Miracle-dz/UniFAR-FTUs huggingface dataset:
The Market Inside the Market: Odd-Lot Quotes

We show how current market practices relating to odd lot quotes result in a large “inside” market where for many stocks better prices routinely exist relative to the National Best Bid or Offer (NBBO). We provide strong evidence that being able to see these odd lot quotes provides valuable information to traders with access to proprietary data feeds. We develop a XGBoost machine learning prediction algorithm that uses odd lot data to predict future prices, and demonstrate a simple and profitable trading strategy using odd lot data. We show that the SEC’s new approach of changing the definition of a round lot reduces, but does not ameliorate, the high incidence of superior odd lot quotes within the NBBO. JEL classification: G14, G21, G23, G24
Influence of Parameters of Boundary Electromagnetic Pulse Simulator on Transmitting Mode

Parameters of bounded-wave electromagnetic pulse(EMP) simulator influence transmitting mode of electromagnetic wave in working region of bounded-wave electromagnetic pulse simulator,such as the length and width of bounded-wave electromagnetic pulse simulator,dielectric constant and conductance of loss soil under bounded-wave electromagnetic pulse simulator.In order to obtain the influential coefficients on transmitting mode of all parameters of bounded-wave electromagnetic pulse simulator,in this paper,a numerical analysis model is put forward based on the finite difference time domain(FDTD) method.Comparative magnitude between three electric fields components,comparative magnitude between three magnetic fields components and approximate quantity to transverse electromagnetic wave(TEM) are achieved under all influential parameters using the FDTD numerical model,the results indicate the transmitting mode of electromagnetic wave in working region may infinitely be close to TEM mode if the width of working region of bounded-wave EMP simulator becomes infinite,and comparative magnitude of electromagnetic filed components become smaller with the length and width of working region increasing,especially the width of working region more severely affects transmitting mode and comparative magnitude of electromagnetic filed components,dielectric constant of loss soil doesn't basically affect comparative magnitude of all electromagnetic fields components and transmitting mode of electromagnetic wave in working region,transverse electric filed component gradually increases with conductance of loss soil increasing.It can be concluded that the width of working region and the conductance of loss soil are primary parameters which affecting transmitting mode of electromagnetic wave in working region by calculated results,which can be used to design bounded-wave electromagnetic pulse simulator.
Emotion recognition in election day tweets using optimised kernel extreme learning machine classifier

ABSTRACT Today, microblogging has turned into a very well-known specialised device among web clients. A huge number of clients share ideas on various aspects of daily life. In this manner these sites are rich sources of information utilised with the goal of sentiment investigation. This investigation is essentially valuable as well as challenging since everybody consistently need to know the views of existing clients about an item or service. In this article, the most prominent microblogging platform ‘Twitter’ is selected for the investigation of sentiment classification and mining opinions. This is helpful for shoppers who need to enquire about items before purchase, or organisations that need to screen the open assumption of their brands. A unique approach is presented for classifying the feeling of Political Twitter messages into Happy, Extremely Happy, Sad, Extremely Sad or else Neutral. There are numerous devices that give computerised opinion investigation. The dataset used here is the Twitter corpus Dataset named 2016 Political Election day tweets gathered using the Twitty and Simulation apparatus utilised in this examination is PYTHON. Utilising the corpus, sentiment classifier named Kernel Extreme Learning Machine (KELM) optimised by Salp Swarm Algorithm (SSA) determines the class of political tweets as Happy, Extremely Happy, Sad, Extremely Sad and Neutral Sentiments. This work mainly focus on English tweets. The proposed KELM classifier performance is compared with existing classifier approaches and noted with highest accuracy which defines the effective nature of the classifier. Moreover, test evaluation demonstrate that the proposed procedure is effective and performs superior to recently proposed works.
Reversible and irreversible gas-particle partitioning of dicarbonyl compounds observed in the real atmosphere

