Cheating among elementary school children: A machine learning approach

Academic cheating is common, but little is known about its early emergence. It was examined among Chinese second to sixth graders (N = 2094; 53% boys, collected between 2018 and 2019) using a machine learning approach. Overall, 25.74% reported having cheated, which was predicted by the best machine learning algorithm (Random Forest) at a mean accuracy of 81.43%. Cheating was most strongly predicted by children's beliefs about the acceptability of cheating and the observed prevalence and frequency of peer cheating at school. These findings provide important insights about the early development of academic cheating, and how to promote academic integrity and limit cheating before it becomes entrenched. The present research demonstrates that machine learning can be effectively used to analyze developmental data.     

Disambiguation and co-authorship networks of the U.S. patent inventor database (1975–2010)

Research into invention, innovation policy, and technology strategy can greatly benefit from an accurate understanding of inventor careers. The United States Patent and Trademark Office does not provide unique inventor identifiers, however, making large-scale studies challenging. Many scholars of innovation have implemented ad-hoc disambiguation methods based on string similarity thresholds and string comparison matching; such methods have been shown to be vulnerable to a number of problems that can adversely affect research results. The authors address this issue contributing (1) an application of the Author-ity disambiguation approach (0170 and 0175) to the US utility patent database, (2) a new iterative blocking scheme that expands the match space of this algorithm while maintaining scalability, (3) a public posting of the algorithm and code, and (4) a public posting of the results of the algorithm in the form of a database of inventors and their associated patents. The paper provides an overview of the disambiguation method, assesses its accuracy, and calculates network measures based on co-authorship and collaboration variables. It illustrates the potential for large-scale innovation studies across time and space with visualizations of inventor mobility across the United States. The complete input and results data from the original disambiguation are available at (http://dvn.iq.harvard.edu/dvn/dv/patent); revised data described here are at (http://funglab.berkeley.edu/pub/disamb_no_postpolishing.csv); original and revised code is available at (https://github.com/funginstitute/disambiguator); visualizations of inventor mobility are at (http://funglab.berkeley.edu/mobility/).     

Effective ranking and search techniques for Web resources considering semantic relationships

On the Semantic Web, the types of resources and the semantic relationships between resources are defined in an ontology. By using that information, the accuracy of information retrieval can be improved.     

Synchronization of discrete-time complex dynamical networks with interval time-varying delays via non-fragile controller with randomly occurring perturbation

This paper addresses synchronization problem for discrete-time complex dynamical networks with interval time-varying delays. In order to achieve the synchronization, a feedback controller subjected to randomly occurring perturbations will be considered. The randomly occurring perturbations are assumed to belong to the Binomial sequence. By constructing a suitable Lyapunov–Krasovskii functional, and utilizing reciprocally convex approach and Finsler?s lemma, the synchronization criteria for the networks are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. The networks are represented by the use of Kronecker product technique. The effectiveness of the proposed methods will be verified via numerical examples.     

Study for optical manipulation of a surfactant-covered droplet using lattice Boltzmann method

In this study, we simulated deformation and surfactant distribution on the interface of a surfactant-covered droplet using optical tweezers as an external source. Two optical forces attracted a single droplet from the center to both sides. This resulted in an elliptical shape deformation. The droplet deformation was characterized as the change of the magnitudes of surface tension and optical force. In this process, a non-linear relationship among deformation, surface tension, and optical forces was observed. The change in the local surfactant concentration resulting from the application of optical forces was also analyzed and compared with the concentration of surfactants subjected to an extensional flow. Under the optical force influence, the surfactant molecules were concentrated at the droplet equator, which is totally opposite to the surfactants behavior under extensional flow, where the molecules were concentrated at the poles. Lastly, the quasi-equilibrium surfactant distribution was obtained by combining the effects of the optical forces with the extensional flow. All simulations were executed by the lattice Boltzmann method which is a powerful tool for solving micro-scale problems.     

Changes in velocity profile according to blood viscosity in a microchannel

Red blood cells (RBCs) are important to dictate hemorheological properties of blood. The shear-thinning effect of blood is mainly attributed to the characteristics of the RBCs. Variations in hemorheological properties alter flow resistance and wall shear stress in blood vessels. Therefore, detailed understanding of the relationship between the hemorheological and hemodynamic properties is of great importance. In this study, blood viscosity and blood flow were simultaneously measured in the same microfluidic device by monitoring the flow-switching phenomenon. To investigate blood flows according to hemorheological variations, the flow rate of blood samples (RBCs suspended in autologous plasma, dextran-treated plasma, and in phosphate buffered saline solution) was precisely controlled with a syringe pump. Velocity profiles of blood flows were measured by using a micro-particle image velocimetry technique. The shape of velocity profiles was quantified by using a curve-fitting equation. It is found that the shape of the velocity profiles is highly correlated with blood viscosity. To demonstrate the relationship under ex vivo conditions, biophysical properties and velocity profiles were measured in an extracorporeal rat bypass loop. Experimental results show that increased blood viscosity seems to induce blunt velocity profile with high velocity component at the wall of the microchannel. Simultaneous measurement of blood viscosity and velocity profile would be useful for understanding the effects of hemorheological features on the hemodynamic characteristics in capillary blood vessels.