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This paper presents a monolithic manufacturing process to realize active-matrix meshed TFT arrays on foil with physical voids between pixels, realizing membrane-like structures for use in biometrics-under-display applications. Moreover, however, the concept enables new applications in the biomedical electronics domain.

This letter presented a pencil-on-paper-based ecofriendly capacitive touchpad fabricated through a low-cost lab- and solvent-free fabrication process. Economical, readily available, and biodegradable materials, such as pencil and paper, have been used for sensor fabrication. A touchpad based on five such sensors has been developed and evaluated by using it as a user control interface to on/off LEDs and displaying results on LCD and mobile app. The graphite sensors in the user interface have been shielded from the direct interaction of humans and the environment using changeable cling film to make the interface reliable and reusable. The interface can be used in different conditions and users by changing the shielding film. Simultaneously, the system's functionality will remain consistent and functioned similarly to the conventional touch sensors and buttons. These recyclable and easily arrayed touch sensor-based keypads can contribute to future developments in disposable and lightweight interfaces for human–machine interface, medical and healthcare applications, smart packaging, security monitoring, and consumer products.

In this paper, we analyze the intelligent subdesign of the simulated marking system through an in-depth study of it. This paper proposes a correlation analysis-based quantification of N-element sense values and a rationality enhancement-based scoring fitting algorithm for English essays. This paper also extracts word features, sentence features, and chapter structure features in essays to fit English composition scores. Since not all students can complete the essays according to the topic requirements, a triage scoring model is used to separate the normal essays from the low-scoring essays. Statistically, it was found that the essay scores also showed a certain normal distribution. The standard support vector regression algorithm is prone to data skewing problems, so this paper addresses this problem by using a rationality enhancement method that gives a corresponding penalty factor according to the distribution of the dataset. The results show that the English essay scoring fitting algorithm proposed in this paper can well improve the prediction accuracy of some data and solve the problem of skewed data where the scores show a normal distribution. This paper designs and implements an online mock examination system that incorporates an intelligent scoring system for essays, enabling it to meet the needs of teachers and students for online examinations and intelligent scoring.

As technology advances, learning analytics is expanding to include students’ collaboration settings. Despite their increasing application in practice, some types of analytics might not fully capture the comprehensive educational contexts in which students’ collaboration takes place (e.g., when data is collected and processed without predefined models, which forces users to make conclusions without sufficient contextual information). Furthermore, existing definitions and perspectives on collaboration analytics are incongruent. In light of these circumstances, this opinion paper takes a collaborative classroom setting as context and explores relevant comprehensive models for collaboration analytics. Specifically, this paper is based on Pei-Ling Tan and Koh’s ecological lens (2017, Situating learning analytics pedagogically: Towards an ecological lens. Learning: Research and Practice, 3(1), 1–11. https://doi.org/10.1080/23735082.2017.1305661), which illustrates the co-emergence of three interactions among students, teachers, and content interwoven with time. Moreover, this paper suggests several factors to consider in each interaction when executing collaboration analytics. Agendas and recommendations for future research are also presented.

Purpose The rapid spread and severity of the coronavirus (COVID-19) virus have prompted a spate of scholarly research that deals with the pandemic. The purpose of this study is to measure and assess the coverage of COVID-19 research on social media and the engagement of readers with COVID-19 research on social media outlets. Design/methodology/approach An altmetric analysis was carried out in three phases. The first focused on retrieving all papers related to COVID-19. Phase two of the research aimed to measure the presence of the retrieved papers on social media using altmetric application programming interface (API). The third phase aimed to measure Mendeley readership categories using Mendeley API to extract data of readership from Mendeley for each paper. Findings The study suggests that while social media platforms do not give accurate measures of the impact as given by citations, they can be used to portray the social impact of the scholarly outputs and indicate the effectiveness of COVID-19 research. The results confirm a positive correlation between the number of citations to articles in databases such as Scopus and the number of views on social media sites such as Mendeley and Twitter. The results of the current study indicated that social media could serve as an indicator of the number of citations of scientific articles. Research limitations/implications This study’s limitation is that the studied articles’ altmetrics performance was examined using only one of the altmetrics data service providers (altmetrics database). Hence, future research should explore altmetrics on the topic using more than one platform. Another limitation of the current research is that it did not explore the academic social media role in spreading fake information as the scope was limited to scholarly outputs on social media. The practical contribution of the current research is that it informs scholars about the impact of social media platforms on the spread and visibility of COVID-19 research. Also, it can help researchers better understand the importance of published COVID-19 research using social media. Originality/value This paper provides insight into the impact of COVID-19 research on social media. The paper helps to provide an understanding of how people engage with health research using altmetrics scores, which can be used as indicators of research performance.

