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Simple, low-cost methods for sensing volatile organic compounds that leave no trace and do not have a detrimental effect on the environment are able to protect communities from the impacts of contaminants in water supplies. This paper reports the development of a portable, autonomous, Internet of Things (IoT) electrochemical sensor for detecting formaldehyde in tap water. The sensor is assembled from electronics, i.e., a custom-designed sensor platform and developed HCHO detection system based on Ni(OH) 2 -Ni nanowires (NWs) and synthetic-paper-based, screen-printed electrodes (pSPEs). The sensor platform, consisting of the IoT technology, a Wi-Fi communication system, and a miniaturized potentiostat can be easily connected to the Ni(OH) 2 -Ni NWs and pSPEs via a three-terminal electrode. The custom-made sensor, which has a detection capability of 0.8 µM/24 ppb, was tested for an amperometric determination of the HCHO in deionized (DI) and tap-water-based alkaline electrolytes. This promising concept of an electrochemical IoT sensor that is easy to operate, rapid, and affordable (it is considerably cheaper than any lab-grade potentiostat) could lead to the straightforward detection of HCHO in tap water.

This work illustrates a novel prototype of a transmittance hyperspectral imaging (HSI) scanner, operating in the 400-900 nm range, and designed on purpose for non-invasive analysis of photographic materials, such as negatives, films and slides. The instrument provides high-quality spectral data and high-definition spectral images on targets of small size (e.g., 35 mm film strips) and is the first example of HSI instrumentation specifically designed for applications in the photographic conservation field. The instrument was tested in laboratory and on a set of specimens selected from a damaged photographic archive. This experimentation, though preliminary, demonstrated the soundness of a technical approach based on HSI for large-scale spectroscopic characterization of photographic archival materials. The obtained results encourage the continuation of experimentation of HSI as an advanced tool for photography conservation.

As a fundamental but difficult topic in computer vision, 3D object segmentation has various applications in medical image analysis, autonomous vehicles, robotics, virtual reality, lithium battery image analysis, etc. In the past, 3D segmentation was performed using hand-made features and design techniques, but these techniques could not generalize to vast amounts of data or reach acceptable accuracy. Deep learning techniques have lately emerged as the preferred method for 3D segmentation jobs as a result of their extraordinary performance in 2D computer vision. Our proposed method used a CNN-based architecture called 3D UNET, which is inspired by the famous 2D UNET that has been used to segment volumetric image data. To see the internal changes of composite materials, for instance, in a lithium battery image, it is necessary to see the flow of different materials and follow the directions analyzing the inside properties. In this paper, a combination of 3D UNET and VGG19 has been used to conduct a multiclass segmentation of publicly available sandstone datasets to analyze their microstructures using image data based on four different objects in the samples of volumetric data. In our image sample, there are a total of 448 2D images, which are then aggregated as one 3D volume to examine the 3D volumetric data. The solution involves the segmentation of each object in the volume data and further analysis of each object to find its average size, area percentage, total area, etc. The open-source image processing package IMAGEJ is used for further analysis of individual particles. In this study, it was demonstrated that convolutional neural networks can be trained to recognize sandstone microstructure traits with an accuracy of 96.78% and an IOU of 91.12%. According to our knowledge, many prior works have applied 3D UNET for segmentation, but very few papers extend it further to show the details of particles in the sample. The proposed solution offers a computational insight for real-time implementation and is discovered to be superior to the current state-of-the-art methods. The result has importance for the creation of an approximately similar model for the microstructural analysis of volumetric data.

We present a rotational terahertz imaging system for inline nondestructive testing (NDT) of press sleeves for the paper industry during fabrication. Press sleeves often consist of polyurethane (PU) which is deposited by rotational molding on metal barrels and its outer surface mechanically processed in several milling steps afterwards. Due to a stabilizing polyester fiber mesh inlay, small defects can form on the sleeve's backside already during the initial molding, however, they cannot be visually inspected until the whole production processes is completed. We have developed a fast-scanning frequenc-modulated continuous wave (FMCW) terahertz imaging system, which can be integrated into the manufacturing process to yield high resolution images of the press sleeves and therefore can help to visualize hidden structural defects at an early stage of fabrication. This can save valuable time and resources during the production process. Our terahertz system can record images at 0.3 and 0.5 THz and we achieve data acquisition rates of at least 20 kHz, exploiting the fast rotational speed of the barrels during production to yield sub-millimeter image resolution. The potential of automated defect recognition by a simple machine learning approach for anomaly detection is also demonstrated and discussed.

