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Mobile robot navigation is a critical aspect of robotics, with applications spanning from service robots to industrial automation. However, navigating in complex and dynamic environments poses many challenges, such as avoiding obstacles, making decisions in real-time, and adapting to new situations. Reinforcement Learning (RL) has emerged as a promising approach to enable robots to learn navigation policies from their interactions with the environment. However, application of RL methods to real-world tasks such as mobile robot navigation, and evaluating their performance under various training–testing settings has not been sufficiently researched. In this paper, we have designed an evaluation framework that investigates the RL algorithm's generalization capability in regard to unseen scenarios in terms of learning convergence and success rates by transferring learned policies in simulation to physical environments. To achieve this, we designed a simulated environment in Gazebo for training the robot over a high number of episodes. The training environment closely mimics the typical indoor scenarios that a mobile robot can encounter, replicating real-world challenges. For evaluation, we designed physical environments with and without unforeseen indoor scenarios. This evaluation framework outputs statistical metrics, which we then use to conduct an extensive study on a deep RL method, namely the proximal policy optimization (PPO). The results provide valuable insights into the strengths and limitations of the method for mobile robot navigation. Our experiments demonstrate that the trained model from simulations can be deployed to the previously unseen physical world with a success rate of over 88 % . The insights gained from our study can assist practitioners and researchers in selecting suitable RL approaches and training–testing settings for their specific robotic navigation tasks. [ABSTRACT FROM AUTHOR]

FishSounds is an online portal that provides open and user-friendly access to academic scholarship regarding the sounds made by fish species. It is the result of an international collaboration between students, scientists, and information professionals, and has become a resource used around the globe for research, education, journalism, and general interest. This website is just the first instance of a new approach to sharing knowledge and an emerging cyberinfrastructure for open scholarship. The codebase behind FishSounds was designed to be reusable with other datasets, and in the coming years, additional portals will connect users to knowledge from varied subject areas across academic disciplines. This discussion examines the development and reception of FishSounds as a case study for the creation of these websites, called searchable online catalogues of knowledge or SOCKs. As it is publicly released, the SOCK platform will continue to evolve and develop new strategies based on the lessons learned from different audiences accessing FishSounds. [ABSTRACT FROM AUTHOR]

Understanding the development trajectory of digital platforms is central to digital platform management. We develop a parametric model that investigates the development trajectories of blockchain platforms, accounting for the feedback between blockchains' utility change and people's adoption and abandonment behavior. We consider a typical blockchain participant to simultaneously play three roles on the platform, user, investor, and laborer, each contributing to blockchains' multi-faceted utility: providing service for transaction/interaction, providing a medium for digital investment, and providing workspace for online labor. The model describes a three-phase development trajectory for blockchain platforms: a chaotic initial stage, a rapid growth stage, and a mature stage of stable market cycles. The model was used to match 112 token price series, demonstrating robust performance across different fitting setups and outperforming existing models. The study identifies two temporal parameters, the time delay in quitting the platform and the holding time of the platform's token, that significantly differentiate blockchains' development trajectories. We extend the model to study forking events; results suggest that fork launch time is more important than forking amplitude in influencing the main chain's subsequent development and that forking can increase the exposure of the forked platform. We develop a parametric model that investigates the development trajectories of blockchain platforms, accounting for the feedback between blockchains' utility change and people's adoption and abandonment behavior. A typical blockchain participant is considered to simultaneously play three roles on the platform, user, investor, and laborer, each contributing a unique element to blockchains' multifaceted utility. The model predicts a three-phase development trajectory for blockchain platforms: a chaotic initial stage, a rapid growth stage, and a mature stage of stable market cycles. The roles have different functions at different developmental stages, and their interactions determine phase transitions. The model was used to match 112 token price series, demonstrating robust performance across different fitting setups and outperforming existing models. The study identifies two temporal parameters—the time delay in quitting the platform and the holding time of the platform's token—that significantly differentiate blockchains' development trajectories. We also extend the model to study forking events, finding that fork launch time is more important than forking amplitude in influencing the main chain's subsequent development and that forking can increase the exposure of the forked platform. History: Yong Tan, Senior Editor; Yan Huang, Associate Editor. Funding: This work was supported by the Research Grants Council, University Grants Committee [Grants GRF 14500521, GRF 14501320, GRF 14503818, GRF 165052947, and TRS:T31-604/18-N]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2022.0243. [ABSTRACT FROM AUTHOR]

