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Accurately identifying core technological innovation pathways (TIPs) and evaluating opportunities in emerging technologies is important. In this article, we present an integrated framework that combines sentiment analysis, subject-action-object (SAO) analysis, machine learning, altmetrics, and expert judgments to extract technical intelligence, chart technological innovation pathways, and analyze which research avenues have the most future promise. For industry stakeholders, our approach provides a comprehensive, time-efficient, and future-oriented evaluation system to support decision making. For researchers, our methodology should inspire new ways of thinking about technological opportunity analysis—particularly, exploring the merits of finding new and advantageous combinations of existing bibliometric and nonbibliometric techniques, rather than reinventing the wheel. For example, this methodology is to integrate bibliometric analysis with sentiment analysis to gauge the attitudes of domain experts toward a topic's potential value. We combine SAO analysis and machine learning to identify relationships between topics from tremendous short texts. Beyond traditional techniques, we have also drawn on altmetrics to further validate the findings our of analysis. A case study on gold nanoparticles demonstrates the merits of our framework, revealing anti-cancer therapies and dye-sensitized solar cells (DSSCs) as the two applications with most future potential and societal impact in this field.

Deep learning models have demonstrated improved efficacy in image classification since the ImageNet Large Scale Visual Recognition Challenge started since 2010. Classification of images has further augmented in the field of computer vision with the dawn of transfer learning. To train a model on huge dataset demands huge computational resources and add a lot of cost to learning. Transfer learning allows to reduce on cost of learning and also help avoid reinventing the wheel. There are several pretrained models like VGG16, VGG19, ResNet50, Inceptionv3, EfficientNet etc which are widely used. This paper demonstrates image classification using pretrained deep neural network model VGG16 which is trained on images from ImageNet dataset. After obtaining the convolutional base model, a new deep neural network model is built on top of it for image classification based on fully connected network. This classifier will use features extracted from the convolutional base model.

The development of patient education (PE) materials is costly and resource-intensive, and no mechanisms exist for sharing materials across cancer centers/hospitals to limit duplicated effort. The aim of this study was to explore the incidence and cost implication of duplicated PE efforts.PE leaders from all (14) cancer centers in Ontario, Canada, submitted their collections of systemic therapy PE materials. Materials were categorized by topic and were coded as duplicate (more than one other material exists on the same topic and there was significant content and/or textual overlap), adapted (material was adapted from an existing material) or unique (no other material addresses the topic).304 materials were included and50 % of materials had duplicate content (n = 166, 55 %), a small proportion were adapted (n = 27, 9%), and less than half were unique (n = 111, 37 %). The majority of materials were considered amenable to adaptation meaning that the content was not dependent on a specific institutional context (n = 283, 93 %). The opportunity for cost savings if duplication of effort could be avoided is approximately $800 K for systemic therapy materials produced in cancer centers.There is need to refine the process for developing PE materials. Creating mechanisms of sharing can help facilitate equal access to materials and can result in significant cost savings.Efforts are needed to better coordinate the development of PE materials among patient educators. Better coordination would allow patient education programs to focus on other important challenges.

Intervention adaptations expand the availability of evidence-based treatments across clinical settings and demographically different populations. These adaptations utilize systematic strategies to preserve core components of an intervention. Intervention adaptations made from one public system to another (e.g., juvenile justice to mental health) reduce the need to invent a new intervention. In this column, the authors discuss the adaptation of Treatment Foster Care Oregon, an evidence-based program for treating youths with serious emotional and behavioral disturbance, to Michigan's public mental health system. Challenges encountered in this adaptation and solutions are presented.

In order to cope with the COVID-19 crisis, the French Parliament has adopted an Act creating a new emergency powers regime, dubbed state of health emergency, which is currently in force. The present paper aims at analysing and providing a critical appraisal of this regime. In particular, it will be demonstrated that this regime is rather imbalanced in that it confers important powers to the executive with limited checks and balances. It will also be contended that the creation of a new regime was not necessary, and that it would have been wiser to amend the existing state of emergency.

This article shows that the Spanish court was an experimental pedagogical space oriented toward cultivating women as political subjects. In order to do so, I will examine Pedro de Guevara’s Nueva y...