Abstract. Glyoxal and methylglyoxal are vital carbonyl compounds in the atmosphere and play substantial roles in radical cycling and ozone formation. The partitioning process of glyoxal and methylglyoxal between the gas and particle phase via reversible and irreversible pathways could efficiently contribute to secondary organic aerosol (SOA) formation. However, the relative importance of two partitioning pathways still remain elusive, especially in the real atmosphere. In this study, we launched five field observations in different seasons and simultaneously measured glyoxal and methylglyoxal in the gas and particle phase. The field-measured gas-particle partitioning coefficients were 5–7 magnitudes higher than the theoretical ones, indicating the significant roles of reversible and irreversible pathways in the partitioning process. The particulate concentration of dicarbonyls and product distribution via the two pathways were further investigated using a box model coupled with the corresponding kinetic mechanisms. We recommended the irreversible reactive uptake coefficient γ for glyoxal and methylglyoxal in different seasons in the real atmosphere, and the average value of 8.0 × 10−3 for glyoxal and 2.0 × 10−3 for methylglyoxal best represented the the loss of gaseous dicarbonyls by irreversible gas-particle partitioning processes. Compared to the reversible pathways, the irreversible pathways played a dominant role, with a proportion of more than 90 % in the gas-particle partitioning process in the real atmosphere and the proportion was significantly influenced by relative humidity and inorganic components in aerosols. However, the reversible pathways were also substantial, especially in winter, with a proportion of more than 10 %. These two pathways of dicarbonyls jointly contributed to more than 25 % of SOAs in the real atmosphere. To our knowledge, this study was the first to systemically examine both reversible and irreversible pathways in the ambient atmosphere, strove to narrow the gap between model simulations and field-measured gas-particle partitioning coefficients, and revealed the importance of gas-particle processes for dicarbonyls in SOA formation.
Malware Detection and Classification in IoT Network using ANN

Internet of Things is an emerging technology in the modern world and its network is expanding constantly. Meanwhile, IoT devices are a soft target and vulnerable to attackers. The battle between malware attackers and security analysts is persistent and everlasting. Because malware is evolving constantly and thus asserting pressure on researchers and security analysts to cope up with modern threats by improving their defense systems. Complexity and diversity of current malicious software present immense challenges for protecting IoT networks from malware attacks. In this paper, we have explored the potential of neural networks for detection and classification of malware using IoT network dataset comprising of total 4,61,043 records with 3,00,000 as benign while 1,61,043 as malicious. With the proposed methodology, malware is detected with an accuracy of 94.17% while classified with 97.08% accuracy
Assessing the Efficacy of the Concept of Judicial Accountability Through the Lens of the Constitution of Pakistan

Superior Courts judges are expected to have a higher standard of conduct. It is necessary for the judiciary as an institution, to maintain its probity and independence. The proposition that the Superior Court Judge is only responsible for his conduct and not that of his independent wife and children. This study makes clear that Judges are supposed to know the interests of members of their families in monetary terms. This work further explores an appealing hypothesis that the President should act in his discretion when authorizing an investigation against a Superior Court Judge under Article 48(2). The study concluded that under the Constitutional process for performing the executive function of authorizing an investigation into information against a Superior Court Judge, the President should act on the advice of the PM or the Cabinet under Article48(1) of the Constitution and not invoke his discretionary power under Article 48(2).
Anti-allergic Effects Of Fertilized Red Ginseng Marc On 2,4-dinitrochlorobenzene-induced Atopic Dermatitis-like Mice Model

