Clean Space Research Articles

A Process Evaluation Approach to Central Line-Associated Bloodstream Infection Reduction in a Neonatal Population.

To reduce the rate of central line-associated bloodstream infections (CLABSI) in the M Health Fairview Neonatal Intensive Care Unit (NICU) from 2.15 infections per 1,000 central line days to less than one per 1,000 line days using process evaluation. An interdisciplinary team used process mapping and Failure Modes and Effects Analysis (FMEA) to identify root causes and improvement opportunities in central line maintenance. The focus was on neonates born at <32 weeks of gestational age and weighing less than 750 g. Interventions included standardized clean space, algorithms to reduce line access, and standardized kits for line maintenance. Over 4years, the project achieved an 86.6% reduction in CLABSI events, decreasing from 15 events in 2019 to two in 2023. The CLABSI rate dropped by 85%, from 2.15 to 0.32 per 1,000 line days. Statistical analysis indicated a significant reduction in FMEA risk scores for the identified failure modes, with an average reduction of 33%. The process-focused approach and interdisciplinary collaboration significantly reduced CLABSI rates in the NICU. Future efforts should aim to maintain these improvements and achieve a target of zero CLABSI events.

Performance extrapolation of an ultraviolet-based photocatalytic air purifier against near-ambient-level formaldehyde

The practical utility of an air purifier (AP) with built-in adsorbent/catalyst-based filtration systems is assessed for the treatment of indoor volatile organic compounds (VOCs) through extrapolation of its performance based on a lab-scale chamber study. The feasibility of a commercial prototype AP unit with TiO2-based filters is tested in this work against 0.5–5 ppm formaldehyde (FA) in a 17 L chamber with an air recirculation rate of 565 h−1 under the control of key process variables (e.g., initial FA concentration, flow rate, and dark/light conditions). The performance of the AP unit is evaluated by the clean air delivery rate (CADR), quantum yield, and space time yield in diverse operation settings (e.g., photocatalysis only or along with adsorption). The effects of ultraviolet (UV) irradiation are evident as the CADR value of 5 ppm FA sharply increases from 5.67 (UV-off) to 15 L/min (UV-on): however, the CADR values increase only slightly (12 to 15 L/min) as the recirculation flow rate changes from 100 to 160 L/min, respectively. Further, FA concentration vs. time relationship exhibit an apparent bimodal exponential decay, with the fastest and near 100 % removal at [FA] < 0.5 ppm. The performance of the proposed AP platform in relatively large real-world volume (e.g., 4 m3, 2.4 h−1 air recirculation rate) is further estimated through extrapolation to offer valuable guidelines for the construction of AP systems in real-world applications.

Deep embedding based tensor incomplete multi-view clustering

The majority of multi-view data are extracted from real life, which often lose information in some views. To solve this problem, existing incomplete multi-view clustering algorithms explore the valuable information from incomplete data while populating the missing information. Nevertheless, they suffer from the following two limitations: 1) The non-linear relationships of high-dimensional available data are not considered. 2) Although some methods utilize information from different views to fill in missing information, they still cannot precisely explore the missing information of each view. To this end, this article proposes a novel one-step incomplete multi-view framework, referred to as deep embedding based tensor incomplete multi-view clustering (DETIMC). Concretely, in this framework, the high-dimensional available data are projected into the low-dimensional embedding space by deep non-negative matrix factorization (NMF), which can obtain a clean space while capturing the complex non-linear relationship of available data. Moreover, a novel double-enhanced missing-view inferring strategy is developed, in which the weighted higher-order information of different views and the clustering structure information are simultaneously exploited. Comprehensive experiments on several benchmark datasets exhibit the superiority of DETIMC over conventional and state-of-the-art algorithms.

International Law Review Of Space Debris Mitigation Efforts

Space debris has become an increasingly pressing issue in space exploration and utilization. This article conducts a comprehensive review of aspects of international law relating to space debris mitigation efforts. This research analyzes existing legal frameworks, including relevant multilateral treaties and international legal principles related to the space environment. With a focus on the principles of shared responsibility and avoidance of damage to the space environment, the study identifies key challenges in managing space junk and reducing the risk of collisions in earth orbit. An in-depth analysis of the role of national space agencies and international organizations in implementing mitigation measures was also carried out. In the context of international cooperation, this article evaluates existing collaborative efforts and proposes new measures to improve the effectiveness of space debris mitigation. A better understanding of legal responsibility and burden-sharing in addressing these issues became a central point in the study. By analyzing recent developments in space law and international environmental regulations, this article provides insight into the direction the global community might take in addressing future space debris mitigation challenges. It is hoped that this research can provide guidance for policymakers, academics, and legal practitioners in their efforts to maintain a clean and sustainable space environment.

