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This work presents a unique approach to the design, fabrication, and characterization of paper-based origami robotic systems consisting of stackable pneumatic actuators. These paper-based actuators (PBAs) use materials with high elastic modulus-to-mass ratios, accordion-like structures, and direct coupling with pneumatic pressure for extension and bending. The study contributes to the scientific and engineering understanding of foldable components under applied pneumatic pressure by constructing stretchable and flexible structures with intrinsically nonstretchable materials. Experiments showed that a PBA possesses a power-to-mass ratio greater than 80 W/kg, which is more than four times that of human muscle. This work also illustrates the stackability and functionality of PBAs by two prototypes: a parallel manipulator and a legged locomotor. The manipulator consisting of an array of PBAs can bend in a specific direction with the corresponding actuator inflated. In addition, the stacked actuators in the manipulator can rotate in opposite directions to compensate for relative rotation at the ends of each actuator to work in parallel and manipulate the platform. The locomotor rotates the PBAs to apply and release contact between the feet and the ground. Furthermore, a numerical model developed in this work predicts the mechanical performance of these inflatable actuators as a function of dimensional specifications and folding patterns. Overall, we use stacked origami actuators to implement functionalities of manipulation, gripping, and locomotion as conventional robotic systems. Future origami robots made of paper-like materials may be suitable for single use in contaminated or unstructured environments or low-cost educational materials.

Background The screening of biological hazards, chemical contaminants and allergens in food products is a major concern of food industry since they can cause serious illnesses and even lead to death. Therefore, there is a significant interest in developing low-cost, robust, and rapid detection methods for food safety and quality analysis. Conventional methods provide accurate analytical characteristics, but require well-equipped laboratories, trained personnel, costly reagents, and complicated sample preparation procedures prior to the detection in order to obtain reliable results. Hence, they are not always ideal for on-site food surveillance. Scope and approach This paper discusses the fundamentals of microfluidic paper-based analytical devices (μPADs) and reviews the recent progress in their usage for screening biological hazards, harmful chemical residues, and allergens in food products to systematically evaluate the strengths and weaknesses of this technology. It then covers future trends and useful strategies that could be employed in μPADs design and fabrication procedures to address the critical challenges in equipment-free food analysis. Key findings and conclusions μPADs offer promising avenues to revolutionize food safety and quality analysis with merits of equipment-free sample preparation and detection at low-cost. Despite the advancement in the microfluidic technology, the manufacturing of user-friendly sample-to-answer μPADs still requires intensive research studies to be employed for robust and sensitive food safety and quality analysis.

The pulp and paper industry is highly energy-intensive. In mills that use chemical pulping, roughly half of the higher heating value of the cellulosic material used to manufacture the product typically is incinerated to generate steam and electricity that is needed to run the processes. Additional energy, much of it non-renewable, needs to be purchased. This review considers publications describing steps that pulp and paper facilities can take to operate more efficiently. Savings can be achieved, for instance, by minimizing unnecessary losses in exergy, which can be defined as the energy content relative to a standard ambient condition. Throughout the long series of unit operations comprising the conversion of wood material to sheets of paper, there are large opportunities to more closely approach a hypothetical ideal performance by following established best-practices.

The majority of chemical experiments conducted during educational programs are carried out in laboratories because they require instructors with special skills, in addition to large, expensive instruments. Recently, there has been an increasing demand for chemical experiments that can be carried out anywhere. Herein, we propose a novel type of paper-based analytical device (PAD) for enabling quantitative analysis without the requirement for a micropipette, since the PAD features a large sample loading zone and a waste zone, enabling accurate volume control of a liquid sample. We initially employed a micropipette to evaluate the PAD and demonstrate the quantitative analysis of ascorbic acid (AA) and pH using different loading volumes. Finally, we determined the AA concentrations and pH values of commercially available beverages using disposable plastic droppers, and the obtained results were in good agreement with those obtained through conventional methods. This PAD format can therefore be used as a novel educational tool for conducting certain chemical analyses in remote learning environments.

Graphical abstract Enzyme-linked immunosorbent assay (ELISA) is widely used for the detection of disease biomarkers. However, it utilizes time-consuming procedures and expensive instruments, making it infeasible for point-of-care (POC) analysis especially in resource-limited settings. In this work, a multicolorimetric ELISA biosensor integrated on a paper/polymer hybrid microfluidic device was developed for rapid visual detection of disease biomarkers at point of care, without using costly equipment. This multicolormetric ELISA platform was built on multiple distinct color variants resulted from the catalytic oxidation of 3,3′,5,5′-tetramethylbenzidine (TMB) and the etching of gold nanorods (AuNRs). The vivid color changes could be easily distinguished by the naked eye, and their red mean values allowed quantitative biomarker detection, without using any sophisticated instruments. When this multicolorimetric ELISA was integrated on a paper/polymer hybrid analytical device, it not only provided integrated processing and high portability but also enabled fast assays in about 50 min due to the unique advantages of paper/polymer hybrid devices. The limit of detection of 9.1 ng/μL of the hepatitis C virus core antigen, a biomarker for hepatitis C, was achieved using this multicolorimetric ELISA platform. This multicolor ELISA analytical device provides a new versatile, user-friendly, affordable, and portable immunosensing platform with high potential for on-site detections of various viruses, proteins, and biomarkers for low-resource settings such as at home, public venues, rural areas, and developing nations. Supplementary Information The online version contains supplementary material available at 10.1007/s00216-021-03359-8.