Paper-based digital microfluidic biochip (PB-DMFB) technology provides a promising solution to many biochemical applications. However, PB-DMFB manufacturing process may suffer from potential security threats. For example, both Trojan insertion and man-in-the-middle attack may affect the functionality of PB-DMFBs. To ensure the correct functionality of PB-DMFBs, we propose a watermarking scheme to hides information in the PB-DMFB layout, which allows users to check design integrity and authenticate the source of the PB-DMFB design. As a result, it serves as a first countermeasure against both Trojan insertion and man-in-the-middle attacks for PB-DMFBs.

In the age of Evidence-Based Medicine, Clinical Guidelines (CGs) are recognized to be an indispensable tool to support physicians in their daily clinical practice. Medical Informatics is expected to play a relevant role in facilitating diffusion and adoption of CGs. However, the past pioneering approaches, often fragmented in many disciplines, did not lead to solutions that are actually exploited in hospitals. Process Mining for Healthcare (PM4HC) is an emerging discipline gaining the interest of healthcare experts, and seems able to deal with many important issues in representing CGs. In this position paper, we briefly describe the story and the state-of-the-art of CGs, and the efforts and results of the past approaches of medical informatics. Then, we describe PM4HC, and we answer questions like how can PM4HC cope with this challenge? Which role does PM4HC play and which rules should be employed for the PM4HC scientific community? This research received no external funding

The last decade has witnessed an impressive paradigm shift in practically all networking fields: from hardware-based appliances to software-based infrastructures. Network functions traditionally hard-coded in the network devices have been redesigned in software and deployed in virtualized networking scenarios, with impressive advantages in terms of management flexibility and upgradable capability. Still, at a time in which we strive for more and more network processing and computing resources, such a softwarization process risks to bring about a severe toll in terms of performance and energy consumption. We believe, and posit, that programmable hardware architectures tailored for supporting high performance network processing tasks may come to the rescue. With this position paper, after motivating our position, we further briefly review the past and present of programmable hardware for networking, and we discuss its possible evolution towards more comprehensive "higher layer" HW-accelerated processing tasks.

Along with the unceasing growth of worldwide economic and the associated issues on resources, energy and environment, clean energy generating technologies that are based on recyclable materials, if possible, may become the future trend of development. Here, we report the design of a cheap, lightweight, and recyclable single-electrode triboelectric nanogenerator (TENG) that utilizes waste paper as the triboelectric material. Under the current strategy, we successfully developed green energy machines without vastly increasing the mining of various critical minerals around the world. The as-designed TENG could not only collect and convert mechanical energy into electricity with sound efficiency, but also has the merit for continuous reuse and quick construction. The maximum output power density is as high as 171 mW·m−2 at a resistance of 130 MΩ and could be integrated into a book for monitoring reading actions, thus providing a new approach to the low-cost, green and sustainable self-powered electronic systems.

In this paper, we will deliberate how to control robot car using Wi-Fi module through a webpage using computer or smartphone. The advantage of using robot car is it can be used for various purposes like this project can be modified quite easily to include a spy camera as well that can stream the videos to the user over Wi-Fi. Attempts would be made to use solar cells instead of the regular lithium-ion battery for the project. This robot car can also be used to push the objects from one place to another. This project will be enhanced with better Wi-Fi which would enable long distance communication.

