Super-Resolution Reconstruction of Images Based on Microarray Camera

In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a highresolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. Microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array images. The array images are interpolated to obtain a HR image initially followed by a convolution neural network (CNN) procedure for enhancement. The convolution layers of our convolution neural network are 3×3 or 1×1 layers, of which the 1×1 layers are used to improve the network performance particularly. A bottleneck structure is applied to reduce the parameter numbers of the nonlinear mapping and to improve the nonlinear capability of the whole network. Finally, we use a 3×3 deconvolution layer to significantly reduce the number of parameters compared to the deconvolution layer of FSRCNN-s. The experiments show that the proposed method can not only ameliorate effectively the texture quality of the target image based on the array images information, but also further enhance the quality of the initial high resolution image by the improved CNN.     

Supramolecular Assembly of Aminoethylene‐Lipopeptide PMO Conjugates into RNA Splice‐Switching Nanomicelles

Phosphorodiamidate morpholino oligomers (PMOs) are oligonucleotide analogs that can be used for therapeutic modulation of pre‐mRNA splicing. Similar to other classes of nucleic acid‐based therapeutics, PMOs require delivery systems for efficient transport to the intracellular target sites. Here, artificial peptides based on the oligo(ethylenamino) acid succinyl‐tetraethylenpentamine (Stp), hydrophobic modifications, and an azide group are presented, which are used for strain‐promoted azide‐alkyne cycloaddition conjugation with splice‐switching PMOs. By systematically varying the lead structure and formulation, it is determined that the type of contained fatty acid and supramolecular assembly have a critical impact on the delivery efficacy. A compound containing linolenic acid with three cis double bonds exhibits the highest splice‐switching activity and significantly increases functional protein expression in pLuc/705 reporter cells in vitro and after local administration in vivo. Structural and mechanistic studies reveal that the lipopeptide PMO conjugates form nanoparticles, which accelerate cellular uptake and that the content of unsaturated fatty acids enhances endosomal escape. In an in vitro Duchenne muscular dystrophy exon skipping model using H2K‐mdx52 dystrophic skeletal myotubes, the highly potent PMO conjugates mediate significant splice‐switching at very low nanomolar concentrations. The presented aminoethylene‐lipopeptides are thus a promising platform for the generation of PMO‐therapeutics with a favorable activity/toxicity profile.     

Evaluating the transfer of technology between application domains: a critical evaluation of the human component in the system

Technology can take many forms from the development of sophisticated electronics to the application of basic procedural principles. Technology transfer can also take several forms, however, in this case, it is the transfer of technological principles between application domains that is of primary interest. This paper presents a framework (the Five ‘M’s framework) that can be used to consider the likely success of technology transfer. The framework is based upon a sociotechnical system approach. The framework is illustrated with an evaluation of the introduction of intelligent cruise control into motor vehicles. It is argued that this is a technological concept first developed as an aerospace application in the form of the autopilot. In this case, it is argued that the transfer of this technology in its current form may potentially compromise safety.     

Ice-slurry production using direct contact heat transfer

An ice slurry generation system was developed using direct contact heat transfer between water and the coolant, Fluroinert FC-84. The location of the coolant nozzle is an important design consideration to avoid clogging due to freezing of water. An ice fraction of up to about 40 percent was obtained with the nozzle located at the bottom of the ice slurry tank and the jet directed upwards into the water. Two simplified model were developed to extract the heat transfer coefficient between the coolant drops and the water. The first model requires as input the average drop diameter and the residence time while the second model uses the measured drop diameter distribution. The estimated heat transfer coefficients are much smaller than those computed using single-sphere correlations.     

The ability of the Millon Clinical Multiaxial Inventory--Third Edition to detect malingering.

This study investigated the ability of the Millon Clinical Multiaxial Inventory--Third Edition (MCMI-III) to discriminate students malingering psychopathology (n=106) from bona fide psychiatric inpatients (n=202). Students were randomly assigned to a fake-bad or an honest-responding condition. Analyses investigated the ability of the modifier indices to discriminate fake-bad group participants from the psychiatric inpatients. Scale X raw cutoff score >178 yielded a positive predictive power (PPP) of 0.0, a negative predictive power (NPP) of 63.1, and a hit rate of 63.1%. Optimal cutoff scores were developed. Scale X Base Rate (BR) >84 provided a PPP of 55.6, an NPP of 72.1, and a hit rate of 65.2%. Scale Y BR     

Software for dynamic reconfigurable order picking systems

This paper describes an approach, conceptual framework, and software architecture for dynamic reconfiguration of the order picking system. The research and development project was sponsored by the Material Handling Research Center (MHRC), a National Science Foundation sponsored Cooperative Industry/University Research Center. The storage configuration is assumed to be an in-the-aisle order picking system in which stockkeeping units (SKUs) can occupy variable capacity storage locations and stock-splitting is allowed among zones (clusters). The product mix may include multiple product families with different life cycles, correlated demand within families and commonality of demand across families.     

Bayesian and Dempster-Shafer fusion

The Kalman Filter is traditionally viewed as a prediction-correction filtering algorithm. In this work we show that it can be viewed as a Bayesian fusion algorithm and derive it using Bayesian arguments. We begin with an outline of Bayes theory, using it to discuss well-known quantities such as priors, likelihood and posteriors, and we provide the basic Bayesian fusion equation. We derive the Kalman Filter from this equation using a novel method to evaluate the Chapman-Kolmogorov prediction integral. We then use the theory to fuse data from multiple sensors. Vying with this approach is the Dempster-Shafer theory, which deals with measures of “belief”, and is based on the nonclassical idea of “mass” as opposed to probability. Although these two measures look very similar, there are some differences. We point them out through outlining the ideas of the Dempster-Shafer theory and presenting the basic Dempster-Shafer fusion equation. Finally we compare the two methods, and discuss the relative merits and demerits using an illustrative example.