Metal–organic frameworks for electronics: emerging second order nonlinear optical and dielectric materials

Metal–organic frameworks (MOFs) have been intensively studied over the past decade because they represent a new category of hybrid inorganic–organic materials with extensive surface areas, ultrahigh porosity, along with the extraordinary tailorability of structure, shape and dimensions. In this highlight, we summarize the current state of MOF research and report on structure–property relationships for nonlinear optical (NLO) and dielectric applications. We focus on the design principles and structural elements needed to develop potential NLO and low dielectric (low-κ) MOFs with an emphasis on enhancing material performance. In addition, we highlight experimental evidence for the design of devices for low-dielectric applications. These results motivate us to develop better low-dielectric and NLO materials and to perform in-depth studies related to deposition techniques, patterning and the mechanical performance of these materials in the future.     

The effect of Cu addition on the thermoelectric properties of Cu2CdGeSe4

Recently, research in copper based quaternary chalcogenide materials has focused on the study of thermoelectric properties due to the complexity in the crystal structure. In the present work, stoichiometric quaternary chalcogenide compounds Cu_2+xCd_1−xGeSe₄ (x = 0, 0.025, 0.05, 0.075, 0.1, 0.125) were prepared by solid state synthesis. The powder X-ray diffraction patterns of all the samples showed a tetragonal crystal structure with the space group I-42m of the main phase, whereas the samples with x = 0 and x = 0.025 revealed the presence of an orthorhombic phase in addition to the main phase as confirmed by Rietveld analysis. The elemental composition of all the samples characterized by Electron Probe Micro Analyzer showed a slight deviation from the nominal composition. The transport properties were measured in the temperature range of 300 K–723 K. The electrical conductivity of all the samples increased with increasing Cu content due to the enhancement of the hole concentration caused by the substitution of Cd (divalent) by Cu (monovalent). The positive Seebeck coefficient of all the samples in the entire temperature ranges indicates that holes are the majority carriers. The Seebeck coefficient of all the samples decreased with increasing Cu content and showed a reverse trend to the electrical conductivity. The total thermal conductivity of all the samples decreased with increasing temperature which was dominated by the lattice contribution. The maximum figure of merit ZT = 0.42 at 723 K was obtained for the compound Cu_2.1Cd_0.9GeSe₄.     

AgMgAl metallic glassy and intermetallic thin films for electric contact applications

The AgMgAl thin films, in an attempt in replacing the expensive pure Au contact films, are prepared by co-sputtering. The surface morphology, roughness, amorphous or crystalline atomic structure, grain size, and electric resistivity are systematically examined. Depending on the film compositions, the films can be fully amorphous or fully nanocrystalline, or a composite with the mixture of nanocrystalline phases dispersed in the amorphous matrix. Under the as-sputtered condition, the crystalline group has the lowest resistivity, ranging from 27 to 37 μΩ·cm, the composite group lies in the middle, 31–70 μΩ·cm, and the fully amorphous group possesses the highest resistivity, 87–122 μΩ·cm. Appropriate short thermal annealing for the amorphous films can drastically lower the resistivity down to as low as 9 μΩ·cm, already compatible to pure Au (3–7 μΩ·cm). This study demonstrates the feasibility of the AgMgAl films in replacing the pure Au.     

Facebook use and academic performance among college students: A mixed-methods study with a multi-ethnic sample

This paper uses a mixed-methods approach to examine the relation between online academic disclosure and academic performance. A multi-ethnic sample of college students (N = 261; male = 66; female = 195; M age ≈ 22 years) responded to open-ended questions about their Facebook use. Thematic analysis revealed that over 14% of the Facebook wall posts/status updates (N = 714) contained academic themes; positive states were more frequent than negative and neutral states and students with lower GPAs expressed negative states more often. A path analysis suggested that academic performance may determine college students’ Facebook use, rather than the reverse. Implications for student support services are discussed.     

Digital Microfluidics for Manipulation and Analysis of a Single Cell

The basic structural and functional unit of a living organism is a single cell. To understand the variability and to improve the biomedical requirement of a single cell, its analysis has become a key technique in biological and biomedical research. With a physical boundary of microchannels and microstructures, single cells are efficiently captured and analyzed, whereas electric forces sort and position single cells. Various microfluidic techniques have been exploited to manipulate single cells through hydrodynamic and electric forces. Digital microfluidics (DMF), the manipulation of individual droplets holding minute reagents and cells of interest by electric forces, has received more attention recently. Because of ease of fabrication, compactness and prospective automation, DMF has become a powerful approach for biological application. We review recent developments of various microfluidic chips for analysis of a single cell and for efficient genetic screening. In addition, perspectives to develop analysis of single cells based on DMF and emerging functionality with high throughput are discussed.     

A problem solving oriented intelligent tutoring system to improve students' acquisition of basic computer skills

Personalization and intelligent tutor are two key factors in the research on learning environment. Intelligent tutoring system (ITS), which can imitate the human teachers' actions to implement one-to-one personalized teaching to some extent, is an effective tool for training the ability of problem solving. This research firstly discusses the concepts and methods of designing problem solving oriented ITS, and then develops the current iTutor based on the extended model of ITS. At last, the research adopts a quasi-experimental design to investigate the effectiveness of iTutor in skills acquisition. The results indicate that students in iTutor group experience better learning effectiveness than those in the control group. iTutor is found to be effective in improving the learning effectiveness of students with low-level prior knowledge.     

The implementation of a smartphone-based fall detection system using a high-level fuzzy Petri net

The falling down problem has become one of the very important issues of global public health in an aging society. The specific equipment was adopted as the detection device of falling-down in the early studies, but it is inconvenient for the elderly and difficult for future application. The smart phone more commonly used than the specific fall detection equipment is selected as a mobile device for human fall detection, and a fall detection algorithm is developed for this purpose. What the user has to do is to put the smart phone in his/her thigh pocket for falling down detection. The signals detected by the tri-axial G-sensor are converted into signal vector magnitudes as the basis of detecting a human body in a stalling condition. The Z-axis data sets are captured for identification of human body inclination and the occurrence frequencies at the peak of the area of use are used as the input parameters. A high-level fuzzy Petri net is used for the analysis and the development of identifying human actions, including normal action, exercising, and falling down. The results of this study can be used in the relevant equipments or in the field of home nursing.     

Customer satisfaction and loyalty analysis with classification algorithms and Structural Equation Modeling

Businesses can maintain their effectiveness as long as they have satisfied and loyal customers. Customer relationship management provides significant advantages for companies especially in gaining competitiveness. In order to reach these objectives primarily companies need to identify and analyze their customers. In this respect, effective communication and commitment to customers and changing market conditions is of great importance to increase the level of satisfaction and loyalty. To evaluate this situation, level of customer satisfaction and loyalty should be measured correctly with a comprehensive approach. In this study, customers are investigated in 4 main groups according to their level of satisfaction and loyalty with a criteria and group based analysis with a new method. We use classification algorithms in WEKA programming software and Structural Equation Modeling (SEM) with LISREL tools together to analyze the effect of each satisfaction and loyalty criteria in a satisfaction–loyalty matrix and extend the customer satisfaction and loyalty post-analysis research bridging the gap in this field of research. To convert developed conceptual thought to experimental study, white goods industry is exemplified. 15 criteria are used for evaluation in 4 customer groups and a satisfaction–loyalty survey developed by experts is applied to 200 customers with face-to-face interviews. As a result of the study, a customer and criteria grouping method is created with high performance classification methods and good fit structural models. In addition, results are evaluated for developing a customer strategy improvement tool considering method outcomes.