To date, 55% of inhabitants of the developing world still live in rural regions and they have a very urgent need to improve the level of disease diagnosis, especially in resource-limited settings. Herein, we present a microfluidic system that centrifuges whole blood and quantifies contained biomarkers in a rapid, feasible and integrated way. Such a device provides a blood-in/answer-out capability and is small enough to be carried by any individual in any environment. The successful integration a hand-powered centrifuge and immunoassay unit within a rotational paper-based device allows for diagnostic application by untrained users and in environments where access to electricity cannot be assumed. In addition, the low cost (~$ 0.5), light weight and small instrumental footprint make the device ideally suited for rapid on-site detection. To validate the applicability of the system in a clinical diagnostic testing, we successfully perform enzyme-linked immunosorbent assay (ELISA) analysis of carcinoembryonic antigen and alpha fetoprotein from human blood samples. We expect that this powerful platform technology will provide the opportunities for point-of-care diagnosis in resource-limited settings.

Introduction MyChild Solution is an innovative Electronic Immunisation Register (EIR) reliant on Smart Paper Technology, thereby eliminating the need for electronic devices and internet connectivity at the point-of-care. The goal of this study is to characterise the quality of routine immunisation data generated using MyChild Solution compared to data obtained through the conventional health management information system (HMIS) used in The Gambia. Method We used the World Health Organization’s (WHO) Data Quality Review (DQR) Toolkit to evaluate MyChild Solution’s data quality in the 19 health facilities across two regions implementing MyChild Solution in The Gambia at the time of the evaluation. We evaluated all applicable data quality metrics as well as additional metrics of interest, including the incidence of recording errors, the incidence of incomplete indicator level data, and implausible dates. Where possible, we compared results to those of the conventional HMIS. Results Both MyChild Solution and the conventional HMIS produced 100% complete and timely data in their reference years. Both systems had no moderate or extreme outliers and showed the expected Penta 1 to Penta 3 dropout direction. However, the proportion of verification factors that are not acceptable was higher in the conventional HMIS. MyChild Solution was found to near perfectly (99.98%) digitise scanned documents. These and other data quality indicators evaluated demonstrate that MyChild Solution produces high quality data with high completeness, timeliness, and consistency compared to the conventional HMIS system. Conclusion MyChild Solution produces high quality data as per the DQR Toolkit metrics and other metrics of interest of interest. The more internally consitent data produced through MyChild Solution compared to the conventional HMIS demonstrates its potential for supporting data-driven decision-making in immunisation.

The EU White Paper on AI mentions healthcare as one of the sectors where AI applications might pose high risks. These comments provide the vision on the regulatory framework for high-risk healthcare AI applications. The key takeaways concern transparency, preventing bias, safety and quality of AI applications used for medical purposes. I suggest that the transparency of AI shall not be equated to its explainability. To increase transparency and ensure the safety of AI healthcare applications, cooperation between manufacturers and users of AI (healthcare providers) shall be improved. I highlight that biased AI decisions alert on the inaccuracy of algorithms. While discrimination and stigmatization are difficult to identify and prove, especially for AI and especially for healthcare, controlling of AI’s accuracy is an efficient tool to prevent and mitigate biases in AI systems. Finally, I briefly compare the two regulations that might apply to AI tools in healthcare - the Medical Devices Regulation (EU) 2017/745 (MDR) and the In-vitro Diagnostic Medical Devices Regulation (EU) 2017/746 (IVDR). I conclude that the IVDR is more tailored to AI characteristics while it is more detailed and more focused on data quality and relevance. Thus, the IVDR rules can be a good starting point for clarifying and implementing a regulatory framework for high-risk AI healthcare applications.