The development of industry and of the Internet of Things (IoTs) have brought energy issues and huge challenges to the environment. The emergence of triboelectric nanogenerators (TENGs) has attracted wide attention due to their advantages, such as self-powering, lightweight, and facile fabrication. Similarly to paper and other fiber-based materials, which are biocompatible, biodegradable, environmentally friendly, and are everywhere in daily life, paper-based TENGs (P-TENGs) have shown great potential for various energy harvesting and interactive applications. Here, a detailed summary of P-TENGs with two-dimensional patterns and three-dimensional structures is reported. P-TENGs have the potential to be used in many practical applications, including self-powered sensing devices, human–machine interaction, electrochemistry, and highly efficient energy harvesting devices. This leads to a simple yet effective way for the next generation of energy devices and paper electronics.

Teaching about biodiversity and its conservation could be an effective way to teach the importance of different species and human dependence on ecological support systems. This study compares the effectiveness of a digital and a paper-based dichotomous identification key for teaching pre-service teachers about plantspecies diversity. Twenty-four Slovenian teachers in pre-service training used a digital version of the key on tablet computers and twenty-nine used a paper-based version to identify woody species in the garden near their university faculty. Both keys contained the same species, identical photographs and the same sequence of steps to identify the species. The accuracy and time taken to identify the five species were measured. The participants also completed a questionnaire about the usability of the identification key. Overall, both versions of the key were equally good for determining species names. The digital version of the key was found to be more time-effective than the paper version only when multiple identification steps were required to identify species. The results confirm that those who scored better on the identification tasks have a better general opinion about the usability of the key especially students using digital version of the key. Implications for teachers using or creating identification keys are discussed in the conclusion.

In this paper, the implementation of artificial neural networks (multilayer perceptron [MLP] and radial base functions [RBF]) and the upgraded Markov chain model have been studied and performed to identify the human behavior patterns during rock, paper, and scissors game. The main motivation of this research is the design and construction of an intelligent robot with the ability to defeat a human opponent. MATLAB software has been used to implement intelligent algorithms. After implementing the algorithms, their effectiveness in detecting human behavior pattern has been investigated. To ensure the ideal performance of the implemented model, each player played with the desired algorithms in three different stages. The results showed that the percentage of winning computer with MLP and RBF neural networks and upgraded Markov model, on average in men and women is 59%, 76.66%, and 75%, respectively. Obtained results clearly indicate a very good performance of the RBF neural network and the upgraded Markov model in the mental modeling of the human opponent in the game of rock, paper, and scissors. In the end, the designed game has been employed in both hardware and software which include the Zana intelligent robot and a digital version with a graphical user interface design on the stand. To the best knowledge of the authors, the precision of novel presented method for determining human behavior patterns was the highest precision among all of the previous studies.

In this paper, we present a system for automatic evaluation of the quality of a question paper. Question paper plays a major role in educational assessment. The quality of a question paper is crucial to fulfilling the purpose of the assessment. In many education sectors, question papers are prepared manually. A prior analysis of a question paper might help in finding the errors in the question paper, and better achieving the goals of the assessment. In this experiment, we focus on higher education in the technical domain. First, we conducted a student survey to identify the key factors that affect the quality of a question paper. The top factors we identified are question relevance, question difficulty, and time requirement. We explored the strategies to handle these factors and implemented them. We employ various concepts and techniques for the implementation. The system finally assigns a numerical quality score against these factors. The system is evaluated using a set of question papers collected from various sources. The experimental results show that the proposed system is quite promising.

The aim of this review is to introduce the information concerning advanced technology of ink-jet printing regarding characteristics and ink-jet paper. It is believed that ink-jet paper having suitable liquid absorption characteristics and drying techniques are required to improve image quality on high-speed inkjet printing. Although the development of high quality ink-jet paper is important, the demand or the dual-purpose coated paper that can be used with offset and ink-jet printing is expected to increase for the time being. Meanwhile, it is important to get cost down and raise the productivity of the inkjet paper to secure competitiveness comparable to that of offset coated paper. For those objectives we think that the development of new technologies is required for pigment development, composition design of the coating ingredients, and rheological characteristics analysis of coating colors.

Edible oils form an integral component in the human diet as well as in the industrial preparations. Any adulteration in oil is concerning from nutritional as well as economical perspective. Although analytical techniques exist for detection of adulterants in oil, most of them require sophisticated instruments, and trained professionals. Microfluidic based lab-on-a-chip technologies have rapidly progressed over the recent years and offer promising alternatives in this regard. In this work, we report development of a paper-based microfluidic lab-on-a-chip for detection of palm oil contamination in sunflower oil. We use the paper-based microfluidic colorimetric detection approach that indicates the presence of adulteration in a visual manner. The data is analyzed using digitally acquired images along with ultraviolet–visible spectrophotometry. The paper-based microfluidic device is fabricated and tested for 10–50% (v/v) palm oil adulteration in sunflower oil. Further, we employ the device for free fatty acid content tests in oil samples. Visual signal acquired from the device is optimized by varying phenolphthalein proportions. The stability of visual colorimetric signal is examined over time and is found to remain steady over the trial period of six days considered in this work. The integration of the detection device with smartphone imaging can prove to be useful for onsite data collection. We believe the approach presented here can be extended to food quality monitoring portable platforms.

