Development and application of a diagnostic instrument to evaluate secondary school students’ conceptions of electrolysis

A two-tier multiple choice diagnostic instrument consisting of 17 items was developed to evaluate students’ understanding of basic electrolysis concepts. This study which used mixed qualitative and quantitative methods, was conducted in 2006 and 2007 to produce the final instrument. Subsequently, the final instrument was administered to 16 year-old secondary school students (N = 330) who had completed the first year of a two year chemistry course. The instrument was found to have a high Cronbach’s alpha reliability coefficient of 0.85 which is greater than the threshold value of 0.5 quoted by Nunally and Bernstein (1994). Analysis of students’ responses demonstrated good discrimination indices between the top and bottom groups of low- and high-achieving students, with the indices ranging from 0.42 to 0.84 for 16 items and 0.28 for one item. The analysis also identified 29 alternative conceptions that involved a variety of electrolysis concepts relating to the nature and reaction of the electrodes, the migration of ions, the preferential discharge of ions, the products of electrolysis, and changes in the concentration and colour of the electrolyte.In addition, there was a mismatch between students’ confidence in answering the items and their correct responses. Students’ level of confidence in providing correct responses to these items ranged from 44% to 72%, but the actual correct responses ranged from 19% to 53%. As no other similar instrument has been reported in the research literature, this instrument is a convenient diagnostic tool that teachers could use to identify students’ preconceptions prior to introducing the topic. In addition, using the instrument in formative assessment during classroom instruction will enable teachers to identify students’ alternative conceptions and institute appropriate remediation measures with the students concerned

EXPLORING THE DETERMINANTS OF TRANSFER BETWEEN PARENTS AND THEIR ADULT CHILDREN: EVIDENCE FROM INDONESIA

Master'sMASTER OF SOCIAL SCIENCE

Online Bearing Remaining Useful Life Prediction Based on a Novel Degradation Indicator and Convolutional Neural Networks

In industrial applications, nearly half the failures of motors are caused by the degradation of rolling element bearings (REBs). Therefore, accurately estimating the remaining useful life (RUL) for REBs are of crucial importance to ensure the reliability and safety of mechanical systems. To tackle this challenge, model-based approaches are often limited by the complexity of mathematical modeling. Conventional data-driven approaches, on the other hand, require massive efforts to extract the degradation features and construct health index. In this paper, a novel online data-driven framework is proposed to exploit the adoption of deep convolutional neural networks (CNN) in predicting the RUL of bearings. More concretely, the raw vibrations of training bearings are first processed using the Hilbert-Huang transform (HHT) and a novel nonlinear degradation indicator is constructed as the label for learning. The CNN is then employed to identify the hidden pattern between the extracted degradation indicator and the vibration of training bearings, which makes it possible to estimate the degradation of the test bearings automatically. Finally, testing bearings' RULs are predicted by using a $\epsilon$-support vector regression model. The superior performance of the proposed RUL estimation framework, compared with the state-of-the-art approaches, is demonstrated through the experimental results. The generality of the proposed CNN model is also validated by transferring to bearings undergoing different operating conditions

THEORETICAL RESEARCH ON EFFECTS OF SUBSTITUENTS AND THE SOLVENT ON QUADRUPLE HYDROGEN BONDED COMPLEXES

Semiempirical AM1 and INDO/CIS methods were used to study the structures and spectroscopy of hydrogen bonded complexes formed by the oligophenyleneethynylene (monomer A) with isophthalic acid (monomer B). The binding energies of the complexes are lowered by increasing electron-donating abilities of the substituents near the hydrogen bonds on monomer A. The first absorptions in the electronic spectra and the vibration frequencies of the N-H bonds in the IR spectra for the complexes are both red-shifted compared with those of the monomers. The presence of dimethylsulfoxide (DMSO) can reduce the binding energy of the complex through hydrogen bonding. This results in a blue-shift for the first absorption in the electronic spectrum and red-shift for the vibration frequencies of the N-H bonds in the IR spectrum of the complex. KEY WORDS: Oligophenyleneethynylene, Hydrogen bonding, Solvent effect, Semiempirical methods Bull. Chem. Soc. Ethiop. 2007, 21(3), 419-426

k-Same-Siamese-GAN: k-Same Algorithm with Generative Adversarial Network for Facial Image De-identification with Hyperparameter Tuning and Mixed Precision Training