Although fabrication of colorimetric paper-based analytical devices (PADs) has drawn increasing attention recently, the signal readout method is still a crucial challenge on the way to practical exploitations. We herein introduce an integration of digital image processing with a model PAD for easing and improving the signal readout procedure. The colorimetric detection mechanism of PAD relies on in-situ induced yellowish silver nanoparticles via the interaction of silver ions, poly(vinyl alcohol), and ammonia with isoniazid. The observed color value is related with the concentration of isoniazid. The proposed algorithm is based on mathematical morphology recognition, and minimizes the errors arising from manual area selection. Besides, it allows the recognition of both circle and square shapes in 96-well plate and A4 size array designs. Since this algorithm automatically provides the blank-corrected numerical matrixes and image profiles of red, green and blue channels, further investigations such as outlier classification, construction of regression/prediction models and calculation of detection limit can be easily performed. Comparison of signal readout results of the developed algorithm with ImageJ software demonstrates significant improvements in analysis speed, reproducibility, accuracy and color values. Therefore, application of the proposed algorithm is promising as a robust technique for practical applications.

Students are increasingly connected to an online world. As such, they expect their university learning experience to emulate their everyday online experiences. Until recently, however, traditional university teaching has tended to focus on 'knowledge transfer'. In order to reengage with students, many universities are providing online tools and courses. But, not all topics are suitable for online learning. Some topics still require hands-on experience - especially where the outcome is targeted to the manufacturing industry. The 3D printer is a teaching tool that benefits from both hands-on and online support. Moreover, it can be used to help reengage students disaffected by traditional teaching methods and as a tool for transitioning to more online teaching methods. This paper outlines how the 3D printer is being used in university classrooms to supplement online teaching which is career focussed.

Introduction: Network and systems medicine has rapidly evolved over the past decade, thanks to computational and integrative tools, which stem in part from systems biology. However, major challenges and hurdles are still present regarding validation and translation into clinical application and decision making for precision medicine. Methods: In this context, the Collaboration on Science and Technology Action on Open Multiscale Systems Medicine (OpenMultiMed) reviewed the available advanced technologies for multidimensional data generation and integration in an open-science approach as well as key clinical applications of network and systems medicine and the main issues and opportunities for the future. Results: The development of multi-omic approaches as well as new digital tools provides a unique opportunity to explore complex biological systems and networks at different scales. Moreover, the application of findable, applicable, interoperable, and reusable principles and the adoption of standards increases data availability and sharing for multiscale integration and interpretation. These innovations have led to the first clinical applications of network and systems medicine, particularly in the field of personalized therapy and drug dosing. Enlarging network and systems medicine application would now imply to increase patient engagement and health care providers as well as to educate the novel generations of medical doctors and biomedical researchers to shift the current organ- and symptom-based medical concepts toward network- and systems-based ones for more precise diagnoses, interventions, and ideally prevention. Conclusion: In this dynamic setting, the health care system will also have to evolve, if not revolutionize, in terms of organization and management. ª Blandine Comte et al. 2020; Published by Mary Ann Liebert, Inc. This Open Access article is distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The United States (U.S.) has 99 operating Nuclear Power Plants (NPPs). The majority of these were designed and commissioned in the 1970s and 1980s. Plants are modernizing their control systems and main control rooms to be able to continue operating past their original 40-year license agreements. U.S. NPP main control rooms are migrating towards hybrid controls with both digital and analog systems. Digital upgrades, while costly, provide improved reliability, reduced maintenance cost, and the potential for fewer unplanned outages and fewer human errors. U.S. utilities have been slow to embrace computerized procedure system (CBP) research, even though CBPs demonstrate clear operational and human factors benefits. Most of the CBP research has been oriented to new reactor designs or full digital control rooms and is not applicable to the piecemeal modernization approach favored by U.S. plants. Research is needed to examine how CBPs impact operations in hybrid control rooms, and how current paper based procedures can be efficiently migrated to computerized platforms. Work is underway to develop tools and perform the obligatory research needed to design and validate CBPs for modernized U.S. nuclear control rooms.