Introduction We developed low-cost, portable paper-based diagnostic devices for detection of human immunoglobulin M (IgM) and immunoglobulin G (IgG) in serum without any sample preparation. These devices can be used to help identify presence of diseases, used to provide rapid results ( Materials and Methods We successfully accomplished colorimetric detection of human IgG and human IgM using a sandwich-style assay within the microfluidic paper device via vertical flow immunoassay configuration. The reaction zone in the wax printed paper layer is a small circular pattern. Gold nanoparticles conjugated with anti-human IgG and IgM antibodies have been used for colorimetric detection of IgG or IgM by naked eye. Colorimetric signal can be precisely quantified through implementation of image analysis software which can be developed as an app for a smartphone. The size of the device is 2 cm × 2 cm × 1 mm. Results Colorimetric detection of human IgG was accomplished at 100 fg/mL concentration using a gold nanoparticle–conjugated anti-human IgG antibody. The developed platform has a dynamic range of IgM and IgG concentrations between 0.1 pg/mL and 100 μg/mL. These devices provided a color readout in Conclusions Because of the inherent simplicity of the device operation and their ease of use, there is no variation between samples and users of the device. This low-cost approach enables multiplexing with >1 measurement performed in parallel at the same time. We anticipate that because of the sensitivity, specificity, ease of use, and overall reliability, this approach will become a standard for diagnosis of diseases and health conditions.

Cocaine (COC) is one of the most widely consumed illegal drugs around the world. Street COC is commonly adulterated with pharmaceutical compounds that mimic or intensify the COC's sensory effect. Adulteration is performed to increase the profit of criminal organizations and each one has their own way of doing it. Therefore, determining the composition of seized COC samples (chemical profile) provides evidence for the police to track criminal organization networks and their activity patterns. Using filter paper as a substrate, we developed a multiple detection paper-based analytical device (PAD) that combines colorimetric and electrochemical measurements to discriminate COC samples according to adulterant's content. A regular graphite lead modified with a gold film made from Au leaf (graphite/Au) to improve electron transfer was used as a working electrode. Silver and Ag/AgCl were used as auxiliary and reference electrodes, respectively. The colorimetric device was patterned using a laser cutter and coupled to the electrochemical device using a double-sided tape, allowing simultaneous analysis to gather more analytical information about COC samples. Graphite/Au was characterized by scanning and transmission electron microscopies and electrochemical assays. The simultaneous colorimetric and electrochemical analyses combined to principal component analysis improved the analytical characterization of COC trial samples and provided a fast discrimination based on the assembled database.

The waste of paper or the paper dump is a serious problem and its occurrence is widespread in various institutions. Wastepaper can be recycled to produce some important and usable products that are ecological and biodegradable. For example, it is used to extract new paper from the old by chemical decomposition. Other products such as paper plates, paper cups, paper spoons, tiles, toys, crafts, etc. can be formed from the slurry. This project also initiates a mould that makes cups and plates from the wastepaper management circuit. With learning institutions being the main consumers, most paper are usually eliminated after its use. The waste remains undeveloped and unused, although is a valuable resource. Studying the design of a manual, economical and efficient paper recycling machine, it can be surmised that the design uses the integration of the knowledge gained about the recycling technology that exists manually from the paper recycling machines used to form a cheap but effective paper recycling system. The advantages of the machine are not only of recycled paper, but also the advantages of the interaction of the manual drive system, which will also reduce the high cost. As the design is not 100% effective, the transmission, belt and chain transmission correspond to the estimated 90% efficiency using the 90% for the design. The power consumption for the design is 450 W and since an average user can produce 100 W constant, it takes 5 people to drive the machine.

Over the last few years, the microfluidics phenomenon coupled with the Internet of Things (IoT) using innovative nano-functional materials has been recognized as a sustainable and economical tool for point-of-care testing (POCT) of various pathogens influencing human health. The sensors based on these phenomena aim to be designed for cost-effectiveness, make it handy, environment-friendly, and get an accurate, easy, and rapid response. Considering the burgeoning importance of analytical devices in the healthcare domain, this review paper is based on the gist of sensing aspects of the microfabricated paper-based analytical devices (μPADs). The article discusses the various used design methodologies and fabrication approaches and elucidates the recently reported surface modification strategies, detection mechanisms viz., colorimetric, electrochemical, fluorescence, electrochemiluminescence, etc. In a nutshell, this article summarizes the state-of-the-art research work carried out over the nano functionalized paper-based analytical devices and associated challenges/solutions in the point of care testing domain.

Background The outpatient setting is a key scenario for the implementation of antimicrobial stewardship (AMS) activities, considering that overconsumption of antibiotics occurs mainly outside hospitals. This publication is the result of a joint initiative by the JPIAMR ARCH and COMBACTE-MAGNET EPI-Net networks, which is aimed at formulating a set of target actions for linking surveillance data with AMS activities in the outpatient setting. Methods A scoping review of the literature was carried out in three research areas: AMS leadership and accountability; antimicrobial usage and AMS; antimicrobial resistance and AMS. Consensus on the actions was reached through a RAND-modified Delphi process involving over 40 experts in infectious diseases, clinical microbiology, AMS, veterinary medicine or public health, from 18 low-, middle- and high-income countries. Results Evidence was retrieved from 38 documents, and an initial 25 target actions were proposed, differentiating between essential or desirable targets according to clinical relevance, feasibility and applicability to settings and resources. In the first consultation round, preliminary agreement was reached for all targets. Further to a second review, 6 statements were re-considered and 3 were deleted, leading to a final list of 22 target actions in the form of a practical checklist. Conclusions This White Paper is a pragmatic and flexible tool to guide the development of calibrated surveillance-based AMS interventions specific to the outpatient setting, which is characterized by substantial inter- and intra-country variability in the organization of healthcare structures, maintaining a global perspective and taking into account the feasibility of the target actions in low-resource settings.

