Microfluidic impedance spectroscopy as a tool for quantitative biology and biotechnology

A microfluidic device that is able to perform dielectric spectroscopy is developed. The device consists of a measurement chamber that is 250 μm thick and 750 μm in radius. Around 1000 cells fit inside the chamber assuming average quantities for cell radius and volume fraction. This number is about 1000 folds lower than the capacity of conventional fixtures. A T-cell leukemia cell line Jurkat is tested using the microfluidic device. Measurements of deionized water and salt solutions are utilized to determine parasitic effects and geometric capacitance of the device. Physical models, including Maxwell-Wagner mixture and double shell models, are used to derive quantities for sub-cellular units. Clausius-Mossotti factor of Jurkat cells is extracted from the impedance spectrum. Effects of cellular heterogeneity are discussed and parameterized. Jurkat cells are also tested with a time domain reflectometry system for verification of the microfluidic device. Results indicate good agreement of values obtained with both techniques. The device can be used as a unique cell diagnostic tool to yield information on sub-cellular units.     

Learning orientations of IT higher education students in UAE University

This research examines the learning preferences of students in UAE University (UAEU). The uniqueness of this research emanates from the fact that no prior research examined this area from the UAE’s perspective. Thus, this research embarks on the fact that student learning strategies vary from one country to another due to many factors. This research utilizes six learning strategies extended from the literature and attempts to examine their importance on UAEU students using survey research. The selected learning strategies were students” motivation, time-poorness, mastery effort, assessment focus, competitiveness, and listening. This research provided interesting insights and contrasts pertaining to the learning strategies of UAEU students. Implications are discussed highlighting different theoretical as well as professional contributions and contentions and portrayed a path where pending issues could be addressed by future research.     

Preface to Special Topic: Microfluidics in cell biology and tissue engineering

In this special issue of Biomicrofluidics, a wide variety of applications of microfluidics to tissue engineering and cell biology are presented. The articles illustrate the benefits of using microfluidics for controlling the cellular environment in a precise yet high rate manner using minimum reagents. The topic is very timely and takes a stab at portraying a glimpse of what is to come in this exciting and emerging field of research.     

Emotions Management Skills and Barriers with Library Staff: A Correlational Survey of Agriculture Students

The literature has identified barriers with library staff as one of the important barriers affecting academic activities of students and also recognized the relationship of various academic and demographic characteristics of students with it. The emotions management skills of students may be one of the possible correlates of the barriers with library staff. This study was designed to investigate the levels of barriers with library staff and emotions management skills as well as their possible correlation using two standardized scales. The data were collected from the final year undergraduate agriculture students. The results confirmed the existence of barriers with library staff among the participants of both genders experiencing the same level of anxiety. The participants scored 3.75 (average) on the emotions management scale. The results also revealed significantly negative correlation between emotions management skills and barriers with library staff among these students. These results have many practical implications in the sphere of academic librarianship.     

Neural information retrieval: at the end of the early years

A recent “third wave” of neural network (NN) approaches now delivers state-of-the-art performance in many machine learning tasks, spanning speech recognition, computer vision, and natural language processing. Because these modern NNs often comprise multiple interconnected layers, work in this area is often referred to as deep learning. Recent years have witnessed an explosive growth of research into NN-based approaches to information retrieval (IR). A significant body of work has now been created. In this paper, we survey the current landscape of Neural IR research, paying special attention to the use of learned distributed representations of textual units. We highlight the successes of neural IR thus far, catalog obstacles to its wider adoption, and suggest potentially promising directions for future research.     

The reflection of offline activities on users’ online social behavior: An observational study

The ever increasing presence of online social networks in users’ daily lives has led to the interplay between users’ online and offline activities. There have already been several works that have studied the impact of users’ online activities on their offline behavior, e.g., the impact of interaction with friends on an exercise social network on the number of daily steps. In this paper, we consider the inverse to what has already been studied and report on our extensive study that explores the potential causal effects of users’ offline activities on their online social behavior. The objective of our work is to understand whether the activities that users are involved with in their real daily life, which place them within or away from social situations, have any direct causal impact on their behavior in online social networks. Our work is motivated by the theory of normative social influence, which argues that individuals may show behaviors or express opinions that conform to those of the community for the sake of being accepted or from fear of rejection or isolation. We have collected data from two online social networks, namely Twitter and Foursquare, and systematically aligned user content on both social networks. On this basis, we have performed a natural experiment that took the form of an interrupted time series with a comparison group design to study whether users’ socially situated offline activities exhibited through their Foursquare check-ins impact their online behavior captured through the content they share on Twitter. Our main findings can be summarised as follows (1) a change in users’ offline behavior that affects the level of users’ exposure to social situations, e.g., starting to go to the gym or discontinuing frequenting bars, can have a causal impact on users’ online topical interests and sentiment; and (2) the causal relations between users’ socially situated offline activities and their online social behavior can be used to build effective predictive models of users’ online topical interests and sentiments.     

From praxis to pragmatism: Junior scholars and policy impact

ABSTRACT

Drawing on Buckingham’s observation that academic research either has to become public knowledge or its originators must have a high visibility in the public realm before their research can find inclusion into policymaking processes, this article offers a variety of examples of how academics have managed to bridge the gap between media and communication policy scholarship and policymaking. Contrary to the long-standing belief that policy impact is extremely difficult and rare to achieve, we argue that junior scholars have many opportunities to have their work become part of the policymaking process through new forms of conversation, collaboration, coalition-building, changing perceptions of public knowledge, and a more conceptual understanding of impact.     

Do tax incentives and direct funding enhance innovation input and output in high-tech firms?

Tax incentives and direct funding are two different public support instruments used to facilitate the formation and growth of firms. Limited empirical evidence has compared the effectiveness of two different policies and their interactions for firms. In this paper, we investigate the main and interaction effects of these interventions on high-tech firms. Since large and small firms innovate in different ways, we compare the use of both incentives by Iranian high-tech SMEs and large firms through a factorial design technique. This paper presents significant differences both across instruments and across firm size. Results show that for SMEs, tax exemption has a significant effect on R&D investment, and funding has a significant effect on R&D investment, R&D employees, and new products. However, there aren't any interaction effects between instruments. For large firms, funding is an effective instrument for R&D investment. Also, there is an interaction effect between tax incentives and direct funding on new products. These findings indicate that funding is a more effective instrument than tax exemption, especially for SMEs, but suggest some changes in supporting policies of high-tech firms in Iran.