This paper describes a user identification method conducted across online social networks (OSNs) using information regarding friends’ locations, in contrast to a conventional method based on the similarity of two display names. This latter method encounters the problem of decreased identification accuracy if a user registers different display names across OSNs. Our proposed method aims at addressing this issue by utilizing information on friends’ locations. We convert location information extracted from an OSN to that of such geographic administrative units as country, state and city, and calculate the weighted occurrence frequency of a location pair on the basis of distance between the pair. This is based on the hypothesis that a friend list relatively rarely includes an account pair whose locations are extremely distant from one another. We calculate a similarity score between two accounts’ weighted occurrence frequencies for each geographic administrative unit. Finally, we identify a user on the basis of individual similarity scores or weighted average scores for a given geographic administrative unit. Evaluation experiments show that our proposed method improves performance over that of a conventional method (accuracy: 83.1%$\rightarrow$91.2%).

International audience; Internet of Things (IoT) is a network where several and various interconnected, smart objects continuously generate alarge amount of data transmitted over Internet. Several efforts and research works in IoT focused on hardware constraints, lowcost, application design, as well as good communication technologies. However, due to the intrinsic characteristics of diversity,heterogeneity, large-scale, dynamic and large volume of data generated and various IoT applications needs, using traditionaldatabase management mechanisms and analytics architectures is not generally suitable. Then, it is challenging to provideefficient IoT data storage and query processing mechanisms for satisfying IoT application needs. This paper identifies the mainspecifications and mechanisms of data and query management for IoT and classifies them. Moreover, this work presentsadvances on data and query management mechanisms on IoT, shows their advantages and limits and discusses the challengingopen research issues that need to be addressed for providing guidelines for further contributions.

The creation of 3D paper unfolded models with complex geometry requires precision in the design process. Achieving this is through the use of accessible resources and modern technological means which possess the necessary technical and functional capabilities. The successful realization of the models is through the use of a structured methodology containing design stages that are defined in the exact sequence. The present study aims to create the unfoldings of complex three-dimensional models by covering the stages of providing accessible resurses with a personal and commercial license that are transformed in sequence until the ready-made variants.

As a rapidly developing field, paper-based microfluidic devices (μPADs) are expected to have profound implications, especially for in vitro diagnosis. In particular, integrated μPADs, with the merits of capillary-driven force, cost effectiveness, mass production and ease of use, are emerging as ideal tools for personal diagnosis; sample collection/pretreatment, signal transduction and results output can be simplified into one μPAD with minimal need for complex operation. In this review, we emphasize the latest developments of integrated μPADs and highlight the accomplishments and challenges of each component, including sample collection/pretreatment, signal transduction and amplification, and results output. Moreover, we give an overview of the growing trend of novel integrated μPADs and analyze existing challenges as well as potential directions for integrated μPADs for point-of-care testing (POCT).

Due to the security threats faced in the connected world, the consideration of security requirements during system design and modeling has become a necessity. Unfortunately, the identification of new requirements that may arise throughout additional phases of a system’s life-cycle (e.g. operation) must also be considered due to the ever-changing threat landscape. These new requirements may derive in system adaptations or modifications that ensure continuous system security. The identification of these new requirements and the implementation of their derived changes must be performed in a timely manner in order to avoid time windows where the system is vulnerable to security attacks. Unfortunately, the timely implementation of security-related changes is a challenge when dealing with automation systems as it may affect their availability and functionality. This position paper presents an approach that allows semiautomatic identification of system vulnerabilities in order to facilitate the derivation of new requirements that allow to ensure the security of a system. This identification is carried out throughout multiple phases of a system’s life-cycle.

