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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.

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

This study aims at understanding the role of the tools chosen throughout the processes of solving a non-routine mathematical problem and communicating its solution. In assuming that problem-solving is a synchronous activity of mathematization and expression of mathematical thinking we take our proposed Mathematical Problem Solving with Technology (MPST) model to analyze the processes of solving-and-expressing-problems. Resorting to qualitative methods for data collection and analysis, we report on the case of an 8th grader working on a covariation problem to examine the role that paper-and-pencil and digital tools play in the development of a conceptual model of the situation. We found that the resources used throughout the solving-and-expressing activity influenced the depth of the conceptual model developed, within a process of progressive mathematization. Whereas paper-and-pencil led to the emergence of a conceptual model based on exploring particular cases, the digital transformation of the solution was triggered by the process of communicating its mathematical justification and expanded the previous model. Moreover, the complexity of this activity is evidenced by its multiple sequences of processes. Finally, the integration process seems crucial as the concomitant use of technological and mathematical resources precedes major advancements in the expansion of the conceptual model.

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.

Continuous manufacturing is an indicator of a maturing industry, as can be seen by the example of the petrochemical industry. Patent expiry promotes a price competition between manufacturing companies, and more efficient and cheaper processes are needed to achieve lower production costs. Over the last decade, continuous biomanufacturing has had significant breakthroughs, with regulatory agencies encouraging the industry to implement this processing mode. Process development is resource and time consuming and, although it is increasingly becoming less expensive and faster through high‐throughput process development (HTPD) implementation, reliable HTPD technology for integrated and continuous biomanufacturing is still lacking and is considered to be an emerging field. Therefore, this paper aims to illustrate the major gaps in HTPD and to discuss the major needs and possible solutions to achieve an end‐to‐end Integrated Continuous Biomanufacturing, as discussed in the context of the 2019 Integrated Continuous Biomanufacturing conference. The current HTPD state‐of‐the‐art for several unit operations is discussed, as well as the emerging technologies which will expedite a shift to continuous biomanufacturing., With an ever‐growing interest in shifting to integrated continuous biomanufacturing (ICB), the major gaps and state‐of‐the‐art perceived by academia and industry members in high‐throughput process development (HTPD) technologies for the development and implementation of this type of operation (ICB) are debated in this paper, with a special focus on the HT tools for the different unit operations in a typical biopharmaceutical process. The current needs in ICB and possible solutions to fulfill these needs are also highlighted

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.

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.

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.

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.

In paper production, a jumbo reel is cut into multiple intermediate rolls, and each intermediate roll is then sheeted as finished goods. This problem is called a cutting stock problem and is proven to be NP-hard. The objective is to minimize material waste or trim loss from all the cuttings. In the case that any intermediate roll is not entirely used for its associated order, the intermediate roll itself could turn to be a dead stock. We use the concept of universal sizes of intermediate rolls to eliminate the dead stock. A pre-defined number of universal sizes of intermediate rolls is to be used to serve all the orders. The problem is solved using Reinforcement Artificial Bee Colony algorithm with Integer Linear Programming subroutine. This proposed approach is then tested with a set of 1,055 orders and 127 different sizes of sheet papers from a paper manufacturer. The results reveal that our method outperforms other algorithms. Our method offers the total trim loss of 3.51%, compared to the trim loss reported by the industry of at least 5%. This approach not only reduces the number of partially cut rolls, but also decreases the number of the jumbo reels needed to serve all the orders. Therefore, both the inventory cost and material cost can be saved.

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.

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.

In recent history, the Panama Papers have comprised one of the largest and most influential leaks detailing information on offshore entities, company officers and financial (and legal) intermediaries, and has led to a global exposé of corruption and tax evasion. A systematic analysis of this information can provide valuable insights into the structure and properties of these entities and the relations between them. Network science can be applied as a scientific framework for understanding the structure of such relational, heterogeneous datasets at scale. In this article, we use an existing, relational version of the Panama Papers to selectively construct various networks, and then study the properties of the underlying system using well-defined analytical methods from network science, including degree properties, country assortativity analyses, connectivity and single-point network metrics like transitivity and density. We also illustrate significant structural features in these networks by conducting a triad census and exploring the networks’ core-periphery structure. Together, these results are used to show that the Panama Papers constitute a distinct class of networks that differ significantly from ordinary social and information networks. We also propose, construct and analyze ‘higher-order’ networks from the raw data, such as a ‘social’ network of officers. We confirm that some of these higher-order networks also show significant non-random deviations from expected or typical behavior, including in their degree distributions.

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.