Effect of in-app components,medium, and screen size of electronic textbooks on reading performance,behavior, and perception

Although many app-based textbooks are available for students, reading have not been thoroughly outlined. This study aimed to understand how changes from paper to electronic textbooks have affected the academic reading task, investigate student users’ perceptions of in-app components and screen sizes, and identify issues affecting in-app components and task requirements. A mixed factorial design experiment was employed. Results showed that there were no significant changes in comprehension and time spent reading between print text and the iPad. Yet, student highlighting, notetaking, and reading behavior and perception significantly changed based on condition. In addition, students struggled to use in-app components and found them frustrating especially when accounting for sentence splitting. The findings presented can assist in understanding the changes in student reading behavior, which can be used to improve interface design of future e-textbooks.     

Microwave dielectric properties of SrLa[Ga1−x(Mg0.5Ti0.5)x]O4 and SrLa[Ga1−x(Zn0.5Ti0.5)x]O4 (x = 0.2-0.8) ceramics

SrLa[Ga_1−x(R_0.5Ti_0.5)_x]O₄ (R = Mg, Zn) ceramics were prepared by a standard solid state sintering method. The single-phase ceramics with K₂NiF₄-type layered perovskite structure and I4/mmm space group were obtained, indicating that SrLa(R_0.5Ti_0.5) and SrLaGaO₄ can form the unlimited solid solutions. With increasing x for R = Mg and Zn, ε_r increases monotonously, the Qf value first increases and then decreases, while τ_f increases from a negative to a positive value. The optimized microwave dielectric properties were obtained as following: ε_r = 23.3, Qf = 89 400 GHz, τ_f = −0.8 ppm/°C for SrLa[Ga_0.6(Mg_0.5Ti_0.5)_0.4]O₄ and ε_r = 23.3, Qf = 76 200 GHz, τ_f = 0.2 ppm/°C for SrLa[Ga_0.7(Zn_0.5Ti_0.5)_0.3]O₄, indicating that the present solid solution ceramics are the promising candidates as microwave resonator materials for the telecommunication applications.     

Graph-based video fingerprinting using double optimal projection

A double optimal projection method that involves projections for intra-cluster and inter-cluster dimensionality reduction are proposed for video fingerprinting. The video is initially set as a graph with frames as its vertices in a high-dimensional space. A similarity measure that can compute the weights of the edges is then proposed. Subsequently, the video frames are partitioned into different clusters based on the graph model. Double optimal projection is used to explore the optimal mapping points in a low-dimensional space to reduce the video dimensions. The statistics and geometrical fingerprints are generated to determine whether a query video is copied from one of the videos in the database. During matching, the video can be roughly matched by utilizing the statistics fingerprint. Further matching is thereafter performed in the corresponding group using geometrical fingerprints. Experimental results show the good performance of the proposed video fingerprinting method in robustness and discrimination.     

Formation of ST12 phase Ge nanoparticles in ZnO thin films

In this work, we focus on the Ge nanoparticles (Ge-np) embedded ZnO multilayered thin films. Effects of reactive and nonreactive growth of ZnO layers on the rapid thermal annealing (RTA) induced formation of Ge-np have been specifically investigated. The samples were deposited by sequential r.f. and d.c. sputtering of ZnO and Ge thin film layers, respectively on Si substrates. As-prepared thin film samples have been exposed to an ex-situ RTA at 600 °C for 60 s under forming gas atmosphere. Structural characterizations have been performed by X-ray Diffraction (XRD), Raman scattering, Secondary Ion Mass Spectroscopy (SIMS), and Scanning Electron Microscopy (SEM) techniques. It has been realized that reactive or nonreactive growth of ZnO layers significantly influences the morphology of the ZnO: Ge samples, most prominently the crystal structure of Ge-np. XRD and Raman analysis have revealed that while reactive growth results in a mixture of diamond cubic (DC) and simple tetragonal (ST12) Ge-np, nonreactive growth leads to the formation of only DC Ge-np upon RTA process. Formation of ST12 Ge-np has been discussed based on structural differences due to reactive and nonreactive growth of ZnO embedding layer.     

