Large-volume methacrylate monolith for plasmid purification : process engineering approach to synthesis and application

The extent of exothermicity associated with the construction of large-volume methacrylate monolithic columns has somewhat obstructed the realisation of large-scale rapid biomolecule purification especially for plasmid-based products which have proven to herald future trends in biotechnology. A novel synthesis technique via a heat expulsion mechanism was employed to prepare a 40 mL methacrylate monolith with a homogeneous radial pore structure along its thickness. Radial temperature gradient was recorded to be only 1.8 °C. Maximum radial temperature recorded at the centre of the monolith was 62.3 °C, which was only 2.3 °C higher than the actual polymerisation temperature. Pore characterisation of the monolithic polymer showed unimodal pore size distributions at different radial positions with an identical modal pore size of 400 nm. Chromatographic characterisation of the polymer after functionalisation with amino groups displayed a persistent dynamic binding capacity of 15.5 mg of plasmid DNA/mL. The maximum pressure drop recorded was only 0.12 MPa at a flow rate of 10 mL/min. The polymer demonstrated rapid separation ability by fractionating Escherichia coli DH5α-pUC19 clarified lysate in only 3 min after loading. The plasmid sample collected after the fast purification process was tested to be a homogeneous supercoiled plasmid with DNA electrophoresis and restriction analysis.

Histogram matching and global initialization for laser-only SLAM in large unstructured environments

This paper presents an enhanced algorithm for matching laser scan maps using histogram correlations. The histogram representation effectively summarizes a map's salient features such that pairs of maps can be matched efficiently without any prior guess as to their alignment. The histogram matching algorithm has been enhanced in order to work well in outdoor unstructured environments by using entropy metrics, weighted histograms and proper thresholding of quality metrics. Thus our large-scale scan-matching SLAM implementation has a vastly improved ability to close large loops in real-time even when odometry is not available. Our experimental results have demonstrated a successful mapping of the largest area ever mapped to date using only a single laser scanner. We also demonstrate our ability to solve the lost robot problem by localizing a robot to a previously built map without any prior initialization.

Parallel streaming signature EM-tree: A clustering algorithm for web scale applications

The proliferation of the web presents an unsolved problem of automatically analyzing billions of pages of natural language. We introduce a scalable algorithm that clusters hundreds of millions of web pages into hundreds of thousands of clusters. It does this on a single mid-range machine using efficient algorithms and compressed document representations. It is applied to two web-scale crawls covering tens of terabytes. ClueWeb09 and ClueWeb12 contain 500 and 733 million web pages and were clustered into 500,000 to 700,000 clusters. To the best of our knowledge, such fine grained clustering has not been previously demonstrated. Previous approaches clustered a sample that limits the maximum number of discoverable clusters. The proposed EM-tree algorithm uses the entire collection in clustering and produces several orders of magnitude more clusters than the existing algorithms. Fine grained clustering is necessary for meaningful clustering in massive collections where the number of distinct topics grows linearly with collection size. These fine-grained clusters show an improved cluster quality when assessed with two novel evaluations using ad hoc search relevance judgments and spam classifications for external validation. These evaluations solve the problem of assessing the quality of clusters where categorical labeling is unavailable and unfeasible.

Speed-based diagnostics of aerodynamic and mass imbalance in large wind turbines

Any kind of imbalance in the operation of a wind turbine has adverse effect on the downstream torsional components as well as tower structure. It is crucial to detect imbalance at its very inception. The identification of the type of imbalance is also required so that appropriate measures of fault accommodation can be performed in the control system. In particular, it is important to distinguish between mass and aerodynamic imbalance. While the former is gradually caused by a structural anomaly (e.g. ice deposition, moisture accumulation inside blade), the latter is generally associated to a fault in the pitch control system. This paper proposes a technique for the detection and identification of imbalance fault in large scale wind turbines. Unlike most other existing method it requires only the rotor speed signal which is readily available in existing turbines. Signature frequencies have been proposed in this work to identify imbalance type based on their physical phenomenology. The performance of this technique has been evaluated by simulations using an existing benchmark model. The effectiveness of the proposed method has been confirmed by the simulation results.

Fish-scale bio-inspired multifunctional ZnO nanostructures

Scales provide optical disguise, low water drag and mechanical protection to fish, enabling them to survive catastrophic environmental disasters, predators and microorganisms. The unique structures and stacking sequences of fish scales inspired the fabrication of artificial nanostructures with salient optical, interfacial and mechanical properties. Herein, we describe fish-scale bio-inspired multifunctional ZnO nanostructures that have similar morphology and structure to the cycloid scales of the Asian Arowana. These nanostructured coatings feature tunable light refraction and reflection, modulated surface wettability and damage-tolerant mechanical properties. The salient properties of these multifunctional nanostructures are promising for applications in: - (i) optical coatings, sensing or lens arrays for use in reflective displays, packing, advertising and solar energy harvesting; - (ii) self-cleaning surfaces, including anti-smudge, anti-fouling and anti-fogging, and self-sterilizing surfaces, and; - (iii) mechanical/chemical barrier coatings. This study provides a low-cost and large-scale production method for the facile fabrication of these bio-inspired nanostructures and provides new insights for the development of novel functional materials for use in 'smart' structures and applications.