Technical Evaluations Research Articles

Assessment of the viability of photovoltaic system implementation on the New Media Tower of Universitas Multimedia Nusantara using PVSyst software: A feasibility study.

The urgency of addressing climate change, exacerbated by greenhouse gas emissions, necessitates sustainable solutions, including green building practices and renewable energy adoption. This study focuses on the feasibility of implementing solar photovoltaic systems at Universitas Multimedia Nusantara (UMN), particularly in Building C, known as the New Media Tower, which is designed with green building principles. Solar energy, an increasingly prominent renewable source, presents a viable solution to reduce carbon footprints. Before installation, thorough simulations using software like PVSyst are essential to predict energy output and evaluate system efficiency. Several studies have explored PV system feasibility using simulations, highlighting the importance of software selection for accurate assessments. Building C offers potential locations for PV installation, with the rooftop being a primary consideration due to its expansive area and minimal shading. The rooftop PV system simulation shows an annual energy production of 202 MWh, close to the target of 209.64 MWh, while the parking area system only generates 64.5 MWh/year. Technical evaluations reveal that only the rooftop PV system meets electricity generation targets, highlighting its superiority over the parking area system. Financial analysis demonstrates the rooftop system's viability, with a payback period of 8.2 years and a return on investment (ROI) of 115.8%. Although the upfront investment is substantial, the long-term benefits justify implementation. Overall, this study underscores the technical and financial feasibility of rooftop photovoltaic systems on Building C at UMN, offering valuable insights for sustainable energy initiatives in academic institutions.

Towards a rational framework for economic and risk assessment of energy efficiency projects

Shifting towards a low-carbon and sustainable economy requires both a shift to Renewable Energy Sources (RES) and a significant increase in Energy Efficiency (EE) targets. This paper introduces a novel, user-friendly, and step-by-step framework for the techno-economic and risk-based assessment of EE Projects (FEEP). The four-stage methodology represents a step beyond traditional methods by systematically identifying intervention areas, conducting technical evaluations, and providing a comprehensive tool for economic and risk assessment. The proposed tool may empower decision-makers to select the most suitable approaches for the economic viability analysis of future projects. The framework incorporates environmental assessment, quantifying anticipated CO2 reductions from EE measures. A real-world case study demonstrates how the new framework allows structuring the decision-making process under a reliable and straightforward approach, providing additional confidence to the investors through visual risk assessment indicators. The paper concludes with how managers and EE analysts of private and public institutions can take advantage of the proposed methodology to evaluate and benchmark a broader range of EE initiatives.

Holistic Assessment for Social Housing Retrofitting: Integrating Seismic, Energy, and Social Aspects in the REHOUSE Project

There are many existing buildings for which seismic rehabilitation interventions are required, especially in earthquake-prone areas like Italy. At the same time, the huge energy cost increase in Europe highlights the need for sustainable techniques that are able to increase the energy efficiency of buildings. These issues are even more significant for weak social groups living in social housing buildings, often in poor and vulnerable conditions. In order to address the solution regarding building renovations from the social, structural, and energy efficiency perspectives, in the framework of the Horizon Europe REHOUSE (Renovation packagEs for HOlistic improvement of EU’s bUildingS Efficiency, maximizing RES generation and cost-effectiveness) Project, this paper proposes an integrated methodology of building assessment that was tested on a social housing building in Margherita di Savoia, a small town of Apulia Region, Italy. In addition to the structural and energy aspects, the social one is particularly important since the building is located in the “Capitanata Area”, considered to be one of the most socially vulnerable areas in Italy. For this reason, an assessment methodology must consider reducing the overall impact of the assessment activities while explaining to tenants the purpose of the assessment and future renovation actions, maintaining the accuracy of the assessment results. Therefore, this study outlines an assessment methodology, demonstrated through its application to the case study building, that integrates the structural, energy, and social aspects, showing that the tenants’ involvement is also crucial for the technical evaluations. The final result is a low-impact approach for the building knowledge gathering needed to start a deep renovation intervention in social housing.

