Ultrahigh‐Areal‐Capacitance Flexible Supercapacitor Electrodes Enabled by Conformal P3MT on Horizontally Aligned Carbon‐Nanotube Arrays

Nanocarbon electronic conductors combined with pseudocapacitive materials, such as conducting polymers, display outstanding electrochemical properties and mechanical flexibility. These characteristics enable the fabrication of flexible electrodes for energy‐storage devices; that is, supercapacitors that are wearable or can be formed into shapes that are easily integrated into vehicle parts. To date, most nanocarbon materials such as nanofibers are randomly dispersed as a network in a flexible matrix. This morphology inhibits ion transport, particularly under the high current density necessary for devices requiring high power density. Novel flexible densified horizontally aligned carbon nanotube arrays (HACNTs) with controlled nanomorphology for improved ion transport are introduced and combined with conformally coated poly(3‐methylthiophene) (P3MT) conducting polymer to impart pseudocapacitance. The resulting P3MT/HACNT nanocomposite electrodes exhibit high areal capacitance of 3.1 F cm^?2 at 5 mA cm^?2, with areal capacitance remaining at 1.8 F cm^?2 even at a current density of 200 mA cm^?2. The asymmetric supercapacitor cell also delivers more than 1–2 orders of magnitude improvement in both areal energy and power density over state‐of‐the‐art cells. Furthermore, little change in cell performance is observed under high strain, demonstrating the mechanical and electrochemical stability of the electrodes.     

Book reviews

Abstract

In 1934, a group of ardent admirers published America &; Alfred Stieglitz, a eulogy of such Whitmanesque hyperbole that it is almost embarrassing to recall that Alfred Stieglitz (1864–1946) was still very much alive, and would, indeed, live on for another decade, well nourished by such loving encomiums. By contrast, the fate of his contemporary Lewis Hine (1874–1940), a documentarian of genius and human compassion matched only by David Octavius Hill, John Thomson, Thomas Annan, or Jacob Riis, was a study in cruel neglect. America &; Lewis Hine, mimicking the title of the Stieglitz book even to the ampersand, and perhaps selected as a duplicating title in angry and justifiable reproach, seems a tragically belated effort to elevate Hine to the highest pantheon of the demigods of photography.     

“Green labelled” pectins with gelling and emulsifying properties can be extracted by enzymatic way from unexploited sources

Functional properties of “green labelled” pectins extracted with enzymes from chicory root, citrus peel and cauliflower by-products were assessed. Chicory and citrus pectins were selected to study their gelling properties, while cauliflower pectin was chosen to investigate its emulsifying ability. High methoxy chicory and citrus pectins were shown to gel in the presence of sucrose at acidic pH, whereas their corresponding low methoxy pectins were able to gel in the presence of calcium. Additionally, HM cauliflower pectin exhibited emulsifying ability. Atomic Force Microscopy was used to better understand the gelling mechanism of pectins and particularly the first steps of gel setting. The present work demonstrates that “green labelled” enzyme-extracted pectins can be successfully used as gelling or emulsifying agents. The present study allows enhancing the value of “green” extraction of pectins, since such extraction leads to products with good functional properties that can directly be used for food and non-food purposes.     

CTRL: Extension of CTL with regular expressions and fairness operators to verify genetic regulatory networks

Model checking has proven to be a useful analysis technique not only for concurrent systems, but also for genetic regulatory networks (Grns). Applications of model checking in systems biology have revealed that temporal logics should be able to capture both branching-time and fairness properties (needed for specifying multistability and oscillation properties, respectively). At the same time, they should have a user-friendly syntax easy to employ by non-experts. In this paper, we define Computation Tree Regular Logic (Ctrl), an extension of Ctl with regular expressions and fairness operators that attempts to match these criteria. Ctrl subsumes both Ctl and Ltl, and has a reduced set of temporal operators indexed by regular expressions. We also develop a translation of Ctrl into Hennessy-Milner Logic with Recursion (HmlR), an equational variant of the modal μ-calculus. This has allowed us to obtain an on-the-fly model checker with diagnostic for Ctrl by directly reusing the verification technology available in the Cadp toolbox. We illustrate the application of the Ctrl model checker by analyzing the Grn controlling the carbon starvation response of Escherichia coli.     

