Modular Tool Research Articles

Pervasive Real-Time Analytical Framework—A Case Study on Car Parking Monitoring

Due to the amount of data emerging, it is necessary to use an online analytical processing (OLAP) framework capable of responding to the needs of industries. Processes such as drill-down, roll-up, three-dimensional analysis, and data filtering are fundamental for the perception of information. This article demonstrates the OLAP framework developed as a valuable and effective solution in decision making. To develop an OLAP framework, it was necessary to create the extract, transform and load the (ETL) process, build a data warehouse, and develop the OLAP via cube.js. Finally, it was essential to design a solution that adds more value to the organizations and presents several characteristics to support the entire data analysis process. A backend API (application programming interface) to route the data via MySQL was required, as well as a frontend and a data visualization layer. The OLAP framework was developed for the ioCity project. However, its great advantage is its versatility, which allows any industry to use it in its system. One ETL process, one data warehouse, one OLAP model, six indicators, and one OLAP framework were developed (with one frontend and one API backend). In conclusion, this article demonstrates the importance of a modular, adaptable, and scalable tool in the data analysis process and in supporting decision making.

Modeling control strategies for prosumers in a Python-based modular simulation tool

The planned massive increase of producers and consumers such as electric vehicles, heat pumps and photovoltaic systems in distribution grids will lead to new challenges in the electrical power system. These can include grid congestions at the low voltage level but also at higher voltage levels. Control strategies can enable the efficient use of flexibilities and therefore help mitigate upcoming problems. However, they need to be evaluated carefully before their application in the energy system to avoid any unwanted effects and to choose the most fitting strategy for each application. In this publication, a Python-based modular simulation tool for developing and analysing control strategies for prosumers, which uses pandapower (Thurner et al. 2018), is presented. It is intended for sequential simulations and enables detailed operational analyses, which include evaluating the influence on grid situations, the necessary behavior of energy system components, required measurements and communications. This publication also gives an overview of control strategies, existing simulation tools, how the modular simulation tool fits in and illustrates its functionalities in an application example, which further highlights its versatility and efficiency. Time series simulations with the tool allow analyses regarding the effect of control strategies on power flow results. Moreover, the simulation tool also facilitates evaluating the behavior of energy system components (e.g. distribution substations), necessary communications and measurements as well as any faults that might occur.

Техническое обслуживание и ремонт цапф барабанной мельницы плавучего комплекса горного оборудования

Introduction. In order to develop promising deposits of non-ferrous metals in the Arctic zone, in particular the Pavlovskoye lead-zinc deposit on Novaya Zemlya, it is necessary to develop climate-saving geo-technologies for mining. In this connection, a concept of conservation geo-technology has been developed and proposed through the use of a specially designed floating complex of mining equipment, included together with the quarry equipment in a single technological chain for the extraction of ore raw materials and its processing into concentrate. However, for the full functioning of the concept of this geo-technology, it is necessary to carry out preventive maintenance and repair of mining equipment at the site of its operation on a floating complex. Research methods and materials. The methodological basis of the work is a systematic approach to the studied means of carrying out repair and restoration works of mining machinery and equipment, which includes both theoretical analysis and generalization of the results of fundamental and applied works of domestic and foreign authors, including methods and theories of designing technology for repairing metalworking and mining processing complexes, multicriteria analysis and simulation modeling. Research results. The article proposes a new technology for the implementation of repair work to restore the working surfaces of hollow loading and unloading support trunnions of hydrostatic sliding bearing units of a drum mill in cramped deck conditions of a floating complex of mining equipment for the development of deposits in the Arctic zone. The structure of the built-in mechanized modular machine tool complex is developed and presented, with the help of which the hollow support trunnions of the drum mill are directly machined according to the patented repair technology. Conclusion. It is shown that the use of the described repair technology by means of an embedded mechanized modular complex will reduce the complexity of the overhaul of the trunnions without the need to perform dismantling work to disconnect the mill drum body from the hollow trunnion caps, which has a positive effect on the accuracy of processing the working surfaces of hollow trunnions.

