Students Weigh In: Usability Test of Online Library Tutorials

Librarians can improve their online tutorials by borrowing usability testing techniques from the computer science field to improve the human-computer interface. This study involved a multimethod usability test of librarian-created tutorials to determine what students learned, how they felt on several affective questions, and what they suggested for improving the tutorials. Results of pre- and post-tests showed that student knowledge increased, and surveys and focus group findings lean to several suggestions for improving engagement and placing tutorials where they will be most effective. This case study demonstrates the value of user input to improve the effectiveness of online instruction for information literacy.     

Optics clustered to output unique solutions: a multi-laser facility for combined single molecule and ensemble microscopy

Optics clustered to output unique solutions (OCTOPUS) is a microscopy platform that combines single molecule and ensemble imaging methodologies. A novel aspect of OCTOPUS is its laser excitation system, which consists of a central core of interlocked continuous wave and pulsed laser sources, launched into optical fibres and linked via laser combiners. Fibres are plugged into wall-mounted patch panels that reach microscopy end-stations in adjacent rooms. This allows multiple tailor-made combinations of laser colours and time characteristics to be shared by different end-stations minimising the need for laser duplications. This setup brings significant benefits in terms of cost effectiveness, ease of operation, and user safety. The modular nature of OCTOPUS also facilitates the addition of new techniques as required, allowing the use of existing lasers in new microscopes while retaining the ability to run the established parts of the facility. To date, techniques interlinked are multi-photon/multicolour confocal fluorescence lifetime imaging for several modalities of fluorescence resonance energy transfer (FRET) and time-resolved anisotropy, total internal reflection fluorescence, single molecule imaging of single pair FRET, single molecule fluorescence polarisation, particle tracking, and optical tweezers. Here, we use a well-studied system, the epidermal growth factor receptor network, to illustrate how OCTOPUS can aid in the investigation of complex biological phenomena.     

Identifying and understanding urban sport areas using Nokia Sports Tracker

Current advancements in pervasive technologies allow users to create and share an increasing amount of whereabouts data. Thus, some rich datasets on human mobility are becoming available on the web. In this paper we extracted approximately 790,000 mobility traces from a web-based repository of GPS tracks—the Nokia Sports Tracker Service. Using data mining mechanisms, we show that this data can be analyzed to uncover daily routines and interesting schemes in the use of public spaces. We first show that our approach supports large-scale analysis of people’s whereabouts by comparing behavioral patterns across cities. Then, using Kernel Density Estimation, we present a mechanism to identify popular sport areas in individual cities. This kind of analysis allows us to highlight human-centered geographies that can support a wide range of applications ranging from location-based services to urban planning.     

Coreference resolution: an empirical study based on SemEval-2010 shared Task 1

This paper presents an empirical evaluation of coreference resolution that covers several interrelated dimensions. The main goal is to complete the comparative analysis from the SemEval-2010 task on Coreference Resolution in Multiple Languages. To do so, the study restricts the number of languages and systems involved, but extends and deepens the analysis of the system outputs, including a more qualitative discussion. The paper compares three automatic coreference resolution systems for three languages (English, Catalan and Spanish) in four evaluation settings, and using four evaluation measures. Given that our main goal is not to provide a comparison between resolution algorithms, these are merely used as tools to shed light on the different conditions under which coreference resolution is evaluated. Although the dimensions are strongly interdependent, making it very difficult to extract general principles, the study reveals a series of interesting issues in relation to coreference resolution: the portability of systems across languages, the influence of the type and quality of input annotations, and the behavior of the scoring measures.     

Experimental characterization of electrostatically actuated in-plane bending of microcantilevers

Experimental validation of numerical models developed by the authors to predict the static behaviour of microelectrostatic actuators is described. Cantilever microbeams, currently used in connection with RF-MEMS and micro-scale material testing were analysed. A set of microcantilevers, bending in the plane of the wafer, i.e. in the same plane as the profiling system’s target, was tested. This differs from the popular case of out-of-plane microbeams, usually studied in the literature. Geometry nonlinearity caused by large deflection of the microbeam was investigated and nonlinear coupled formulation of electromechanical equilibrium was performed. Coupled-field analysis was implemented using the Finite Element Method (FEM), to predict displacements and pull-in voltage measured by Fogale Zoomsurf 3D, subsequently plotting the displacement-versus-voltage curve to complete model validation. FEM nonlinear analysis, based on iterative approach with mesh morphing, and FEM non-incremental approach, including a special element proposed by the authors, are compared to the linear solution and to experimental results. Geometry nonlinearity appears relevant in microbeam modelling and requires a nonlinear solution of the coupled problem. Investigative work, which compared the results of 2D and 3D models to experimental data, revealed that some three dimensional effects are significant in model validation, but the 2D approach may be effective in predicting static behaviour provided that at least a microbeam thickness equivalent is adopted.     

Robust network monitoring in the presence of non-cooperative traffic queries

We present the design of a predictive load shedding scheme for a network monitoring platform that supports multiple and competing traffic queries. The proposed scheme can anticipate overload situations and minimize their impact on the accuracy of the traffic queries. The main novelty of our approach is that it considers queries as black boxes, with arbitrary (and highly variable) input traffic and processing cost. Our system only requires a high-level specification of the accuracy requirements of each query to guide the load shedding procedure and assures a fair allocation of computing resources to queries in a non-cooperative environment. We present an implementation of our load shedding scheme in an existing network monitoring system and evaluate it with a diverse set of traffic queries. Our results show that, with the load shedding mechanism in place, the monitoring system can preserve the accuracy of the queries within predefined error bounds even during extreme overload conditions.     

Observer-invariant histopathology using genetics-based machine learning

Prostate cancer accounts for one-third of noncutaneous cancers diagnosed in US men and is a leading cause of cancer-related death. Advances in Fourier transform infrared spectroscopic imaging now provide very large data sets describing both the structural and local chemical properties of cells within prostate tissue. Uniting spectroscopic imaging data and computer-aided diagnoses (CADx), our long term goal is to provide a new approach to pathology by automating the recognition of cancer in complex tissue. The first step toward the creation of such CADx tools requires mechanisms for automatically learning to classify tissue types—a key step on the diagnosis process. Here we demonstrate that genetics-based machine learning (GBML) can be used to approach such a problem. However, to efficiently analyze this problem there is a need to develop efficient and scalable GBML implementations that are able to process very large data sets. In this paper, we propose and validate an efficient GBML technique——based on an incremental genetics-based rule learner. exploits massive parallelisms via the message passing interface (MPI) and efficient rule-matching using hardware-implemented operations. Results demonstrate that is capable of performing prostate tissue classification efficiently, making a compelling case for using GBML implementations as efficient and powerful tools for biomedical image processing.     

Complexes With Biologically Active Ligands. Part 6 Ni(II) Coordination Compounds of Hydrazine and Heterocyclic Sulfonamides as Inhibitors of the Zinc Enzyme Carbonic Anhydrase

Ternary Ni(II) complexes of hydrazine and eight heterocyclic sulfonamides possessing carbonic anhydrase (CA) inhibitory properties, were prepared and characterized by elemental analysis, spectroscopic, magnetic, thermogravimetric, and conductimetric measurements. The complexes behave as strong inhibitors for two isozymes (I and II) of carbonic anhydrase.