This paper examines the contexts of literature reviewing among scholars in Africa, particularly social scientists. It argues quite forcefully that reviews are becoming increasingly characterized by avoidable gaps and therefore represent some form of enigma, which remain largely unrecognized. The implications are not only debilitating but also alienating from the global intellectual milieu. The paper chronicles the issues and suggests the path to achieving standard reviews in contemporary academic scenery, rather than reinventing the wheel and, by implication, demeaning the essence of knowledge production and propagation.

Addressing design evaluation as a critical yet under-researched domain, this study analyzes the design evaluation structure and its variables and criteria that guide its outcomes. Within a scope of architectural design in practice and education, this study develops a new tool for design quality evaluation. The study consists of four main parts. The first is explorative which reviews and analyzes literature in the assessment and evaluation fields. The second is derivative and used to develop a tool for design quality evaluation (DQE) that combines design criteria and detailed evaluation rubrics. The tool which is named “Evaluation Wheel” is intended to help designers, educators and other design-related stakeholders judge design products succinctly, comprehensively, systematically and graphically. The third part is experimental and is used to test the applicability of the proposed wheel. A set of design products are evaluated by a group of designers using two methods; one uses various design criteria, and the other uses the wheel tool introduced in this research. The fourth part is analytical and evaluative which uses deductive, inductive and abductive reasoning techniques to analyze and compare the findings of the third part. The findings are presented and discussed. The results that indicate a reduction of the discrepancies of the scores among the evaluators seem to support the uptake of the proposed wheel in the design evaluation fields. Keywords: Design evaluation tool, Evaluation criteria, Affective engineering, Design rubrics, Architectural assessment, Design quality indicator, Quality assurance

Rather than reinventing the wheel for each new position, leaders in libraries may choose to rely on heuristics that leading thinkers in organizational theory have pointed out exist in many organiza...

Purpose The purpose of this paper is to advance knowledge of organizational change towards diversity by bringing together concepts from organizational learning and diversity studies. Design/methodology/approach This longitudinal study was conducted over two years. It involved interviews, observation of meetings and consultation of documentation and the analysis focused on organizational learning. The key research question was how do organizational members institutionalize their individual learning process to change in organizational cultures, routines and structures in a sustainable way? Findings The results showed that there had been learning at the individual level but this did not necessarily mean that participants had been able to transfer their learning into behaviour change. Research limitations/implications The research suggested that training alone may not be sufficient to promote effective organizational change regarding diversity. Additional measures are likely to be required, for example, including diversity targets in performance management plans and reviews. Practical implications In order to achieve greater diversity, organizations are likely to need to use a number of methods to supplement initial training. Social implications This research gives insight into how greater diversity may be achieved in organizations. Originality/value Previous literature understates the complexity of the change processes for enhanced diversity to be sustained in organizations. This study has originality in its focus on organizational learning.

This article provides an account of a project (funded by the Ferens Education Trust) which is designed to enhance clinical legal education (CLE) provision within my own institution, develop networks with local stakeholders, promote civic engagement, supplement over-stretched advice provision and elicit valuable research data. The intention in providing a ‘warts and all’ account of how this project developed is to offer an insight into the trials and tribulations of setting up such a scheme, to offer comfort to those who like me, are new to this kind of task and, to assist in efforts to avoid reinventing the wheel. Perhaps more importantly, it aims also to highlight the potential for CLE schemes to facilitate research.

We decided to embark on our almost-completed project of archiving the records of the National Pay Equity Coalition (NPEC) for two reasons. First, women activists campaigning for pay equity seemed to be in danger of reinventing the wheel. So much of what we had researched and written about was still vitally relevant but was invisible because it had been produced before the digital era. We needed to get that information out there.

To prevent each vehicle manufacturer from “reinventing the wheel” and spending vast amounts of time and engineering, a paradigm shift is needed. Transferring the vehicle design to standardized hardware would enable software to take the key role and allow the horizontal approach in design, where each feature may be added as a module. This sets the stage for a central vehicle computer—a brain for next generation vehicles which is everything but easy to design. This article discusses one such design and identifies the required building blocks for this rising market.

With the recent development on a knowledge-based economy and project-based work, organizations gather and store their lessons and knowledge gained from projects to avoid ‘reinventing the wheel’ in future projects. To disseminate knowledge and experience at the group and organization levels, they further seek to develop a procedure to support project-based learning. This study conducts an in-depth case study in Siemens to investigate the perception of the individuals on barriers and enablers of implementing lessons learned. It also provides practical recommendations on how to enhance the dissemination of knowledge throughout the organization. The results of this study show that the retrieval of the information is a major barrier to lessons learned. To encourage more informal learning, organizations need to adopt various information communication systems and appropriate organizational culture and structure.