How to Support Startups in Responsible Innovation Processes: A Tool Analysis

Innovation plays a vital role in economic growth and addressing societal challenges such as climate change, poverty, and ageing populations. However, the impacts of innovation are not always predictable, and negative outcomes can emerge unexpectedly. Anticipating the long-term effects of innovation is becoming increasingly important as technology and innovation continue to advance at a rapid pace. Responsible Innovation (RI) is an approach that aims to govern research and innovation by involving stakeholders early on to improve anticipation of consequences and make innovation ethically acceptable, environmentally sustainable, and socially desirable. Small enterprises, particularly start-ups, face significant challenges in implementing sustainability and responsibility in their innovation processes due to limited resources. This study aims to explore existing tools for operationalizing RI in a business context and assess their applicability to start-ups. The findings reveal that while there are numerous ongoing projects and tools for RI in a business context, there is a lack of tools specifically designed for start-ups. By identifying key concepts and characteristics of tools for RI implementation in start-ups, the paper contributes to the field of RI by laying the groundwork for the development of an RI tool tailored to the needs of start-ups. The study provides recommendations for improving existing RI tools, including the development of modular and user-adaptive tools. This research expands the knowledge base on RI, offers a theoretical foundation for further research, and paves the way for the development of the COMPASS self-check tool for RI implementation in start-ups.

Situational awareness and decision-making in a crisis situation: A crisis management cell in virtual reality

In a constantly evolving and hyper-connected world, the crises we are facing are changing, exceeding borders, and impacting every sector of activity. More data can be gathered from the crisis site, arriving in a large flow of various types from multiple sources such as sensors, open data, or social media. This huge amount of data coming continuously from the crisis site leads to an ever-changing situational awareness that must be built and understood as quickly as it is evolving to ensure a relevant and effective crisis response. To build a shared situational awareness, decision-makers can gather in a room where they can share and compare the information they receive from the crisis site to build a common operational picture that they can use to make decisions and implement them: this is a crisis management cell. However, the tools in traditional crisis management cells may not be able to keep up with the new requirements induced by these changes: we need modular and dynamic tools able to adapt to the crisis and the needs of the crisis managers while ensuring collaboration and information sharing not only between the stakeholders but also with remote experts that might be needed to understand the situation. We need to start conceiving the future crisis management cell that would meet the new exigencies of crisis management. This paper proposes our version of that future crisis management cell, using virtual reality to provide a dynamic and modular crisis management cell linked to artificial intelligence and decision-support systems.

AP-NURSE: A Modular Tool to Ease the Life of Patients Suffering from Cognitive Diseases

This paper presents the development and testing of the AP-NURSE monitoring tool aimed to ease the everyday life of patients with Alzheimer’s and Parkinson’s diseases as well as those who take care of such patients. It summarises the activities carried out as part of the international Interreg CE niCE-life project. The team of STU designed, developed, constructed, and tested the AP-NURSE intelligent tool. The paper starts with demographic information on Slovakia. It highlights the fact that population aging is a significant issue, which requires measures to mitigate its consequences at local and European levels. The next part describes the final design of AP-NURSE Home and Care devices and their versions, including details on their hardware and software. A significant part of the paper deals with the testing of AP-NURSE in both laboratory and authentic environments. The laboratory testing was carried out directly at STU. The final testing in an authentic environment was conducted in two social and healthcare centres in Bratislava and in Warsaw. After the activities described in this paper, AP-NURSE reached TRL-6. The AP-NURSE Home platform developed based on the ESP microcontrollers demonstrated the best functionality and has the potential to be used in real practice.

DarkPACK: A modular software to compute BSM squared amplitudes for particle physics and dark matter observables

