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This paper extends our previous work on silver-enhancement based self-assembling structures for designing reliable, self-powered biosensors with forward error correcting (FEC) capability. At the core of the proposed approach is the integration of paper-based microfluidics with quick response (QR) codes that can be optically scanned using a smart-phone. The scanned information is first decoded to obtain the location of a web-server which further processes the self-assembled QR image to determine the concentration of target analytes. The integration substrate for the proposed FEC biosensor is polyethylene and the patterning of the QR code on the substrate has been achieved using a combination of low-cost ink-jet printing and a regular ballpoint dispensing pen. A paper-based microfluidics channel has been integrated underneath the substrate for acquiring, mixing and flowing the sample to areas on the substrate where different parts of the code can self-assemble in presence of immobilized gold nanorods. In this paper we demonstrate the proof-of-concept detection using prototypes of QR encoded FEC biosensors.

This study introduced a barcode-like design into a paper-based blood typing device by integrating with smartphone-based technology. The concept of presenting a paper-based blood typing assay in a barcode-like pattern significantly enhanced the adaptability of the assay to the smartphone technology. The fabrication of this device involved the use of a printing technique to define hydrophilic bar channels which were, respectively, treated with Anti-A, -B, and -D antibodies. These channels were then used to perform blood typing assays by introducing a blood sample. Blood type can be visually identified from eluting lengths in bar channels. A smartphone-based analytical application was designed to read the bar channels, analogous to scanning a barcode, interpret this information, and then report results to users. The proposed paper-based blood typing device is rapidly read by smartphones and easy for the user to operate. We envisage that the adaptation of paper-based devices to the widely accepted smartphone technology will increase the capability of paper-based diagnostics with rapid assay result interpretation, data storage, and transmission.

This article proposes an Enhanced Memetic Differential Evolution (EMDE) for designing digital filters which aim at detecting defects of the paper produced during an industrial process. Defect detection is handled by means of two Gabor filters and their design is performed by the EMDE. The EMDE is a novel adaptive evolutionary algorithm which combines the powerful explorative features of Differential Evolution with the exploitative features of three local search algorithms employing different pivot rules and neighborhood generating functions. These local search algorithms are the Hooke Jeeves Algorithm, a Stochastic Local Search, and Simulated Annealing. The local search algorithms are adaptively coordinated by means of a control parameter that measures fitness distribution among individuals of the population and a novel probabilistic scheme. Numerical results confirm that Differential Evolution is an efficient evolutionary framework for the image processing problem under investigation and show that the EMDE performs well. As a matter of fact, the application of the EMDE leads to a design of an efficiently tailored filter. A comparison with various popular metaheuristics proves the effectiveness of the EMDE in terms of convergence speed, stagnation prevention, and capability in detecting solutions having high performance.

It can be tempting for providers to reach for paper, especially when things get hectic. Planning and support help keep the hybrid record from getting more hybrid than it has to be.

Objectives: To evaluate the efficiency and acceptance of digital pen and paper technology for real-time clinical data acquisition., Methods: A prospective interventional unblinded study involving consecutive patients in two clinical settings during a defined time-frame was proposed. The first trial was designed as a stress test to evaluate acceptance in a workload-intensive environment. Acceptance was assessed using observations and a satisfaction questionnaire. The second trial was intended to determine the reliability of data acquisition in a controlled environment. Reliability was assessed by comparing the performance of the digital pen against scanner analysis and a double human blinded acquisition., Results: Overall, users were satisfied with the use of the digital pen (median 3 on a Likert-scale (-5, 5)). Without any specific user training, successful data acquisition was greater than 80%. Use of this technology required less adaptation than standard computer devices, and was easy to learn and use. Ergonomic problems shaded the perception of the technology by inducing an increased cognitive load. Digitalized data was missing either because of a bug or due to lack of data validation. The reliability obtained with the digital pen was significantly lower to that obtained with the scanner., Conclusions: Natural technology such as the digital pen proved to be a good tool in stressful clinical environments without interfering with the normal workload or increasing the time for data acquisition. However, in order to improve quality of data acquisition, designing acquisition forms specifically for the use of digital pens is of paramount importance.

The article explores on the simple procedure for processing event recorder data. The strip chart device called event recorder reads the state of an electrical switch with reference to time used in various studies is said to require a long to process the gathered data. According to the author, the usual procedure uses scissors to cut the strip charts into segments representing the desired time base which is tedious. He suggests the use of a stapler and paper cutter as an alternative for collecting the gathered data.