Procrastination,participation, and performance in online learning environments

The present study focuses on a specific learner characteristic in the management of time – procrastination-, and its role in an online learning environment. More specifically, it was expected that procrastination would influence the successfulness of online learning and that this could be explained by the level of participation of learners in discussion forums. A study was conducted to test this hypothesis among a sample of learners taking a 10-week course on environmental and land use issues. As predicted, a negative relationship was found between procrastination and performance, and this relationship was mediated by the level of the learners’ participation in discussion forums. In other words, it appears that if high procrastinators are less successful online learners than low procrastinators, it is partly due to their lack of participation in discussion forums during the learning process. Additionally, some behavioral differences between high and low procrastinators were found in the times they decided to (re)start working at a distance, felt motivated to work on their course, and felt like dropping out of the course. To conclude, some practical implications for tutoring online activities and for stimulating participation in online learning environments have been proposed.     

Face-to-face contact at the midpoint of an online collaboration: Its impact on the patterns of participation, interaction, affect, and behavior over time

This paper describes some of the consequences of introducing a face-to-face contact during an online collaborative learning session. Previous research on the development of online groups has suggested a critical transition period at the midpoint of a collaborative task in which group members redefine their behavior. The purpose of the present study was to determine whether face-to-face contact between participants during this period influences the patterns of participation, interaction, affect and behavior over time. Results show that a face-to-face contact introduced at the midpoint of a collaborative task has a positive influence on participation. However, a time sequence analysis of interactions revealed a further transition which appears between the face-to-face contact and the deadline. This transition is characterized by a decline of participation and task-focused interactions. At the same time, the analyses revealed an increase of interactions oriented towards emotional regulation and coordination, as well as a greater need of face-to-face contact, desire to drop out, and use of synchronous communications. These findings are based on an in-depth and longitudinal examination of a small sample, which limits their generalizability, but they may have a number of implications for the design of blended learning programs and the facilitation of collaborative tasks in distributed learning environments.     

Comparing the effectiveness of peer instruction to individual learning during a chromatography course

Peer instruction has been recognized as an instructional method having a positive impact on learning compared to traditional lectures in science. This method has been widely supported by the socio‐constructivist approach to learning giving a positive role to interaction between peers in the construction of knowledge. As far as we know, no study has been conducted from the socio‐cognitive approach which suggests that individuals working alone perform better than those interacting with others in groups. Thus, the aim of the present study was to examine whether peer instruction improves learning when compared with an individual learning method that does not require any interaction with peers. After being randomly divided into either a peer instruction or an individual learning condition in a chromatography course, students had to answer to a series of multiple‐choice questions using clickers at the beginning (pre‐test) and end of (post‐test) the session. Results revealed that the percentage of correct answers increased similarly from the pre‐ to the post‐test in both conditions. Nevertheless, students perceived the peer instruction method as being more satisfying, engaging and useful than the individual learning method. The findings revealed that peer instruction provides subjective benefits, but failed to demonstrate a greater learning gain.     

Seeker—Autonomous Long‐range Rover Navigation for Remote Exploration

Under the umbrella of the European Space Agency (ESA) StarTiger program, a rapid prototyping study called Seeker was initiated. A range of partners from space and nonspace sectors were brought together to develop a prototype Mars rover system capable of autonomously exploring several kilometers of highly representative Mars terrain over a three‐day period. This paper reports on our approach and the final field trials that took place in the Atacama Desert, Chile. Long‐range navigation and the associated remote rover field trials are a new departure for ESA, and this activity therefore represents a novel initiative in this area. The primary focus was to determine if current computer vision and artificial intelligence based software could enable such a capability on Mars, given the current limit of around 200 m per Martian day. The paper does not seek to introduce new theoretical techniques or compare various approaches, but it offers a unique perspective on their behavior in a highly representative environment. The final system autonomously navigated 5.05 km in highly representative terrain during one day. This work is part of a wider effort to achieve a step change in autonomous capability for future Mars/lunar exploration rover platforms.     

A combined neural network and DEA for measuring efficiency of large scale datasets

Data Envelopment Analysis (DEA) is one of the most widely used methods in the measurement of the efficiency and productivity of Decision Making Units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper proposes a neural network back-propagation Data Envelopment Analysis to address this problem for the very large scale datasets now emerging in practice. Neural network requirements for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of large datasets. Finally, the back-propagation DEA algorithm is applied to five large datasets and compared with the results obtained by conventional DEA.