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Label stiker adalah jenis selembar kertas cetak, plastik vinil atau bahan lain yang terdapat perekat di salah satu sisinya. Pada dasarnya stiker terdiri dari atas 3 material berbeda, yaitu material pembawa, material perekat dan kertas release atau lebih dikenal dengan kertas silikon. Dari material yang dapat dibuat menjadi bahan baku utama dari mainan tradisional adalah kertas release di mana kertas release dapat dibuat menjadi mainan tradisional sontoloyo atau solame. Kemudian material tersebut harus dipisahkan terlebih dahulu agar dapat dibuat menjadi mainan dengan cara mengupas material pembawa dan material perekat dari kertas release. Pengrajin mainan tradisional yang menggunakan teknik manual dalam proses pengupasan sehingga proses produksinya memakan waktu yang cukup lama, salah satunya terdapat di kota Cirebon. Sehingga penulis menciptakan alat Perancangan Mesin Pengupas Label Stiker bertujuan dari membantu mempercepat proses produksi pengupasan label stiker agar mempersingkat waktu produksi dan juga membantu permasalahan pengolahan serta pemanfaatan limbah stiker menjadi produk yang dapat dipakai kembali. Alat yang direalisasikan berukuran tinggi 90cm, lebar 40cm, panjang 80cm, menggunakan Arduino Uno sebagai microcontroller utamanya, sensor IR, proximity, motor DC, relay, LCD dan catu daya 12V. Di mana penulis mendapatkan hasil bahwa dengan menggunakan alat ini dapat mempercepat proses pengupasan di mana rata-rata waktu pengupasan selama 6,50 menit. A sticker label is a type of printed paper, vinyl or other material that has adhesive on one side. Basically, stickers consist of 3 different materials, namely carrier material, adhesive material and release paper or better known as silicone paper. Of the materials that can be made into the main raw material for traditional toys is release paper where release paper can be made into traditional sontoloyo or solame toys. Then the material must be separated first so that it can be made into toys by peeling off the carrier material and adhesive material from the release paper. Traditional toy craftsmen who use manual techniques in the stripping process so that the production process takes quite a long time, one of which is in the city of Cirebon. So the authors created a label sticker peeling machine with the aim of helping speed up the production process of stripping sticker labels in order to shorten production time and also help with processing problems and utilizing sticker waste into products that can be reused. The realized tool measures 90cm high, 40cm wide, 80cm long, uses Arduino Uno as its main microcontroller, IR sensor, proximity, DC motor, relay, LCD and 12V power supply. Where the authors get the result that using this tool can speed up the stripping process where the average stripping time is 6.50 minutes.

In most cases, three-dimensional paper-based microfluidic analytical devices (3D-μPADs) were fabricated manually by stacking or folding methods. For the first time, digital light processing stereolithography (DLP-SLA) 3D printing technology was adopted to automatically make 3D-μPADs. In the fabrication process, a printing pause was set between two layers to allow paper to be placed in the resin tank. The resin on the fresh paper spontaneously bonded to the former cured paper layer during curing, thus realizing the automatic bonding and alignment between different layers of paper and avoiding the human participation and errors as in stacking and folding methods. There was a gap between two vertical aligned flow paths, therefore the liquid did not flow spontaneously from the upper layer to the lower layer. Most of the fluid flow in 3D-μPADs was spontaneous or manually activated, which was not conducive to complex assays that require different regents to be delivered sequentially. Herein, we used an electric field or airflow to trigger the fluid flow and demonstrated the flow controllability by a proof-of-concept colorimetric assay. The limits of detection of glucose and albumin were 0.8 mM and 3.5 μM, respectively, which were sufficient for clinical requirements. Given the characteristic of flow controllability, we believe that the proposed 3D-μPADs have great potential to make paper-based complex assays automated and programmable.

