Scientific Research Infrastructure Research Articles

Physical activity at diagnosis is associated with tumor downstaging after neoadjuvant chemoradiotherapy in patients with rectal cancer

BackgroundPatients with rectal cancer are often treated with neoadjuvant chemoradiotherapy, followed by a waiting period and surgical resection. Good or complete response to neoadjuvant chemoradiotherapy might enable organ preservation, which highlights the need to increase response rates. Pre-clinical studies suggest that physical activity during neoadjuvant chemoradiotherapy may improve tumor downstaging. PurposeTo investigate whether physical activity and physical functioning of patients with rectal cancer at diagnosis are associated with tumor downstaging after neoadjuvant chemoradiotherapy. Materials and methodsPatients were included if they participated in the Dutch Prospective ColoRectal Cancer Cohort, a nationwide cohort providing an infrastructure for scientific research, and received neoadjuvant chemoradiotherapy for rectal cancer. Tumor downstaging was dichotomized into good/complete or moderate/poor downstaging. Physical activity (total physical activity, moderate-to-vigorous physical activity (MVPA), and Dutch physical activity guideline adherence) and physical functioning were assessed using questionnaires. Logistic regression analyses were performed to examine associations of physical activity and physical functioning with tumor downstaging, adjusted for relevant confounders. Results268 patients (aged 62 ± 11 years, 33 % female) with rectal cancer were included. Patients with moderate (OR = 2.07; 95%CI = 1.07 – 4.07; p = 0.03) or high (OR = 2.05; 95%CI = 1.05 – 4.07; p = 0.04) levels of MVPA were more likely to have good/complete tumor downstaging than patients with low levels. No significant associations with tumor downstaging were found for total physical activity, Dutch physical activity guideline adherence, and physical functioning. ConclusionsWe found augmented tumor downstaging in patients with rectal cancer with moderate or high levels of self-reported MVPA before the start of neoadjuvant chemoradiotherapy compared to patients with low levels.

Concept and challenges of a social media observatory as a DIY research infrastructure

This article describes the basic concept, ethical and legal considerations, technical implementation as well as resulting tools and data collections of the Social Media Observatory (SMO). Since 2020, the SMO is developed as an open science research infrastructure within the Research Institute Social Cohesion (RISC) in Germany. It focuses on (the support of) long-term monitoring of public communication on selected platforms and online news media to answer social science-related research questions. Based on systematically compiled lists of public speaker categories, such as parliamentarians or media organizations, it collects statistics as well as content data to study the German social media discourse in comparison to mass media. Aggregated results are published via interactive dashboards. Raw data is published as ID lists for reproduction or shared with researchers upon request. Following a do-it-yourself approach to infrastructure, the SMO further provides various tools, curated datasets, and documented workflows, for instance, to run thematic ad-hoc data collections. As a main feature, it maintains a curated knowledge base in wiki format to enable other researchers to perform systematic social media observations on their own.

Technology transfer from procurement relationships in big science contexts

Big Science is a fertile learning environment for the transfer of knowledge and technology to suppliers since it boosts economic performance, innovation and reputation. However, despite the growing importance of this topic in the literature, empirical evidence is still limited. This paper investigates technology transfer from Big Science through procurement relationships related to the need to develop front-end technologies for Big Science research infrastructures. The results show that the benefits generated for companies include intangible dimensions, such as the acquisition of technical knowledge and improved reputation. In addition, this procurement relationship leads to organizational changes such as the introduction of new specific organizational units and improved investment in R&D. In turn companies are able enter new markets thanks to the newly acquired competencies.

An iterative and interdisciplinary categorisation process towards FAIRer digital resources for sensitive life-sciences data

For life science infrastructures, sensitive data generate an additional layer of complexity. Cross-domain categorisation and discovery of digital resources related to sensitive data presents major interoperability challenges. To support this FAIRification process, a toolbox demonstrator aiming at support for discovery of digital objects related to sensitive data (e.g., regulations, guidelines, best practice, tools) has been developed. The toolbox is based upon a categorisation system developed and harmonised across a cluster of 6 life science research infrastructures. Three different versions were built, tested by subsequent pilot studies, finally leading to a system with 7 main categories (sensitive data type, resource type, research field, data type, stage in data sharing life cycle, geographical scope, specific topics). 109 resources attached with the tags in pilot study 3 were used as the initial content for the toolbox demonstrator, a software tool allowing searching of digital objects linked to sensitive data with filtering based upon the categorisation system. Important next steps are a broad evaluation of the usability and user-friendliness of the toolbox, extension to more resources, broader adoption by different life-science communities, and a long-term vision for maintenance and sustainability.