Resilience is a well‐used term in many disciplines, but inconsistently or little applied in river geomorphology and river science. Recent developments in ecosystem ecology conceptualize resilience as comprising system resistance to, and recovery from disturbance. The objectives of this paper are to consider how the concept of resilience in this bivariate form applies to river geomorphology and provide a framework for bridging the disciplines of ecology and geomorphology within the setting of river management, using principles of resilience. River geomorphology sets the physical template upon which lotic processes act, thus, understanding the resilience of this template is critical. The importance of consistency in defining the principles of resilience thinking within the context of river science and management is important especially when promoting ecosystem resilience as a river management goal. The application of resilience thinking with respect to river habitat is provided through a series of examples from Australian and New Zealand river systems. AIM: How is the concept of resilience applied to river geomorphology, and what does a geomorphologically resilient river look like?

Applications depend on libraries to avoid reinventing the wheel. Libraries may have incompatible changes during evolving. As a result, applications will suffer from compatibility failures. There has been much research on addressing detecting incompatible changes in libraries, or helping applications co-evolve with the libraries. The existing solution helps the latest application version work well against the latest library version as an afterthought. However, end users have already been suffering from the failures and have to wait for new versions. In this paper, we propose DepOwl, a practical tool helping users prevent compatibility failures. The key idea is to avoid using incompatible versions from the very beginning. We evaluated DepOwl on 38 known compatibility failures from StackOverflow, and DepOwl can prevent 32 of them. We also evaluated DepOwl using the software repository shipped with Ubuntu-19.10. DepOwl detected 77 unknown dependency bugs, which may lead to compatibility failures.

Chronic pain affects approximately one-third of the population worldwide. The primary goal of animal research is to understand the neural mechanisms underlying pain so better treatments can be developed. Despite an enormous investment in time and money, almost no novel treatments for pain have been developed. There are many factors that contribute to this lack of translation in drug development. The mismatch between the goals of drug development in animals (inhibition of pain-evoked responses) and treatment in humans (restoration of function) is a major problem. To solve this problem, a number of pain-depressed behavioral tests have been developed to assess changes in normal behavior in laboratory animals. The use of home cage wheel running as a pain assessment tool is especially useful in that it is easy to use, provides an objective measurement of the magnitude and duration of pain, and is a clinically relevant method to screen novel drugs. Pain depresses activity in humans and animals, and effective analgesic treatments restore activity. Unlike traditional pain-evoked tests (e.g., hot plate, tail flick, von Frey test), restoration of home cage wheel running evaluates treatments for both antinociceptive efficacy and the absence of disruptive side effects (e.g., sedation, paralysis, nausea). This article reviews the literature using wheel running to assess pain and makes the case for home cage wheel running as an effective and clinically relevant method to screen novel analgesics for therapeutic potential.

When dealing with academic integrity in programming, code similarity detectors are often used to raise suspicion of student programs with undue similarity. However, it appears that only detectors designed for that purpose are discussed in computing education publications, although similarity detectors for other purposes might also be beneficial, both to foster research and to avoid ‘reinventing the wheel’. This paper maps similarity detectors used to identify code clones, repeated code segments in a software system, to the classifications used for academic integrity purposes. It will help academic integrity researchers to understand code clone similarity detectors and to read papers from that area. While there are other reviews of code clone detection, ours should be easier for computing educators to read as it uses the terminologies of academic integrity.

Public interest in the combined application domain of Artificial Intelligence (AI) - based Big Data Analysis and Visualization is currently peaking. Yet until recently, there was no reference model that provided common ground for information exchange in bigger projects or collaboration scenarios, that prevented scientists and private companies from reinventing the wheel. The introduction of AI2VIS4BigData Reference Model recently filled this gap. This paper targets to introduce the AI2VIS4BigData Reference Model, its elements and all interconnections between them in very detail. It provides an overview of example reference models, their general history and objectives and introduces the reference models that were utilized to derive AI2VIS4BigData.