Fragmented connectivity in South Africa is the dominant barrier for digitising initiatives. New insights surfaced when a university-based nursing programme introduced tablets within a supportive network learning environment. A qualitative, explorative design investigated adult nurses' experiences of the realities when moving from paper-based learning towards using tablets within a blended learning environment. Purposive sampling was applied. 45 (N) participants were included, each receiving a preloaded tablet (15 running on iOS, 15 on Android 4.2.2 Jelly Bean and 15 on Windows® 8 operating systems), being WiFi-dependent, integrated into a supportive learning network. Participants completed eleven compulsory Internet-based activities. Three reflective focus groups with 18 (n) participants concluded the project. Through self-empowerment and supportive environment, students adopted seamlessly, overcame network and resource-related challenges. Valuable lessons were learned within the digital divide, integrate tablets into distance learning from a resilient and pragmatic approach.

Microfluidic paper-based analytical devices (μPADs) have attracted much attention over the past decade. They embody many advantages, such as abundance, portability, cost-effectiveness, and ease of fabrication, making them superior for clinical diagnostics, environmental monitoring, and food safety assurance. Despite these advantages, μPADs lack the high sensitivity to detect many analytes at trace levels than other commercial analytical instruments such as mass spectrometry. Therefore, a preconcentration step is required to enhance their sensitivity. This review focuses on the techniques used to separate and preconcentrate the analytes onto the μPADs, such as ion concentration polarization, isotachophoresis, and field amplification sample stacking. Other separations and preconcentration techniques, including liquid-solid and liquid-liquid extractions coupled with μPADs, are also reviewed and discussed. In addition, the fabrication methods, advantages, disadvantages, and the performance evaluation of the μPADs concerning their precision and accuracy were highlighted and critically assessed. Finally, the challenges and future perspectives have been discussed.

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

This study explored the relationship between syntactic complexity and rhetorical functions and the relationship between syntactic complexity and level of move/step realization in learner-generated research paper introductions. We created a corpus of 79 introductions written by undergraduate L2 students at intermediate to high-intermediate levels. We annotated the introductions for moves and steps, measured their syntactic complexity at the global, clausal, and phrasal levels, and rated their level of move/step realization across four levels (no, low, intermediate, and high). We conducted one-way MANOVA, one-way ANOVA, Pearson correlation, and stepwise multiple linear regression analyses. We found sentences realizing Reviewing items of previous research function to be significantly longer than other steps in Move1 and to contain significantly more clausal and phrasal complexity features. Sentences performing Claiming centrality function also demonstrated significantly more phrasal complexity features as measured by complex nominals per clause. We also found a higher level of phrasal complexity in introductions with a higher level of move/step realization, which can be attributed to introductions including Step1 and Step3, rather than containing all steps. Our findings imply that there is value in developing explicit instructions on how to use complex structures in performing rhetorical steps in research paper introductions. © 2021 Elsevier Ltd

There is a need for an accurate end-of-life indicator for packaged food (meat, seafood, dairy food etc.) beyond a simple “best use by” date on the food package. In this work, we propose a low cost solution by repurposing the food’s barcode as a colorimetric sensor array to monitor food condition. A smart phone camera is used to read color information from the sensor barcode for quantitative estimate of the food aging and quality. The sensor is based on cross-reactive vapor sensitive dyes encapsulated in resin microbeads, which are impregnated onto a low cost paper substrate in a barcode pattern. The entire sensor platform is validated by accurately monitoring chicken aging and eventual spoilage under different temperature conditions. The proposed food diagnostics platform has the potential to reduce food waste and eliminate food-borne illness.