Atopic dermatitis (AD) is a chronic and allergic skin disease, however, there is no cure for the disease. Many studies have shown anti-AD potentials of red ginseng, while red ginseng marc (RGM) remained after the ginseng extraction is discarded as industrial waste. However, it is recently reported that RGM, particularly fermented RGM (fRGM), still contains the bioactive properties. Thus, anti-allergic effects of fRGM were examined in 2,4-dinitrochlorobenzene-induced AD-like mice model. The model was topically treated with distilled water (control), dexamethasone, or fRGM for six weeks. The treatments of fRGM alleviated the skin lesions and reduced serum IgE levels, compared with the control. The fRGM also reduced skin levels of lipid peroxidation and superoxide anion, however, increased glutathione contents, with down-regulated gene expressions for inflammatory mediators. The histopathological analyses demonstrated that fRGM suppressed the epidermal thickening, collagen deposition, and inflammatory cell and mast cell infiltration, which involved the anti-inflammatory, anti-oxidant, and anti-apoptotic effects. Further, fRGM suppressed hypertrophic changes and inflammatory responses in the spleen and lymph node. The beneficial effects were observed in the dexamethasone and fRGM groups, however, the antioxidant effects were evident only in the fRGM treatments. These provide useful information for developing fRGM as therapeutic sources for AD.
CenGCN: Centralized Convolutional Networks with Vertex Imbalance for Scale-Free Graphs

Graph Convolutional Networks (GCNs) have achieved impressive performance in a wide variety of areas, attracting considerable attention. The core step of GCNs is the information-passing framework that considers all information from neighbors to the central vertex to be equally important. Such equal importance, however, is inadequate for scale-free networks, where hub vertices propagate more dominant information due to vertex imbalance. In this paper, we propose a novel centrality-based framework named CenGCN to address the inequality of information. This framework first quantifies the similarity between hub vertices and their neighbors by label propagation with hub vertices. Based on this similarity and centrality indices, the framework transforms the graph by increasing or decreasing the weights of edges connecting hub vertices and adding self-connections to vertices. In each non-output layer of the GCN, this framework uses a hub attention mechanism to assign new weights to connected non-hub vertices based on their common information with hub vertices. We present two variants CenGCN_D and CenGCN_E, based on degree centrality and eigenvector centrality, respectively. We also conduct comprehensive experiments, including vertex classification, link prediction, vertex clustering, and network visualization. The results demonstrate that the two variants significantly outperform state-of-the-art baselines.
3D Reconnection Geometries With Magnetic Nulls: Multispacecraft Observations and Reconstructions

Magnetic reconnection is universal in various plasma environments like the solar atmosphere, planetary magnetosphere, and laboratory to trigger explosive phenomena. Its nature and magnetic structure in two dimensions (2D) have been abundantly analyzed. The three‐dimensional (3D) characteristics of reconnection are different from 2D, and the mysteries of its 3D geometry are under exploration. A critical character in 3D is the presence of magnetic nulls, which is essential when the magnetic field topology is changing. The four identical spacecraft from the Cluster mission enable several methods for analyzing and visualizing the 3D nature of the magnetic structure. In this paper, we focus on reviewing the magnetic topology of the reconnection geometry containing 3D magnetic null points. Applying the fitting‐reconstruction method to Cluster data, magnetic null pairs or multiple magnetic nulls linked by separators or helically wrapped spines are found in the reconnection diffusion region and turbulent outflow region. The reconstructed magnetic structures show that the 2D features are parts of local approximations of the 3D geometries. The 2D regimes of antiparallel and component reconnection can simultaneously occur in 3D separator reconnection. The flux ropes are formed along the spine line or in a region enclosed by wrapped fan surfaces in the presence of spiral null points.
Influence of Social Media on Psychological Distress Among Youth: A Case Study of Instagram

This study investigates the role of Instagram causing psychological distress among youth. Instagram is an application through which a person can share photos online and edit them by using different filters that are also available within the application. It is a social networking service that provides a platform to a person to share their images easily with their friends or followers. Understanding the impact of Instagram on youth's well-being has become a priority due to a simultaneous increase in mental health problems. The researcher applied the theory of social comparison. The researcher used the quantitative methodology to obtain results which were further analyzed statistically. Data was collected from 250 respondents using the survey as a tool for data gathering. The general findings of the study show Instagram causes psychological distress among youth. It also highlighted the kind of posts and stories that caused is tress among youth.
Scaling the Unpleasantness of Sounds According to the BTL Model: Ratio-Scale Representation and Psychoacoustical Analysis