СИНХРОНИЗАЦИЯ ПОДАЧИ СЕМЯН И РАБОЧЕЙ ЖИДКОСТИ В КАМЕРУ СМЕШИВАНИЯ ПРОТРАВЛИВАТЕЛЯ

The results of production tests of the PS-20K-4 seed dresser with a modified electrical control circuit in order to synchronize the supply of seeds and working fluid to the mixing chamber of the treater when it is put into operation are presented. At each start-up of the dressers, the supply of seeds to the chamber is ahead of the supply of working fluid to it due to the inertia of the working bodies of the hydraulic system, especially this is manifested on dressing machines equipped with centrifugal pumps for supplying working fluid (PS-20K-4, PS-22, etc.). To ensure the synchronization of the supply of seeds and working fluid to the mixing chamber, a device is proposed, the main part of which is the PVI-11 time delay relay for switching on the seed disc drive. Before starting the dresser, the time of movement of the liquid from the pump to the sprayer is determined. For the time obtained in this way, a delay is set on the PVI-11 attachment. Production tests have shown the advantage of the treater with changes made to the electrical control circuit. With the factory control scheme of the treater, the total weight of untreated seeds and seeds with reduced completeness of treatment, which are defective, increases with the increase in the installed capacity of the unit from 5 to 20 t/h, respectively from 26.4 to 48 kg at the beginning of each machine start-up. With the established synchronization of the supply of seeds and working fluid to the mixing chamber when starting the dressing machine, there were no defective seeds. Operational, technological, technical and economic evaluations of the unit showed that the shift time utilization factor was τ_c = 0.83, Shift productivity increased by 25 % due to a reduction in the time for additional treatment of untreated and insufficiently treated seeds. The indicators of technical and operational reliability were Ktn = 0.98 and Ken = 0.94, respectively. Reduced costs by 35%, reducing labor costs by 25%. The annual economic effect with 140 hours of operating amounted to 29915.6 thousand rubles.

Development of a selective sequential process for H2S enrichment and CO2 capture in aqueous MDEA solutions

The typical acid gas removal process can simultaneously remove acid gases from the raw gas using an aqueous MDEA solution. But it cannot further separate and capture hydrogen sulfide and carbon dioxide, and increases the burden on subsequent processing. Recovering carbon dioxide from that not only increases the H2S content in the acid gas, but also achieves the CO2 capture. To realize these, acid gas enrichment and carbon dioxide capture are integrated into the typical acid gas removal process. In this study, a novel selective sequential process in aqueous MDEA solutions is proposed for H2S enrichment and CO2 capture. And an optimization framework is proposed to optimize the parameters of the whole process, mainly to improve the efficiency of the column equipment. It is found that small diameter column is suitable for enhancing selectivity and large diameter column is suitable for maximizing productive capacity. To demonstrate the performance of the proposed process, the evaluation results, carbon sulfur ratio (3.81), return on investment (6.26) and carbon dioxide capture ratio (−0.63) are obtained from technical, economic and environmental evaluations. In comparison with the typical process, the novel process can achieve H2S enrichment and CO2 capture while remaining economically viable. This study presents a method for collaborative removal of H2S and CO2 in acid gas removal process. It is advantageous to reduce carbon dioxide emissions.

CyberAIBot: Artificial Intelligence in an Intrusion Detection System for CyberSecurity in the IoT

The cyber ecosystem presents two interesting properties. Attackers and defenders are normally the same entity; a detailed knowledge of defensive strategies optimises an attack whereas a good defence, based on a layered structure also includes attacks. In addition, Artificial Intelligence (AI) provides new techniques and tools to both attackers and defenders such as Generative Adversarial Networks (GANs) based on Generators and Discriminators for impersonation or Deep Learning (DL) for exhaustive scanning. To address this dilemma, this article presents CyberAIBot: Artificial Intelligence in an Intrusion Detection System for CyberSecurity in the Internet of Things (IoT) aimed at Operational Technology (OT) and Information Technology (IT) network traffic. CyberAIBot is based on a Deep Learning management structure in a private or local edge cloud computing approach where AI makes decisions as close as possible to the source of data. CyberAIBot gradually detects, learns, and adapts to different cyber attacks. In detail, CyberAIBot uses Deep Learning (DL) technical clusters trained in specific attacks and a Deep Learning (DL) management cluster specialises in taking management decisions rather than technical evaluations. This management cluster supervises conflicting classifications from the deep learning technical clusters. CyberAIbot is trained against several datasets and its performance is evaluated between two classification algorithms, the Long Short-Term Memory (LSTM) networks and Support Vector Machines (SVMs). The SVM DL clusters learn faster (average 15x) although the LSTM DL clusters perform better (average 30%). The LSTM DL management cluster performs better than the SVM DL management cluster although it recognises fewer traffic types. The total number of data points analysed by CyberAIBot is 5.52E+08, equivalent to the distance between the planet Earth to the Moon in meters.