Background Display signage is ubiquitous and essential in hospitals to serve several clerical, operational, and clinical functions, including displaying notices, providing directions, and presenting clinical information. These functions improve efficiency and patient engagement, reduce errors, and enhance the continuity of care. Over time, signage has evolved from analog approaches such as whiteboards and handwritten notices to digital displays such as liquid crystal displays, light emitting diodes, and, now, electronic ink displays. Electronic ink displays are paper-like displays that are not backlit and show content by aligning microencapsulated color beads in response to an applied electric current. Power is only required to generate content and not to retain it. These displays are very readable, with low eye strain; minimize the emission of blue light; require minimal power; and can be driven by several data sources, ranging from virtual servers to electronic health record systems. These attributes make adapting electronic ink displays to hospitals an ideal use case. Objective In this paper, we aimed to outline the use of signage and displays in hospitals with a focus on electronic ink displays. We aimed to assess the advantages and limitations of using these displays in hospitals and outline the various public-facing and patient-facing applications of electronic ink displays. Finally, we aimed to discuss the technological considerations and an implementation framework that must be followed when adopting and deploying electronic ink displays. Methods The public-facing applications of electronic ink displays include signage and way-finders, timetables for shared workspaces, and noticeboards and bulletin boards. The clinical display applications may be smaller form factors such as door signs or bedside cards. The larger, ≥40-inch form factors may be used within patient rooms or at clinical command centers as a digital whiteboard to display general information, patient and clinician information, and care plans. In all these applications, such displays could replace analog whiteboards, noticeboards, and even other digital screens. Results We are conducting pilot research projects to delineate best use cases and practices in adopting electronic ink displays in clinical settings. This will entail liaising with key stakeholders, gathering objective logistical and feasibility data, and, ultimately, quantifying and describing the effect on clinical care and patient satisfaction. Conclusions There are several use cases in a clinical setting that may lend themselves perfectly to electronic ink display use. The main considerations to be studied in this adoption are network connectivity, content management, privacy and security robustness, and detailed comparison with existing modalities. Electronic ink displays offer a superior opportunity to future-proof existing practices. There is a need for theoretical considerations and real-world testing to determine if the advantages outweigh the limitations of electronic ink displays.

Summary Skin-interfaced wearable electronics can find a broad spectrum of applications in healthcare, human-machine interface, robotics, and others. The state-of-the-art wearable electronics usually suffer from costly and complex fabrication procedures and nonbiodegradable polymer substrates. Paper, comprising entangled micro- or nano-scale cellulose fibers, is compatible with scalable fabrication techniques and emerges as a sustainable, inexpensive, disposable, and biocompatible substrate for wearable electronics. Given various attractive properties (e.g., breathability, flexibility, biocompatibility, and biodegradability) and rich tunability of surface chemistry and porous structures, paper offers many exciting opportunities for wearable electronics. In this review, we first introduce the intriguing properties of paper-based wearable electronics and strategies for cellulose modifications to satisfy specific demands. We then overview the applications of paper-based devices in biosensing, energy storage and generation, optoelectronics, soft actuators, and several others. Finally, we discuss some challenges that need to be addressed before practical uses and wide implementation of paper-based wearable electronics., Graphical abstract, Biodevices; Bioelectronics; Electronic materials

Machine learning (ML) has increasingly been adopted in safety-critical systems such as autonomous vehicles (AVs) and industrial robotics. In these domains, reliability and safety are important considerations, and hence it is critical to ensure the resilience of ML systems to faults and errors. On the other hand, soft errors are becoming more frequent in commodity computer systems due to the effects of technology scaling and reduced supply voltages. Further, traditional solutions for masking hardware faults such as Triple-Modular Redundancy (TMR) are prohibitively expensive in terms of their energy and performance overheads. Therefore, there is a compelling need to ensure the resilience of ML applications to soft errors on commodity hardware platforms.We first experimentally assess the resilience of safety-critical ML applications to soft errors. We demonstrate through fault injection experiments that even a single bit flip due to a soft error can lead to misclassification in Deep Neural Network (DNN) applications deployed in AVs, leading to safety violations. However, not all the errors in an DNN will result in serve consequences such as safety violations, and hence it is sufficient to protect the DNN from the ones that do. Unfortunately, finding all possible errors that result in safety violations is a very compute intensive task. We propose BinFI, a fault injection approach that efficiently injects critical faults that are highly likely to result in safety violations, based on the unique properties of DNNs. Finally, we propose Ranger, an approach to protect DNNs from critical faults with minimal performance overheads and no accuracy loss. We will conclude by presenting some of our ongoing work, and the future challenges in this area.