Optimised phase compositions and improved microwave dielectric properties based on calcium tin silicates

The Ca_(1+2y)Sn_(1-x)Si_(1+y)O_(5-2x+4y) low-permittivity microwave dielectric ceramics were prepared through solid-state reaction at 1350–1450 °C for 5 h. The relations between microwave dielectric properties and phase compositions for non-stoichiometric Ca_(1+2y)Sn_(1-x)Si_(1+y)O_(5-2x+4y) ceramics have been investigated. A single CaSnSiO₅ phase with abnormally positive temperature coefficient of resonant frequency (τ_f = + 62.5 ppm/°C) was synthesised at 1450 °C. This composition was an effective τ_f compensator of CaSiO₃ and Ca₃SnSi₂O₉ phases with typically negative τ_f value. The CaSiO₃ second phase was related to the Sn deficiency in the CaSn_(1-x)SiO_(5-2x) (0 < x < 1.0) composition, whereas the Ca₃SnSi₂O₉ second phase was obtained by controlling the Ca:Sn:Si ratios on the basis of the Ca_(1+2y)SnSi_(1+y)O_(5+4y) (0 < y < 1.0) composition. A promising low-permittivity millimetre-wave ceramic with most excellent microwave dielectric properties (ε_r = 10.2, Q×f = 81,000 GHz and τ_f = −4.8 ppm/°C) was produced from the Ca_(1+2y)SnSi_(1+y)O_(5+4y) (y = 0.4) ceramic.     

Nickel foam-supported Fe,Ni-Polyporphyrin microparticles: Efficient bifunctional catalysts for overall water splitting in alkaline media

Developing highly active, stable and sustainable electrocatalysts for overall water splitting is of great importance to generate renewable H₂ for fuel cells. Herein, we report the synthesis of electrocatalytically active, nickel foam-supported, spherical core-shell Fe-poly(tetraphenylporphyrin)/Ni-poly(tetraphenylporphyrin) microparticles (FeTPP@NiTPP/NF). We also show that FeTPP@NiTPP/NF exhibits efficient bifunctional electrocatalytic properties toward both the oxygen evolution reaction (OER) and the hydrogen evolution reaction (HER). Electrochemical tests in KOH solution (1 M) reveal that FeTPP@NiTPP/NF electrocatalyzes the OER with 100 mA cm⁻² at an overpotential of 302 mV and the HER with 10 mA cm⁻² at an overpotential of 170 mV. Notably also, its catalytic performance for OER is better than that of RuO₂, the benchmark OER catalyst. Although its catalytic activity for HER is slightly lower than that of Pt/C (the benchmark HER electrocatalyst), it shows greater stability than the latter during the reaction. The material also exhibits electrocatalytic activity for overall water splitting reaction at a current density of 10 mA cm⁻² with a cell voltage of 1.58 V, along with a good recovery property. Additionally, the work demonstrates a new synthetic strategy to an efficient, noble metal-free-coordinated covalent organic framework (COF)-based, bifunctional electrocatalyst for water splitting.     

A Novel Beam Search to Improve Neural Machine Translation for English-Chinese

Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, overcoming the weaknesses of conventional phrase-based translation systems. Although NMT based systems have gained their popularity in commercial translation applications, there is still plenty of room for improvement. Being the most popular search algorithm in NMT, beam search is vital to the translation result. However, traditional beam search can produce duplicate or missing translation due to its target sequence selection strategy. Aiming to alleviate this problem, this paper proposed neural machine translation improvements based on a novel beam search evaluation function. And we use reinforcement learning to train a translation evaluation system to select better candidate words for generating translations. In the experiments, we conducted extensive experiments to evaluate our methods. CASIA corpus and the 1,000,000 pairs of bilingual corpora of NiuTrans are used in our experiments. The experiment results prove that the proposed methods can effectively improve the English to Chinese translation quality.