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The emerging demands for healthcare where access is limited due to political, environmental, or socio-economic factors have been driving research into bio-medical devices that perform in both diagnostic and therapeutic roles at lower costs and greater accessibility. Paper microfluidic devices are used in many applications, particularly medical diagnostics and offer an excellent combination of utility and low cost making them particularly valuable in resource-limited applications and point-of-care usage across a wide variety environmental conditions. Microfluidic biological diagnostics continue to mature as researchers discover new ways to exploit the technological possibilities, and address liabilities. The increasing complexity of paper-based microfluidic devices beyond home pregnancy tests is driving the need to produce new tools and methodologies that enable more robust biological diagnostics and potential therapeutic applications. However, the process of developing new paper microfluidic devices is limited due to having to manually design and fabricate designs to research. Often, researchers must design scores of different devices to find a combination of parameters that functions as expected. In this work, a novel software framework to support automated development of paper-based microfluidic devices is introduced to facilitate both research and fabrication to accelerate the investigative process and reduce material utilization and manpower. Unlike to existing lab-on-a-chip technologies, paper-based microfluidics differs in terms of substrate technologies and use a passive flow method to deliver fluids and reagents for assays. While numerous analogies between microfluidics and semiconductor technologies have been espoused, the physical differences between the fluid dynamics and electrical current are significant which suggests that current trends in physical design for microfluidics must change course in order to be of practical use to designers. Within this framework, a methodology is introduced to address design automation such as dynamically placing and routing microfluidic components in a non-discrete design space while avoiding invalid design layouts, accounting for fluid volume usage, surface area utilization, and the timing required to perform specified biological assays and also optimizing device parameters, enabling researchers to focus on the science and thereby accelerating the development of new, low-resource paper microfluidic devices for a developing world.

Made available in DSpace on 2022-04-29T08:31:12Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-10-01 Organization and planning of reverse logistics networks make sustainable processes more efficient. Thus, an important sector for connecting the collection and waste paper recycling echelons is the intermediate center. In this study, a Mixed Integer Linear Programming model, which is multi-objective, multi-product, multi-level and multi-period, was developed to optimize the waste paper logistics processes of intermediate centers. The formulation includes the following echelons: collection, considering vehicle routing with different capacities; inventory of non-baling materials; baling sorted waste and inventory of bales; selling bales; disposal of non-recyclable waste. The aims of the model include: maximizing the collected waste; minimizing distances; maximizing both the production and sale of bales, and minimizing costs. According to research carried out in the literature, the developed model is a new proposal and to implement it, the Weighted Goal Programming and Revised Multi-Choice Goal Programming approaches were used to deal with multiple objectives and incorporate uncertainty into the quantity of waste available for collection. To analyze the proposed model, computational tests were executed with instances based on real data from a Brazilian company in the sector. For all performed tests, General Algebraic Modeling System 23.6.5 modeling language and CPLEX 12.2.0.2 solver were used for modeling and optimization. The results show that this study presents formulation and technological approaches that represent real situations and provide competitive solutions to the problem. Sáo Paulo State University “Júlio de Mesquita Filho” [Universidade Estadual Paulista Júlio de Mesquita Filho] School of Engineering of Guaratinguetá [Faculdade de Engenharia de Guaratinguetá] Production Department, Av. Ariberto Pereira da Cunha, 333, Portal das Colinas Agulhas Negras Military Academy [Academia Militar das Agulhas Negras] Rodovia Presidente Dutra, km 306, s/n Escola Preparatória de Cadetes do Exército Avenida Papa Pio XII 350 Jardim Chapadão Campinas - SP Brazil, Avenida Papa Pio XII, 350, Jardim Chapadão, Campinas - SP Sáo Paulo State University “Júlio de Mesquita Filho” [Universidade Estadual Paulista Júlio de Mesquita Filho] School of Engineering of Guaratinguetá [Faculdade de Engenharia de Guaratinguetá] Production Department, Av. Ariberto Pereira da Cunha, 333, Portal das Colinas