Process-monitoring laboratories in the pulp and paper industry generally use a combination of wet chemical analyses and physical measurements to certify the fitness of a production pulp for a specific end-use. These laboratory tests require time and the effort of trained personnel, limiting their utility for real-time process control. Here we show that Raman probes of unrefined cellulosic pulps, well-suited to the online measurement of in-process materials, can predict the quality attributes of manufactured papers. The accuracy of prediction improves when the covariance is modelled in a reduced measurement space selected by a data-driven, feature-selection technique referred to as a Template Oriented Genetic Algorithm (TOGA). TOGA, combined with discrete wavelet transform (DWT), isolates functional-group features that correlate best with mechanical properties paper derived from refined pulp. Paper makers refine market pulps to build sheet strength using a beating process that decreases freeness as it increases fibre-fibre bonding. Methods demonstrated here predict manufactured sheet properties obtainable after any specified degree of refining from the Raman spectrum of an unrefined pulp. This analysis capacity will enable both vendors of market pulp and makers of sheet paper to specify in advance the amount of beating required to produce a desired product, thereby saving cost and conserving resources.

Around 60% of the paper worldwide is made from recovered paper. Especially adhesive contaminants, so called stickies, reduce paper quality. To remove stickies but at the same time keep as many valuable fibers as possible, multi-stage screening systems with several interconnected pressure screens are used. When planning such systems, suitable screens have to be selected and their interconnection as well as operational parameters have to be defined considering multiple conflicting objectives. In this contribution, we present a Mixed-Integer Nonlinear Program to optimize system layout, component selection and operation to find a suitable trade-off between output quality and yield.

In order for enterprise imaging to be successful across a multitude of specialties, systems, and sites, standards are essential to categorize and classify imaging data. The HIMSS-SIIM Enterprise Imaging Community believes that the Digital Imaging Communications in Medicine (DICOM) Anatomic Region Sequence, or its equivalent in other data standards, is a vital data element for this role, when populated with standard coded values. We believe that labeling images with standard Anatomic Region Sequence codes will enhance the user’s ability to consume data, facilitate interoperability, and allow greater control of privacy. Image consumption—when a user views a patient’s images, he or she often wants to see relevant comparison images of the same lesion or anatomic region for the same patient automatically presented. Relevant comparison images may have been acquired from a variety of modalities and specialties. The Anatomic Region Sequence data element provides a basis to allow for efficient comparison in both instances. Interoperability—as patients move between health care systems, it is important to minimize friction for data transfer. Health care providers and facilities need to be able to consume and review the increasingly large and complex volume of data efficiently. The use of Anatomic Region Sequence, or its equivalent, populated with standard values enables seamless interoperability of imaging data regardless of whether images are used within a site or across different sites and systems. Privacy—as more visible light photographs are integrated into electronic systems, it becomes apparent that some images may need to be sequestered. Although additional work is needed to protect sensitive images, standard coded values in Anatomic Region Sequence support the identification of potentially sensitive images, enable facilities to create access control policies, and can be used as an interim surrogate for more sophisticated rule-based or attribute-based access control mechanisms. To satisfy such use cases, the HIMSS-SIIM Enterprise Imaging Community encourages the use of a pre-existing body part ontology. Through this white paper, we will identify potential challenges in employing this standard and provide potential solutions for these challenges.

pH of fluids is an important indicator in biomedical and environmental studies. Conventional pH analysis techniques are often either instrumentation-intensive, expensive or qualitative in nature. Microfluidics based analytical devices have emerged as powerful alternative to overcome some of the existing limitations. These devices are characterized by low reagent and sample volumes, controlled flow, cost-effectiveness and portability. In this work, we report a microfluidic paper-based lab-on-a-chip pH sensing platform that incorporates passive fluid flow of samples. The colorimetric pH detection is integrated with mobile phone based image acquisition, followed by digital image processing and analysis for quantitative interpretation of data. The images are analyzed using image processing algorithms and color space. Regression analysis of data acquired from digital image analysis was used to evaluate the mathematical model for estimation of pH. The insights gained by this work would prove useful in development and deployment of portable and miniaturized sensors.

In society, there is widespread and growing acceptance of the value of cooperation between industry and universities being collaborative Research and Development (R&D) domain and industrial policy the fuel of knowledge-based economies. In this paper, different domains of cooperation between the University and Industry as well as their generated benefits for each partner are identified. These benefits have been assigned to each domain of cooperation, showing a large number of benefits associated to collaborative R&D. Leading us to make a statement - collaborative R&D is the key cooperation domain for sustainable long-term university-industry partnerships. Suggestions are given about how to continue this research study.

Introduction:The Ministry of Public Health in Lebanon is in the process of converting the surveillance reporting from a cumbersome paper-based system to a web-based electronic platform (DHIS-2) to have real-time information for early detection of alerts and outbreaks and for initiating a prompt response.Objectives:This paper aimed to document the Lebanese experience in implementing DHIS-2 for the disease surveillance system. It also targets to assess the improvement of reporting rates and timeliness of the reported data and to disclose the encountered challenges and opportunities. MethodologyThis is a retrospective description of processes involved in the implementation of the DHIS-2 tool in Lebanon. Initially, it was piloted for the school-based surveillance in 2014; then its use was extended in May 2017 to cover other specific surveillance systems. This included all surveillance programs collecting aggregate data from hospitals, medical centers, dispensaries, or laboratories at the first stage. As part of the national roll-out process, the online application was developed. The customized aggregated-based datasets, organization units, user accounts, specific and generic dashboards were generated. More than 80 training sessions were conducted throughout the country targeting 1290 end-users including health officers at the national and provincial levels, focal persons working in all public and private hospitals, laboratories, and medical centers as well. Completeness and timeliness of reported data were compared before and after the implementation of DHIS-2. Challenges and lessons learned during the roll-out process are listed.ResultsFor laboratory-based surveillance, completeness of reporting increased from 70.8% in May to 89.6% in October. Timeliness has improved from 25% to 74%. For medical centers, an improvement of 8.1% for completeness and 9.4% in timeliness was recorded before and after training sessions. For zero reporting, completeness remains the same (88%) and timeliness has improved from 74% to 87%. The main challenges faced during the implementation of DHIS-2 were mainly infrastructural and system-related in addition to poor internet connectivity and limited workforce and frequent changes to DHIS-2 versions.ConclusionImplementation of DHIS-2 improved timeliness and completeness for aggregated data reporting. Continued on-site support, monitoring, and system enhancement are needed to improve the performance of DHIS-2.