Microfluidic paper combines pump-free water transport at low cost with a high degree of sustainability, as well as good availability of the paper-forming cellulosic material, thus making it an attractive candidate for point-of-care (POC) analytics and diagnostics. Although a number of interesting demonstrators for such paper devices have been reported to date, a number of challenges still exist, which limit a successful transfer into marketable applications. A strong limitation in this respect is the (unspecific) adsorption of protein analytes to the paper fibers during the lateral flow assay. This interaction may significantly reduce the amount of analyte that reaches the detection zone of the microfluidic paper-based analytical device (µPAD), thereby reducing its overall sensitivity. Here, we introduce a novel approach on reducing the nonspecific adsorption of proteins to lab-made paper sheets for the use in µPADs. To this, cotton linter fibers in lab-formed additive-free paper sheets are modified with a surrounding thin hydrogel layer generated from photo-crosslinked, benzophenone functionalized copolymers based on poly-(oligo-ethylene glycol methacrylate) (POEGMA) and poly-dimethyl acrylamide (PDMAA). This, as we show in tests similar to lateral flow assays, significantly reduces unspecific binding of model proteins. Furthermore, by evaporating the transport fluid during the microfluidic run at the end of the paper strip through local heating, model proteins can almost quantitatively be accumulated in that zone. The possibility of complete, almost quantitative protein transport in a µPAD opens up new opportunities to significantly improve the signal-to-noise (S/N) ratio of paper-based lateral flow assays.

Photoresist is the key material in the fabrication of micropatterns or microstructures. Tuning the surface wettability of photoresist film is a critical consideration in its application of microfluidics. In this work, the surface wettability tuning of acrylic resin photoresist by oxygen plasma or ultra-violet/ozone, and its aging performance in different atmospheres, were systematically studied. The chemical and physical characterizations of the surfaces before and after modification show a dramatic decrease in the C-C group and increase in surface roughness for oxygen plasma treatment, while a decrease of the C-C group was found for the UV/ozone treatment. The above difference in the surface tuning mechanism may explain the stronger hydrophilic modification effect of oxygen plasma. In addition, we found an obvious fading of the wettability tuning effect with an environment-related aging speed, which can also be featured by the decrease of the C-C group. This study demonstrates the dominated chemical and physical changes during surface wettability tuning and its aging process, and provides basis for surface tuning and the applications in microfluidics.

Introducing spacers into pixelated electrowetting displays (EWDs) normally gives mechanical strengthening, while bringing undesired disturbance of water/oil interfacial dynamics. Hence, spacer array is a key pixel structure needs careful consideration in the design and fabrication of electrowetting displays. Here, we propose a spacer array, which is designed standing on the junction of adjacent pixel walls, fabricated by photolithography. The spacer array provides mechanical strength enhancement and reliable oil motion controllability. By optimizing the spacer distribution density, the EWD device may achieve 28% increase in open ratio (white area fraction) and withstand 60 N/mm 2 pressure. This design of spacer array reasonably solves the contradiction between mechanical strength enhancement and optoelectronic performance in EWDs, providing potential applications in oil-water two-phase microfluidic devices., Competing Interests: The authors declare no conflict of interest.

The paper addresses the evaluation of the uncertainty sources of a test bed system for calibrating voltage transformers vs. temperature. In particular, the Monte Carlo method has been applied in order to evaluate the effects of the uncertainty sources in two different conditions: by using the nominal accuracy specifications of the elements which compose the setup, or by exploiting the results of their metrological characterization. In addition, the influence of random effects on the system accuracy has been quantified and evaluated. From the results, it emerges that the choice of the uncertainty evaluation method affects the overall study. As a matter of fact, the use of a metrological characterization or of accuracy specifications provided by the manufacturers provides respectively an accuracy of 0.1 and 0.5 for the overall measurement setup.