The exchange of academic marks between HEIs (Higher Education Institutions) is mandatory in every student mobility programs (i.e. the EU Erasmus Program) but that process remains to present date with insufficient technological support and the absence of a comprehensive reference model that allows the integration of potential technological solutions for the exchange of academic data with existing Academic Information Systems seems to limit greatly the possibility of adopting solutions of this type referred to in the existing literature. This work addresses this issue, conducting an initial bibliographic review aimed at the identification of the fundamental requirements of such an architecture as well as explores some of the technologies that are showing potential for usage in the safe exchange of academic results between partner HEIs, with particular interest in blockchain technology applied in an educational context. info:eu-repo/semantics/publishedVersion

As the use of simulation has become more established in the delivery of healthcare education and training, there has been a corresponding increase in healthcare simulation research. Simulation-based research can be divided into research about simulation (answers research questions in which the focus is on simulation itself) and research through simulation (simulation as a method/tool for research). However, there are barriers, particularly for smaller less well-resourced simulation centres, that may prohibit participation in research. Therefore, it is suggested that quality improvement (QI) through simulation may be a pragmatic way in which simulation centres of all sizes can contribute to improving patient care beyond education and training. QI is defined as systematic, data-guided activities designed to bring about immediate, positive changes in the delivery of healthcare. Although not the case in healthcare, other industries routinely used simulation to support QI. For example, in aviation simulation is used to inform the design of the working environment, the appropriate use of technology, to exercise emergency procedures and to ‘re-fly’ flights following an adverse event as part of the mishap investigation. Integrating simulation within healthcare QI can support the development of novel interventions as well helping to address heretofore intractable issues.

A possible practical engineering approach to creation of the general artificial intelligence is considered. The choice of approach is based on modular hierarchical representation of knowledge, where each module uses its own methods of representation and knowledge processing. Work with knowledge is done by a hierarchical multi-agent system. The description of system’s individual elements and information about the current development state are given.

Our research objective is making quantum computing real with Qiskit for USAF-Pentagon JADC2 (Joint All Domain Command & Control) thus contributing to USAF-DoD core missions. JADC2 is the US Air Force led and Joint Staff coordinated key effort central to Joint Services C4I-ISR and C2 (Command & Control) integration enabling the new Joint Warfighting Concept for All-Domain Operations. The resulting ‘New American Way of War’ is anticipated to yield “significant advantage over everybody in the world for a long time” according to the Vice-Chairman of the Joint Chiefs General John Hyten.

Invented in China and brought to Europe by Muslim merchants across the Silk Road, the use of paper in the West took off in the Mediterranean towards the end of the Middle Ages. Overshadowed in cultural and media history by the invention of print, paper has played a fundamental role as the media infrastructure for innumerable processes involving the registration and communication of knowledge and value in communities and institutions, from religious orders, mercantile societies, to global empires. This thematic section of Cromohs features four essays. Three essays examine particular cases of paper as a medium for the codification and exchange of knowledge, information and value, whereas the fourth outlines the state of the art on the history of the so-called paper revolution and methodological issues illustrated with relevant case studies. These essays exemplify the research conducted by the Paper in Motion workgroup within the People in Motion COST action.

One of the software for compiling a bibliography automatically can take advantage of the facilities of the Mendeley Desktop application. Mendeley Desktop is a reference management software that helps organize scientific articles, namely in creating citations and bibliography. With this software, writers can manage reading sources that are used as references in compiling their writings. The use of Mendeley Desktop can also be integrated with Microsoft Word, so it can be more easily for writers for each scientific paper. The purpose of holding this training activity is to help the teachers of SMP Swasta Gita Surya Eban in order to utilize of the facilities provided by the software and the citations and references on the Mendeley Desktop so that scientific writing can be done more easily, quickly, and efficiently. From the training results, it was found that the training carried out could add knowledge and solutions to the use of Mendeley Desktop with the evaluation results increase significantly. The writers hope that by holding this training, teachers at SMP Swasta Gita Surya Eban can apply the citation / reference software from Mendeley Desktop in writing scientific papers.