Tissue paper conversion consists of the transformation of base tissue papers into finished tissue products to meet specific demands. When base tissue paper arrives at the converting line, it already holds different requirements that were met during its manufacture in the paper machine (e.g., grammage, bulk, tensile index, etc.). However, what happens during converting can still influence the performance and quality of the finished products. The current work addresses this topic and aims to evaluate the influence of converting conditions on the final softness. For that, two 5-ply finished tissue products were analyzed using different methodologies for their proper characterization in terms of softness and surface analysis. The analyzed products are composed by the same base tissue papers, but some changes were applied on their settings in the converting line. In particular, the base tissue papers arrangement and the embossing pressure affected the finished products, resulting in one of them being softer and more pleasant to touch, with a global handfeel (HF) value of 75.3 units, and the other revealed to be rougher and less pleasant, with a global handfeel (HF) value of 68.0 units.

Directed evolution has become an important method to unleash the latent potential of enzymes to make them uniquely suited for human purposes. However, the need for a large reagent volume and sophisticated instrumentation hampers its broad implementation. In an attempt to address this problem, here we report a paper-based high-throughput screening approach that should find broad application in generating desired enzymes. As an example case, the dehalogenation reaction of the halohydrin dehalogenase was adopted for assay development. In addition to visual detection, quantitative measurements were performed by measuring the color intensity of an image that was photographed by a smartphone and processed using ImageJ free software. The proposed method was first validated using a gold standard method and then applied to mutagenesis library screening with reduced consumption of reagents (i.e., ≤ 10 μl per assay) and a shorter assay time. We identified two active mutants (P135A and G137A) with improved activities toward four tested substrates. The assay not only consumes less reagents but also eliminates the need for expensive instrumentation. The proposed method demonstrates the potential of paper-based whole-cell screening coupled with digital image colorimetry as a promising approach for the discovery of industrially important enzymes.Key Points• A frugal method was developed for directed enzyme evolution.• Mutagenesis libraries were successfully screened on a paper platform.• Smartphone imaging was efficiently used to measure enzyme activities.

A good quality control system is important to be implemented to increase productivity and minimize defects in products. One of the quality control methods is failure mode and effect analysis (FMEA). This study uses the FMEA to identify the causes of the defects and recommend the prevention methods to overcome the causes of the defects in an Indonesian paper mill. The risk priority number (RPN) is calculated by multiplying the severity, occurrence, and detection of the failures that have been determined. Unsymmetrical and tainted products are the most dominant defects in the paper mill. An inappropriate machine setting is the cause of unsymmetrical products with the highest RPN of 343. The second highest RPN is problems with bleaching machines that caused tainted products with an RPN value of 216. This study offers suggestions to Indonesian paper mill to prevent and minimize defective products.

Renewable paper reusing plays a significant role in the sustainable environment under the background of the shortage in forest resources and the pollution from the paper industry. The conventional reusing stream of waste office paper appears to have low reusing rates while consuming massive amounts of energy in intermediate steps. In this study, we developed a novel portable renewable desktop paper reusing system based on font area detection and greyscale sensor. The proposed system consists of two main parts, namely, a greyscale sensor and font area detection model and a polishing mechanism. Acting as an ink mark detector for waste desktop paper, the greyscale sensor and font area detection model can detect the font in the waste desktop paper using an adaptive dynamic compensation schematic. The polishing mechanism will grind the font area of the wasted desktop paper, and this paper reusing processing is non-chemical, energy saving and environmentally friendly. The proposed system is demonstrated through simulations and experimental results, which show that the proposed renewable desktop paper reusing system is portable and is effective for reusing waste office paper in the office. An accuracy of 99.78% is demonstrated in the greyscale sensor and font area detection model, and the average reuse rate of one piece of paper is 2.52 times, verifying that the proposed portable system is effective and practical in renewable desktop paper reusing applications.

With characters of low cost, portability, easy disposal, and high accuracy, as well as bulky reduced laboratory equipment, paper-based sensors are getting increasing attention for reliable indoor/outdoor onsite detection with nonexpert operation. They have become powerful analysis tools in trace detection with ultra-low detection limits and extremely high accuracy, resulting in their great popularity in medical detection, environmental inspection, and other applications. Herein, we summarize and generalize the recently reported paper-based sensors based on their application for mechanics, biomolecules, food safety, and environmental inspection. Based on the biological, physical, and chemical analytes-sensitive electrical or optical signals, extensive detections of a large number of factors such as humidity, pressure, nucleic acid, protein, sugar, biomarkers, metal ions, and organic/inorganic chemical substances have been reported via paper-based sensors. Challenges faced by the current paper-based sensors from the fundamental problems and practical applications are subsequently analyzed; thus, the future directions of paper-based sensors are specified for their rapid handheld testing.