Summary The goal of the present study was to determine, (1) whether auditory unpleasantness is jugded consistently across a wide range of acoustic stimuli, and (2) which sound features contribute to that sensation. To that effect, all possible paired comparisons on a heterogeneous set of ten environmental sounds were collected from 60 listeners. The judgments conformed with the highly restrictive BTL model [1], thus justifying a ratio-scale representation of perceived unpleasantness. The resulting scale values varied by a factor exceeding 100 (boat diesel vs. jackhammer). While they were not predicted by differences in A-weighted sound pressure level, a linear combination of the psychoacoustic parameters of roughness and sharpness accounted for more than 94% of the variance in perceived unpleasantness.
Flexibly Controlling the Polycrystallinity and Improving the Foaming Behavior of Polylactic Acid via Three Strategies

Controlling foamability plays the central role in preparing PLA foams with high performances. To achieve this, chain extension was often used to improve the rheological property of PLA resins; however, despite the availability of this approach, it often deteriorates the biodegradability of PLA and greatly increases the processing cost and complexity. Hence, we reported a special crystallization induction method to design PLA foams with a tunable cellular structure and a high expansion ratio. A novel crystallization-promoting agent combination (D-sorbitol, CO2, and phenylphosphonic acid zinc salt) was used to induce PLA to enhance the chain interaction force and chain mobility and to provide crystallization templets. A series of PLAs with tunable stereocomplex (Sc)/α crystallinity and rapid non-isothermal crystallization ability were obtained. The effect of various crystallization properties on the foaming behavior of PLA was studied. The results demonstrated that proper crystallization conditions (a small spherulite size, a crystallinity of 6%, and rapid crystallization ability) could virtually contribute to the optimized cellular structure with the highest cell density of 4.36 × 106 cell/cm3. When the Sc crystallinity was above 10%, PLA had a superior foamability, which thereby resulted in a high foaming expansion ratio of 16.2. A variety of cellular morphologies of PLA foams could be obtained by changing the foaming temperature and the crystallization property. The proposed crystallization-induced approach provided a useful method for controlling the cellular structure and the performances of the PLA foams.
Research on Robot Fuzzy Neural Network Motion System Based on Artificial Intelligence

An intelligent controller based on a self-learning interval type-II fuzzy neural network is proposed to make the motion controller of the industrial intelligent robot with good adaptability. This controller has a parallel structure and contains an interval type-II fuzzy neural network and a conventional PD controller. For the design of the interval type-II fuzzy neural network, the interval type-II fuzzy set is established using the slave design method. In the design process of the interval type-II fuzzy set of the front piece, a dual sequence symmetric trapezoidal subordinate function arrangement method is proposed, which makes the self-learning law and stability analysis of the system in an analytic form and facilitates the implementation of the algorithm in hardware. In the design of the neural network self-learning law, a parametric self-learning algorithm based on sliding mode control theory is established to adjust the structural parameters of the interval type-II fuzzy neural network online, and the stability of the system is proved by using Lyapunov's stability theorem. Three sets of validation simulation experiments are given in conjunction with the trajectory tracking problem of the Delta parallel robot. The simulation results show that, in the presence of system uncertainty, the intelligent controller based on interval self-learning interval type-II fuzzy neural network can significantly improve the trajectory tracking accuracy and robustness of the system and make the control system highly adaptable to the environment. Experiments of intelligent control system based on self-learning interval type-II fuzzy neural network and experiments of reusable particle swarm optimal motion planning method are designed, and the effectiveness of the intelligent control system and motion planning method is verified on the experimental platform. The experimental results show that the intelligent control system based on the self-learning interval type-II fuzzy neural network can effectively improve the accuracy and stability of robot trajectory tracking control, and the reusable particle swarm optimal motion planning method can quickly solve the robot motion planning problem with complex constraints online.
Evaluation of Upper Limb Joint Contribution to Racket Head Speed in Elite Tennis Players Using IMU Sensors: Comparison between the Cross-Court and Inside-Out Attacking Forehand Drive