Non-contact vital sign monitoring enables the estimation of vital signs, such as heart rate, respiratory rate and oxygen saturation (SpO2), by measuring subtle color changes on the skin surface using a video camera. For patients in a hospital ward, the main challenges in the development of continuous and robust non-contact monitoring techniques are the identification of time periods and the segmentation of skin regions of interest (ROIs) from which vital signs can be estimated. We propose a deep learning framework to tackle these challenges. Approach: This paper presents two convolutional neural network (CNN) models. The first network was designed for detecting the presence of a patient and segmenting the patient’s skin area. The second network combined the output from the first network with optical flow for identifying time periods of clinical intervention so that these periods can be excluded from the estimation of vital signs. Both networks were trained using video recordings from a clinical study involving 15 pre-term infants conducted in the high dependency area of the neonatal intensive care unit (NICU) of the John Radcliffe Hospital in Oxford, UK. Main results: Our proposed methods achieved an accuracy of 98.8% for patient detection, a mean intersection-over-union (IOU) score of 88.6% for skin segmentation and an accuracy of 94.5% for clinical intervention detection using two-fold cross validation. Our deep learning models produced accurate results and were robust to different skin tones, changes in light conditions, pose variations and different clinical interventions by medical staff and family visitors. Significance: Our approach allows cardio-respiratory signals to be continuously derived from the patient’s skin during which the patient is present and no clinical intervention is undertaken.

Infectious diseases and antimicrobial resistance are major burdens in developing countries, where very specific conditions impede the deployment of established medical infrastructures. Since biosensing devices are nowadays very common in developed countries, particularly in the field of diagnostics, they are at a stage of maturity at which other potential outcomes can be explored, especially on their possibilities for multiplexing and automation to reduce the time-to-results. However, the translation is far from being trivial. In order to understand the factors and barriers that can facilitate or hinder the application of biosensors in resource-limited settings, we analyze the context from several angles. First, the technology of the devices themselves has to be rethought to take into account the specific needs and the available means of these countries. For this, we describe the partition of a biosensor into its functional shells, which define the information flow from the analyte to the end-user, and by following this partition we assess the strengths and weaknesses of biosensing devices in view of their specific technological development and challenging deployment in low-resource environments. Then, we discuss the problem of cost reduction by pointing out transversal factors, such as throughput and cost of mistreatment, that need to be re-considered when analyzing the cost-effectiveness of biosensing devices. Beyond the technical landscape, the compliance with regulations is also a major aspect that is described with its link to the validation of the devices and to the acceptance from the local medical personnel. Finally, to learn from a successful case, we analyze a breakthrough inexpensive biosensor that is showing high potential with respect to many of the described aspects. We conclude by mentioning both some transversal benefits of deploying biosensors in developing countries, and the key factors that can drive such applications.

Failure to utilize valving and automation techniques has restricted the complexity of fluidic operations that can be performed in paper microfluidic devices. We developed a toolkit of paper microfluidic valves and methods for automatic valve actuation using movable paper strips and fluid-triggered expanding elements. To the best of our knowledge, this is the first functional demonstration of this valving strategy in paper microfluidics. After introduction of fluids on devices, valves can actuate automatically a) after a certain period of time, or b) after the passage of a certain volume of fluid. Timing of valve actuation can be tuned with greater than 8.5% accuracy by changing lengths of timing wicks, and we present timed on-valves, off-valves, and diversion (channel-switching) valves. The actuators require ~30 μl fluid to actuate and the time required to switch from one state to another ranges from ~5 s for short to ~50s for longer wicks. For volume-metered actuation, the size of a metering pad can be adjusted to tune actuation volume, and we present two methods – both methods can achieve greater than 9% accuracy. Finally, we demonstrate the use of these valves in a device that conducts a multi-step assay for the detection of the malaria protein PfHRP2. Although slightly more complex than devices that do not have moving parts, this valving and automation toolkit considerably expands the capabilities of paper microfluidic devices. Components of this toolkit can be used to conduct arbitrarily complex, multi-step fluidic operations on paper-based devices, as demonstrated in the malaria assay device.

To determine delivered dose to the spinal cord, a technique has been developed to propagate manual contours from kilovoltage computed-tomography (kVCT) scans for treatment planning to megavoltage computed-tomography (MVCT) guidance scans. The technique uses the Elastix software to perform intensity-based deformable image registration of each kVCT scan to the associated MVCT scans. The registration transform is then applied to contours of the spinal cord drawn manually on the kVCT scan, to obtain contour positions on the MVCT scans. Different registration strategies have been investigated, with performance evaluated by comparing the resulting auto-contours with manual contours, drawn by oncologists. The comparison metrics include the conformity index (CI), and the distance between centres (DBC). With optimised registration, auto-contours generally agree well with manual contours. Considering all 30 MVCT scans for each of three patients, the median CI is \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$0.759 \pm 0.003$ \end{document}0.759±0.003, and the median DBC is (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$0.87 \pm 0.01$ \end{document}0.87±0.01) mm. An intra-observer comparison for the same scans gives a median CI of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$0.820 \pm 0.002$ \end{document}0.820±0.002 and a DBC of (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$0.64 \pm 0.01$ \end{document}0.64±0.01) mm. Good levels of conformity are also obtained when auto-contours are compared with manual contours from one observer for a single MVCT scan for each of 30 patients, and when they are compared with manual contours from six observers for two MVCT scans for each of three patients. Using the auto-contours to estimate organ position at treatment time, a preliminary study of 33 patients who underwent radiotherapy for head-and-neck cancers indicates good agreement between planned and delivered dose to the spinal cord.