Dynamic Graph Regularized Broad Learning With Marginal Fisher Representation for Noisy Data Classification.

Broad learning system (BLS) is an effective neural network requiring no deep architecture, however it is somehow fragile to noisy data. The previous robust broad models directly map features from the raw data, which inevitably learn useless or even harmful features for data representation when the inputs are corrupted by noise and outliers. To address this concern, a discriminative and robust network named as dynamic graph regularized broad learning (DGBL) with marginal fisher representation is proposed for noisy data classification. Different from the previous works, DGBL eliminates the effect of noise before the random feature mapping by the proposed robust and dynamic marginal fisher analysis (RDMFA) algorithm. The RDMFA is able to extract more robust and informative representations for classification from the latent clean data space with dynamically generated graphs. Furthermore, the dynamic graphs learned from RDMFA are incorporated as regularization terms into the objective of DGBL to enhance the discrimination capacity of the proposed network. Extensive quantitative and qualitative experiments conducted on numerous benchmark datasets demonstrate the superiority of the proposed model compared to several state-of-the-art methods.

Re‐entry safety: Analysis and plasma wind tunnel testing of spacecraft design solutions to reduce on‐ground casualty risk

In compliance with ISO 24,113 and ESA Space Debris Mitigation requirements, spacecrafts in Low Earth Orbit (LEO) must be removed from their operational orbit within 25 years and re-enter the Earth's atmosphere having an on-ground casualty risk lower than 1 in 10,000.To maximize the number of uncontrolled re-entries, which have much less impact on system mass and costs, ESA's Clean Space initiative is investigating design for containment (D4C) techniques and collaborating with European industries and space agencies to assess, model, analyse, and test new concepts through re-entry tools and plasma wind tunnel experiments. The main objectives are to understand the survivability of materials and techniques suitable for different containment concepts, to improve re-entry modelling, and implement effective D4C measures.This paper shows the results of these activities, that have been the first milestones in the knowledge of D4C, although further investigations are needed.

Planning Hatvan: Urban Planning and Repression in One of Baia Mare’s Roma Neighbourhoods (1950-1989)

Abstract This paper starts from the premise that social space, the state space, is a socially productive territory characterized, among other things, by hierarchical social, economic and political relations. This hierarchical dimension of space comes to the fore when researching the urban marginalization of Roma people in Romania. The mechanisms of exclusion employed by the state against Roma groups are situated in a wide range of other policies, among which uneven territorial development ranks chief. As such, this paper seeks to analyse the junction between these processes. It asks the question: how did the process of urban planning reinforce the urban marginalization of Roma people during socialism in Baia Mare? In order to address this question, I mobilize the results of two years of archival research in the city of Baia Mare, coupled with the discursive analysis of this archival material. I perform a diachronic analysis of how Roma people were targeted by state practices of urban marginalization, such as stigmatization, criminalization and repression. I show how the policies of systematisation of Baia Mare shaped the territory of a particular neighbourhood – Hatvan, attempting to manage and control the Roma population there. Throughout the 1960s, Hatvan was considered a focal point for crime. This led to a large-scale plan to completely transform the area through evictions, demolitions and the displacement of Roma people. The result was a place that was seen as clean, ordered and lawful social space, which became what is currently known as the Vasile Alecsandri neighbourhood. However, this space continues to this day to be one of social marginalisation, economic deprivation and institutionalised racism.

Enhancing the hospital at home experience

Background Hospital at Home programs have demonstrated to be safe, feasible and cost effective. However, challenges such as infection control, cleanliness, space constraints and insufficient resources may hamper the adoption and effectiveness of such programs. Aims To understand the challenges of providing and receiving healthcare in the community, design a solution to meet the challenges, and to pilot and evaluate the solution. Methods This is a three-phase mixed method study. Phase 1, nurses, patients and caregivers were surveyed to understand their challenges in providing or receiving healthcare at home. Results of the survey in Phase 1 were used in Phase 2 to design a solution. In phase 3, an integrated structure was designed and piloted for stakeholders’ evaluation. Results Twenty nurses and 50 patient-caregiver dyads responded to Phase 1 survey. Physical home environment was most cited by the nurses as their main challenge, particularly the lack of a dedicated and clean space to conduct nursing procedures. Medication management was the greatest challenge faced by the patient-caregiver dyads. Based on these findings, a prototype of an integrated structure was fabricated in Phase 2. Ten patient-caregiver dyads and nine community nurses tested the prototype in Phase 3. The participants found the structure useful to store and organize their healthcare items, and there was ample clean workspace to carry out nursing procedures. Conclusion An integrated structure that can fulfil the physical, spatial and interpersonal needs at an affordable price could be useful in facilitating the delivery of hospital care in the home setting. Patient Contribution Patient-caregiver dyads were key stakeholders in our study. They provided valuable feedback and suggestions on the prototype and design of the integrated structure.