Multiple specific solutions reinventing the wheel on how to integrate the IoT technology characterise the actual scenario of Industry 4.0. This paper proposes a software architecture for integrating IoT-based solutions in a generic scenario. Our main contribution is the definition of formal processes for capturing, processing and presenting data to the user. The proposed architecture was evaluated in the construction of a system for controlling access to a parking lot in Universidad Nacional de Educacion. The experimental evaluation of the architecture shows that the design of a solution based on the proposed architecture increases the extensibility of the IoT solution and increases the easiness to integrate the solution with a legacy system. As a result, an open source, easy to extend software architecture is presented.

AI2VIS4BigData is a reference model for Artificial Intelligence (AI) - based Big Data Analysis and Visualization that provides uniform terminology and logical entity-relationships to scientists and professionals working in this application domain. It thereby enables re-utilization of concepts and software, prevents reinventing the wheel and facilitates collaboration scenarios. AI2VIS4BigData was systematically derived from two foundation reference models utilizing reasoned assumptions. These assumptions required subjective decisions which were not evaluated right away. This publication targets to change that through presenting two qualitative evaluation approaches that were conducted in the course of an official satellite workshop of an international conference. Selected scientific and industrial experts participated thereby in an expert round table workshop and a survey. The validation results confirm the reference model’s practical applicability and legitimate the substantial majority of subjective decisions that were taken in the course of the reference model derivation. This publication concludes with outlining five research fields for future work that comprise the non-validated subjective decisions.

India is an industrialized country, and about 70% of the residents rely on agriculture. Leaves are damaged by chemicals, and climates issues. An unknown illness is found on plants leads to the lowering of quality of produced. Internet of Things is a practice of reinventing the wheel agriculture by enabling farmers to tackle the problems in the industry with practical farming techniques. IoT helps to inform knowledge about factors like weather, and moisture condition. We proposed IoT, ML, and image processing based method to identify the infection. IOT enabled camera to capture the image then required region of interest is extracted. After ROI extraction, image is enhanced to remove the unwanted details form the image and to improve image quality. We compute image features. At the end we do the classification which is a twostep process training and testing and done by SVM. Our proposed method gives 92% accuracy.

The final chapter of this book brings together our theoretical observations and our empirical findings to present a practical concept of how to engage in a process of communication, reflection and strategy development that allows a family to embark on an examination of itself and its relationship with its business. The chapter offers a guide to a prototypical process of family strategy formulation, broken down into 12 topic areas. As we see it, work on family strategy means shifting from hope to trust. Those who continue to make family strategy decisions in ways that have proven effective in the past have to hope that the family circumstances and environmental demands continue to fit the familiar solutions. Anyone initiating a family strategy process is calling on the family to engage in a significant effort to communicate, and, even when a family strategy has finally been established, dispute and conflict will not disappear.

This publication will introduce the reference model AI2VIS4BigData for the application domains Big Data analysis, AI, and visualization. Without a reference model, developing a software system and other scientific and industrial activities in this topic field lack a common specification and a common basis for discussion and thus pose a high risk of inefficiency, reinventing the wheel and solving problems that have already been solved elsewhere. To prevent these disadvantages, this publication systematically derives the reference model AI2VIS4BigData with special focus on use cases where Big Data analysis, artificial intelligence (AI), and visualization mutually support each other: AI-powered algorithms empower data scientists to analyze Big Data and thereby exploit its full potential. Big Data enables AI specialists to comfortably design, validate, and deploy AI models. In addition, AI’s algorithms and methods offer the opportunity to make Big Data exploration more efficient for both, involved users and computing and storage resources. Visualization of data, algorithms, and processing steps improves comprehension and lowers entry barriers for all user stereotypes involved in these use cases.

Knowledge Graphs can be considered as fulfilling an early vision in Computer Science of creating intelligent systems that integrate knowledge and data at large scale. Stemming from scientific advancements in research areas of Semantic Web, Databases, Knowledge representation, NLP, Machine Learning, among others, Knowledge Graphs have rapidly gained popularity in academia and industry in the past years. The integration of such disparate disciplines and techniques give the richness to Knowledge Graphs, but also present the challenge to practitioners and theoreticians to know how current advances develop from early techniques in order, on one hand, take full advantage of them, and on the other, avoid reinventing the wheel. This tutorial will provide a historical context on the roots of Knowledge Graphs grounded in the advancements of Logic, Data and the combination thereof.