Assessment of Power Equipment Operational Safety in the Sustainable Management of Residual Lifespan

Introduction. Ensuring the safe operation of energy facilities is a critical issue at all life cycle stages. It is associated with the adoption of management decisions when rescheduling and assessing the remaining resources, which are made based on a comprehensive assessment of the technical condition of the equipment, taking into account the economic efficiency and environmental requirements for further operation, which is the basis for technical and economic assessments. Aim and tasks. This study aims to develop a technical and economic assessment of the safe operation of power equipment to ensure sustainable management of the remaining service lifespan. Results. An algorithm for assessing pipeline system elements by the coolant environment is proposed, which allows for the pipeline load and changes in erosion and corrosion caused by coolant movement. It was proposed that the equipment be systematised by safety class and coolant. When conducting a technical and economic assessment, these parameters and the costs of extending the service life and upgrading the existing equipment were considered in the standard calculations of a certain type of equipment. For this purpose, mathematical models for calculating the residual life for each type, obtained and confirmed based on empirical studies, are proposed. Research findings into ensuring the reliability and safety of operation with various heat carriers have shown that it is necessary to consider low-cycle and high-cycle loads and erosion processes. It was found that the erosive wear rate is 0.3-0.4 mm/year for bending sections of the main circulation pipeline, where maximum loads occur relative to low-cycle and vibration loads, and the stress is 212.5 MPa when assessing the residual life of 7 years. Conclusions. The cost-effectiveness of reassigning the service life is reasonable, as it does not require additional investment in upgrading or replacing equipment subject to annual technical diagnostics. The systematisation of pipelines, improved codifiers, lifespan assessment models, and algorithms for evaluating the remaining life under various loadings enhance the regulatory framework for safe nuclear power plant operations and support technical and economic evaluations for extending their lifespan.

Assessing the effects of fluorine-free and PFAS-containing firefighting foams on development and behavioral responses using a zebrafish-based platform

Significant progress has been made in developing fluorine-free firefighting foams (F3) as alternatives to perfluoroalkyl substances (PFAS)-containing aqueous film-forming foams (AFFF) to help eliminate the health and environmental concerns linked to PFAS exposure. However, developing viable F3 options hinges on a thorough assessment of potential risks alongside the technical performance evaluations. This study showcases the capability of a zebrafish-based platform to discern the developmental and behavioral toxicities associated with exposure to one AFFF and two F3 formulations. To facilitate direct exposure to the chemicals, embryos were enzymatically dechorionated and then exposed to the diluted formulations (6–120 hours post fertilization (hpf)) at concentrations folding from 0.1% of the manufacturer-recommended working concentrations. The exposure regimen also included daily automated media changes (50%) and mortality assessments (24 and 120 hpf). At 120 hpf, a comprehensive assessment encompassing overall development, prevalence of morphological defects, and behavioral responses to acute stressors (visual, acoustic, and peripheral irritant) was conducted. Exposure to both F3s significantly increased larval mortalities to percentages exceeding 90%, whereas AFFF exposures did not cause any significant effect. Overall development, marked by total larval length, was significantly impacted following exposures to all foams. Behavioral responses to acute stressors were also significantly altered following exposures to both F3s, whereas the AFFF did not alter behavior at the concentrations tested. Our findings demonstrate toxicities associated with tested F3 formulations that encompass several endpoints and highlight the utility of the proposed platform in evaluating the developmental toxicities of current and future foam formulations.

The Application and Evaluation of the LMDI Method in Building Carbon Emissions Analysis: A Comprehensive Review