The Effect of Spatial Production in Hair Salons on Customer’s Revisit Intention and Word-of-Mouth Intention

The purpose of this study is to provide more practical basic data for hair salon marketing strategies by examining the effect of spatial production in hair salons on customer’s revisit intention and word-of-mouth intention. As a result, it was found that only the cleanliness factor of spatial production had a significant positive effect on the customer's revisit intention, and the cleanliness and differentiation factor of spatial production had a significant positive effect on the customer's word-of-mouth intention. Specific improvements in cleanliness and differentiation are as follows in order to promote revisit and word-of-mouth of beauty salon customers. First, in order to secure regular customers, the priority should be to create a clean space, and in the case of already existing hair salons, the revisit rate of existing customers can be increased by cleanly managing the space where the customer directly exists. Second, in order to attract new customers, it is believed that the effect of creating new customers through word-of-mouth can be increased by focusing on cleanliness as previously mentioned, and by using the brand's representative color so that customers can experience the brand's unique sensibility in the salon space. This study is meaningful because previous research on beauty salon space was insignificant, and it suggests that more attention should be paid to the cleanliness and differentiation of beauty salon space to revisit customers and attract new customers. However, in this study, several items that hinder reliability in relation to functionality were deleted, and in future studies, it is considered necessary to further revise and supplement functionality-related items so that the constituent concepts of spatial performance can be evaluated more closely.

The effects of a shock to critical minerals prices on the world oil price and inflation

Critical minerals (CMs) such as lithium, cobalt, nickel, and rare earth metals, are essential to the development of clean energy technologies, electronics, and defense and space industries, among others. Demand for these minerals is expected to grow quickly as energy transitions accelerate. As the post-pandemic economic recovery demonstrated, disturbances in CM supplies can also create serious bottlenecks in global supply-chains. In this study, we develop a GVAR model that can examine the consequences of market disturbances from CM price shocks on major global and country-specific macroeconomic indicators. Counterfactual simulations of a CM price shock suggest that that CMs, as a rising industry, are starting to have an impact on the macro level. The industry and its impacts are not fully developed yet but appear to have diverse implications across countries similar in some respects to the current major commodity – oil. A CM price shock has statistically significant implications for inflation in the UK and South Korea. At the same time, geopolitical shocks to crude oil prices have significant implications for CM prices. The cross-price elasticity of oil with respect to CM prices is positive in the United States, where CM's and oil are substitutes, and negative for Saudi Arabia where CMs and oil are compliments. These scenarios indicate the unsuitability of a one size fits all energy policy and a need for closer examination of the national and country specific relationships between the oil and CM sectors.

CO2 system integrated with ejector and mechanical subcooling: A comprehensive assessment

To achieve the goal of clean annual space heating and cooling for residential buildings, the concept of annual space heating and cooling transcritical CO2 system combined with ejector and mechanical subcooling is proposed. The problem of large throttling loss and performance degradation when CO2 system is applied for residential space heating and cooling can be solved. A theoretical model of the new proposed system is developed, and then optimized by the method of genetic algorithm. Moreover, taking an ordinary residential building located in 70 cities belonging to different climate zones as the application scenario, the seasonal, annual, environmental, and economic performance of eight heating and cooling solutions are compared and discussed. The results indicate that the COP and exergy efficiency of the new proposed system is significantly improved in contrast to conventional mechanical subcooling system, which increases by 11.48% and 21.64% in heating mode, and 8.99% and 8.69% in cooling mode, respectively. The annual performance coefficient of the new proposed system is 7.21%∼8.21% higher than conventional mechanical subcooling system. Additionally, the life cycle carbon emissions of the new proposed system can be significantly reduced by 12.23%∼89.58% compared with the combined solution of coal-fired boiler and R32. With the advancement of CO2 technology, it is possible to improve the economic performance of CO2 systems and the price of the new proposed system is lower than all solutions when the price of compressor is reduced by 60%. This study can provide a theoretical reference for the development and optimization of CO2 combined heating and cooling system, and provide a feasible solution for residential annual space heating and cooling.