Non-communicable diseases (NCDs) are one of the main challenges to the development and well-being of populations. Based on the documents issued by the United Nations system (FAO, ECOSOC, UNGA, and WHO), it is argued that the 2030 Agenda is partially harmonized with the recommendations of these organizations. This partial harmonization is explained through political coherence by illustrating explanatory vectors from 2005 to 2019 for products associated with NCDs risk factors: alcohol, pesticides, ultra-processed foods, and tobacco.

While policy and academic discourses point to important shifts in EU development policy, it remains difficult to ascertain the level of these changes. The main aim of this article is to propose a research agenda on change and continuity in EU development policy. Drawing on the literatures on paradigm change and post-development, this involves four key questions for future research: (1) How can we map the EU's current paradigm? (2) How can we map changes and continuities in this regard? (3) How can we explain changes and continuities? (4) What role do policy experiments play in this regard? In addressing these four questions, the article pays particular attention to what we already know from existing literature and to what issues could guide future research. We highlight that ostensibly significant changes are often 'merely' second order changes that do not challenge underlying philosophical ideas of the Eurocentric, modernist and colonial paradigm. Specifically, we point at the importance of studying whether policy experiments 'reinvent' this paradigm or induce paradigmatic change. In the conclusions, we summarize the research agenda and reflect on the need of a better acknowledgement of the 'PIEUriverse' of alternatives to 'development' within Europe.

Due to extreme volatile condition of market, banks must adopt best practices to respond robustly to competitive challenges. Among bundle of resources present in organization, knowledge is considered an essential organizational resource. The area of main concern for all the companies is to find best ways to identify, store and disseminate knowledge in organizations. It has been the matter of discussion that due to highly active role banks are playing for economy of any country and risk factors deeply associated with the banking business, creating a platform for identifying, capturing and accessing knowledge is challenging job. As a result critical mistakes are repeated on projects and professionals have to keep "reinventing the wheel". Considering the nature of complex and risky banking operations, knowledge management is found an organized platform to access the reliable data for smooth banking services. This paper discusses a range of sustainability practices that banks are executing with help of Information and Communication Technology (ICT) enabled knowledge management platform. The work presented in the case study was carried out for providing understanding how ICT helps knowledge management to grow and support sustainability development.

This article is a critical reaction to the 2020 EJIL Foreword titled ‘Guiding Principles on Shared Responsibility in International Law’. It focuses on Principle 3, concerning a ‘single internationally wrongful act’, and it is divided into its constitutive elements: the meaning of same conduct (Section 2), the attribution to multiple persons (Section 3), the breach of obligations (Section 4) and the indivisible injury (Section 5). The main criticism is that the Guiding Principles make things more complex than they already are. The established principles of international responsibility provide simpler and more effective answers. This is particularly the case for Principle 3, which concerns multiple responsibilities arising from the same conduct. There are two main elements through which the Guiding Principles on Shared Responsibility seek to provide guidance in the case of a plurality of internationally responsible persons. First, they employ the comprehensive notion of an internationally wrongful act, while ARSIWA and ARIO distinguish between the two elements of attribution of conduct and the breach of an obligation. Second, the Guiding Principles consider the injury to be a constitutive element included in the definition of shared responsibility, while ARSIWA and ARIO only employ it in the context of reparation and countermeasures. There are no actual benefits coming from these attempts of clarification.

It is imperative that new solutions in Electronic Design Automation (EDA) appear to cope with the increasing complexity of modern chips. However, the lack of broadly available platforms for rapid application development (RAD) of EDA tools hinders the volume and quality of the contributions from the scientific community. In this paper, we tackle this issue by proposing a RAD platform for EDA tools that enables the contributors to focus on the problem that they want to solve instead of “reinventing the wheel”. The proposed platform encompasses a user-friendly Tcl shell, a standardized data model, templates for quick creation of commands, a system-level Qt Graphical User Interface (GUI) and a user customizable Tk GUI, all synchronized by an event loop orchestrator with distributed processing capabilities. The amount of “boilerplate” code is reduced to a minimum in each stage of development. Finally, we propose the usage of a Continuous Integration/Continuous Deployment cycle to reduce the efforts on distribution of the tools developed on top of the platform. The platform was validated with the development of modules for the design flow of mixed-signal circuits.