Mobile robot navigation is a critical aspect of robotics, with applications spanning from service robots to industrial automation. However, navigating in complex and dynamic environments poses many challenges, such as avoiding obstacles, making decisions in real-time, and adapting to new situations. Reinforcement Learning (RL) has emerged as a promising approach to enable robots to learn navigation policies from their interactions with the environment. However, application of RL methods to real-world tasks such as mobile robot navigation, and evaluating their performance under various training–testing settings has not been sufficiently researched. In this paper, we have designed an evaluation framework that investigates the RL algorithm’s generalization capability in regard to unseen scenarios in terms of learning convergence and success rates by transferring learned policies in simulation to physical environments. To achieve this, we designed a simulated environment in Gazebo for training the robot over a high number of episodes. The training environment closely mimics the typical indoor scenarios that a mobile robot can encounter, replicating real-world challenges. For evaluation, we designed physical environments with and without unforeseen indoor scenarios. This evaluation framework outputs statistical metrics, which we then use to conduct an extensive study on a deep RL method, namely the proximal policy optimization (PPO). The results provide valuable insights into the strengths and limitations of the method for mobile robot navigation. Our experiments demonstrate that the trained model from simulations can be deployed to the previously unseen physical world with a success rate of over 88%. The insights gained from our study can assist practitioners and researchers in selecting suitable RL approaches and training–testing settings for their specific robotic navigation tasks.

Traumatic brain injury (TBI) is a major health problem that affects millions of persons worldwide every year among all age groups, mainly young children, and elderly persons. It is the leading cause of death for children under the age of 16 and is highly correlated with a variety of neuronal disorders, such as epilepsy, and neurodegenerative disease, such as Alzheimer's disease or amyotrophic lateral sclerosis. Over the past few decades, our comprehension of the molecular pathway of TBI has improved, yet despite being a major public health issue, there is currently no U.S. Food and Drug Administration?approved treatment for TBI, and a gap remains between these advances and their application to the clinical treatment of TBI. One of the major hurdles for pushing TBI research forward is the accessibility of TBI models and tools. Most of the TBI models require costume-made, complex, and expensive equipment, which often requires special knowledge to operate. In this study, we present a modular, three-dimensional printed TBI induction device, which induces, by the pulse of a pressure shock, a TBI-like injury on any standard cell-culture tool. Moreover, we demonstrate that our device can be used on multiple systems and cell types and can induce repetitive TBIs, which is very common in clinical TBI. Further, we demonstrate that our platform can recapitulate the hallmarks of TBI, which include cell death, decrease in neuronal functionality, axonal swelling (for neurons), and increase permeability (for endothelium). In addition, in view of the continued discussion on the need, benefits, and ethics of the use of animals in scientific research, this in vitro, high-throughput platform will make TBI research more accessible to other labs that prefer to avoid the use of animals yet are interested in this field. We believe that this will enable us to push the field forward and facilitate/accelerate the availability of novel treatments.

The rapid design and assembly of synthetic DNA constructs have become a crucial component of biological engineering projects via iterative design-build-test-learn cycles. In this perspective, we provide an overview of the workflows used to generate the thousands of constructs and libraries produced each year at the U.S. Department of Energy Joint Genome Institute. Particular attention is paid to describing pipelines, tools used, types of scientific projects enabled by the platform and challenges faced in further scaling output.