The fast detection of trace amounts of hazardous contaminations can prevent serious damage to the environment. Paper-based sensors offer a new perspective on the world of analytical methods, overcoming previous limitations by fabricating a simple device with valuable benefits such as flexibility, biocompatibility, disposability, biodegradability, easy operation, large surface-to-volume ratio, and cost-effectiveness. Depending on the performance type, the device can be used to analyze the analyte in the liquid or vapor phase. For liquid samples, various structures (including a dipstick, as well as microfluidic and lateral flow) have been constructed. Paper-based 3D sensors are prepared by gluing and folding different layers of a piece of paper, being more user-friendly, due to the combination of several preparation methods, the integration of different sensor elements, and the connection between two methods of detection in a small set. Paper sensors can be used in chromatographic, electrochemical, and colorimetric processes, depending on the type of transducer. Additionally, in recent years, the applicability of these sensors has been investigated in various applications, such as food and water quality, environmental monitoring, disease diagnosis, and medical sciences. Here, we review the development (from 2010 to 2021) of paper methods in the field of the detection and determination of toxic substances.

The development of diagnostic tools for measuring a wide spectrum of target analytes, from biomarkers to other biochemical parameters in biological fluids, has experienced a significant growth in the last decades, with a good number of such tools entering the market. Recently, a clear focus has been put on miniaturized wearable devices, which offer powerful capabilities for real-time and continuous analysis of biofluids, mainly sweat, and can be used in athletics, consumer wellness, military, and healthcare applications. Sweat is an attractive biofluid in which different biomarkers could be noninvasively measured to provide rapid information about the physical state of an individual. Wearable devices reported so far often provide discrete (single) measurements of the target analytes, most of them in the form of a yes/no qualitative response. However, quantitative biomarker analysis over certain periods of time is highly demanded for many applications such as the practice of sports or the precise control of the patient status in hospital settings. For this, a feasible combination of fluidic elements and sensor architectures has been sought. In this regard, this paper shows a concise overview of analytical tools based on the use of capillary-driven fluidics taking place on paper or fabric devices integrated with solid-state sensors fabricated by thick film technologies. The main advantages and limitations of the current technologies are pointed out together with the progress towards the development of functional devices. Those approaches reported in the last decade are examined in detail.

Lithium-ion (Li-ion) batteries have been fabricated in various ways to improve flexibility. Flexibility could be enhanced via active materials, separators, electrodes, and electrolytes, which could then be integrated to form flexible electronic devices with promising electrochemical properties compared to traditional non-flexible Li-ion batteries. Recent progress towards flexible Li- ion batteries fabrication, materials, and their electrochemical properties are investigated in this review. Additionally, recent developments in electronic devices utilizing flexible batteries and their future applications are explored. Portable and wearable electronics, as the primary beneficiaries of the flexible, rechargeable, and high-performance Li-ion batteries, are examined. In the end, various applications and challenges of flexible batteries in healthcare and various energy storage systems, considering practical implementation, are argued.

The built environment of an older person’s home can reduce or promote the possibility of a fall or other injury. A user-friendly tool can help the residents to evaluate their home environment withi...

Development of paper-based microfluidic devices that perform colorimetric measurements requires quantitative image analysis. Because the design geometries of paper-based microfluidic devices are not standardized, conventional methods for performing batch measurements of regularly spaced areas of signal intensity, such as those for well plates, cannot be used to quantify signal from most of these devices. To streamline the device development process, we have developed an open-source program called ColorScan that can automatically recognize and measure signal-containing zones from images of devices, regardless of output zone geometry or spatial arrangement. This program, which measures color intensity with the same accuracy as standard manual approaches, can rapidly process scanned device images, simultaneously measure identified output zones, and effectively manage measurement results to eliminate requirements for time-consuming and user-dependent image processing procedures.

This work describes the log-MAP (BCJR) algorithm implementation of a close to capacity dirty paper coding CODEC. The CODEC consists of eight deep pipeline processors. It decodes blocks of 975 bits in 26.9 ms using less than 9.7% of low-cost FPGA (and no DSP blocks). Two pipelines, for alpha and beta, calculate the values of gamma (of the BCJR) to reduce the storage requirements. The final log-likelihood ratio (LLR) is calculated together with alpha, reusing intermediate results. The number of bits used by the different signals of the processor is easily configurable. It was set to six bits to the channel measure signals and eight bits to log of probability signals like alpha, beta, and others. The CODEC clock was 100 MHz. The achieved bit rate is 36.2 Kbps per CODEC, but multiple CODECs can be fit into a single chip. The CODEC is 3.49 dB from the channel capacity.

Advancements in technology have led to the use of smartphones as biosensor detectors. However, it is difficult to obtain stable color information of colorimetric sensors using multiple smartphones owing to different light conditions and image correction operations. In this study, we attempted color detection of the colorimetric paper chip using smartphone-embedded light-emitting diode (LED) and simple transformation calculation. This method enables the acquisition of stable color information using different smartphones by reducing the influence of external light sources. Moreover, we studied characteristics such as convergence and distinction of detection result details by the manufacturers and smartphones. These findings suggested the necessity of classification criteria for the use of smartphones to achieve optimal detection. In addition, white and black references were used to set the standard for color correction of various light sources. Based on our results, we conclude that this approach presents the possibility of smartphone-based colorimetric detection in practical applications.