Water soluble pullulan films were formatted into paper-based microfluidic devices, serving as a controlled time shutoff valve. The utility of the valve was demonstrated by a one-step, fully automatic implementation of a complex pesticide assay requiring timed, sequential exposure of an immobilized enzyme layer to separate liquid streams. Pullulan film dissolution and the capillary wicking of aqueous solutions through the device were measured and modeled providing valve design criteria. The films dissolve mainly by surface erosion, meaning the film thickness mainly controls the shutoff time. This method can also provide time-dependent sequential release of reagents without compromising the simplicity and low cost of paper-based devices.

In radiotherapy, abdominal and thoracic sites are candidates for performing motion tracking. With real-time control it is possible to adjust the multileaf collimator (MLC) position to the target position. However, positions are not perfectly matched and position errors arise from system delays and complicated response of the electromechanic MLC system. Although, it is possible to compensate parts of these errors by using predictors, residual errors remain and need to be compensated to retain target coverage. This work presents a method to statistically describe tracking errors and to automatically derive a patient-specific, per-segment margin to compensate the arising underdosage on-line, i.e. during plan delivery. The statistics of the geometric error between intended and actual machine position are derived using kernel density estimators. Subsequently a margin is calculated on-line according to a selected coverage parameter, which determines the amount of accepted underdosage. The margin is then applied onto the actual segment to accommodate the positioning errors in the enlarged segment. The proof-of-concept was tested in an on-line tracking experiment and showed the ability to recover underdosages for two test cases, increasing \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${{V}_{90 \%}}$ \end{document}V90% in the underdosed area about \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$47 \% $ \end{document}47% and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$41 \% $ \end{document}41%, respectively. The used dose model was able to predict the loss of dose due to tracking errors and could be used to infer the necessary margins. The implementation had a running time of 23 ms which is compatible with real-time requirements of MLC tracking systems. The auto-adaptivity to machine and patient characteristics makes the technique a generic yet intuitive candidate to avoid underdosages due to MLC tracking errors.

In conventional retinal region detection methods for optical coherence tomography (OCT) images, many parameters need to be set manually, which is often detrimental to their generalizability. We present a scheme to detect retinal regions based on fully convolutional networks (FCN) for automatic diagnosis of abnormal maculae in OCT images. The FCN model is trained on 900 labeled age-related macular degeneration (AMD), diabetic macular edema (DME) and normal (NOR) OCT images. Its segmentation accuracy is validated and its effectiveness in recognizing abnormal maculae in OCT images is tested and compared with traditional methods, by using the spatial pyramid matching based on sparse coding (ScSPM) classifier and Inception V3 classifier on two datasets: Duke dataset and our clinic dataset. In our clinic dataset, we randomly selected half of the B-scans of each class (300 AMD, 300 DME, and 300 NOR) for training classifier and the rest (300 AMD, 300 DME, and 300 NOR) for testing with 10 repetitions. Average accuracy, sensitivity, and specificity of 98.69%, 98.03%, and 99.01% are obtained by using ScSPM classifier, and those of 99.69%, 99.53%, and 99.77% are obtained by using Inception V3 classifier. These two classification algorithms achieve 100% classification accuracy when directly applied to Duke dataset, where all the 45 OCT volumes are used as test set. Finally, FCN model with or without flattening and cropping and its influence on classification performance are discussed.