Lifting water is crucial to irrigate agricultural terraces in the Mediterranean region. But the energy demand and emissions of modern forms of water pumping have increased, while many traditional water wheels, which lift water at zero direct emissions, have been abandoned. We explored the state of preservation and the potential for the deployment of traditional water wheels known as “norias” in the Ricote Valley of southeast Spain, where some are still in function, while also investigating the reasons for their widespread abandonment. A mixed method approach is used here to combine GIS-based methods, an expert survey, and a technological and socio-economic assessment of noria renovation. Our findings show that norias in the Ricote Valley have mostly been replaced by thermal-engine water-lifting technologies. The reactivation of traditional irrigation technologies, many of them lying dormant but still standing, could contribute to reducing the high energy demand and the resulting emissions of irrigation systems in the Mediterranean region and beyond. It was estimated by data extrapolation that 16 renovated norias included in our analysis can irrigate 140.3 ha in the Ricote Valley, for a total achievable power of 23.8 kW. To irrigate a similar surface applying diesel motor pumps would produce up to 148 tons of emissions/year and cost up to approx. 70,000 €/year based on a price of 1.25€/l diesel for a maximum of 8760 working hours/year. In the case of electric pumps, we estimate that up to 55 tons of emissions/year and costs up to approx. 48,000 €/year can be saved. Therefore, we argue that rediscovering traditional technologies has potential to contribute to achieving climate actions that reduce GHG emissions (Sustainable Development Goal 13). Moreover, these technologies provide multiple functions and services for a sustainable life on land (Sustainable Development Goal 15), which needs to be considered within a holistic approach. This research was funded by Friedrich-Ebert-Foundation (FES, Germany) and partly supported by the CLICCS Cluster of Excellence (Grant ID: 2037) funded by the German Research Foundation (DFG).

Knowledge is considered one of the effective assets which control the success of organizations, and its effective management is crucial. Although knowledge has existed and has been used along all projects, the way it was managed was almost intuitive and highly reliable on in-house systems. As a consequence, knowledge management was introduced in the late 1990s to help companies create, share, and systematically use knowledge. Knowledge management can be defined as the identification, optimization, and active management of intellectual assets that create value, increase productivity, and gain and sustain competitive advantage. Construction field, as one of the most complicated fields, is considered a project- based field where numbers of investments in it are in millions every year. Although knowledge in construction is among the main factors for project success, most of this knowledge lies in the minds of the people, which makes it hard to be captured and stored. Accordingly, effective knowledge management in construction is affected by different factors, including the willingness of people to share their knowledge and the mobilization of the workforce from one project to another without sharing lessons learned and previous knowledge. Here comes the role of application of KM, which could help prevent “reinventing the wheel” in construction. This paper aims at offering a comprehensive overview of the application of KM in construction through reviewing extant literature sources. Topics discussed included factors affecting KM, KM tools and techniques, the processes of KM, and the main benefits and challenges facing KM. There are many factors affecting knowledge management and many tools and techniques to manage knowledge. As for the findings of this paper, they took the form of an analysis of the main benefits and challenges facing the application of KM in construction.

Knowledge sharing can be hindered by barriers that prevent the free flow of information, especially across organizational and other boundaries. Therefore information produced at one location might not be available to entities elsewhere even if there are benefits to sharing this information. This can often lead to 'reinventing the wheel' and wasted investments in duplicating resources and ultimately will lead to the development of knowledge silos. Information technologies can be used to address this problem as they provide opportunities to lower the barriers to knowledge sharing and increase collaboration. This need for knowledge sharing and collaborative technologies can be important for Small Island Developing States (SIDS) within particular regions that are exposed to similar environmental and economic issues that can hinder their development. Although each SIDS may have Knowledge Resources that it uses to address its own issues, there would be benefits to collaborating and sharing these resourc...

La aparición, 25 años después, de una nueva temporada de la serie de televisión creada por Mark Frost y David Lynch desató especulaciones en redes sociales sobre el significado de los sucesos que conforman su ficción, así como una oleada de fanáticos que intenta desentrañar todos y cada uno de los misterios que la anécdota presenta e incluso una especie de nuevo culto tras la muy particular admiración que ahora existe por el episodio 8. Más allá del fenómeno pop (bastante discreto con respecto al que provocan otras series de más reciente creación, como Juego de tronos o Stranger Things), existen aspectos formales que considero importante rescatar en este texto. No se trata de descubrir el hilo negro, pero sí de no dejar pasar aquello que de único y valioso tiene Twin Peaks.