Transmitter and receiver position errors have been known to significantly deteriorate target localization accuracy in a multi-static passive radar (MPR) system. This paper explores the use of calibration targets, whose positions are known to the MPR system, to counter the loss in target localization accuracy arising from transmitter/receiver position errors. This paper firstly evaluates the Cramér-Rao lower bound (CRLB) for bistatic range (BR)-based target localization with calibration targets, which analytically indicates the potential of calibration targets in enhancing localization accuracy. After that, this paper proposes a novel closed-form solution, which includes two steps: calibration step and localization step. Firstly, the calibration step is devoted to refine the inaccurate transmitter and receiver locations using the BR measurements from the calibration targets, and then in the calibration step, the target localization can be accurately achieved by using the refined transmitter/receiver positions and the BR measurements from the unknown target. Theoretical analysis and simulation results indicate that the proposed method can attain the CRLB at moderate measurement noise level, and exhibits the superiority of localization accuracy over existing algorithms.

A piezoelectric fiber patch (PFP) is a transducer type that is suitable for guided-wave-based structural health monitoring (SHM) due to its light, thin, and flexible characteristics. In our previous work, a PFP-based transducer design for selective excitation of the zero-order shear horizontal wave mode (SH0) was introduced (shear horizontal PFP (SHPFP)). In this work, two modified SH0 wave PFP transducer designs are proposed: the rounded corner design and the dual design. The degree of improvement is determined by a numerical simulation and the dual design-the design with the most promise-is experimentally realized. Laser Vibrometry measured the generated wave field, confirming the results from the simulation. The new designs can generate an almost pure SH0 wave. The dual design has a very strong directivity that is useful for several guided-wave-based SHM applications. The conclusions on the design's properties as a transmitter are also valid for its properties as a sensor due to the reciprocity of piezoelectric transducers., Competing Interests: The authors declare no conflicts of interest.

Glucose oxidase (EC 1.1.3.4) sensors that have been developed and widely used for glucose monitoring have generally relied on electrochemical principle. In this study, the potential use of colorimetric method for glucose detection utilizing glucose oxidase-magnetic cellulose nanocrystals (CNCs) is explored. Magnetic cellulose nanocrystals (magnetic CNCs) were fabricated using iron oxide nanoparticles (IONPs) and cellulose nanocrystals (CNCs) via electrostatic self-assembly technique. Glucose oxidase was successfully immobilized on magnetic CNCs using carbodiimide-coupling reaction. About 33% of GOx was successfully attached on magnetic CNCs, and the affinity of GOx-magnetic CNCs to glucose molecules was slightly higher than free enzymes. Furthermore, immobilization does not affect the specificity of GOx-magnetic CNCs towards glucose and can detect glucose from 0.25 mM to 2.5 mM. Apart from that, GOx-magnetic CNCs stored at 4 °C for 4 weeks retained 70% of its initial activity and can be recycled for at least ten consecutive cycles.

Electrical Impedance Tomography (EIT) is a non-invasive detection method to image the conductivity changes inside an observation region by using the electrical measurements at the boundary of this region. In some applications of EIT, the observation domain is infinite and is only accessible from one side, which leads to the so-called open EIT (OEIT) problem. Compared with conventional EIT problems, the observation region in OEIT can only be measured from limited projection directions, which makes high resolution imaging much more challenging. To improve the imaging quality of OEIT, a focusing sensor design strategy is proposed based on shape conformal theory. The conformal bijection is used to map a standard EIT sensor defined at a unit circle to a focusing OEIT sensor defined at an upper half plane. A series of numerical and experimental testes are conducted. Compared with the traditional sensor structure, the proposed focusing sensor has higher spatial resolution at the near-electrode region and is good at distinguishing multi-inclusions which are close to each other., Competing Interests: The authors declare no conflicts of interest.