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 appearance and quick spread of the new severe acute respiratory syndrome coronavirus disease, COVID-19, brought major societal challenges. Importantly, suitable medical diagnosis procedures and smooth clinical management of the disease are an emergent need, which must be anchored on novel diagnostic methods and devices. Novel molecular diagnostic tools relying on nucleic acid amplification testing have emerged globally and are the current gold standard in COVID-19 diagnosis. However, the need for widespread testing methodologies for fast, effective testing in multiple epidemiological scenarios remains a crucial step in the fight against the COVID-19 pandemic. Biosensors have previously shown the potential for cost-effective and accessible diagnostics, finding applications in settings where conventional, laboratorial techniques may not be readily employed. Paper- and cellulose-based biosensors can be particularly relevant in pandemic times, for the renewability, possibility of mass production with sustainable methodologies, and safe environmental disposal. In this review, paper-based devices and platforms targeting SARS-CoV-2 are showcased and discussed, as a means to achieve quick and low-cost PoC diagnosis, including detection methodologies for viral genomic material, viral antigen detection, and serological antibody testing. Devices targeting inflammatory markers relevant for COVID-19 are also discussed, as fast, reliable bedside diagnostic tools for patient treatment and follow-up., The authors acknowledge funding through projects Eco2Covid (POCI-01-02B7-FEDER-068174) and TecniCov (POCI-01-02B7-FEDER-069745), co-funded by FEDER through COMPETE2020 and Lisboa2020. T.P., A.R.C. and A.C.M. acknowledge funding to National Foundation for Science and Technology, I.P., FCT, through their PhD grants, references DFA/BD/8606/2020, SFRH/BD/130107/2017 and SFRH/BD/115173/2016, respectively, info:eu-repo/semantics/publishedVersion

Papers are the most commonly used substrates. A printable paper must have certain properties. These properties include surface smoothness, air permeability, surface energy, colour of the paper, opacity, whiteness, light fastness, gloss, and coefficient of elongation under force. In addition, a good printable paper should not allow ink to pass between its two surfaces. After the papers are produced, they are subjected to surface treatments in order to improve the above-mentioned properties and to provide extra specification. Surface treatments include calendering, surface sizing and coating processes. While filling the recesses and protrusions on the surface with the coating process, the paper's affinity for the ink is increased, and the penetration of the ink to the other surface of the paper is prevented. In the coating process basically, a filler is dispersed in a binder. In this study, it is aimed to obtain the highest quality and most printable paper by changing the type of binder used in the coating. In this study, equal amount (5% w/w) titanium dioxide filler was used in all coating formulations. In coating formulations; cationic starch, hydroxy ethyl cellulose and polyvinyl alcohol polymers were used as binders. Binder amounts are adjusted according to optimum viscosity. The obtained coating formulations were coated on the paper surface with a laboratory type coating device. Colour, gloss, surface smoothness, air permeability, surface energy and surface morphology of the coated papers were determined. It was printed with magenta offset printing ink on three different types of paper coated with different binders, using the IGT C1 offset printability test device, under 400 N/m2 pressure printing conditions. Colour and gloss measurements of the prints were made. As a result; It was determined that three different binders improved the printability parameters.

Herein, we describe the development of a paper-based device to detect nucleic acids of pathogens of interest in complex samples using loop-mediated isothermal amplification (LAMP) by producing a colorimetric response visible to the human eye. To demonstrate the utility of this device in emerging public health emergencies, we developed and optimized our device to detect SARS-CoV-2 in human saliva without preprocessing. The resulting device was capable of detecting the virus within 60 min and had an analytical sensitivity of 97% and a specificity of 100% with a limit of detection of 200 genomic copies/μL of patient saliva using image analysis. The device consists of a configurable number of reaction zones constructed of Grade 222 chromatography paper separated by 20 mil polystyrene spacers attached to a Melinex® backing via an ARclean® double-sided adhesive. The resulting device is easily configurable to detect multiple targets and has the potential to detect a variety of pathogens simply by changing the LAMP primer sets.

Standards are a set of guidelines or criteria used to ensure consistency, quality, safety, and compatibility in products, services, and processes [...]

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.

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.