Investment monitoring key points identification model of big science research infrastructures -- Fuzzy BWM-entropy-PROMETHEE Ⅱ method

With the gradual development of science and technology, more and more countries regard big science research infrastructures (BSRIs) as the top priority in national development. However, the problem of out-of-control investment often occurs in the construction process of BSRIs, which leads to the loss of property and government credibility. Therefore, this paper carries out research on investment monitoring of BSRIs. The price of the contract signed in the process of engineering construction is taken as the investment monitoring point. And the investment monitoring key points are selected considering the monitoring cost. A three - stage index system of investment monitoring key points from the perspective of project life cycle is established. The generalized trapezoidal fuzzy number is used to describe the evaluation information. The entropy method and best-worst method are used to calculate the objective and subjective weights of indexes respectively. PROMETHEE Ⅱ is applied to rank alternative monitoring points. Finally, empirical research is carried out to verify the effectiveness and stability of the model. The comprehensive weights of contract amount, contractor performance, and adjacent contract payment unit investment amount are 28.83%, 18.81% and 15.05% respectively, which are the three most important indicators in the implementation stage.

China’s higher education development evaluation based on GA-BP neural network

The development of higher education supplies a large number of high-level talents to the society, which is the key to building a harmonious society. At present, the development of regional higher education is extremely uneven, and it is the top priority of education development that it is urgent to clarify the situation of regional higher education. This article constructs a comprehensive evaluation index system of higher education development from a total of 19 indicators from five dimensions of talent training, teacher strength, scientific research output, infrastructure and social services, and then uses entropy and genetic algorithm-projection pursuit model to calculate the weight. GA-BP and BP neural network models are used for comprehensive evaluation. It is found that: (1) The most important factors affecting the development of higher education are technology transfer income and the application of R&D achievements in colleges and universities; (2) Compared with BP neural network, GA optimizes BP neural network in terms of effectiveness, convergence speed, and accuracy. (3) Generally speaking, during the research period, the development of China’s higher education has gradually improved, with an average annual growth rate of 3.5%. In terms of sub-regions, the provinces with excellent higher education development levels have increased from 0 in 2008. The number has increased to 5 in 2019, and the development of higher education among provinces is extremely uneven, and the differences between provinces are gradually increasing.

Euro-BioImaging – Interdisciplinary research infrastructure bringing together communities and imaging facilities to support excellent research

Euro-BioImaging – Interdisciplinary research infrastructure bringing together communities and imaging facilities to support excellent research

Pesquisa em educação e comunicação em ciências: contribuições do programa Biota-Fapesp para a educação em biodiversidade

Abstract In this article, we aim to understand the contributions of the Biota-Fapesp Program to the research in biodiversity education and communication. Our research questions are: (i) is the Biota-Fapesp Program following or contributing to the significant advances in conceptual, technological/methodological, and management/governance aspects of biodiversity education/communication research?; (ii) if yes, how do the projects contribute to these advances?; and (iii) what are the main expectations for the future of Biota in education and communication research? Our analyzes highlighted a qualitative contribution from the Biota-Fapesp Program at institutional, methodological, conceptual, and educational levels. However, due to the few projects, it can be considered a summative contribution and not a transformative one. Perspectives for the Biota-Fapesp Program in these areas were divided into three approaches: 1. Research lines and concepts that could be encouraged through specific calls or inclusion in other calls of interest to the Program; 2. Innovative methodological approaches for the area that should be encouraged; 3. Suggestions for scientific research management and infrastructure. Through data and discussions presented below, we hope to contribute to the understanding of the role of Biota-Fapesp in the area, and point out ways to develop research, practices and public policies that promote the strengthening of science as culture.