The Logarithmic Mean Divisia Index (LMDI) method is widely applied in research on carbon emissions, urban energy consumption, and the building sector, and is useful for theoretical research and evaluation. The approach is especially beneficial for combating climate change and encouraging energy transitions. During the method’s development, there are opportunities to develop advanced formulas to improve the accuracy of studies, as indicated by past research, that have yet to be fully explored through experimentation. This study reviews previous research on the LMDI method in the context of building carbon emissions, offering a comprehensive overview of its application. It summarizes the technical foundations, applications, and evaluations of the LMDI method and analyzes the major research trends and common calculation methods used in the past 25 years in the LMDI-related field. Moreover, it reviews the use of the LMDI in the building sector, urban energy, and carbon emissions and discusses other methods, such as the Generalized Divisia Index Method (GDIM), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Interpretive Structural Modeling (ISM) techniques. This study explores and compares the advantages and disadvantages of these methods and their use in the building sector to the LMDI. Finally, this paper concludes by highlighting future possibilities of the LMDI, suggesting how the LMDI can be integrated with other models for more comprehensive analysis. However, in current research, there is still a lack of an extensive study of the driving factors in low-carbon city development. The previous related studies often focused on single factors or specific domains without an interdisciplinary understanding of the interactions between factors. Moreover, traditional decomposition methods, such as the LMDI, face challenges in handling large-scale data and highly depend on data quality. Together with the estimation of kernel density and spatial correlation analysis, the enhanced LMDI method overcomes these drawbacks by offering a more comprehensive review of the drivers of energy usage and carbon emissions. Integrating machine learning and big data technologies can enhance data-processing capabilities and analytical accuracy, offering scientific policy recommendations and practical tools for low-carbon city development. Through particular case studies, this paper indicates the effectiveness of these approaches and proposes measures that include optimizing building design, enhancing energy efficiency, and refining energy-management procedures. These efforts aim to promote smart cities and achieve sustainable development goals.

URLLC-aware and energy-efficient data offloading strategy in high-mobility vehicular mobile edge computing environments

The integration of Internet of Things (IoT) technologies into the vehicular industry has initiated a new era of connected and autonomous vehicles, revolutionizing transportation systems. However, this transformation introduces significant challenges, especially in 5 G networks, such as achieving Ultra-Reliable Low-Latency Communications (URLLC) and maintaining energy efficiency within the high mobility of vehicular environments. These are essential for supporting sustainable and environmentally friendly computing practices. To address these challenges, this paper introduces a URLLC-aware and energy-efficient data offloading strategy, utilizing the Asynchronous Advantage Actor-Critic (A3C) algorithm to navigate the complex dynamics of vehicular Mobile Edge Computing (MEC) environments. Our proposed method balances latency and energy consumption trade-offs while ensuring robust communication reliability. Technical evaluations reveal that our approach significantly outperforms other algorithms, achieving up to 8.2 % energy savings and a reduction of over 29 % in latency.

IrOnTex: Using Ironable 3D Printed Objects to Fabricate and Prototype Customizable Interactive Textiles

In this paper, we propose IrOnTex, an approach to design, fabricate, and prototype customizable interactive textiles by ironing 3D printed elements directly onto fabrics. Our method incorporates multiple filament types to demonstrate functionalities such as electrical conductivity, sensing, and thermo- and photo-sensitivity for interactive applications. Additionally, we integrate a tiling-like fragmented design to improve stretchability and flexibility to match the mechanical behavior of textiles in our 3D printed elements. We characterized the iron-on process through technical evaluations, which showed the durability and reversibility of the approach. We also suggested baseline parameters for prototyping and methods to enhance the functionality of certain materials. The empirical results from the studies were used to develop a design tool to assist the design process. A user study with 10 participants revealed the helpfulness of the tool. To demonstrate the capabilities of the approach, we show a set of example interactive applications. We envision the proposed approach will enable designers to rapidly prototype interactive textile applications.

Energetic/economic/scalability assessment of active solar energy and waste heat utilization in urban environments for H2/freshwater production: A CSP-centered multigeneration system with dual-loop power generation

The imperative to reduce greenhouse gas emissions has intensified the need for sustainable thermal energy systems. This study addresses this exigency by harnessing solar energy and exploiting waste heat to augment energy efficiency in urban settings. The proposed system integrates a concentrated solar power-based Brayton cycle with dual power generation, water desalination, and hydrogen production capabilities. Comprehensive technical and economic evaluations affirm the feasibility of this system. Additionally, transient codes have been utilized to ascertain the performance of the proposed configuration. The investigation reveals that the tower and receiver are the primary sites of exergy destruction, accounting for 48.1 % of the total, with the heliostat field, reverse osmosis, and proton exchange membrane electrolysis contributing 24 %, 8.8 %, and 6.9 %, respectively. The findings show that increasing the pressure ratio in the Brayton cycle leads to improved exergy efficiency and increased power output, but also leads to higher overall costs. A thorough economic evaluation shows that the solar unit, which includes the receiver, heliostat field, compressor, and gas turbine, is the main factor influencing costs, representing 62.6 % of the total system cost rate. The dynamic study conducted to forecast the annual system capacity in San Francisco indicates that electricity production peaks during summer at 242.15 MWh. Conversely, winter exhibits the lowest contribution at 17.3 % with 143.11 MWh.