The RABiT (Rapid Automated Biodosimetry Tool) is a dedicated Robotic platform for the automation of cytogenetics-based biodosimetry assays. The RABiT was developed to fulfill the critical requirement for triage following a mass radiological or nuclear event. Starting from well-characterized and accepted assays we developed a custom robotic platform to automate them. We present here a brief historical overview of the RABiT program at Columbia University from its inception in 2005 until the RABiT was dismantled at the end of 2015. The main focus of this paper is to demonstrate how the biological assays drove development of the custom robotic systems and in turn new advances in commercial robotic platforms inspired small modifications in the assays to allow replacing customized robotics with 'off the shelf' systems. Currently, a second-generation, RABiT II, system at Columbia University, consisting of a PerkinElmer cell::explorer, was programmed to perform the RABiT assays and is undergoing testing and optimization studies.

To determine the impact of white matter hyperintensities (WMHs) on physical health and cognitive function in 60-64 year old individuals residing in the community.A subsample of 478 persons aged 60-64 from a larger community sample underwent brain magnetic resonance imaging (MRI) scans. WMHs on T2 weighted FLAIR (fluid attenuated inversion recovery) MRI scans were assessed using an automated procedure. Subjects were assessed for global cognitive function, episodic memory, working memory (digit span), information processing speed (Symbol Digit Modalities Test; SDMT), fine motor dexterity (Purdue Pegboard), and grip strength, and completed the Physical Component Summary of the Short Form Health Survey (SF-12). Regression analyses were used to examine the effect of WMHs on physical and cognitive function.Deep and periventricular WMHs were present in all subjects, with women having slightly more lesions than men. WMHs were significantly associated with poorer reported physical health on the SF-12 scale, after adjusting for depression, cognitive function, and brain atrophy. WMHs were also related to lower scores on the Purdue Pegboard test, grip strength, choice reaction time, and SDMT, but not on tests of episodic memory, working memory, general intellectual function, and global cognitive function. On regression analyses, the Purdue Pegboard test and grip strength were related to physical disability.WMHs are common, albeit mild, in middle adult life. They are associated with physical disability, possibly through reduced speed, fine motor coordination, and muscular strength. They are also related to slowed information processing speed but not other cognitive functions.

Objectives: A new cerebrospinal fluid (CSF) shunt system, Sinushunt®, has recently been introduced. CSF is shunted from the ventricles to the transverse sinus. The Sinushunt is not a classical differential pressure shunt; instead, it opens as soon as there is a positive pressure over the shunt and the flow is dependent on the resistance of the system, which is high compared with traditional CSF shunts. The objective of this study was to characterise the features of the Sinushunt and to evaluate its influence on the CSF system. Methods: Five brand new Sinushunts with distal catheters were tested. An automated, computerised experimental apparatus based on regulation of pressure, built into an incubator at 37 °C, was used. Opening pressure, resistance, and anti-reflux properties were determined. Results: The mean (SD) opening pressure was highly dependent on the pressure in the sinus: Popen = 1.3 (0.6) mm Hg with Psinus = 0.0 mm Hg, and Popen = 7.5 (0.6) mm Hg for Psinus = 6.5 mm Hg. The mean (SD) resistance of the shunts was 7.9 (0.3) mm Hg/ml/min and not clinically significantly affected by the sinus pressure. In one shunt there was reflux, and in another two shunts there was a very small, but similar, tendency. Conclusions: This study confirms that the resistance of the Sinushunt is comparable to the physiological values in humans. However, the optimal post-operative resistance for different hydrocephalus types is unknown, and randomised clinical trials are needed to confirm improved outcome and reduced complication rate for the Sinushunt compared with traditional low resistance ventriculoperitoneal shunts. A weakness of the anti-reflux system of the Sinushunt must be suspected and has to be further investigated.

Bundles of paper, similar to sterling banknotes, were counted in banks in England and Wales. Subsequent analysis showed that the counting process, both by machine and by hand, transferred nanogram amounts of cocaine to the paper. Crystalline material, similar to cocaine hydrochloride, could be observed on the surface of the paper following counting. The geographical distribution of contamination broadly followed Government statistics for cocaine usage within the UK. Diacetylmorphine, Δ9-tetrahydrocannabinol (THC) and 3,4-methylenedioxymethylamphetamine (MDMA) were not detected during this study.