The COVID-19 pandemic has resulted in significant global social and economic disruption. The highly transmissive nature of the disease makes rapid and reliable detection critically important. Point-of-care (POC) tests involve performing diagnostic tests outside of a laboratory that produce a rapid and reliable result. It therefore allows the diagnostics of diseases at or near the patient site. Paper-based POC tests have been gaining interest in recent years as they allow rapid, low-cost detection without the need for external instruments. In this review, we focus on the development of paper-based POC devices for the detection of SARS-CoV-2. The review first introduces the principles of detection methods that are available to paper-based devices. It then summarizes the state-of-the-art paper devices and their analytical performances. The advantages and drawbacks among methods are also discussed. Finally, limitations of the existing devices are discussed, and prospects are given with the hope to identify research opportunities and directions in the field. We hope this review will be helpful for researchers to develop a clinically useful and economically efficient paper-based platform that can be used for rapid, accurate on-site diagnosis to aid in identifying acute infections and eventually contain the COVID-19 pandemic.

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.

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.

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 importance of user-friendly, inexpensive, sensitive, and selective detection of viruses has been highlighted again due to the recent Coronavirus disease 2019 (COVID-19) pandemic. Among the analytical tools, paper-based devices (PADs) have become a leading alternative for point-of-care (POC) testing. In this review, we discuss the recent development strategies and applications in nucleic acid-based, antibody/antigen-based and other affinity-based PADs using optical and electrochemical detection methods for sensing viruses. In addition, advantages and drawbacks of presented PADs are identified. Current state and insights towards future perspectives are presented regarding developing POC diagnosis platform for COVID-19. This review considers state-of-the-art technologies for further development and improvement in PADs performance for virus detection., Graphical abstract Image 1

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.

In recent years, microfluidic lab-on-paper devices have emerged as a rapid and low-cost alternative to traditional laboratory tests. Additionally, they were widely considered as a promising solution for point-of-care testing (POCT) at home or regions that lack medical infrastructure and resources. This review describes important advances in microfluidic lab-on-paper diagnostics for human health monitoring and disease diagnosis over the past five years. The review commenced by explaining the choice of paper, fabrication methods, and detection techniques to realize microfluidic lab-on-paper devices. Then, the sample pretreatment procedure used to improve the detection performance of lab-on-paper devices was introduced. Furthermore, an in-depth review of lab-on-paper devices for disease measurement based on an analysis of urine samples was presented. The review concludes with the potential challenges that the future development of commercial microfluidic lab-on-paper platforms for human disease detection would face.

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.

Bacillus cereus is one of the most common foodborne pathogens found in various kinds of staple foods such as rice and wheat. A rapid and accurate detection method for this pathogen is highly desirable for the sustainable production of relevant food products. While several classical and molecular-based detection methods are available for the identification of B. cereus, they suffered one or more limitations such as the requirement for a tedious and time-consuming process, less than ideal specificity, and the lack of portability. Herein, we developed the first paper-based sensing device that exhibits high species specificity with sufficiently low limit of detection for the visual detection of specific DNA sequences of B. cereus. The success is attributed to the strategic planning of fabrication in various dimensions including thorough bioinformatics search for highly specific genes, the use of the pyrrolidinyl peptide nucleic acid (PNA) probe whose selectivity advantage is well documented, and an effective PNA immobilization and DNA-binding visualization method with an internal cross-checking system for validating the results. Testing in rice matrices indicates that the sensor is capable of detecting and distinguishing B. cereus from other bacterial species. Hence, this paper-based sensor has potential to be adopted as a practical means to detect B. cereus in food industries.

Paper aims This study identifies fundamental characteristics for developing a paper-based thesis (PBT), providing some recommendations to researchers who decide for this academic research report. Originality This paper contributes to the literature by providing guidance to develop PBTs, which has been attracting researchers' interest because it demonstrates publication capacity and potential as a researcher. Additionally, it is still not entirely clear which issues and countermeasures researchers should address when choosing the paper-based structure. Research method The authors searched for articles of PBTs already published, institutional documents (e.g., regulations for conducting PBTs in Brazil and abroad) and journal papers concerning this subject. A content and document analysis were conducted in the papers and PBT internal regulations, respectively. Main findings Results indicate five main factors that impact the success of a PBT approach: (i) the initial planning for this academic model; (ii) alignment between the articles and the thesis/dissertation; (iii) research design construction; (iv) copyrights requirements; and (v) issues regarding co-authorship. Based on that, the study also builds some guidelines to structure a robust PBT. Implications for theory and practice Our recommendations might be meaningful to scholars and researchers bring more theoretical, empirical, and structural robustness when developing a PBT final document.