Addressing attentional issues in augmented reality with adaptive agents: Possibilities and challenges

Recent work on augmented reality (AR) has explored the use of adaptive agents to overcome attentional issues that negatively impact task performance. However, despite positive technical evaluations, adaptive agents have shown no significant improvements to user task performance in AR. Furthermore, previous works have primarily evaluated such agents using abstract tasks. In this paper, we develop an agent that observes user behaviour and performs appropriate actions to mitigate attentional issues in a realistic sense-making task in AR. We employ mixed methods to evaluate our agent in a between-subject experiment (N=60) to understand the agent’s effect on user task performance and behaviour. While we find no significant improvements in task performance, our analysis revealed that users’ preferences and trust in the agent affected their receptiveness of the agent’s recommendations. We discuss the pitfalls of autonomous agents and highlight the need to shift from designing better Human–AI interactions to better Human–AI collaborations.

SSENPV's Integrated Management Platform

At the Polytechnic of Viseu (PV) [1], the number of students has been increasing [2], and it is hoped that this trend continues, for the sake of the literacy of the population that serves in its area of coverage and for the reduction of the desertification of the interior region in which is inserted. In the case of Students with Specific Educational Needs (SSEN) who attend the PV (SSENPV), it is extremely important to develop procedures that minimize the anxiety brought about by change for these students, as well as to facilitate their adaptation, to make the period of permanence in Higher Education (HE) an inclusive period, generating well-being, promoting academic success, and facilitating the transition to active life. To combat this phenomenon and since the PV is a Higher Education Institution (HEI) that is guided by equity in its community, in particular the student community, the SSENPV census is a crucial measure insofar as it is necessary to implement procedures, which must respect and obey individual specificities. It is also intended that, regarding access to information on the platform, it will allow reducing asymmetries between students as well as access to services.To respond to this reality, within the scope of the Inova & Includes project. IPV I2 [3], a group of researchers, in partnership with the degree course in Computer Engineering at the Superior School of Technology and Management of Viseu (ESTGV) – curricular unit of “Project”, developed an integrated management platform for SSENPV. This platform, which is intended to be a contribution to true equity in education in the PV, is based on the support of social impact in different dimensions, which translates into the implementation of the following profiles:• Informative Profile: dissemination of legislation and other relevant information on Specific Educational Needs (SEN), ensuring centralized and accessible information management and streamlining procedures and support measures.• Academic Profile: registration and updating of data on the SSENPV.• Technical Evaluation and Follow-up Profile: registration of the SSENPV procedural evaluation, with automatic sending of technical evaluations to authorized users.

Evaluation of different evaluation methods for selection of a conceptual design

Designing plays an important part in the production of an artifact, as it is the mental creation before the product becomes a reality. It also plays an interesting engineering activity that affects almost all areas of human life and uses the laws and insights of science. After the various design concepts have been successfully carried out, the evaluation stage becomes crucial in the selection of the best solution. A thorough study of the literature suggests that not too many works have been done on evaluating different evaluation methods in selecting a concept. The objective of this study was to evaluate four design concept evaluation methods for selecting a car hitch. The study found that for a robust selection of solutions, Verein Deutscher Ingenieure (VDI) guidelines and Technical Economic Evaluations were more appropriate to be used.

ECSkin: Tessellating Electrochromic Films for Reconfigurable On-skin Displays

Emerging electrochromic (EC) materials have advanced the frontier of thin-film, low-power, and non-emissive display technologies. While suitable for wearable or textile-based applications, current EC display systems are manufactured in fixed, pre-designed patterns that hinder the potential of reconfigurable display technologies desired by on-skin interactions. To realize the customizable and scalable EC display for skin wear, this paper introduces ECSkin, a construction toolkit composed of modular EC films. Our approach enables reconfigurable designs that display customized patterns by arranging combinations of premade EC modules. An ECSkin device can pixelate patterns and expand the display area through tessellating congruent modules. We present the fabrication of flexible EC display modules with accessible materials and tools. We performed technical evaluations to characterize the electrochromic performance and conducted user evaluations to verify the toolkit's usability and feasibility. Two example applications demonstrate the adaptiveness of the modular display on different body locations and user scenarios.