Looking Back, Looking Forward: What to do with Philippine Agriculture

Compared with our ASEAN neighbors against whom we usually benchmark ourselves, the Philippines is making the least progress in providing a better life for its people. While they have significantly brought their poverty rates down, poverty among Filipinos has persisted at a painfully embarrassing rate of 26%, most of that poverty is found in the countryside, among farmers and fisherfolk. The 1.7% rate of growth of agriculture, which does not even match our population growth during the last five years (2011-2015), is symptomatic of this malaise, yet the ingredients to make agriculture move forward and be more productive, competitive, sustainable, and economically rewarding to our millions of small farmers and fisherfolk are largely in place. Our moderate tropical environment and rainfall with irrigation make year-round growing possible. Our vast and carefully-managed fisheries resources should provide a sustainable supply of affordable and quality animal proteins in our diets. We have a fairly educated workforce and a modest but working higher education and scientific research infrastructure in agriculture. We have an established and increasingly competitive food and beverage manufacturing subsector. Progressive legislations are in place with the Agriculture and Fisheries Modernization Act (AFMA) of 1997 and the Fisheries Code of 1998, and a palpable improving political will to support agriculture is established, as manifested by the expanding congressional appropriations for the Department of Agriculture (DA). What should we do with agriculture in 2016 and beyond to move it forward? Beyond generalities, what do we specifically want to see done by the government and those with a stake in agriculture to help farmers and fisherfolk attain a better standard of living for themselves, for all of us, now and in the future? There is no single magic bullet that will cure all the ills of Philippine agriculture. We need to come together, marshal, and direct our resources along four major platforms of reform, namely (a) reform the bureaucracy of the Department of Agriculture; (b) meaningful participation of stakeholders in the governance of agriculture; (c) continuing investments in rural institutions and infrastructure; and (d) closure on a few important but contentious issues such as a rice-centric agriculture.

Ex‐ante socio‐economic impact assessment for a social science research infrastructure: The case of EuroCohort

ABSTRACTThe aim of this paper is to present the ex ante Socio‐Economic Impact Assessment of a European Social Science Research Infrastructure (RI) named EuroCohort that will provide, over the next 34 years, a longitudinal study of the well‐being of children and young people across Europe.

Systematizing serendipity for big science infrastructures: The ATTRACT project

Big Science Research Infrastructures (BSRIs) are tremendous sources of ‘deep-tech’ with the potential to foment alternative commercial applications in diverse industries. Yet, cultivating novel applications of BSRI technologies is not straightforward due to misalignment between their scientific mission, large technological risks, market uncertainties, and long development times. Given these challenges, research is needed to understand if- and how-serendipitous innovations can be purposefully developed from BSRIs. In this study, we analyse ATTRACT, a novel initiative funded by the European Commission's Horizon 2020 program, which funded 170 projects with €100,000 each to develop a proof-of-concept commercial application of BSRI technologies within one year. Our analysis of this dataset identifies three modes employed by researchers to come up with alternate applications: (1) combining different technologies, (2) applying technology into a different field, and (3) using artificial intelligence or machine learning. In a second step, we conducted multinomial logistic regressions using the project data, expert evaluations, and a questionnaire to identify the antecedents associated with the pursuit of each of the three modes. Our findings suggest that scientists and engineers develop many new ideas about novel potential applications of BSRI technologies in their daily work. The main value of ATTRACT is in facilitating project development through financial resources, brokering relationships with industrial partners, and facilitating the applications of technologies in domains outside of the immediate purview of BSRIs.

Exploration of an integrated competency development model for undergraduates training by participating the international Genetic Engineering Machine Competition

Starting from participating the high-level professional competition, our school has built a talent training system with the spirit of "biomaker" and an innovative practical ability training system. Such system takes the interest of student as the starting point, and relies on the strong scientific research and teaching infrastructure. The programme gives full play to students' initiatives and enhances the scientific research literacy and comprehensive ability of undergraduates majoring in biotechnology. It is an effective exploration of the traditional university education model and meets the urgent demand for innovative talents training in the era of rapid development of life sciences.