Recent developments in molecular breeding and directed evolution have promised great developments in industrial enzymes as demonstrated by exponential improvements in beta-lactamase and green fluorescent protein (GFP). Detection of and screening for improved enzymes are relatively easy if the target enzyme is expressible in a suitable high-throughput screening host and a clearly defined and usable screen or selection is available, as with GFP and beta-lactamase. Fungal cellulases, however, are difficult to measure and have limited expressibility in heterologous hosts. Furthermore, traditional cellulase assays are tedious and time-consuming. Multiple enzyme components, an insoluble substrate, and generally slow reaction rates have plagued cellulase researchers interested in creating cellulase mixtures with increased activities and/or enhanced biochemical properties. Although the International Union of Pure and Applied Chemists standard measure of cellulase activity, the filter paper assay (FPA), can be reproduced in most laboratories with some effort, this method has long been recognized for its complexity and susceptibility to operator error. Our current automated FPA method is based on a Cyberlabs C400 robotics deck equipped with customized incubation, reagent storage, and plate-reading capabilities that allow rapid evaluation of cellulases acting on cellulose and has a maximum throughput of 84 enzyme samples per day when performing the automated FPA.

This Review focuses on recent work in the field of paper microfluidics that specifically addresses the goal of translating the multistep processes that are characteristic of gold-standard laboratory tests to low-resource point-of-care settings. A major challenge is to implement multistep processes with the robust fluid control required to achieve the necessary sensitivity and specificity of a given application in a user-friendly package that minimizes equipment. We review key work in the areas of fluidic controls for automation in paper-based devices, readout methods that minimize dedicated equipment, and power and heating methods that are compatible with low-resource point-of-care settings. We also highlight a focused set of recent applications and discuss future challenges.

Parallelism is a prerequisite for the determination of relative potency in bioactivity assays. It involves the testing of similarity between a pair of dose-response curves of reference standard and test sample. The evaluation of parallelism is a requirement listed by both the United States Pharmacopeia (USP) and European Pharmacopeia (EP). The revised USP Chapters 〈1032〉 and 〈1034〉 suggest testing parallelism using an equivalence method. However, implementation of this method can be challenging for laboratories that lack experience in statistical analysis and software development. In this paper we present a customized assay analysis template that is developed based on a fully good manufacturing practice (GMP)-compliant software package. The template allows for automation of the USP-recommended equivalence parallelism testing method for 4PLmodel in bioassays. It makes the implementation of the USP guidance both practical and feasible. Use of the analysis template is illustrated through a practical example. LAY ABSTRACT: Parallelism is a prerequisite for the determination of relative potency in bioactivity assays. It involves the testing of similarity between a pair of dose-response curves of reference standard and test sample. The evaluation of parallelism is a requirement listed by both the United States Pharmacopeia (USP) and European Pharmacopeia (EP). The revised USP Chapters 〈1032〉 and 〈1034〉 suggest testing parallelism using an equivalence method. However, implementation of this method can be challenging for laboratories that lack experience in statistical analysis and software development. In this paper we present a customized assay analysis template that is developed based on a fully good manufacturing practice (GMP)-compliant software package. The template allows for automation of the USP-recommended equivalence parallelism testing method for 4-parameter logistic model in bioassays. It makes the implementation of the USP guidance both practical and feasible. Use of the analysis template is illustrated through a practical example.

Most laboratory assays take advantage of multi-step protocols to achieve high performance, but conventional paper-based tests (e.g., lateral flow tests) are generally limited to assays that can be carried out in a single fluidic step. We have developed two-dimensional paper networks (2DPNs) that use materials from lateral flow tests but reconfigure them to enable programming of multi-step reagent delivery sequences. The 2DPN uses multiple converging fluid inlets to control the arrival time of each fluid to a detection zone or reaction zone, and it requires a method to disconnect each fluid source in a corresponding timed sequence. Here, we present a method that allows programmed disconnection of fluid sources required for multi-step delivery. A 2DPN with legs of different lengths is inserted into a shared buffer well, and the dropping fluid surface disconnects each leg at in a programmable sequence. This approach could enable multi-step laboratory assays to be converted into simple point-of-care devices that have high performance yet remain easy to use.

A method is described for the preparation of linearising cam. It is based upon the mathematical treatment of the response obtained from an initial scan using the stepwedge prepared from human serum protein on rules, siliconised paper. The form of the equation connecting protein concentration on the paper strip to the reflected light complied with the requirements of a rectangular hyperbola.

An ELISA for the quantitation of the C5a anaphylatoxin of complement in human plasma is presented which is based on the use of both a monoclonal antibody and polyclonal antibodies to C5a. Its detection limit is 1 ng C5a/ml plasma. It detects no C5a in fresh EDTA-plasma. Complete removal of C5 by an optimized precipitation step prior to the assay procedure is an essential feature of the method.