A Study on the Techno-Economics Feasibility of a 19.38 KWp Rooftop Solar Photovoltaic System at Al-Abrar Mosque, Saudi Arabia

This research paper presents a comprehensive study on the implementation of photovoltaic (PV) energy systems at Al-Abrar Mosque in Saudi Arabia. The primary objective was to explore optimal regional solar power strategies. By synergistically integrating technical evaluations of the PV system with economic analyses, including the payback period and levelized cost of energy (LCOE), alongside an investigation of net metering and net billing scenarios, we delineated a pathway toward achieving net zero billing for the mosque’s energy requirements. This study examined two scenarios: Scenario I involved net metering, while Scenario II explored net billing. Our theoretical and simulation results, derived from detailed analyses conducted using PVsyst software, unequivocally demonstrated the superiority of net metering for this specific application. With net metering, the mosque’s energy needs can be efficiently met using minimal infrastructure—comprising only 34 photovoltaic modules and a single inverter. In contrast, net billing requires significantly higher resource demands, underscoring the economic and spatial advantages of net metering. Additionally, the payback period for Scenario I is 7.9 years, while for Scenario II, it extends to 87 years. Through rigorous simulations, this study reaffirmed the practicality and feasibility of the net metering approach within the context of Saudi Arabia. Furthermore, our research provides actionable insights for implementing sustainable solutions at specific sites, such as the Al-Abrar Mosque, and contributes to advancing renewable energy knowledge in the region.

Tool to assess the groundstroke technique of preadolescent tennis players.

In this study, we develop a tool that can be used by tennis coaches to evaluate the groundstroke (forehand and backhand) technique of preadolescent tennis players. The participants of the study were 60 children (30 males and 30 females) aged 10-12 years, with at least two years of training in tennis. The Groundstroke Correction Checklist (GCC) was translated into Turkish by using a blind procedure. The Turkish translation was then evaluated by 15 coaches of the Turkish Tennis Federation who had at least a level-3 coaching license and more than five years of coaching experience. The technical components related to technique in the checklist were labeled as unimportant, important, and very important. Following this, the GCC was converted into a Groundstroke Technique Assessment Test Tool (GTATT) by a selection committee consisting of three experts, and its reliability and validity were assessed by using it in the field. Spearman's correlation was used to analyze the correlation (test-r test) between the technical evaluation scores assigned to the players by the tennis coaches based on the GTATT in the first and second weeks. Intra- and inter-rater reliability was used to analyze the overall scores of technical evaluations in the first and second weeks to assess the reliability of the scale used. We determined each player's number of years of playing experience (TPY), technical evaluation (TE), international tennis-level test score (ITN), I-cord classification order (ICCO), and the number of games won (GW) in a tournament organized among themselves and evaluated the correlations among these parameters by using Spearman's correlation analysis. A statistically high and significant correlation was observed between the technical evaluations of the players' forehand and backhand groundstrokes by the tennis coaches by using the GTATT in the first and second weeks (r > .90, p < .01). The analysis of the intra- and inter-rater reliability of the GTATT yielded excellent agreement between the technical observations of the three coaches of the players' forehand and backhand strokes in the first and second weeks.

L’impact de la simulation en santé et l’importance des facteurs humains

Medical simulation is extensively developing over the recent years. It is based on the acquired experience in aircraft industry simulation with the use of different supportive check-lists. In healthcare settings, the first initiatives came from the learning of surgical techniques. Simulation on manikins allowed training of surgeons before they shift to patients. A new step has occurred with the development of non technical skills evaluations of operating theatre teams, through concrete scenarios.

From solution to structure: empowering inclusive cryo-EM with a pre-characterization pipeline for biological samples.

In addressing the challenges faced by laboratories and universities with limited (or no) cryo-electron microscopy (cryo-EM) infrastructure, the ESRF, in collaboration with the Grenoble Institute for Structural Biology (IBS), has implemented the cryo-EM Solution-to-Structure (SOS) pipeline. This inclusive process, spanning grid preparation to high-resolution data collection, covers single-particle analysis and cryo-electron tomography (cryo-ET). Accessible through a rolling access route, proposals undergo scientific merit and technical feasibility evaluations. Stringent feasibility criteria demand robust evidence of sample homogeneity. Two distinct entry points are offered: users can either submit purified protein samples for comprehensive processing or initiate the pipeline with already vitrified cryo-EM grids. The SOS pipeline integrates negative stain imaging (exclusive to protein samples) as a first quality step, followed by cryo-EM grid preparation, grid screening and preliminary data collection for single-particle analysis, or only the first two steps for cryo-ET. In both cases, if the screening steps are successfully completed, high-resolution data collection will be carried out using a Titan Krios microscope equipped with a latest-generation direct electron counting detector coupled to an energy filter. The SOS pipeline thus emerges as a comprehensive and efficient solution, further democratizing access to cryo-EM research.