Preface

The 15th International Symposium on Materials in the Space Environment (ISMSE) and 13th International Conference on Protection of Materials and Structures from the Space Environment (ICPMSE) took place 18-23 September 2022 in a special venue, the Naturalis Biodiversity Center in the beautiful city of Leiden (the Netherlands). This joint conference was attended by about 210 participants from 25 different countries worldwide.We are now happy to present to you the final version of the conference proceedings. This unique collection includes 42 original scientific papers in a variety of fields, including:• Contamination modelling, applications and monitoring,• Low / Very low Earth orbit (LEO/VLEO),• Lunar environment and dust,• Clean Space and sustainability,• Flight experiments,• Radiation and synergistic effects,• Innovative materials and processes,• Ground facilities and testing,• Long-term storage.The papers reflect well the topics discussed during the conference.To maintain the high quality of the papers, we used a single-blind peer-review process, established within the framework of the Morresier platform provided by IOP. Moreover, all papers are now assigned DOIs and published open access online by IOP.The papers resulted from at least 4 years of work since the last ISMSE conference. Some authors are contributing to several papers as they actively work in several research subgroups and supervise multiple student projects. In each case all authors have contributed to all mandatory aspects: substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; and drafting the work or revising it critically for important intellectual content; and final approval of the version to be published; agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.We hope you find the proceedings informative and we look forward to more exciting high-quality research publications in the future as part of the forthcoming ISMSE-16/ICPMSE-14 event.ISMSE Proceedings Editorial Board:Malgorzata Holynska (Chair, ESA/ESTEC)Adrian Tighe (ESA/ESTEC)Elisabeth Laurent (CNES)Jacob Kleiman (ITL INC)Sophie Duzellier (ONERA)Timothy Minton (University of Colorado Boulder)

LANGUAGE REPRESENTATION OF SPACE (BASED ON THE MATERIAL OF THE TEXTS OF UKRAINIAN SPELLS)

The purpose of the article is to study the linguistic representation of space in the texts of Ukrainian folk spells. To achieve the goal we are to fulfill the following tasks: to define a vocabulary for the designation of spatial concepts, which presents consecrated (clean) and profane (impure) space; analyze traditional formulas that denote space; to describe the linguistic means by which the limitlessness, dynamism, and mobility of space are expressed in the texts of Ukrainian spells. We present examples of Ukrainian spells in the forms in which they occur in the studied texts. So, in the texts of Ukrainian folk spells, we can see the functioning of a consecrated (clean) and a profane (impure) space, the reflections of which are reflected in the vocabulary to designate spatial concepts. Mobility, dynamism of space is conveyed by verbs of motion, and one of the spatial representatives is the lexeme sea, which in turn activates the epithet blue. In addition to verbs of motion, spatial semantics are conveyed by nouns and adverbs of place. Traditional formulas denoting space include constructions with the prepositions by, near, through, in, on, and geographical designations. Clean space is associated with the presence of Christian characters in it, but diseases are sent to places with the meaning of remote (unclean) space. The heavenly space of spells is represented by the symbols the sky, the sun, the moon, stars, and a fiery bugalo. Earthly space contains realities represented by lexemes denoting abstract space (north, south, west, east, side, parts, earth), natural landscape (mountains, forests, mounds, driftwoods, thickets, banks, stones, stumps, slums, ravines), formed territories (road, yard) and buildings (house, church). The spells denoting space are represented by plant names: trees (oak, willow, pear), bushes (viburnum), flowers (rose), herbs (mint, primrose, rowan), agricultural crops (rye), as well as generalized names of plants (tree, grass) and their parts. The lower water-land world is represented by the following nominations: snake, serpent, viper, plow, pike, dead man, devil. Prospects for further research consist in the study of the category of time in the texts of Ukrainian spells.

Projection-based coupled tensor learning for robust multi-view clustering

Multi-view clustering methods based on tensor learning have received extensive attention due to their ability to effectively mine high-order correlation information between views. However, the presence of noise and redundant information in multi-view data can seriously interfere with the performance of clustering tasks. To this end, we propose a projection-based coupled tensor learning method (PCTL). In particular, we first construct an orthogonal projection matrix to obtain the main characteristic information of the raw data of each view and learn the representation matrix in a clean embedding space. Then, we use tensor learning to couple the projection matrix and the representation matrix to mine the high-order information between views and construct a more suitable and optimal representation of the embedding space. A large number of experiments prove that PCTL can effectively suppress the interference of noise and redundant information, and the clustering performance is better than some existing excellent algorithms.