Since the introduction of paper-based analytical devices as potential diagnostic platforms a few decades ago, huge efforts have been made in this field to develop systems suitable for meeting the requirements for the point-of-care (POC) approach. Considerable progress has been achieved in the adaptation of existing analysis methods to a paper-based format, especially considering the chemiluminescent (CL)-immunoassays-based techniques. The implementation of biospecific assays with CL detection and paper-based technology represents an ideal solution for the development of portable analytical devices for on-site applications, since the peculiarities of these features create a unique combination for fitting the POC purposes. Despite this, the scientific production is not paralleled by the diffusion of such devices into everyday life. This review aims to highlight the open issues that are responsible for this discrepancy and to find the aspects that require a focused and targeted research to make these methods really applicable in routine analysis.

Visual individual recognition requires animals to distinguish among conspecifics based on appearance. Though visual individual recognition has been reported in a range of taxa, the features that animals rely on to discriminate between individuals are often not well understood. Northern paper wasp females, Polistes fuscatus, possess individually distinctive color patterns on their faces, which mediate individual recognition. It is currently unclear what facial features P. fuscatus use to distinguish individuals. The anterior optic tubercle, a chromatic processing brain region, is especially sensitive to social experience during development, suggesting that color may be important for recognition in this species. We sought to test the roles of color in wasp facial recognition. Color may be important simply because it creates a pattern. If this is the case, then wasps should perform similarly when discriminating color or grayscale images of the same faces. Alternatively, color itself may be important for recognition, which would predict poorer performance on grayscale image discrimination relative to color images. We found wasps trained on grayscale faces, unlike those trained on color images, did not perform better than chance. Suggesting that color is necessary for the recognition of an image as a face by the wasp visual system.

The Gaussian wiretap channel with noncausal state interference available at the transmitter, which is also called the dirty paper wiretap channel (DP-WTC), has been extensively studied in the literature. Recently, it has been shown that taking actions on the corrupted state interference of the DP-WTC (also called the action-dependent DP-WTC) helps to increase the secrecy capacity of the DP-WTC. Subsequently, it has been shown that channel feedback further increases the secrecy capacity of the action-dependent DP-WTC (AD-DP-WTC), and a sub-optimal feedback scheme is proposed for this feedback model. In this paper, a two-step hybrid scheme and a corresponding new lower bound on the secrecy capacity of the AD-DP-WTC with noiseless feedback are proposed. The proposed new lower bound is shown to be optimal (achieving the secrecy capacity) and tighter than the existing one in the literature for some cases, and the results of this paper are further explained via numerical examples.

Diagnostic and evidential static image, video clip, and sound multimedia are captured during routine clinical care in cardiology, dermatology, ophthalmology, pathology, physiatry, radiation oncology, radiology, endoscopic procedural specialties, and other medical disciplines. Providers typically describe the multimedia findings in contemporaneous electronic health record clinical notes or associate a textual interpretative report. Visual communication aids commonly used to connect, synthesize, and supplement multimedia and descriptive text outside medicine remain technically challenging to integrate into patient care. Such beneficial interactive elements may include hyperlinks between text, multimedia elements, alphanumeric and geometric annotations, tables, graphs, timelines, diagrams, anatomic maps, and hyperlinks to external educational references that patients or provider consumers may find valuable. This HIMSS-SIIM Enterprise Imaging Community workgroup white paper outlines the current and desired clinical future state of interactive multimedia reporting (IMR). The workgroup adopted a consensus definition of IMR as “interactive medical documentation that combines clinical images, videos, sound, imaging metadata, and/or image annotations with text, typographic emphases, tables, graphs, event timelines, anatomic maps, hyperlinks, and/or educational resources to optimize communication between medical professionals, and between medical professionals and their patients.” This white paper also serves as a precursor for future efforts toward solving technical issues impeding routine interactive multimedia report creation and ingestion into electronic health records.