We present here a new package to automatically generate a complete library of 2 to 2 squared amplitudes at leading order in any New Physics model. The package is written in C++ and is based on the MARTY software. The numerical library generated allows for the computation of relic density by embedding the algorithms of SuperIso Relic. Program summaryProgram Title:DarkPACKCPC Library link to program files:https://doi.org/10.17632/dwm6g5ff2c.1Developer's repository link:https://gitlab.in2p3.fr/darkpack/darkpack-publicLicensing provisions: GPLv3Programming language: C++Nature of problem: Creating an all-in-one package that allows for the generation of 2→2 squared amplitudes and related quantities starting from the Lagrangian density. The package has also to provide tools to compute 〈σv〉 and the relic density. The aim is to have a modular tool as user-friendly as possible that provides dark matter observables starting from a BSM Lagrangian density.Solution method: We created a package that computes 2→2 squared amplitudes and related quantities, starting from the Lagrangian density. The package is based on MARTY 1.6[1], since MARTY provides a comprehensive environment that allows for the generation of a ready to use numerical library, starting from the Lagrangian density of the model. This would be very difficult to realize with other softwares, since the user would need to generate the Feynman rules from the Lagrangian density with some software (e.g. Sarah [2]), then use them to generate the squared amplitudes with some other software (e.g. CalcHEP [3] or MadGraph [4]), with a passage of inputs and need of coordination among more codes. Therefore, DarkPACK relies on the creation of a super-set of MARTY's capabilities, intended to generate a structure of the numerical library and to add essential features such as running of the Standard Model parameters. The user needs to implement the model in a C++ file that makes use of MARTY. Moreover, the user needs to use the functions we provide to implement fundamental features for the computation of the relic density. A configuration by hand of the inputs is needed as well, since each model has different input parameters. The package provides also tools to compute the relic density.

РОЗРОБКА НОВОЇ МЕТОДИКИ ЕКСПЕРИМЕНТАЛЬНИХ ДОСЛІДЖЕНЬ ІНТЕНСИВНОСТІ КОЛИВАЛЬНИХ ПРОЦЕСІВ МАШИННО-ТРАКТОРНИХ АГРЕГАТІВ

An important operational indicator of agricultural machine-tractor units is the smoothness of movement, which significantly affects the traction and dynamic performance of their work, productivity, agronomic qualities of the operation, traffic safety, durability and efficiency. As a rule, it is evaluated by the influence of oscillations (translational vertical, transverse, angular longitudinal, etc.), on these indicators, as well as on the physical condition and health of operators who control these units in real production conditions. This article presents an improved method and results of experimental assessment of the smoothness of the movement of the modular agricultural unit, which moves in the footsteps of a constant technological track. Studies of the smoothness of the modular unit showed that the graphs of normalized correlation functions of vertical oscillations of the modular agricultural tool developed by us in its motion in the wake of a constant techno-logical track is characterized by a function containing along with random components harmonic, which are expressed by attenuating periodic oscillations. The range of frequencies of oscillations of the frame of the agricultural tool is concentrated in the range from 0 tо 20 s−1, which is consistent with the frequency range 0…0.3 s−1 in which the variances of oscillations of inequalities of a profile of traces of a technological track are concentrated. Studies have confirmed the effectiveness of the method of estimating the intensity of vertical oscillations of the agricultural unit measuring and recording system based on a tablet computer with Android operating system with built-in accelerometer sensors and Accelerometer Meter application. The developed technique of mathematical modelling and experimental determination of vertical oscillations of the machine-tractor unit can be used in the study of the dynamics of other agricultural machines and units.

EstimateR: an R package to estimate and monitor the effective reproductive number

BackgroundAccurate estimation of the effective reproductive number (R_e) of epidemic outbreaks is of central relevance to public health policy and decision making. We present estimateR, an R package for the estimation of the reproductive number through time from delayed observations of infection events. Such delayed observations include confirmed cases, hospitalizations or deaths. The package implements the methodology of Huisman et al. but modularizes the R_e estimation procedure to allow easy implementation of new alternatives to the currently available methods. Users can tailor their analyses according to their particular use case by choosing among implemented options.ResultsThe estimateR R package allows users to estimate the effective reproductive number of an epidemic outbreak based on observed cases, hospitalization, death or any other type of event documenting past infections, in a fast and timely fashion. We validated the implementation with a simulation study: estimateR yielded estimates comparable to alternative publicly available methods while being around two orders of magnitude faster. We then applied estimateR to empirical case-confirmation incidence data for COVID-19 in nine countries and for dengue fever in Brazil; in parallel, estimateR is already being applied (i) to SARS-CoV-2 measurements in wastewater data and (ii) to study influenza transmission based on wastewater and clinical data in other studies. In summary, this R package provides a fast and flexible implementation to estimate the effective reproductive number for various diseases and datasets.ConclusionsThe estimateR R package is a modular and extendable tool designed for outbreak surveillance and retrospective outbreak investigation. It extends the method developed for COVID-19 by Huisman et al. and makes it available for a variety of pathogens, outbreak scenarios, and observation types. Estimates obtained with estimateR can be interpreted directly or used to inform more complex epidemic models (e.g. for forecasting) on the value of R_e.