The paper presents the results of the analysis on measured parameters of harmonics at the node of the high-voltage network. The measurements were made at the node connecting the pulp-and-paper mill to the 220 kV supply network. This load is nonlinear and has a large capacity. Particular attention is paid to the distributions of the current and voltage harmonics. The paper clearly shows probabilistic properties of the measured parameters of harmonics

Researchers face difficulties in finding relevant papers to their research interest as the number of scientific publication is rapidly increasing on the web. Scientific paper recommenders have emerged as a leading solution to help researchers by automatically suggesting relevant and useful publications. Several approaches have been proposed on improving recommender systems. However, most existing approaches depend on priori user profiles, and thus they cannot recommend papers to new user. Furthermore, the existing approaches utilize non-public contextual information, and thus it cannot adequately find similarities between papers due to copyright restrictions. Also, the existing approaches consider only single level paper-citation relation to identify similarities between papers. Considering the above challenges, this paper presents a collaborative filtering based recommendation approach for scientific papers that does not depend on priori user profiles and which utilizes only public contextual information. Using citation context, we utilized 2-level paper-citation relations to find hidden associations between papers. The rational underlying this approach is that, two papers are co-occurred with same cited paper(s) and two papers are co-occurring with same citing paper(s) are significantly similar to some extent. To evaluate the performance of the proposed approach, publicly available datasets are used to conduct extensive experiments. The experimental results demonstrate that the proposed approach has significantly outperforms the baseline approaches in terms of precision, recall, F1, mean average precision, and mean reciprocal rank, which are commonly used information retrieval metrics. The novelty of this study is that, with the proposed approach, researchers are able to find relevant and useful publications over the internet regardless of their previous research experiences and research area.

The accuracy of a predictive system is critical for predictive maintenance and to support the right decisions at the right times. Statistical models, such as ARIMA and SARIMA, are unable to describe the stochastic nature of the data. Neural networks, such as long short-term memory (LSTM) and the gated recurrent unit (GRU), are good predictors for univariate and multivariate data. The present paper describes a case study where the performances of long short-term memory and gated recurrent units are compared, based on different hyperparameters. In general, gated recurrent units exhibit better performance, based on a case study on pulp paper presses. The final result demonstrates that, to maximize the equipment availability, gated recurrent units, as demonstrated in the paper, are the best options.

The low cost, simplicity, and ease of use of paper microfluidic devices have made them valuable medical diagnostics for applications from pregnancy testing to COVID-19 screening. Meanwhile, the increasing complexity of paper-based microfluidic devices is driving the need to produce new tools and methodologies that enable more robust biological diagnostics and potential therapeutic applications. A new design framework is being used to facilitate both research and fabrication of paper-based microfluidic biological devices to accelerate the investigative process and reduce material utilization and manpower. In this work we present a methodology for this framework to dynamically place and route microfluidic components in a nondiscrete design space where fluid volume usage, surface area utilization, and the timing required to perform specified biological assays are accounted for and optimized while also accelerating the development of potentially lifesaving new devices.

In simple dyadic games such as rock, paper, scissors (RPS), people exhibit peculiar sequential dependencies across repeated interactions with a stable opponent. These regularities seem to arise from a mutually adversarial process of trying to outwit their opponent. What underlies this process, and what are its limits? Here, we offer a novel framework for formally describing and quantifying human adversarial reasoning in the rock, paper, scissors game. We first show that this framework enables a precise characterization of the complexity of patterned behaviors that people exhibit themselves, and appear to exploit in others. This combination allows for a quantitative understanding of human opponent modeling abilities. We apply these tools to an experiment in which people played 300 rounds of RPS in stable dyads. We find that although people exhibit very complex move dependencies, they cannot exploit these dependencies in their opponents, indicating a fundamental limitation in people’s capacity for adversarial reasoning. Taken together, the results presented here show how the rock, paper, scissors game allows for precise formalization of human adaptive reasoning abilities.

The NIST selection process for standardizing Post-Quantum Cryptography Mechanisms is currently running. Many papers already studied their theoretical security, but the resistance in deployed device has not been much investigated so far. In particular, fault attack is a serious threat for algorithms implemented in embedded devices. One particularly powerful technique is to use safe-error attacks. Such attacks exploit the fact that a specific fault may or may not lead to a faulty output depending on a secret value. In this paper, we investigate the resistance of various Post-Quantum candidates algorithms against such attacks.

Due to the increasing use of the Internet and other online resources, there is tremendous growth in the data of text documents. It is not possible to manage this huge data manually. This has led to the growth of fields like text mining and text summarization. This paper presents a title prediction model for research papers using Recursive Recurrent Neural Network (Recursive RNN) and evaluates its performance by comparing it with sequence-to-sequence models. Research papers published between 2018 and 2020 were obtained from a standard repository, viz. Kaggle, to train the title prediction model. The performance of different versions of Recursive RNN and Seq2Seq was evaluated in terms of training and hold-out loss. The experimental results show that Recursive RNN models perform significantly better than the other models.