The frost restraining effect of solar air collector applied to air source heat pump

The air source heat pump has been demonstrated to be an efficient clean space heating technology, but the frosting on the exterior surface of the evaporator will largely decrease its performance. In this paper, the triangular solar air collector is adopted for evaporator frost restraint of the air source heat pump, and the dynamic heat transfer model of the triangular solar air collector and quasi-steady-state frosting model of the evaporator were established and coupled. The effect of frost layer thickness variation on evaporator air flow is considered based on the resistance factor to improve the applicability of the model. The heat flux and water vapor diffusion flux at different frost time and frost thickness were calculated, and the frosting characteristics of the air source heat pump with the triangular solar air collector and the conventional air source heat pump were compared on varying working conditions and typical daily meteorological parameters. Results show that triangular solar air collector can effectively restrain the frosting of the air source heat pump, and when the solar irradiance is 500 W/m2, the triangular solar air collector can reduce the frost thickness by more than 15 %. The triangular solar air collector increases the total heat flux by 101.4 W/m2 under frosting conditions, which reduces half of the defrosting times and increases the heat exchange of the evaporator by 36.6 % during a typical day, indicating that triangular solar air collector significantly improved the energy efficiency of air source heat pump on frosting condition.

Towards accessibility or affordability? Multidimensional energy poverty across the South African urban–rural divide

This study combines energy affordability and accessibility into a multidimensional energy poverty measure, which we stratify by rural and urban locale. Accessibility considers a number of binary indicators related to the type of energy used for a series of household activities, while affordability is determined by the ratio of household required energy expenditure to total expenditure. We employ an equivalence scale approach to estimate household energy requirements using publicly available household expenditure survey data. Our results suggest extensive urban–rural disparities across our multidimensional indicators—37% of rural households are affordability deprived, which is nearly double urban affordability deprivation; the rural–urban differences are at least double, when it comes to clean cooking, lighting, space heating, water heating and multidimensional headcount poverty. After splitting the households by degrees of energy poverty, it is found that the extreme energy-poor are more likely to be income-poor. However, urban extreme energy-poor is driven by affordability deprivation, while more than half of the rural extreme energy-poor are deprived in both affordability and accessibility.

Life cycle assessment as a tool for sustainable space activity in Aotearoa New Zealand

New Zealand’s space sector is at the early stages of growth but already attracts 1.5% of global private investment in space and contributes NZD 1.75 billion per year in revenue to the national economy. Growth has in part been due to the country’s desirable location for space operations due to a combination of geographic advantages, with its clear seas and skies and access to a wide range of launch angles, a skilled workforce, and strong government financial incentives.There are however challenges to future space activities such as the risk to long-term access and use of Earth’s orbital environment, specifically from space debris and a growing challenge to the whole-of-life of space operations, from the climate emergency and biodiversity crises. Consequently, there is increasing global motivation and urgency to quantify environmental consequences of space activities, which have historically been omitted from legislative and regulatory requirements. This paper provides a summary of the commercial development of New Zealand’s space sector and where appropriate environmental regulation and legislation may have been overlooked, as well as outlining broader environmental concerns of space operations.New Zealand’s emerging space industry offers a unique opportunity to integrate international best practices for environment and sustainability at a foundational level, for example, the European Space Agency’s Clean Space Initiative and their Life Cycle Assessment (LCA) Tool and Eco-design Framework. These types of tools provide valuable sources of information to support policy and business decisions.This paper provides a case study for an environmental LCA for a New Zealand designed and launched CubeSat which is the most launched satellite type from New Zealand. The case study indicates how the LCA can be used to identify environmental hotspots during the preliminary and detailed design phases as well as the launch event. Barriers and gaps in data collection have also been identified. As a result of this work, a set of recommendations have been made for further research requirements on the application of LCA to space activities.