Copyright of HMD: Praxis der Wirtschaftsinformatik is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• The study provides a framework and course design of dBTI based on the WeChat mini-program. • Gender, PSAS somatic score and ISI score are adherence-related factors in dBTI. • Individuals suffering from moderate insomnia have better adherence. • Higher adherence leads to better improvement in symptoms for insomnia, especially in ISI score and PSAS somatic score. Brief therapy for insomnia (BTI) is a short-term cognitive behavioral therapy for insomnia. At present, there is no study combining BTI with digital technology. However, in the context of the outbreak of coronavirus disease 2019 (COVID-19), patients with acute insomnia may need an online treatment which can quickly improve insomnia symptoms. Our team built a digital BTI (dBTI) platform based on the WeChat mini program. This research provides a framework design and a course design of dBTI, and evaluates the system via recruiting participants suffering from acute insomnia in pandemic. What's more, it explores patients' adherence, the efficiency of the system and their relationship. As the result demonstrates, 68% of participants have completed more than half of the course with medium to high adherence. Gender, pre-sleep arousal scale (PSAS) somatic score and insomnia severity index (ISI) score have affected participants' adherence, and higher adherence has led to better improvement in the severity of insomnia and somatic pre-sleep arousal. It is proved that the platform we built is effective, which not only offers an entry point for the study of how to set up a dBTI platform, but also provides theoretical basis for its clinical application. [ABSTRACT FROM AUTHOR]

The performance of metal cutting tools directly affects the manufacturing efficiency and machining quality of products. With the increasing demands in manufacturing industry of cutting performance, machining efficiency, customization, and quick response, traditional tool design methods can no longer meet the above requirements due to many repetitive work, large amount of calculation, complex process, and low efficiency. Parametric design has become a new development direction of customized tool design because of its fast, stable, and accurate characteristics. Based on the parametric design of cutting tools, this paper develops a tool parametric design platform by using the method of secondary development of commercial CAD software. The platform realizes automatic operation in the background without commercial CAD software interface, completes the parametric modeling process of tools, generates 2D drawings and 3D models conforming to ISO 13399 standard, and realizes the cloud storage function of model data and the parametric design of many kinds of tools. Compare with that traditional modeling method, using this parametric modeling platform, the modeling efficiency is increased by 90% on average. This platform is of great significance to improve the design efficiency of complex customized tools and shorten the original design cycle by 30%. [ABSTRACT FROM AUTHOR]

Background: A challenge facing researchers conducting mobile health (mHealth) research is the amount of resources required to develop mobile apps. This can be a barrier to generating relevant knowledge in a timely manner. The recent rise of "no-code" software development platforms may overcome this challenge and enable researchers to decrease the cost and time required to develop mHealth research apps. Objective: We aimed to describe the development process and the lessons learned to build Pathverse, a no-code mHealth app design platform. Methods: The study took place between November 2019 and December 2021. We used a participatory research framework to develop the mHealth app design platform. In phase 1, we worked with researchers to gather key platform feature requirements and conducted an exploratory literature search to determine needs related to this platform. In phase 2, we used an agile software framework (Scrum) to develop the platform. Each development sprint cycle was 4 weeks in length. We created a minimum viable product at the end of 7 sprint cycles. In phase 3, we used a convenience sample of adults (n=5) to gather user feedback through usability and acceptability testing. In phase 4, we further developed the platform based on user feedback, following the V-model software development process. Results: Our team consulted end users (ie, researchers) and utilized behavior change technique taxonomy and behavior change models (ie, the multi-process action control framework) to guide the development of features. The first version of the Pathverse platform included features that allowed researchers to (1) design customized multimedia app content (eg, interactive lessons), (2) set content delivery logic (eg, only show new lessons when completing the previous lesson), (3) implement customized participant surveys, (4) provide self-monitoring tools, (5) set personalized goals, and (6) customize app notifications. Usability and acceptability testing revealed that researchers found the platform easy to navigate and that the features were intuitive to use. Potential improvements include the ability to deliver adaptive interventions and add features such as community group chat. Conclusions: To our knowledge, Pathverse is the first no-code mHealth app design platform for developing mHealth interventions for behavior. We successfully used behavior change models and the behavior change technique taxonomy to inform the feature requirements of Pathverse. Overall, the use of a participatory framework, combined with the agile and hybrid-agile software development process, enabled our team to successfully develop the Pathverse platform. [ABSTRACT FROM AUTHOR]

The emergence of the novel SARS-CoV-2 and COVID-19 has brought into sharp focus the need for a vaccine to prevent this disease. Vaccines have saved millions of lives since their introduction to the public over 200 years ago. The potential for vaccination reached new heights in the mid-20th century with the development of technologies that expanded the ability to create novel vaccines. Since then, there has been continued technological advancement in vaccine development. The resulting platforms provide the promise for solutions for many infectious diseases, including those that have been with us for decades as well as those just now emerging. Each vaccine platform represents a different technology with a unique set of advantages and challenges, especially when considering manufacturing. Therefore, it is essential to understand each platform as a separate product and process with its specific quality considerations. This review outlines the relevant platforms for developing a vaccine for SARS-CoV-2 and discusses the advantages and disadvantages of each.

