Miracle-dz/UniFAR-FTUs huggingface dataset:
A Deep Multi-View Framework for Anomaly Detection on Attributed Networks (Extended Abstract)

Many existing anomaly detection methods on attributed networks do not seriously tackle the inherent multi-view property in attribute space but concatenate multiple views into a single feature vector, which inevitably ignores the incompatibility between heterogeneous views caused by their own statistical properties. In practice, the distinct but complementary information brought by multi-view data promises the potential for more effective anomaly detection than the efforts only based on single-view data. Furthermore, abnormal patterns naturally behave diversely in different views, which coincides with people’s desire to discover specific abnormalities according to their preferences for views (attributes). Most existing methods cannot adapt to people’s requirements as they fail to consider the idiosyncrasy of user preferences. Thus, in this paper, we propose a multi-view framework ALARM to incorporate user preferences into anomaly detection and simultaneously tackle heterogeneous attribute characteristics through multiple graph encoders and a well-designed aggregator that supports self-learning and user-guided learning. Experiments on synthetic and real-world datasets corroborate the desirable performance of ALARM and its effectiveness in supporting user-oriented anomaly detection.
Optimal Allocation of EV Charging Stations to Support Vast Internal Combustion Engine Vehicle Replacement

Global warming has become a serious issue throughout the entire world. It is mainly caused by environmental pollution from burning fossil fuels. According to the California Air Resources Board, transportation is the state's single largest source of global warming emissions and air pollution. The policymakers proposed a plan that 100% of new cars and light trucks sold in California would be zero-emission vehicles, such as electric vehicles (EVs), by 2035. In this scenario, finding optimal locations of EV charging stations (EVCSs) is highly manifested to support transition to EVs from internal combustion engine vehicles. EV integration into the existing power distribution system will help reduce not only environmental emissions but also operational costs for the utility companies, which leads to financial incentives for the EV owners and general public. This research presents ideas of identifying the optimal locations, finding appropriate charging capacities based on the types of vehicles, and improving operational performance of distribution systems. In addition, EVCSs can work in a hybrid manner where electricity is provided by utilities, solar energy, and energy storage units. By adopting the concept of microgrids, EV owners charge their vehicles during off-peak hours and unload the energy back to the grid during peak hours at higher prices. Utility companies utilize the energy to further reduce their dependency on fossil fuels to provide electricity. The PG&E 69-bus distribution system is used to find the optimal location of charging stations. The operational costs and emissions are evaluated to improve the operational performance.
An Optimal Methodology for Mitigating the Impacts of EVs and Solar Systems on the Grid by Utilizing Existing Residential Battery Storage Capacity With No Further Grid Upgrades

High penetration of distributed energy resources creates power quality problems such as voltage deviations and power loss on the distribution network. This paper proposes a methodology to improve voltage deviations and decrease power losses caused by solar systems and EV chargers by allocating Permitted Percentage (PP) of battery-based solar systems of residences with already available storage capacity. This methodology enables the utilities to deploy PP for sending charging/discharging commands to improve the grid's power quality. The simulation results of the proposed model were tested in the IEEE 33-bus distribution network. Particle swarm optimization was used to find the optimum charging/discharging commands from the utility for the storages. The effectiveness of the proposed model was shown by determining the capacity of a different combination of PP, and ratios between non-battery- based and battery-based solar residences in the improvement of voltage deviation and power loss of the distribution network.
Narrative Review of Use and Continued Relevance of the Maternal Infant Responsiveness Instrument

Background: The Maternal Infant Responsiveness Instrument (MIRI) was developed in 2002 to measure a critical aspect of maternal-infant health. The objective of this analysis was to examine use, results, and continued relevance of the MIRI 20 years after its creation. Methods: For the completion of this narrative review, 5 electronic databases were accessed using key search terms. Inclusion criteria were English-language, peer-reviewed research using the MIRI. Hand searches of reference lists were conducted. Five authors performed screening, data extraction, appraisal, and summarized findings. Results: Fifteen studies were included. All studies reported an internal consistency of α > 0.70 for the MIRI. Positive correlations were reported with self-efficacy, infant temperament, and life satisfaction. Inverse relationships were reported with stress, depression, and experiential avoidance. Depressive symptomatology, life satisfaction, self-esteem, self-efficacy, and previous childcare experience were predictors of maternal responsiveness. Discussion: Maternal well-being (postpartum depression and stress) can affect maternal responsiveness. Given the pervasive disparities in maternal health and well-being, it is important to have reliable measures of the effects of those disparities. The MIRI, a valid and reliable measure, may be useful for assessing the effectiveness of interventions designed to improve infant and maternal well-being.
Research on Perception and Control Technology for Robot Dexterous Operation

