Role of end-groups and catalyst in polyester cyclodepolymerization and cycle-chain equilibria

The influence of polyesters end-groups on cyclic oligoester formation is investigated using a series of hydroxy-, carboxy- and methylester-terminated aliphatic polyesters, in the presence of various ester interchange catalysts. The presence of hydroxy end-groups is the preponderant factor on cyclodepolymerization kinetics. This indicates that the main reaction is the intramolecular hydroxy–ester interchange reaction between hydroxy end-groups and ester functions in the chain. Carboxy-ester and ester–ester interchanges play a minor role, as the cycle-chain equilibrium is reached only very slowly when carboxy- or ester-terminated polyesters are reacted. High temperature and the presence of tin catalysts are also favorable factors, while, as expected, dilution shifts the equilibrium toward the formation of high yields of cyclic oligoesters. A mechanism is proposed, based on the reverse of the “coordination-insertion” mechanism established for the ring-opening polymerization of lactones.     

Nitroarenes as Antitubercular Agents: Stereoelectronic Modulation to Mitigate Mutagenicity

Nitroarenes are less preferred in drug discovery due to their potential to be mutagenic. However, several nitroarenes were shown to be promising antitubercular agents with specific modes of action, namely, nitroimidazoles and benzothiazinones. The nitro group in these compounds is activated through different mechanisms, both enzymatic and non‐enzymatic, in mycobacteria prior to binding to the target of interest. From a whole‐cell screening program, we identified a novel lead nitrobenzothiazole (BT) series that acts by inhibition of decaprenylphosphoryl‐β‐d ‐ribose 2′‐epimerase (DprE1) of Mycobacterium tuberculosis (Mtb). The lead was found to be mutagenic to start with. Our efforts to mitigate mutagenicity resulted in the identification of 6‐methyl‐7‐nitro‐5‐(trifluoromethyl)‐1,3‐benzothiazoles (cBTs), a novel class of antitubercular agents that are non‐mutagenic and exhibit an improved safety profile. The methyl group ortho to the nitro group decreases the electron affinity of the series, and is hence responsible for the non‐mutagenic nature of these compounds. Additionally, the co‐crystal structure of cBT in complex with Mtb DprE1 established the mode of binding. This investigation led to a new non‐mutagenic antitubercular agent and demonstrates that the mutagenic nature of nitroarenes can be solved by modulation of stereoelectronic properties.     

Gaze tutor: A gaze-reactive intelligent tutoring system

We developed an intelligent tutoring system (ITS) that aims to promote engagement and learning by dynamically detecting and responding to students' boredom and disengagement. The tutor uses a commercial eye tracker to monitor a student's gaze patterns and identify when the student is bored, disengaged, or is zoning out. The tutor then attempts to reengage the student with dialog moves that direct the student to reorient his or her attentional patterns towards the animated pedagogical agent embodying the tutor. We evaluated the efficacy of the gaze-reactive tutor in promoting learning, motivation, and engagement in a controlled experiment where 48 students were tutored on four biology topics with both gaze-reactive and non-gaze-reactive (control condition) versions of the tutor. The results indicated that: (a) gaze-sensitive dialogs were successful in dynamically reorienting students’ attentional patterns to the important areas of the interface, (b) gaze-reactivity was effective in promoting learning gains for questions that required deep reasoning, (c) gaze-reactivity had minimal impact on students’ state motivation and on self-reported engagement, and (d) individual differences in scholastic aptitude moderated the impact of gaze-reactivity on overall learning gains. We discuss the implications of our findings, limitations, future work, and consider the possibility of using gaze-reactive ITSs in classrooms.     

The activation of mechanisms linking judgements of work design and management with musculoskeletal pain

The report of work-related musculoskeletal pain may be related to worker evaluations of the design and management of work through two mechanisms: one biomechanical and the other stress-related. This study of engineering workers (n = 204) explored the validity of these mechanisms using sequential logistic regression. Analyses suggested that workers' ratings of the adequacy of the design and management of their work were related to their report of work-related musculoskeletal pain. However, the mechanisms appeared to be activated in certain conditions. The reporting of pain in the upper body was both biomechanically- and stress-related, whereas that in the lower body was only biomechanically-related. It is argued that the mechanism activated appeared to be determined by the anatomical location of the pain, and probably the variance shared between the different aspects of work design and management, on the one hand, and the mechanical load of the job, on the other.     

GEO_BUG: a geographical modelling environment for assessing the likelihood of pest development

This paper describes software designed to explore pest phenology (development) over space and time. The framework presented links sequences of interpolated daily maximum and minimum temperatures with a variety of process-based phenology and accumulated temperature models. The flexibility offered by this approach is demonstrated using examples of gridded maps of pest phenology on target dates, graphs of the sequences of pest development at individual locations and assessments of error in the predicted dates over the course of a model run. Finally, the potential application of the software in support of agricultural management systems, policy development and integrated research is discussed.     

Accessing the spoken word

Spoken-word audio collections cover many domains, including radio and television broadcasts, oral narratives, governmental proceedings, lectures, and telephone conversations. The collection, access, and preservation of such data is stimulated by political, economic, cultural, and educational needs. This paper outlines the major issues in the field, reviews the current state of technology, examines the rapidly changing policy issues relating to privacy and copyright, and presents issues relating to the collection and preservation of spoken audio content .     

Personalizing 3D virtual fashion stores: Exploring modularity with a typology of atmospherics based on user input

This research develops a typology of atmospherics that contains user-identified modules and modular options for personalizing 3D virtual fashion stores. A content analysis of 46 focus group discussions (n = 170) was conducted to understand the user’s perspective for personalizing 3D virtual fashion store atmospherics. Based on three atmospheric categories (pathfinding assistant, environment, and the manner of product presentation), 17 modules and 207 modular options were identified for personalizing 3D virtual stores. This research pioneers the development of an atmospherics typology for personalizing 3D virtual shopping environments as a persuasive selling tool in the emerging field of 3D virtual reality (VR) retailing.     

A Cognitive Bias Approach to Feature Selection and Weighting for Case-Based Learners

Research in psychology, psycholinguistics, and cognitive science has discovered and examined numerous psychological constraints on human information processing. Short term memory limitations, a focus of attention bias, and a preference for the use of temporally recent information are three examples. This paper shows that psychological constraints such as these can be used effectively as domain-independent sources of bias to guide feature set selection and weighting for case-based learning algorithms.We first show that cognitive biases can be automatically and explicitly encoded into the baseline instance representation: each bias modifies the representation by changing features, deleting features, or modifying feature weights. Next, we investigate the related problems of cognitive bias selection and cognitive bias interaction for the feature weighting approach. In particular, we compare two cross-validation algorithms for bias selection that make different assumptions about the independence of individual component biases. In evaluations on four natural language learning tasks, we show that the bias selection algorithms can determine which cognitive bias or biases are relevant for each learning task and that the accuracy of the case-based learning algorithm improves significantly when the selected bias(es) are incorporated into the baseline instance representation.