In biopharmaceutical process development time, cost and reliability are the relevant keywords. During the development of chromatographic processes these targets are challenged by many possible scaffolds, ligands and process parameters. The common response to this diversity is the establishment of platform processes in the development of chromatographic unit operations. However, while developing a platform library to simplify and accelerate chromatographic processes, the potential combination of scaffold, ligands and process parameters need to be characterized. This challenge is addressed in a case study on novel mixed mode (MM) adsorber for the removal of monoclonal antibody (mAb) aggregates. We propose a rigorous strategy to reduce the various experimental design space resulting from possible combinations in scaffolds, backbones and ligands. This strategy is based on theoretical considerations, identification of adsorber selectivity and capacity for the identification of a suitable membrane system. For this system, each potential MM membrane adsorber candidate is investigated in its high molecular weight species reduction potential for a given mAb feed stream and referenced to the performance of Capto™ Adhere. The introduced strategy can reduce the developmental effort in an early stage from three to two possible stationary phases. Thereafter, initial examinations at different ionic capacities enlighten one favorable stationary phase. Finalizing the development strategy procedure by studying five different MM ligands by HTS and confirming the study with a 2–3 MV higher dynamic breakthrough capacity in benchtop experiments and provides an insight in the benefits of a living process platform library. [ABSTRACT FROM AUTHOR]

There has been much debate around the role of metrics in scholarly communication, with particular focus on the misapplication of journal metrics, such as the impact factor in the assessment of research and researchers. Various initiatives have advocated for a change in this culture, including the Declaration on Research Assessment (DORA), which invites stakeholders throughout the scholarly communication ecosystem to sign up and show their support for practices designed to address the misuse of metrics. This case study provides an overview of the process undertaken by a large academic publisher (Taylor & Francis Group) in signing up to DORA and implementing some of its key practices in the hope that it will provide some guidance to others considering becoming a signatory. Our experience suggests that research, consultation and flexibility are crucial components of the process. Additionally, approaching signing with a project mindset versus a ‘sign and forget’ mentality can help organizations to understand the practical implications of signing, to anticipate and mitigate potential obstacles and to support cultural change.

There has been much debate around the role of metrics in scholarly communication, with particular focus on the misapplication of journal metrics, such as the impact factor in the assessment of research and researchers. Various initiatives have advocated for a change in this culture, including the Declaration on Research Assessment (DORA), which invites stakeholders throughout the scholarly communication ecosystem to sign up and show their support for practices designed to address the misuse of metrics. This case study provides an overview of the process undertaken by a large academic publisher (Taylor & Francis Group) in signing up to DORA and implementing some of its key practices in the hope that it will provide some guidance to others considering becoming a signatory. Our experience suggests that research, consultation and flexibility are crucial components of the process. Additionally, approaching signing with a project mindset versus a 'sign and forget' mentality can help organizations to understand the practical implications of signing, to anticipate and mitigate potential obstacles and to support cultural change. [ABSTRACT FROM AUTHOR]

The purpose of this study was to simulate crowdfunding in the technology entrepreneurship ecosystem in order to better understand this phenomenon. The research method is a qualitative-quantitative mixture based on the system dynamics method. For data collection, library studies, review of scientific literature, articles and specialized publications, and interviews with experts were used. Data analysis and analysis was done using the system's dynamics approach and using Vensim software. The results of the analysis of the data showed that the research model as well as the interactions of the effective variables in this regard, such as the role of government, investors, entrepreneurs and so on. Cash flows show a high sensitivity to changes in the number of investors (population) per unit. Increasing economic regulation also has many effects on the variables of sustainable entrepreneurship development and the development of crowdfunding platforms, in which the development of sustainable entrepreneurship is sharply increasing. And increasing investment will have a beneficial effect on strengthening innovation in centers of growth and technology and reducing government interference; changing the costs of promotion will increase the rate of promotion of crowdfunding in the 18th to 30th period and have a very good effect on tax cuts.