The article shows in which areas other countries can benefit from the work of the Norwegian platform NDLA (ndla.no). This assessment is based on interviews with 13 representatives of the platform, three cooperation partners and one representative of Norwegian textbook publishers. The experiences described refer to a large-scale Open Educational Resources (OER) platform for upper secondary education, which was founded in 2006. The contents and experiences of the interviews were categorised into four areas: creation process, consumption, context based decisions and peer-production. The openness of the colleagues through the interviews conducted allows –for the first time– insights into the structures, strategies and considerations of NDLA. In conclusion, the special potential of such a state funded OER platform for inclusive education and which aspects might be relevant for higher education is shown.

There have long been calls to reduce the bureaucratization of clinical trials and make them more ‘sensible’, with the focus on approvals and guidelines. Here, I focus on the mundane environments of a multi-centre clinical trial to ask how ‘sensible’ it is to standardize trials at the level of material objects. Drawing on ethnographic data collected in the UK, South Africa and Vietnam, I present three vignettes of material standardisation. While acknowledging some positive effects, I argue that standardising in this way may be antithetical to sustainable and relevant clinical research. Three dimensions of this are discussed: 1) the external validity of evidence from pragmatic trials 2) the gap between experimentation and implementation and 3) long-term site capacity to conduct research. Drawing on the literature on ‘situated standardisation’, the paper concludes by suggesting a greater acknowledgement of the need for trials not only to be ‘sensible’ but also ‘situated’.

Application programming interfaces (APIs) offer a plethora of functionalities for developers to reuse without reinventing the wheel. Identifying the appropriate APIs given a project requirement is critical for the success of a project, as many functionalities can be reused to achieve faster development. However, the massive number of APIs would often hinder the developers' ability to quickly find the right APIs. In this light, we propose a new, automated approach called WebAPIRec that takes as input a project profile and outputs a ranked list of {web} APIs that can be used to implement the project. At its heart, WebAPIRec employs a personalized ranking model that ranks web APIs specific (personalized) to a project. Based on the historical data of {web} API usages, WebAPIRec learns a model that minimizes the incorrect ordering of web APIs, i.e., when a used {web} API is ranked lower than an unused (or a not-yet-used) web API. We have evaluated our approach on a dataset comprising 9,883 web APIs and 4,315 web application projects from ProgrammableWeb with promising results. For 84.0% of the projects, WebAPIRec is able to successfully return correct APIs that are used to implement the projects in the top-5 positions. This is substantially better than the recommendations provided by ProgrammableWeb's native search functionality. WebAPIRec also outperforms McMillan et al.'s application search engine and popularity-based recommendation., Comment: IEEE Transactions on Emerging Topics in Computational Intelligence, 2017

Purpose This study aims to discuss how business model innovation from both incumbents and startups growingly may stem from past products, services, and approaches reinvented. This results in what is labeled the “Reinventing the Wheel (RTW)” innovation paradigm, where the future is seen through the lenses of the past. Design/methodology/approach This study is based on historical analysis of common business model innovation patterns found in a longitudinal sample of both incumbent companies and startups in the time frame 2008-2016. Findings The RTW paradigm unlocks business model innovation through: the reinvention of past resources and competencies; the use of digital technologies; and the centrality given to customer experience and customer journey. The resulting RTW cycle is made of five steps to follow in the attempt to make the most out of this paradigm: survey, learn, disclose, exploit, and reinvent. Practical implications Entrepreneurs and managers are presented with the key elements, steps, and implications of an emerging business model innovation paradigm to possibly apply in their incumbent or startup context. Originality/value This study presents an original approach to look at business model innovation, in a way that is complementary to alternative practices like the blue ocean strategy, big-bang disruption, and lean startup.

Economic data and financial markets are intriguing to researchers working on data and quantitative models. With rapid growth of and increasing access to data in digital form, finance, economics, and marketing data are poised to become one of the most important and tangible big data applications, owing not only to the relatively clean organization and structure of the data but also to clear application objectives and market demands. However, data-related economic studies often have different viewpoints from signal processing (SP). Also, many fundamental economics and business problems have been well formulated and studied in both theory and practice. The knowledge of foundational finance and economic theories will help SP and data researchers avoid reinventing the wheel and develop meaningful and useful research in these areas.