A modular plasmid toolkit applied in marine bacteria reveals functional insights during bacteria-stimulated metamorphosis.

A conspicuous roadblock to studying marine bacteria for fundamental research and biotechnology is a lack of modular synthetic biology tools for their genetic manipulation. Here, we applied, and generated new parts for, a modular plasmid toolkit to study marine bacteria in the context of symbioses and host-microbe interactions. To demonstrate the utility of this plasmid system, we genetically manipulated the marine bacterium Pseudoalteromonas luteoviolacea, which stimulates the metamorphosis of the model tubeworm, Hydroides elegans. Using these tools, we quantified constitutive and native promoter expression, developed reporter strains that enable the imaging of host-bacteria interactions, and used CRISPR interference (CRISPRi) to knock down a secondary metabolite and a host-associated gene. We demonstrate the broader utility of this modular system for testing the genetic tractability of marine bacteria that are known to be associated with diverse host-microbe symbioses. These efforts resulted in the successful conjugation of 12 marine strains from the Alphaproteobacteria and Gammaproteobacteria classes. Altogether, the present study demonstrates how synthetic biology strategies enable the investigation of marine microbes and marine host-microbe symbioses with potential implications for environmental restoration and biotechnology. IMPORTANCE Marine Proteobacteria are attractive targets for genetic engineering due to their ability to produce a diversity of bioactive metabolites and their involvement in host-microbe symbioses. Modular cloning toolkits have become a standard for engineering model microbes, such as Escherichia coli, because they enable innumerable mix-and-match DNA assembly and engineering options. However, such modular tools have not yet been applied to most marine bacterial species. In this work, we adapt a modular plasmid toolkit for use in a set of 12 marine bacteria from the Gammaproteobacteria and Alphaproteobacteria classes. We demonstrate the utility of this genetic toolkit by engineering a marine Pseudoalteromonas bacterium to study their association with its host animal Hydroides elegans. This work provides a proof of concept that modular genetic tools can be applied to diverse marine bacteria to address basic science questions and for biotechnology innovations.

A predictive model of Lunar Gateway molecular outgassing and plume-induced contamination

The Gateway space station will operate both as a lunar outpost and a hub for space exploration missions in support of a long-term human presence on the Moon, and is under development by NASA in collaboration with ESA, CSA, JAXA, and international commercial partners. Gateway will experience induced molecular contamination from sources including materials outgassing, venting, and the nominal operation of its chemical and electric propulsion systems. The degradation effects of molecular contamination on spacecraft are well-documented and understood, and predictive modeling tools have been developed to aid in the mitigation of such contamination effects in the mission design phase. Therefore, the Gateway Induced Environments and Thermal teams have worked with JPL Contamination Control to develop modular simulation tools for the prediction of molecular contaminant depositions across the mission life, and for use in requirements derivation and sensitivity assessments. Free-molecular transport and deposition of outgassing products onto sensitive Gateway receiver surfaces is calculated using a viewfactor matrix approach, while International Space Station (ISS)-heritage bipropellant plume models are used to evaluate contaminant fluxes generated by the operation of thrusters on Gateway modules and the Orion spacecraft. The alteration of optical properties, e.g. the solar absorptance, of contaminated surfaces is likewise calculated using an ISS-heritage semi-empirical model premised on flight and laboratory testing data. This framework is intended to support early identification of potential integration issues and establish a baseline for incorporating improved analysis and test data as the Gateway design matures.