In this paper, we deal with the integration of the Theory of Documentational Approach to Didactics (DAD) with a design process, as a methodology for the construction of an artifact directed to teaching geometry online. The ADA provides theoretical support to guide the analysis of resource choices and production of teachers' documents and brings reflexive research as a methodological part to analyze the actions of the teacher in documentational genesis. Thus, following seven steps of a design process: define, research, ideate, prototype, select, implement, and learn, we relate design techniques to scientific research methods. Aiming to solve the difficulties of online teacher planning of geometry, we set up a methodological structure for the construction of a platform. The methodological structure was composed of the application of field research, problem mapping, question method, reflexive investigation, brainstorming and prototype. The methods were chosen according to the objectives of each of the seven stages of the design process. In a first analysis, it is possible to identify the potentialities of the integration of the ADA with design processes, to produce an artifact that assists teaching activities. [ABSTRACT FROM AUTHOR]

Copyright of Educação Matemática Pesquisa is the property of Pontificia Universidade Catolica de Sao Paulo, Programa de Estudos Pos-Grad. em Educacao Matematica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Modular system architectures in both product and manufacturing domains are of high interest in both academia and industry, as having modular product platforms and reconfigurable manufacturing systems are a key enabler for companies to obtain the strategic flexibility needed to respond to rapidly shifting market and customer requirements. Previous research has focused extensively on modularizing products and manufacturing equipment. However, to fully reap the benefits of modularization, this cannot be treated solely as engineering efforts taking place in one domain or cross domains with co-platforming, but rather as a top management initiative. The purpose of this research is to review state-of-the-art literature on modularization/platforming looking across managerial levels and business domains, market, product, and manufacturing. [ABSTRACT FROM AUTHOR]

Service robotics is currently being established alongside classic industrial robotics. Service robots can be adapted to new tasks with little effort. Nevertheless, there are still only a few service robotics applications in use. The development of the individual components leads to high costs for the users. Therefor the SeRoNet (Service Robotic Network) project addresses the development of a digital platform that brings together the various players in service robotics. In this paper relevant roles are identified, analysed in terms of their gains and losses and finally services are derived and clustered to ensure the successful market launch of the platform. [ABSTRACT FROM AUTHOR]

As products are being developed over time and across organisations, the risk for unintended accumulation and mis-conception of margins allocated may occur. Accumulation of margins can result in over design, but also add risk due to under allocation. This paper describes the different terminology used in one organisation and shows the different roles margins play across the design process and in particular the how margins are a critical but often overlooked aspect of product platform design. The research was conducted in close collaboration with a truck manufacturer between 2013 and 2018. The objective was to gain understanding of the current use of margins, and associated concepts evolve along the product life cycle, across organisation and product platform representations. It was found that margins already play an important role throughout the entire design process; however, it is not recognised as a unified concept which is clearly communicated and tracked throughout the design process. Rather different stakeholders have different notions of margins and do not disclose the rationale behind adding margins or the amount that they have added. Margins also enabled designers to avoid design changes as existing components and systems can accommodate new requirements and thereby saving significant design time.

Aerial spraying using UAV has gained great interest worldwide. UAV spraying can overcome crop height limits and is unlikely to crust soil or damage crop plants. More experiments concerning spraying are needed, such as spraying method tests, spraying droplet analysis, variable rating spraying tests, etc. These experiments either take a long time for real flights or have an unrecognized danger to UAV in real flights. To address this problem, an indoor spraying platform, which consists of X-Y direction movement and wind field generation was developed to simulate UAV aerial spraying. The maximum moving speed in the horizontal direction was 3.5 m/s and 0.25 m/s in the vertical direction. The horizontal moving distance was 11 m and the vertical moving distance was 0.5 m. The platform consists of 4 parts: upper machine software, central controller, X-Y moving part and far end spraying structure. CAN bus was used for communication between the central control board and far end controller. An experiment was carried out to test how the platform performs with different moving speeds and different wind strength. The wind strength test shows that wind forces the deposit down to the ground when droplets were equally affected by 2 wind forces. The result shows that the platform can meet the requirement of UAV aerial spraying. [ABSTRACT FROM AUTHOR]