— In an unstructured environment, multiple objects are closely arranged, which leads to the complexity of robot grasping. Deep reinforcement learning(DRL) can take long - term reasoning, and make better and more robust decisions in a series of decisions, allowing the robot to continuously learn from its own experience. In this paper, we demonstrate that a new deep reinforcement learning algorithm based on Q - learning and attention mechanisms can effectively solve the robot grasping problem. In addition, we present a grasp and move strategy that reduces complexity by replacing hand - designed features with data - driven ones. The robot is used to move the objects to create a larger grasping space when the objects are densely distributed to improve the grasping success rate. The application of the proposed model on a simulated UR5 robot manipulator demonstrates the effectiveness and stability of the model. The results show that our proposed method outperforms the baseline framework in terms of grasping accuracy and efficiency.
Towards Developing a Measure to Assess Contagiousness of Toxic Tweets

Toxicity is rampant on social media platforms. In this study, we use COVID-19 datasets discussing the use of face masks, vaccines, 5G, and Bill Gates conspiracy theories to examine the contagiousness of tweets with hateful or toxic content. While the majority of people believe that face masks or vaccines are effective in fighting against COVID-19, a smaller minority do not. Another major issue during the pandemic was the conspiracies surrounding 5G technology and Bill Gates. Studies indicate that the worries surrounding mobile technology have fueled certain conspiracy theories linking 5G and Bill Gates with the COVID-19 virus. Using these polarizing datasets, we measure the type and intensity of hate speech in each dataset. Then we propose a definition for a toxicity contagiousness score to study the propagation of toxicity in each dataset. Our study revealed that in the 5G dataset, low toxic content has a positive correlation with the conta-giousness score. Highly toxic content in the Bill Gates and pro-mask datasets also showed a positive correlation. However, in the anti-community dataset, such as anti-mask and anti-vaccine, highly toxic content had a negative correlation with the contagiousness score. These findings shed light on how different types of content and contexts can influence the spread of toxicity in online communities.
Visual Autism

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder characterized by deficits in social communication and restricted, repetitive behaviors. It affects approximately 2.2% of children. Both genetic and environmental risk factors have been identified for ASD. Visual comorbidities are relatively common among children with ASD. Between 20 and 44% of ASD children have visually significant refractive error, on-third have strabismus, and one-fifth have amblyopia. In addition, ASD is 30 times more common in children with congenital blindness. It is unknown whether the association of ASD with visual morbidity is causal, comorbid, or contributing. Structural and functional abnormalities have been identified in MRIs of ASD children, and ASD children have been noted to have aberrant eye tracking. ASD children with visually significant refractive errors and poor spectacle compliance (present in 30% of ASD children) offer the opportunity for investigation into how improved visual acuity influences ASD behaviors. In this review, we focus on what is known of the visual system, refractive surgery, and ASD.
Coherent coupling in light-matter systems

The strength of interaction between light and matter states is characterised by the Rabi frequency Ω which describes the rate at which they exchange energy. When Ω exceeds the system linewidth then the system is correctly described by dressed eigenstates of the coupled light-matter system. This is the strong coupling regime. Strong coupling has been demonstrated at the surface of polar dielectrics between phonon oscillations of the ionic species and light resulting in evanescent field confinement in modes termed surface phonon polaritons (SPhPs ). Recent fabrication advances allow for creation of user defined SPhP resonators that support sub-diffraction SPhPs confined in three dimensions. We present a numerical study of these localised SPhP resonances in subwavelength cylindrical SiC resonators finding modes with long lifetimes and strong electric field enhancements. Additionally we investigate numerically and experimentally interactions between the localised SPhPs and the delocalised SPhP of a planar SiC interface demonstrating that this can also be coherent. Strong light-matter coupling is also possible when a material with an resonant electronic transition such as an organic semiconductor is sandwiched in a planar optical microcavity. By employing a molecule with a broad electronic transition it is possible to reach the ultrastrong coupling (USC) regime where the coupling frequency becomes an appreciable fraction of the bare frequency and new physics is predicted. We investigate experimentally the electroluminescence properties of an optical microcavity in this regime utilising for the active layer the oligomer TDAF. We demonstrate light-matter couplings exceeding 20% of the bare resonant frequencies. Our bias resolved measurements allow for conclusions about the process of polariton formation under electrical pumping to be drawn. Finally we present a method to describe the coupled eigenstates in arbitrary, inhomogeneous dielectric environments. By following Hopfield procedure we show that it is possible to diagonalise and correctly quantise the modes of the system. We also show how this model can be extended to include losses and illustrate an application to the specific case of the SPhP at a planar interface.
Accessibility and effectiveness of mechanical thrombectomy for ischaemic stroke in Latin American countries: a rapid review of the literature