This study aimed to quantify and compare the upper limb angular kinematics and its contributions to the racket head speed between the cross-court (CC) and inside-out (IO) attacking tennis forehand of elite tennis players in a competitive environment. A new approach was used to study the forehand drive with mini-inertial sensors of motion capture to record the kinematic data. Six strokes in each direction per participant (72 shots in total) were chosen for analysis. Upper limb kinematics were calculated in the Visual 3D platform (Visual 3D Professional V5.01.21, C-motion, Germantown, MD, USA). The method used to calculate the upper limb’s contributions was performed with MATLAB software and used the segment’s (upper arm, forearm and hand) angular velocities and their respective displacement vectors obtained through the inertial sensors. Upper limb kinematics demonstrated a higher shoulder rotation in the IO direction with significant differences at the end of the backswing, which could be a key factor in distinguishing the two directions of the shot. Results also demonstrated that the horizontal flexion of the upper arm (around the shoulder joint) was primarily responsible for the racket velocity in the anteroposterior direction (48.1% CC and 45.2% IO), followed by the extension of the forearm (around the elbow joint) (17.3% CC and 20.9% IO) and the internal rotation of the upper arm (around the shoulder joint) (15.6% CC and 14.2% IO). No significant differences were shown in the contributions of upper limbs to the racket head velocity between the two directions of the shot. Tennis coaches and players should develop a specific training programme to perform higher angular velocities in these specific joint rotations.
Mapping the connections of health professionals to COVID-19 myths and facts in the Australian Twittersphere

ABSTRACT The spread of COVID-19 misinformation on social media has elicited concern amongst scholars, health agencies and governments owing to its potential harms to public health. This article addresses the question of how networks of Australian health professionals engaged with COVID-19 facts and myths on Twitter between August and October 2020. After reviewing selected literature on COVID-19 misinformation, we present our analytical choices and the methodology we used to constitute datasets of COVID-19 factual and mythical hashtags and of verified Australian health professional accounts (N:377). The article distinguishes between the capacities of ‘actor-actants’ and ‘issue-actants,’ and between the adoption of ‘field’ and ‘contested’ hashtags during a controversy. We identify categories of Australian health professional Twitter accounts such as GPs, nurses, specialists, public health professionals and researchers, and analyse the patterns of connections between these actor-actants and COVID-19 facts and myths. We find that these categories exhibit clearly distinct behaviour when tweeting or retweeting factual and mythical hashtags. Even though the rate of Australian health professionals’ connection with myths in comparison to facts on Twitter is low, hashtags such as #hydroxychloroquine attracted significant engagement. We examine these hashtags’ context and find that they were mainly being debunked, though a minority of accounts endorsed them. We analyse these adoption patterns, and critically assess the ‘echo chamber effect. ’ We also consider public health and privacy implications for the dissemination of accurate information, for trust in health professionals during a pandemic, and for combatting misinformation.
DESENVOLVIMENTO DE Talinum Fruticosum (L.) Juss. SOB INCIDÊNCIA DIRETA DA RADIAÇÃO E EM AMBIENTE PROTEGIDO

O gênero Talinum pertence à família Talinaceae, agrupada anteriormente nafamília Portulacaceae (SOUZA; LORENZI, 2000). De acordo com Arantes (2019), aespécie Talinum fruticosum (L.) Juss é uma Planta Alimentícia Não Convencional(PANC), possivelmente originária da América do Sul. Porém, discute-se também apossibilidade da origem Africana (AGBONON et al., 2010).