For a data holder, such as a hospital or a government entity, who has a privately held collection of personal data, in which the revealing and/or processing of the personal identifiable data is restricted and prohibited by law. Then, "how can we ensure the data holder does conceal the identity of each individual in the imagery of personal data while still preserving certain useful aspects of the data after de-identification?" becomes a challenge issue. In this work, we propose an approach towards high-resolution facial image de-identification, called k-Same-Siamese-GAN, which leverages the k-Same-Anonymity mechanism, the Generative Adversarial Network, and the hyperparameter tuning methods. Moreover, to speed up model training and reduce memory consumption, the mixed precision training technique is also applied to make kSS-GAN provide guarantees regarding privacy protection on close-form identities and be trained much more efficiently as well. Finally, to validate its applicability, the proposed work has been applied to actual datasets - RafD and CelebA for performance testing. Besides protecting privacy of high-resolution facial images, the proposed system is also justified for its ability in automating parameter tuning and breaking through the limitation of the number of adjustable parameters

Mechanical Performance of Simple Supported Concrete Beam-Cable Composite Element with External Prestress

A new reinforcement technology of external prestress based on stretch tilted belly poles has been presented. Taking simply supported beam, which is reinforced by three titled belly poles, as a research object to establish a model of reinforced simply supported beam. Relationship expressions about deflection and internal force increment of external cable or about load and deflection have been deduced. Finite element model is established by ABAQUS. The influence of structure performance of reinforced simply supported beam with cable section, cable sag and initial internal force value was investigated. Three tests are carried out to testify the results of theoretical analysis and numerical simulation. The results show that the redistributions of internal force and sectional stress have occurred, and the stiffness, crack load, ultimate load, and structure ductility are all improved with the increase of three design parameters. For example, the crack load, ultimate load, and structure ductility have increased, respectively, by 24%~40%, 15%~42%, and 14%~40%. High initial internal force, small section, and big cable sag should be avoided, because the probability of brittle failure of structure will increase. The analytical result shows that the reliability of internal increment expression of external cable and carrying capacity expression can be used in the engineering practice

Effect of salidroside on ventricular remodeling after acute myocardial infarction

Purpose: To investigate the remodeling influence of salidroside (SAL) on the ventricles following acute myocardial infarction (AMI) in rats, and the processes involved.Methods: A total of 65 Sprague Dawley (SD) rats were assigned to 5 groups: sham (n = 13), model, and low-, medium- and high-dose SAL groups given SAL at doses of 12, 34, and 36 mg/day, respectively, with 13 rats in each group. Changes in pathological structure, collagen area, ratio of collagen I/collagen III, left ventricular mass index (LVW/BW), ratio of cardiac weight to body weight (HW/BW), creatine kinase MB isoenzyme (CK-MB), lactate dehydrogenase-1 (LDH-1), endothelin (ET), laminin (LN), and hyaluronic acid (HA) were evaluated. Expression levels of dishevelled-1 (DVL-1) and β-catenin in myocardial tissues of the rats were also determined.Results: The LVW/BW values were significantly higher in the low SAL and medium SAL groups than those in AMI rats, while the ratio of collagen I/III and expression levels of DVL-1 and β-catenin proteins were significantly lower than those in the model group (p < 0.05). The myocardial structure of rats in the sham group was normal, with no obvious lesions. The levels of CK-MB, LDH-1, ET, LN, and HA in medium and high-dose SAL groups were significantly lower than those in the model group (p < 0.05).Conclusion: Salidroside mitigates remodeling of ventricles following AMI in rats by modulating the Wnt/β-catenin signal route

Event-triggered distributed H∞ state estimation with packet dropouts through sensor networks

This study is concerned with the event-triggered distributed H∞ state estimation problem for a class of discrete-time stochastic non-linear systems with packet dropouts in a sensor network. An event-triggered communication mechanism is adopted over the sensor network with hope to reduce the communication burden and the energy consumption, where the measurements on each sensor are transmitted only when a certain triggering condition is violated. Furthermore, a novel distributed state estimator is designed where the available innovations are not only from the individual sensor, but also from its neighbouring ones according to the given topology. The purpose of the problem under consideration is to design a set of distributed state estimators such that the dynamics of estimation errors is exponentially mean-square stable and also the prespecified H∞ disturbance rejection attenuation level is guaranteed. By utilising the property of the Kronecker product and the stochastic analysis approaches, sufficient conditions are established under which the addressed state estimation problem is recast as a convex optimisation one that can be easily solved via available software packages. Finally, a simulation example is utilised to illustrate the usefulness of the proposed design scheme of event-triggered distributed state estimators.This work was supported in part by Royal Society of the UK, the National Natural Science Foundation of China under Grants 61329301, 61203139, 61473076, 61374127 and 61422301, the Shanghai Rising-Star Program of China under Grant 13QA1400100, the ShuGuang project of Shanghai Municipal Education Commission and Shanghai Education Development Foundation under Grant 13SG34, the Fundamental Research Funds for the Central Universities, DHU Distinguished Young Professor Program, and the Alexander von Humboldt Foundation of Germany