Introduction. Stroke constitutes a major cause of death and disability in Latin America. Although the number of stroke survivors has increased in recent decades, a small proportion receives the appropriate treatment. Mechanical thrombectomy (MT) revolutionised stroke management by treating patients within a 24-hour window period, compared to the usual 4.5 hours with intravenous recombinant tissue plasminogen activator (IV rtPA). Objective. To evaluate the current status of mechanical thrombectomy in Latin American countries regarding availability, accessibility, effectiveness, and cost-utility. Methods. A rapid review of the literature was performed by identifying papers published in MEDLINE in English or Spanish from 2015 to current. Reference list search complemented the database research. Included studies were randomised controlled trials and observational studies. Data extraction was performed by one reviewer, and data synthesis was performed following the SWIM guidelines. Results. 10 studies were included. Only one study was a randomised controlled trial. Studies reported that MT is available in Latin American countries. The proportion of treated patients varied from 3% to 19.9%. Recanalisation rates were above 69% in all studies, while functional in-dependence (mRS 0-2) varied from 25% to 50%. Financial barriers were considered as the main limiting factor to access MT. No study realised a cost-utility analysis. Conclusion. Evidence of the efficacy and effectiveness of MT and its main barriers to access is consistent among Latin American countries. Further research
Performance Analysis of Patch Antenna Using Slot Shaped Metasurface

 Abstract : Performance of a polarization reconfigurable antenna using Metasurface is analyzed. A patch antenna along with a metasurface (MS) is called Polarization Reconfigurable Metasurfaced Antenna (PRMS). The MS of circular shape with a rectangular slot is placed above the circular patch antenna having a circular substrate. By rotating the MS mechanically with respect to the patch antenna, the polarization of the antenna is reconfigured to Linear polarization (LP) and circular polarization (CP). The diameter of the MS and substrate of the patch antenna is 80mm. The radius of the patch is 16.65mm. The radiation pattern and reflection coefficient (S11) is analyzed. The gain and bandwidth of the patch antenna is improved by using a MS. Results show that the PRMS antenna in circular polarization achieves an operating bandwidth of 2.4 -3GHz.
Information and the Reconstruction of Quantum Physics

The reconstruction of quantum physics has been connected with the interpretation of the quantum formalism, and has continued to be so with the recent deeper consideration of the relation of information to quantum states and processes. This recent form of reconstruction has mainly involved conceiving quantum theory on the basis of informational principles, providing new perspectives on physical correlations and entanglement that can be used to encode information. By contrast to the traditional, interpretational approach to the foundations of quantum mechanics, which attempts directly to establish the meaning of the elements of the theory and often touches on metaphysical issues, the newer, more purely reconstructive approach sometimes defers this task, focusing instead on the mathematical derivation of the theoretical apparatus from simple principles or axioms. In its most pure form, this sort of theory reconstruction is fundamentally the mathematical derivation of the elements of theory from explicitly presented, often operational principles involving a minimum of extra‐mathematical content. Here, a representative series of specifically information‐based treatments—from partial reconstructions that make connections with information to rigorous axiomatizations, including those involving the theories of generalized probability and abstract systems—is reviewed.
Micro, Small and Medium Enterprises (MSMEs) financing, employment and national economic welfare in Nigeria

This study examines the effect of Micro, Small and Medium Enterprises (MSMEs) financing on employment and national economic welfare in Nigeria from 1980 – 2020 using the Autoregressive Distributed Lag (ARDL) technique. MSMEs financing was measured by government loans to MSMEs, while employment was measured by unemployment. Empirical results show that the effect of MSMEs on unemployment was negative and insignificant in the long run and negative and significant in the short run. It was also found that government external debt and labour force participation had a positive and insignificant effect on unemployment in the long and short run. Real GDP growth (annual %) had a negative and significant effect on unemployment in the long and short runs. The findings also showed that MSMEs had a positive effect on economic welfare in the long and short-run but the long-run effect was insignificant, while the short run was significant. On the other hand, the effect of government external debt and labour force participation on economic welfare was found to be negative and insignificant in the long and short run. However, inflation hurt economic welfare in the long and short-run but the effect was significant in the long run and insignificant in the short run. The government should ensure that funds set aside for MSMEs development get to them. Also, training MSMEs periodically on entrepreneurship management is recommended. Laws can be made to guide against the underemployment of labour by the private sector and control the engagement of the labour force.
The Inﬂuence of Parents’ Socio-Rconomic Status on Student Academic Achievement at Vocational Schools