Rapid increase in scholarly publications on the web has posed a new challenge to the researchers in finding highly relevant and important research articles associated with a particular area of interest. Even a highly relevant paper is sometimes missed especially for novice researchers due to lack of knowledge and experience in finding and accessing the most suitable articles. Scholarly recommender system is a very appropriate tool for this purpose that can enable researchers to locate relevant publications easily and quickly. However, the main downside of the existing approaches is that their effectiveness is dependent on priori user profiles and thus, they cannot recommend papers to the new users. Furthermore, the system uses both public and non-public metadata and therefore, the system is unable to find similarities between papers efficiently due to copyright restrictions. Considering the above challenges, in this research work, a novel hybrid approach is proposed that separately combines a Content Based Filtering (CBF) recommender module and a Collaborative Filtering (CF) recommender module. Unlike previous CBF and CF approaches, public contextual metadata and paper-citation relationship information are effectively incorporated into these two approaches separately to enhance the recommendation accuracy. In order to verify the effectiveness of the proposed approach, publicly available datasets were employed. Experimental results demonstrate that the proposed approach outperforms the baseline approaches in terms of standard metrics (precision, recall, F1-measure, mean average precision, and mean reciprocal rank), indicating that the proposed approach is more efficient in recommending scholarly publications.

International audience; This paper focuses on the problem of the hierarchical multi‐label classification of research papers, which is the task of assigning the set of relevant labels for a paper from a hierarchy, using reduced amounts of labelled training data. Specifically, we study leveraging unlabelled data, which are usually plentiful and easy to collect, in addition to the few available labelled ones in a semi‐supervised learning framework for achieving better performance results. Thus, in this paper, we propose a semi‐supervised approach for the hierarchical multi‐label classification task of research papers based on the well‐known Co‐training algorithm, which exploit content and bibliographic coupling information as two distinct papers' views. In our approach, two hierarchical multi‐label classifiers, are learnt on different views of the labelled data, and iteratively select their most confident unlabelled samples, which are further added to the labelled set. The success of our suggested Co‐training‐based approach lies in two main components. The first is the use of two suggested selection criteria (i.e., Maximum Agreement and Labels Cardinality Consistency) that enforce selecting confident unlabelled samples. The second is the appliance of an oversampling method that rebalances the labels distribution of the initial labelled set, which reduces the reinforcement of the label imbalance issue during the Co‐training learning. The proposed approach is evaluated using a collection of scientific papers extracted from the ACM digital library. Performed experiments show the effectiveness of our approach with regards to several baseline methods.

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.

Performance/security trade-off is widely noticed in CFI research, however, we observe that not every CFI scheme is subject to the trade-off. Motivated by the key observation, we ask three questions: ➊ does trade-off really exist in different CFI schemes? ➋ if trade-off do exist, how do previous works comply with it? ➌ how can it inspire future research? Although the three questions probably cannot be directly answered, they are inspiring. We find that a deeper understanding of the nature of the trade-off will help answer the three questions. Accordingly, we proposed theGPTconjecture to pinpoint the trade-off in designing CFI schemes, which says that at most two out of three properties (fine granularity, acceptable performance, and preventive protection) could be achieved.

This research studied the strategies that players use in sequential adversarial games. We took the Rock-Paper-Scissors (RPS) game as an example and ran players in two experiments. The first experiment involved two humans, who played the RPS together for 100 times. Importantly, our payoff design in the RPS allowed us to differentiate between participants who used a random strategy from those who used a Nash strategy. We found that participants did not play in agreement with the Nash strategy, but rather, their behavior was closer to random. Moreover, the analyses of the participants’ sequential actions indicated heterogeneous cycle-based behaviors: some participants’ actions were independent of their past outcomes, some followed a well-known win-stay/lose-change strategy, and others exhibited the win-change/lose-stay behavior. To understand the sequential patterns of outcome-dependent actions, we designed probabilistic computer algorithms involving specific change actions (i.e., to downgrade or upgrade according to the immediate past outcome): the Win-Downgrade/Lose-Stay (WDLS) or Win-Stay/Lose-Upgrade (WSLU) strategies. Experiment 2 used these strategies against a human player. Our findings show that participants followed a win-stay strategy against the WDLS algorithm and a lose-change strategy against the WSLU algorithm, while they had difficulty in using an upgrade/downgrade direction, suggesting humans’ limited ability to detect and counter the actions of the algorithm. Taken together, our two experiments showed a large diversity of sequential strategies, where the win-stay/lose-change strategy did not describe the majority of human players’ dynamic behaviors in this adversarial situation.