The Prospective Dutch Colorectal Cancer (PLCRC) cohort: real-world data facilitating research and clinical care

Real-world data (RWD) sources are important to advance clinical oncology research and evaluate treatments in daily practice. Since 2013, the Prospective Dutch Colorectal Cancer (PLCRC) cohort, linked to the Netherlands Cancer Registry, serves as an infrastructure for scientific research collecting additional patient-reported outcomes (PRO) and biospecimens. Here we report on cohort developments and investigate to what extent PLCRC reflects the “real-world”. Clinical and demographic characteristics of PLCRC participants were compared with the general Dutch CRC population (n = 74,692, Dutch-ref). To study representativeness, standardized differences between PLCRC and Dutch-ref were calculated, and logistic regression models were evaluated on their ability to distinguish cohort participants from the Dutch-ref (AU-ROC 0.5 = preferred, implying participation independent of patient characteristics). Stratified analyses by stage and time-period (2013–2016 and 2017–Aug 2019) were performed to study the evolution towards RWD. In August 2019, 5744 patients were enrolled. Enrollment increased steeply, from 129 participants (1 hospital) in 2013 to 2136 (50 of 75 Dutch hospitals) in 2018. Low AU-ROC (0.65, 95% CI: 0.64–0.65) indicates limited ability to distinguish cohort participants from the Dutch-ref. Characteristics that remained imbalanced in the period 2017–Aug’19 compared with the Dutch-ref were age (65.0 years in PLCRC, 69.3 in the Dutch-ref) and tumor stage (40% stage-III in PLCRC, 30% in the Dutch-ref). PLCRC approaches to represent the Dutch CRC population and will ultimately meet the current demand for high-quality RWD. Efforts are ongoing to improve multidisciplinary recruitment which will further enhance PLCRC’s representativeness and its contribution to a learning healthcare system.

Design and Analysis of Mechatronic Systems for Autonomous Underwater Exploration

The design and analysis of mechatronic systems for autonomous underwater exploration play a crucial role in advancing the capabilities of underwater robotic platforms. This abstract presents a comprehensive overview of the research conducted on the design and analysis of mechatronic systems for autonomous underwater exploration. The objective of this research is to enhance the performance, efficiency, and reliability of underwater robotic systems in order to enable effective and efficient exploration of the underwater environment.Mechatronic systems for autonomous underwater exploration require a multidisciplinary approach that integrates mechanical, electrical, and software engineering principles. This research focuses on the design and analysis of these integrated systems, addressing challenges such as robustness, adaptability, power management, and control mechanisms. The design and analysis of mechatronic systems for autonomous underwater exploration present a multidisciplinary research area that combines mechanical, electrical, and software engineering principles. This research aims to enhance the performance, efficiency, and reliability of underwater robotic platforms by addressing challenges related to design, analysis, control, power management, and sensor integration. The findings from this research will contribute to the advancement of autonomous underwater exploration, enabling better understanding and utilization of the underwater environment for various applications, including scientific research, environmental monitoring, and underwater infrastructure inspection.

Computing infrastructure for scientific research in a digital transformation

The article discusses the main aspects of the importance of developing a high-performance environment for scientific research in the context of digital transformation. Some historical facts are presented that testify to the role played by the Soviet scientists in the development of this sphere. An analysis of the experience of the FRC CSC RAS in the creation of a modern high-performance platform and its use for scientific research is given.

Preserving US microbe collections sparks future discoveries.

SummaryCollections of micro‐organisms are a crucial element of life science research infrastructure but are vulnerable to loss and damage caused by natural or man‐made disasters, the untimely death or retirement of personnel, or the loss of research funding. Preservation of biological collections has risen in priority due to a new appreciation for discoveries linked to preserved specimens, emerging hurdles to international collecting and decreased funding for new collecting. While many historic collections have been lost, several have been preserved, some with dramatic rescue stories. Rescued microbes have been used for discoveries in areas of health, biotechnology and basic life science. Suggestions for long‐term planning for microbial stocks are listed, as well as inducements for long‐term preservation.