The clinical importance of blood group (BG) antigens is related to their ability to induce immune antibodies that can cause hemolysis. Yet, ABO and D (Rh) are still considered to be the key antigens for healthy blood transfusion and secondary antigens are the next priority. Serological typing is the most widely used typing method. Rapid and accurate blood grouping plays an important role in some clinical conditions, rather than conventional techniques. Hence, developing a simple and economical model for rapid blood grouping would facilitate these tests. In recent decades, paper-based microfluidics such as μPADs has gained much interest in wide application areas such as point-of-care diagnostic. In this study, we evaluated μPADs that are performed for blood grouping and its recent progress. A comprehensive literature search was performed using databases including PUBMED, SCOPUS, Web of Science and Google Scholar. Keywords were blood grouping or typing, paper analytical device, rapid test, etc. After investigation of search results, 16 papers from 2010 to 2020 were included. Further information in detail was classified in Table 1. Generally, two principles for blood typing μPADs are introduced. The lateral chromatographic flow method and the vertical flow-through method that detects BG in a visual-based manner. To detect results with acceptable clarity many factors and challenges like paper, blood sample, buffer, Ab and RBC interaction and also μPADs stability need to be considered, which are discussed. In conclusion, the simplicity, stability, cheapness, portability and biocompatibility of μPADs for blood grouping confirming its utility and also they have the capability to robust, universal blood-grouping platform. Table 1 Summary of blood grouping tests using paper-based analytical devices Antigens Type of diagnosis Validation method Sample No Accuracy Action time Paper type Stability Sample dilution Buffer Ref A, B, Rh Forward volunteers records 5 - - Whatman No. 4 - 1/2 PBS* (Khan et al. 2010) A, B, Rh Forward gel assay test and conventional slide test 100 100% 1 min Whatman No. 4 and Kleeenex paper towel 7 Days in 4 °C 1/1 NSS (Al-Tamimi et al. 2012) A, B, Rh Forward gel card assay 99 100% 20 Sec + Washing Kleeenex paper towel - 1/1 NSS (Li et al. 2012) A, B, Rh Forward - - - - Kleeenex paper towel - 45/100 PSS (Li et al. 2013) A, B, Rh Forward gel card assay 98 100% 1.5 min Kleeenex paper towel - 85/100 PBS (Guan et al. 2014b) C, E, c, e, K, Jka, Jkb, M, N, S, P1, and Lea Forward gel card assay 266 100% - Kleeenex paper towel - 1/1 NSS (Li et al. 2014b) A, B, Rh Forward and Reverse conventional slide test 96 ≈ 91% 10 min Whatman No. 1 21 Days in 4 °C 1/2 NSS (Noiphung et al. 2015) C, c, E, e, K, k, Fya, Fyb, Jka, Jkb, M, N, S and s, P1, Lea and Leb Forward - 478 - - Kleeenex paper towel - 1/1 NSS, PBS (Then et al. 2015) A, B Forward and Reverse conventional slide test 76 100% 5-8 min Whatman No. 4 38 Days in 4 °C 1/4, 1/1 NSS (Songjaroen and Laiwattanapaisal 2016) D, K Forward volunteers records 210 - 7.5 min Kleenex paper towel - 1/1 NSS (Yeow et al. 2016) A, B, c, e, D, C, E, M, N, S, s, P1, Jka, Jkb, Lea, Leb, Fya, and Fyb Forward and Reverse gel card assay 3550 ≈100% 30 s Fiber glass and cotton linter 180 Days in 25 °C 45/100, 1/1 PBS (Zhang et al. 2017) A, B Forward conventional slide test 598 100% 3 min Whatman No. 113 14 Day in 4 °C 1/1 NSS (Songjaroen et al. 2018) A, B, Rh Forward conventional slide test - - 30 Sec + Washing Unrefined sisal paper - 1/2 NSS (Casals-Terré et al. 2019) A, B, Rh Forward - - - - Whatman No.1 - 1/1 NSS (Ansari et al. 2020) ABORh Forward and Reverse conventional slide test - 100% Unrefined Eucalyptus papers - 1/2 NSS, PBS (Casals-Terré et al. 2020) A, B, Rh Forward - - - 30 Sec + Washing Whatman No. 4 modified with chitosan ≥ 100 days in 25 °C 1/1 NSS (Parween et al. 2020)

Foam forming technology has attracted much attention during the past few years in the paper industry. Its advantages compared to conventional water forming are a new product portfolio and increased process efficiency. To support the paper industry in pushing foam forming technology forward, process simulation is needed to provide supporting data for strategic decision-making and as a basis for equipment dimensioning. This study examined the conversion of an existing wallpaper machine from water to foam forming technology using process simulation. To determine the required process configuration and parameter changes in the existing process, both published and unpublished data on the foam forming process were collected. This paper also describes modeling of the foam phase in the selected simulation software. The suitability of existing paper process equipment for foam was analyzed. Simulations revealed that undisturbed operation with foam requires some equipment modifications and re-arrangements in water circuits. With foam forming, the water balance in both short and long circulation changes remarkably compared to conventional water forming, leading to a large increase in the long circulation volume flows.

Background In recent times, the use of thermal papers has increased exponentially and the fingerprints on thermal papers are frequently encountered. Although fingerprint development on paper has been standardized, that on thermal paper is complicated. Thermal papers turn black on the application of heat which poses a problem in the visualization of fingerprints which makes it difficult to visualize. Main body One solution to this problem is to use heat or steam for the development of white fingerprints on darker backgrounds. Second solution might be to dissolve the chemicals present on the surface of the thermal papers using acetone. Many studies to develop fingerprints on thermal papers using iodine fuming, ninhydrin, 1,8-diazofluorene-9-one, and p-dimethylaminocinnamaldehyde have been performed. In the present review, an attempt has been made to summarize the problem posed to fingerprint development on thermal papers and the probable solutions attempted by different authors. Conclusion Although the development of fingerprints is difficult on thermal papers, it can be achieved either by subjecting the thermal paper to controlled heat or by removing the temperature-sensitive layer before treating it with other fingerprint development methods.

The recycling of waste paper has been an effective way to achieve the environmental-friendly growth of papermaking industry. Focusing on the mixed-pulping process which has been generally employed, to ensure the required properties of the deinking pulp (DIP) and minimize the purchase cost of waste paper, an intelligent model scheduling the mixing ratio of waste paper was developed in the study. Primarily, driven by the field data of mixing ratio of waste paper and DIP properties, the prediction models of DIP properties were developed by SVM, GA-SVM, and BP-NN algorithms. Subsequently, based on the best prediction model, the scheduling model for the mixing ratio of waste paper was set up by NSGAII algorithm. The experimental results showed that, based on the obtained best BP-NN prediction model of DIP properties, the developed NSGAII scheduling model for the ratio of waste paper could achieve excellent scheduling results under the rigorous constraints and multi-objective. Compared with the previous study, the developed prediction and scheduling models in this study reduced the purchase cost of waste paper by 2.16%, and improved the acceptable proportion of DIP property from 56.07% to 100%.

The paper discusses current research efforts focusing on security and privacy for 5G cellular networks. It then outlines research directions.