Dhenu Svasthya Bot: An AI driven well-being and health monitoring setup for science and engineering applications

In this paper, an AI driven well-being and health monitoring set-up for the science &amp; engineering applications is being presented. "Dhenu Svasthya" represents an initiative at the intersection of agriculture, animal welfare, and artificial intelligence. This project's primary mission is to significantly enhance the overall health and living conditions of cattle, with a focus on improving their well-being and productivity. At the core of "Dhenu Svasthya" lies a sophisticated health monitoring system. Utilizing advanced AI ML method this system continuously tracks and analyzes key health indicators in cattle. It observes and records jaw movements, heart rate, acetone levels, bellowing patterns, and body temperature in real-time. The objective is to detect anomalies, deviations, or early signs of distress promptly. This proactive approach enables timely intervention by cattle owners, reducing the likelihood of disease and ensuring the optimal health of the animals. Environmental Cleanliness is another pivotal aspect of the project is the assessment of the cattle's living environment. Maintaining a clean and hygienic space is paramount for the cattle’s well-being. "Dhenu Svasthya" deploys AI technology to evaluate the cleanliness of the surroundings. The system provides actionable insights to users, allowing them to address potential cleanliness issues promptly and maintain a healthier living environment for their cattle. To extend the project's reach and accessibility, we are actively working on integrating "Dhenu Svasthya" with cloud services and other data management platforms. It aims to empower cattle owners and farmers with the information and insights needed for effective cattle management, thereby improving overall livestock welfare. In summary, "Dhenu Svasthya" is an ambitious undertaking that leverages AI to usher in a new era of cattle care. By continuously monitoring health, ensuring environmental cleanliness, and embracing data integration, this project aspires to be a game-changer in the field of livestock management. Its overarching goal is to promote the well-being of cattle, enhance agricultural sustainability, and ultimately benefit both the animals and those who depend on them for their livelihoods. The work carried out is the seventh semester main-project by the students of Electronics &amp; Communication Engineering under the guidance of the faculties supervision (guide).

Restorative Justice As A Reason For Termination Of Investigations On Criminal Acts Of Hurt Or Destruction In The Electronic Information And Transaction Law

The implementation of restorative justice in the criminal justice system should be carried out comprehensively, considering criminal decisions have only been retaliation and condolences so far. Only sad decisions ultimately lead to overcapacity in correctional institutions. As in the case of defamation, initially, this defamation was only regulated in Article 310 of the Criminal Code (KUHP), which in essence, contains the prohibition against attacking honor, slandering, and defaming someone in written form. And pictures. However, over time, defamation regulation is also regulated in Law Number 19 of 2016 concerning Information and electronic transactions, commonly known as the ITE Law. Furthermore, Circular Letter (SE) No. SE/2/11/2021 concerning Ethical Cultural Awareness to Create a Clean, Healthy, and Productive Digital Space for Indonesia. The statement in the SE stated that the National Police has the principle that criminal law is a last resort (ultimum remidium) and always prioritizes and seeks restorative justice in existing cases, including termination of investigations. The type of research used in this research is normative juridical research, this type of research is research that refers to legal norms and rules in its study. The results of this study are to understand the restorative justice arrangement as a reason for stopping the investigation and the role of the investigator in carrying out mediation in defamation cases regulated in the ITE Law.

Center consistency guided multi-view embedding anchor learning for large-scale graph clustering

Multi-view clustering has attracted extensive attention since it can integrate the complementary information of different views. Nonetheless, most existing methods suffer from cubic time computational complexity, so they have to face the challenge of maladjustment to medium and large-scale datasets. Whereupon, researchers usually employ anchor selection strategies to select a proportion of data points as landmarks to simulate the original data, and then build a bipartite graph to bridge the relationship between the original data points and anchors. However, for multi-view data, the existing strategies have three shortcomings, including: (1) on account of redundancy and corruption, the quality of anchors may be greatly affected; (2) these strategies are static ones or deficiency of views consistency; and (3) due to the differences in source, latent distribution, and the dimension of each view, the consensus bipartite graph cannot exploit the comprehensive information of all views precisely. In order to address these problems, this paper first proposes a novel method for scalable clustering, dubbed center consistency guided multi-view embedding anchor learning (2C-MEAL). Specifically, considering the redundancy and corruption, embedding learning is adopted to filter out the adverse information, as well as unify the dimensions of all views. Then, dynamic center consistency guided anchor learning is proposed to adaptively learn a set of high-quality anchors in the clean embedding space. Meanwhile, the refined bipartite graph is obtained for clustering purposes. Overall, 2C-MEAL has promising clustering performance and linear complexity. Experimentally, clustering experiments on benchmark datasets demonstrate that 2C-MEAL possesses effectiveness and efficiency over state-of-the-art methods.