The early diagnosis of Alzheimer’s disease (AD) remains a challenge for medical scientists worldwide, leading to a number of research efforts that focus on biosensor development for AD biomarkers. However, the application of these complicated biosensors is limited in medical diagnosis, due to the difficulties in robust sensing platform development, high costs, and the necessity for technical professionals. We successfully developed a robust straightforward manufacturing process for the fabrication of multi-chamber paper devices using the wax printing method and exploited it to detect amyloid beta 42 oligomers (AβO42, a significant biomarker of AD) using copper-enhanced gold nanoprobe colorimetric immunoblotting. Small hydrophilic reaction chambers could concentrate the target sample to the desired size to improve the sensing performance. The copper-enhanced gold nanoprobe immunoblot using the designed multi-chamber platform exhibited a highly sensitive performance with a limit of detection of 320 pg/mL by the naked eye and 23.7 pg/mL by a smartphone camera. This process from sensing manufacture to sensing conduction is simple to perform whenever medical technicians require time- and cost-savings, without complicated instruments or the need for technical professionals, making it feasible to serve as a diagnostic tool worldwide for the early monitoring of AD and scalable devices for the sensing application of various biomarkers in clinical settings.

To explore whether the brain contains pattern differences in the rock–paper–scissors (RPS) imagery task, this paper attempts to classify this task using fNIRS and deep learning. In this study, we designed an RPS task with a total duration of 25 min and 40 s, and recruited 22 volunteers for the experiment. We used the fNIRS acquisition device (FOIRE-3000) to record the cerebral neural activities of these participants in the RPS task. The time series classification (TSC) algorithm was introduced into the time-domain fNIRS signal classification. Experiments show that CNN-based TSC methods can achieve 97% accuracy in RPS classification. CNN-based TSC method is suitable for the classification of fNIRS signals in RPS motor imagery tasks, and may find new application directions for the development of brain–computer interfaces (BCI).

Paper waste in the mockups design with regular, irregular, and amorphous patterns is a critical problem in digital printing presses. Paper waste reduction directly impacts production costs, generating business and environmental benefits. This problem can be mapped to the two-dimensional irregular bin-packing problem. In this paper, an iterated local search algorithm using a novel neighborhood structure to detect overlaps between amorphous shapes is introduced. This algorithm is used to solve the paper waste problem, modeled as one 2D irregular bin-packing problem. The experimental results show that this approach works efficiently and effectively to detect and correct the overlaps between regular, irregular, and amorphous figures.

Graphical Abstract Illustration of the assembly, distribution, and point-of-care use of a rapidly-deployable, cell-free COVID-19 biosensor: 1) Assemble: Assembling CFPS reagents by mixing E. coli lysate, murine RNase Inhibitor (mRI), energy sources, cofactors, and toehold switch riboregulator plasmid. 2) Print: aliquoting CFPS reagents onto paper substrates housed in a plastic test cassette. 3) Dehydrate: lyophilizing CFPS reagents on paper substrates. 4) Distribute. 5) Saliva sample: applying saliva samples onto cassette without pretreatments. 6) Reaction: bioluminescent protein expression in presence of target RNA (+), or ribosome detachment in absence of target RNA (-). 7) Visual result: bioluminescent output in the presence of target RNA and NanoLuc luciferase expression., The COVID-19 pandemic has illustrated the global demand for rapid, low-cost, widely distributable and point-of-care nucleic acid diagnostic technologies. Such technologies could help disrupt transmission, sustain economies and preserve health and lives during widespread infection. In contrast, conventional nucleic acid diagnostic procedures require trained personnel, complex laboratories, expensive equipment, and protracted processing times. In this work, lyophilized cell-free protein synthesis (CFPS) and toehold switch riboregulators are employed to develop a promising paper-based nucleic acid diagnostic platform activated simply by the addition of saliva. First, to facilitate distribution and deployment, an economical paper support matrix is identified and a mass-producible test cassette designed with integral saliva sample receptacles. Next, CFPS is optimized in the presence of saliva using murine RNase inhibitor. Finally, original toehold switch riboregulators are engineered to express the bioluminescent reporter NanoLuc in response to SARS-CoV-2 RNA sequences present in saliva samples. The biosensor generates a visible signal in as few as seven minutes following administration of 15 μL saliva enriched with high concentrations of SARS-CoV-2 RNA sequences. The estimated cost of this test is less than 0.50 USD, which could make this platform readily accessible to both the developed and developing world. While additional research is needed to decrease the limit of detection, this work represents important progress toward developing a diagnostic technology that is rapid, low-cost, distributable and deployable at the point-of-care by a layperson.