monomethyl auristatin E (MMAE) prodrug nanoparticles for safe and effective chemotherapy. The cathepsin B-specific cleavable FRRG peptide and MMAE are chemically conjugated via one-step simple synthetic chemistry. The resulting FRRG-MMAE molecules form stable nanoparticles without any additional carrier materials by hydrophobic interaction-derived aggregations. The FRRG-MMAE nanoparticles efficiently accumulate within the tumor tissues owing to the enhanced permeability and retention (EPR) effect and inhibit the tubulin polymerization by releasing free MMAE in the cathepsin B-overexpressed tumor cells. In contrast, FRRG-MMAE nanoparticles maintain a non-toxic inactive state in the normal tissues owing to innately low cathepsin B expression, thereby reducing MMAE-related severe toxicity. Collectively, this study provides a promising approach for safe and effective chemotherapy via MMAE-based prodrug nanoparticles, which may open new avenues for advanced drug design for translational nanomedicine.
Design and Development of a Three Phase Induction Motor Drive using NI-myRIO

This paper aims to describe the design, implementation, and operation of a three-phase inverter. As a general rule, inverters are used in applications that require high power, such as industrial induction motors. This Three-phase Inverter is composed of three legs, each of which consists of two switches. As a result, there are six switches in total. Three-phase inverter circuit uses MOSFETs and IGBTs as switching devices for which a microcontroller provides gate pulses. Here, pulses are generated and given to switches employing the NI-MYRio processor. Inverters in three phases can be operated in any of two conduction modes, 180° or 120°. The operation is carried out in 180° conduction mode in this paper. It is interfaced with Mat Lab, which generates the pulses and sends them to Arduino. In the case of NI-myRIO, pulses are generated through LabVIEW software. This paper successfully implements a three-phase inverter on hardware to drive a three-phase induction motor.
ON PURE-STRATEGY EQUILIBRIA IN MATRIX GAMES

In this paper we find a sufficient condition to guarantee the existence of pure-strategy equilibria in matrix games. In the process of formulating our condition, the alternative theorem of Farkas is used. The formulated condition is necessary and sufficient to the existence of pure-strategy equilibria in undominated matrix games.
Memristor Degradation Analysis Using Auxiliary Volt-Ampere Characteristics

The memristor is one of the modern microelectronics key devices. Due to the nanometer scale and complex processes physic, the development of memristor state study approaches faces limitations of classical methods to observe the processes. We propose a new approach to investigate the degradation of six Ni/Si3N4/p+Si-based memristors up to their failure. The basis of the proposed idea is the joint analysis of resistance change curves with the volt-ampere characteristics registered by the auxiliary signal. The paper considers the existence of stable switching regions of the high-resistance state and their interpretation as stable states in which the device evolves. The stable regions’ volt-ampere characteristics were simulated using a compact mobility modification model and a first-presented target function to solve the optimization problem.
Center Loss Guided Prototypical Networks for Unbalance Few-Shot Industrial Fault Diagnosis

The success of deep learning is based on a large number of tagged data, which is challenging to satisfy on many occasions. Especially in industry fault diagnosis, considering the cost of data collection, the fault data are few and severely unbalanced. Therefore, it is not enough to support a reliable data-driven deep learning model. Few-shot learning effectively solves the few sample problems, but traditional methods pay little attention to the impact of unbalanced data. However, imbalanced data exists in large quantities. At the same time, unbalanced data often causes decision boundaries to be biased towards categories with larger sample sizes, resulting in lower accuracy. This study proposes a prototype network incorporating center loss for diagnosing industrial faults with few-shot samples. Based on the prototypical networks, by adding center loss at the loss level, the mapping points of the samples in the feature space play the role of intraclass contraction and interclass separation, thereby improving the classification effect. The experiment takes the TE process industrial data set as an example. Comparing various current few-shot learning methods reflects the superiority of the method proposed in the few-shot imbalanced scenario.