Current bias compensation methods for distributed localization consider the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements noise, but ignore the negative influence by the sensor location uncertainties on source localization accuracy. Therefore, a new bias compensation method for distributed localization is proposed to improve the localization accuracy in this paper. This paper derives the theoretical bias of maximum likelihood estimation when the sensor location errors and positioning measurements noise both exist. Using the rough estimate result by MLE to subtract the theoretical bias can obtain a more accurate source location estimation. Theoretical analysis and simulation results indicate that the theoretical bias derived in this paper matches well with the actual bias in moderate noise level so that it can prove the correctness of the theoretical derivation. Furthermore, after bias compensation, the estimate accuracy of the proposed method achieves a certain improvement compared with existing methods.

Oil motion control is the key for the optical performance of electro-fluidic displays (EFD). In this paper, we introduced an extra pinning structure (EPS) into the EFD pixel to control the oil motion inside for the first time. The pinning structure canbe fabricated together with the pixel wall by a one-step lithography process. The effect of the relative location of the EPS in pixels on the oil motion was studied by a series of optoelectronic measurements. EPS showed good control of oil rupture position. The properly located EPS effectively guided the oil contraction direction, significantly accelerated switching on process, and suppressed oil overflow, without declining in aperture ratio. An asymmetrically designed EPS off the diagonal is recommended. This study provides a novel and facile way for oil motion control within an EFD pixel in both direction and timescale., Competing Interests: The authors declare no conflict of interest.

Integrating polypyrrole-cellulose nanocrystal-based composites with glucose oxidase (GOx) as a new sensing regime was investigated. Polypyrrole-cellulose nanocrystal (PPy-CNC)-based composite as a novel immobilization membrane with unique physicochemical properties was found to enhance biosensor performance. Field emission scanning electron microscopy (FESEM) images showed that fibers were nanosized and porous, which is appropriate for accommodating enzymes and increasing electron transfer kinetics. The voltammetric results showed that the native structure and biocatalytic activity of GOx immobilized on the PPy-CNC nanocomposite remained and exhibited a high sensitivity (ca. 0.73 μA·mM(-1)), with a high dynamic response ranging from 1.0 to 20 mM glucose. The modified glucose biosensor exhibits a limit of detection (LOD) of (50 ± 10) µM and also excludes interfering species, such as ascorbic acid, uric acid, and cholesterol, which makes this sensor suitable for glucose determination in real samples. This sensor displays an acceptable reproducibility and stability over time. The current response was maintained over 95% of the initial value after 17 days, and the current difference measurement obtained using different electrodes provided a relative standard deviation (RSD) of 4.47%.

Research, design, fabrication and results of various screen printed capacitive humidity sensors is presented in this paper. Two types of capacitive humidity sensors have been designed and fabricated via screen printing on recycled paper and cardboard, obtained from the regional paper and cardboard industry. As printing ink, commercially available silver nanoparticle-based conductive ink was used. A considerable amount of work has been devoted to the humidity measurement methods using paper as a dielectric material. Performances of different structures have been tested in a humidity chamber. Relative humidity in the chamber was varied in the range of 35%-80% relative humidity (RH) at a constant temperature of 23 °C. Parameters of interest were capacitance and conductance of each sensor material, as well as long term behaviour. Process reversibility has also been considered. The results obtained show a mainly logarithmic response of the paper sensors, with the only exception being cardboard-based sensors. Recycled paper-based sensors exhibit a change in value of three orders of magnitude, whereas cardboard-based sensors have a change in value of few 10s over the entire scope of relative humidity range (RH 35%-90%). Two different types of capacitor sensors have been investigated: lateral (comb) type sensors and modified, perforated flat plate type sensors. The objective of the present work was to identify the most important factors affecting the material performances with humidity, and to contribute to the development of a sensor system supported with a Radio Frequency Identification (RFID) chip directly on the material, for use in smart packaging applications. Therefore, the authors built a passive and a battery-supported wireless module based on SL900A smart sensory tag's IC to achieve UHF-RFID functionality with data logging capability.