Coronavirus diseases 2019 (COVID-19) response: Highlights of Ghana's scientific and technological innovativeness and breakthroughs

While more attention has been placed on scientific innovativeness and breakthroughs in the advanced countries’ attempt to contain the spread and develop vaccines for the Coronavirus Diseases 2019 (COVID-19), little attention has been paid to the few but significant innovations being achieved in some African countries. This is understandable because the scientific capacity and research infrastructure of most African countries are deficient and weak compared to other regions of the world. Nevertheless, the African country of Ghana, despite its acute healthcare and scientific infrastructure deficit, is achieving some innovational and scientific breakthrough in the COVID-19 fight. Ghanaian scientist was among the first in Africa to successfully sequenced the genome of the novel coronavirus (SARS-CoV-2). The country's laboratory leading the fight has also introduced some innovative testing methods allowing the country to test a far greater scale per million than the rest of Africa. Besides, drones are being used to deliver samples to the laboratory centers for testing. Local scientists and developers have also developed rapid diagnostic test kits, ventilators, and solar-powered handwashing machines. This paper highlights Ghana's innovativeness, scientific, and technological breakthroughs achieved so far in the fight against the pandemic.

The First Very Broadband Mediterranean Network: 30 Yr of Data and Seismological Research

Abstract Starting in 1988, with the installation of the first broadband (BB) instrument in Italy, the Mediterranean Very Broadband Seismographic Network (MedNet) program established a backbone network of BB stations of the highest quality in the Mediterranean Sea countries. The Mediterranean region is characterized by relevant and frequent seismicity related to its complex tectonics, due to the convergence of two major plates, Africa and Eurasia, and the involvement of other minor plates, as the Adriatic plate. Therefore, the MedNet project became a scientific research infrastructure of excellence, able to fill the gap of regional coverage when the availability of seismic BB instruments was still scarce. The main characteristics of the MedNet network are the highest quality of the seismographic instrumentation at remote sites and very low level of anthropogenic noise with stable conditions of pressure and temperature. After 30 yr of recordings, the MedNet program has proven that the early adoption of very BB instruments in selected sites have been the best choice. A large number of studies benefited from MedNet data, as seismic source computation and Earth structure reconstruction, at local and global scale. We present a concise overview of the contribution given by MedNet data in the last three decades to motivate and financially support the existence of this valuable infrastructure, and to further maintain this project.

Systematising Serendipity for Big Science Infrastructures: the ATTRACT Project

The potential of big science research infrastructures to make contributions far beyond their scientific purview has long been acknowledged. However, less consensus exists about the specific mechanisms with which such value can realised. This paper describes the ATTRACT project. A novel approach funded with €20 million by the European Commission Horizon 2020 programme, ATTRACT represents a consortium of leading European scientific centres, academic institutions, and industry associations formed to harness their world-class scientific instrumentation technologies towards entrepreneurship within European economies. ATTRACT will award 170 projects centred on breakthrough imaging and detection technologies €100,000 each to develop a proof-of-concept within one year. With the goal of scaling a select few of the most promising projects, ATTRACT will facilitate additional iterations of public and private funding along with relevant commercial and legal support to bridge the gap between supply-push and demand-pull innovation policy instruments. The paper describes the ATTRACT project: its motivation, philosophy, design, and results to date.

STUDY OF TIMELINE AND PROFILE BASED SCHEDULING IN GRID ENVIRONMENT – A SCOPE TO IMPROVE CLOUD SCHEDULING.

The word grid computing is originated from a new computing infrastructure for scientific research in various areas. Cloud is the commercial version of grid. There are various challenges in Grid computing which are applicable in cloud also. The main challenges are resource management, job scheduling, security problems, fault tolerance, virtualisation etc. In the above current research challenges, job scheduling is the fundamental issue in achieving high performance in grid and cloud computing systems. However, it is a big challenge for efficient scheduling algorithm design and implementation. In scheduling algorithms, some are cost effective and some others are performance based. CPU intensive problems are very much increased and the research on effective scheduling is going deeply and widely. In this scenario, the scheduling problem is very interesting and this is the perfect time to develop a new scheduling strategy. The computing power in the grid is scattered around the globe. Any resource owner can put his own cost and other several policies for renting his resource. In such an environment the scheduling will be difficult and price variant. So developing an optimum scheduling algorithm with optimised cost and reduced waiting time is always better than an optimum duration or time based approach. Utilising the resources effectively in a minimum amount of cost and waiting time of jobs are always a better approach. The profile based selection is another approach in grid. In this paper we discusses two algorithms developed by us. We also portraits the possibilities of the same in cloud environment.