Thisstudyaddresseswhether parents’ socioeconomic statusinﬂuences their children’s academic achievement in a speciﬁc context: 10th graders at a vocational high school in Makassar City. The study employs the ex-post facto research method and a quantitative strategy, employing multiple linear regression analysis to test the hypotheses. The population of the study is the 132 10th-grade students at the vocational high school, and a sample of 62 students is selected at random using a systematic sampling method. Documentation and questionnaires are used to collect data, with the questionnaire used to collect information about parents’ socioeconomic status and student achievement. This study is expected to contribute to understanding the factors inﬂuencing student achievement, particularly socioeconomic status. By examining the relationship between parents’ socioeconomic status and student achievement, the study may identify potential intervention areas to improve student academic outcomes. In addition, the study’s use of multiple linear regression analysis to examine the effect of parents’ socioeconomic status on student achievement contributes to the literature on this topic and makes a methodological contribution to education research. This study can potentially inform educational policies and interventions to improve students’ academic performance from diverse socioeconomic backgrounds. It also demonstrates the importance of contextual factors when examining the relationship between parental socioeconomic status and student achievement.
Linear instability of low Reynolds number massively separated flow around three NACA airfoils

Two- and three-dimensional modal and non-modal instability mechanisms of steady spanwise-homogeneous laminar separated flow over airfoil profiles, placed at large angles of attack against the oncoming flow, have been investigated using global linear stability theory. Three NACA profiles of distinct thickness and camber were considered in order to assess geometry effects on the laminar–turbulent transition paths discussed. At the conditions investigated, large-scale steady separation occurs, such that Tollmien–Schlichting and cross-flow mechanisms have not been considered. It has been found that the leading modal instability on all three airfoils is that associated with the Kelvin–Helmholtz mechanism, taking the form of the eigenmodes known from analysis of generic bluff bodies. The three-dimensional stationary eigenmode of the two-dimensional laminar separation bubble, associated in earlier analyses with the formation on the airfoil surface of large-scale separation patterns akin to stall cells, is shown to be more strongly damped than the Kelvin–Helmholtz mode at all conditions examined. Non-modal instability analysis reveals the potential of the flows considered to sustain transient growth which becomes stronger with increasing angle of attack and Reynolds number. Optimal initial conditions have been computed and found to be analogous to those on a cascade of low pressure turbine blades. By changing the time horizon of the analysis, these linear optimal initial conditions have been found to evolve into the Kelvin–Helmholtz mode. The time-periodic base flows ensuing linear amplification of the Kelvin–Helmholtz mode have been analysed via temporal Floquet theory. Two amplified modes have been discovered, having characteristic spanwise wavelengths of approximately 0.6 and 2 chord lengths, respectively. Unlike secondary instabilities on the circular cylinder, three-dimensional short-wavelength perturbations are the first to become linearly unstable on all airfoils. Long-wavelength perturbations are quasi-periodic, standing or travelling-wave perturbations that also become unstable as the Reynolds number is further increased. The dominant short-wavelength instability gives rise to spanwise periodic wall-shear patterns, akin to the separation cells encountered on airfoils at low angles of attack and the stall cells found in flight at conditions close to stall. Thickness and camber have quantitative but not qualitative effect on the secondary instability analysis results obtained.
psychmeta: An R Package for Psychometric Meta-Analysis

Over the past four decades, psychometric meta-analysis (PMA) has emerged a key way that psychological disciplines build cumulative scientific knowledge. Despite the importance and popularity of PMA, software implementing the method has tended to be closed-source, inflexible, limited in terms of the psychometric corrections available, cumbersome to use for complex analyses, and/or costly. To overcome these limitations, we created the psychmeta R package: a free, open-source, comprehensive program for PMA.
SOCIAL NETWORK NODES RANKING IN TERMS OF LOGARITHMIC FUNCTION OF ITS LINK WEIGHTS

Social networks are the basis of all interactions among its participants (usually people), which happen in the process of transmitting information. Lately this term is becoming more and more popular, but hardly anyone can really imagine how much it surrounds us. Social type networks are represented by means of graphs and node connections, which reflect real cooperation. It is necessary to conduct the detailed network analysis, evaluate the results by all specified standards and separate the most important nodes for ranking them in these networks. Existing ranking algorithms mainly evaluate everything in general, which does not allow to clearly recognise the consequence of nodes inter se. In the given article we provide the analysis of work educts of well-known node ranking algorithms (HITS, PageRank) and compare obtained data with expert network evaluation. Big amount of nodal connections in social networks and their various configuration in most cases do not allow to use the base type ranking algorithms, since the neglect of seemingly irrelevant connections induces false results. The base type algorithm HITS was adjusted for efficiency of the quasiheirarchic networks research. It allows to perform analysis and node ranking based on specified criteria (the amount of input and output connections inter se), which corresponds with the results of expert evaluation. It is displayed, that in some cases the received method offers corresponding with real social relations between subjects insights, and exponents of node authorships with previously provided social roles. Received algorithm allows to evaluate and educe the most relevant nodes in social character networks. It can be used in various spheres, where social networks are formed.