Dynamical modelling and experimental validation of a fast and accurate district heating thermo-hydraulic modular simulation tool

This paper presents a new thermo-hydraulic model for district heating systems simulations, which aims at being a fast and accurate tool to simulate highly renewable networks characterized by fluctuating energy profiles. The main novel aspect of the tool lies in the heat transmission modelling over long pipes based on a Lagrangian numerical approach. In comparison to other existing models, this approach significantly reduces computational time and it increases results' accuracy. The elaborated method avoids numerical diffusion in the results and consequently allows proper prediction of temperature propagation, especially in case of fast changes of fluctuating profiles. The tool is built following a modular procedural programming approach in order to facilitate the simulation of multicomponent system. Thanks to its modular structure, every components of the system is built with the same structure that is differently declined according to each component's requirements. In this way, new additional elements' models easily fit the existing ones.The model is validated under real operating conditions with hourly monitoring data of an Italian district heating network.The results show good correspondence also in the most peripheral nodes of the network, where the largest deviations are normally encountered, thus making the model a reliable and fast simulation tool for district heating network design and operational control.

Hybrid spheroid microscaffolds as modular tissue units to build macro-tissue assemblies for tissue engineering.

Since its inception, tissue engineering and regenerative medicine (TERM) has been relying on either scaffold-based or scaffold-free strategies. Recent reports outlined the possibility of a synergistic, convergence approach, referred to as the third TERM strategy, which could alleviate bottlenecks of the two previous options. This strategy requires the fabrication of highly porous microscaffolds, allowing to create single spheroids within each of them. The resulting tissue units can then be combined and used as modular building blocks for creating tissue constructs through a bottom-up self-assembly. Such strategy can have a significant impact for the future of TERM, but so far, no reports have assessed its feasibility in detail. This work reports a first systematic study, which includes a comparison of the in vitro behavior of tissue units based on adipose derived stem cell spheroids cultured within microscaffolds versus conventional spheroids. We first proved that the presence of the microscaffold neither impairs the cells 'ability to form spheroids nor impacts their viability. Importantly, the fusiogenic and the differentiation potential (i.e. chondrogenesis and osteogenesis), which are important features for cellularized building blocks to be used in TERM, are preserved when spheroids are cultured within microscaffolds. Significant benefits of microscaffold-based tissue units include the enhanced cell retention, the decreased compaction and the better control over the size observed when larger tissue constructs are formed through self-assembly. The proof of concept study presented here demonstrates the great potential offered by those microsize tissue units to be used as building blocks for directed tissue self-assembly. STATEMENT OF SIGNIFICANCE: One of the most exciting and recent advances in tissue engineering and regenerative medicine (TERM) is to combine together multiple micro-size cellularized units, which are able to self-assemble altogether to recreate larger tissue constructs. In this work, we produce such modules by forming single spheroids within highly porous microscaffolds, and study how this new microenvironment impacts on the spheroid's behavior and stemness potential. This work highlights as well that such novel route is enabled by two-photon polymerization, which is an additive manufacturing technique offering high spatial resolution down to 100 nm. These findings provide a first scientific evidence about the utilization of hybrid spheroid microscaffold-based tissue units with great perspective as a modular tool for TERM.

Research on the strong transient process of the secondary air system in the Aero-engine based on the network method

A coupled model of engine mainstream way with secondary air system was established based on the network method. The change rule of engine performance, air system parameters and axial force was simulated when the aero-engine was sunk in shaft failure. The dynamic parameters of the secondary air system could be forecast accurately based on the analysis of transient algorithm, and the transient axial force also could be calculated. So the simulation data can be provided for the engineering design, and it can help the designer improve the secondary air system design. Moreover, its modular character allows integration of further detailed air-system unites and establishment of more complex air system network. The resultant modular tool is prospect in studying the complex dynamic characteristics and mechanism in Aero-engine air system.

Toward the end-to-end optimization of particle physics instruments with differentiable programming

The full optimization of the design and operation of instruments whose functioning relies on the interaction of radiation with matter is a super-human task, due to the large dimensionality of the space of possible choices for geometry, detection technology, materials, data-acquisition, and information-extraction techniques, and the interdependence of the related parameters. On the other hand, massive potential gains in performance over standard, “experience-driven” layouts are in principle within our reach if an objective function fully aligned with the final goals of the instrument is maximized through a systematic search of the configuration space. The stochastic nature of the involved quantum processes make the modeling of these systems an intractable problem from a classical statistics point of view, yet the construction of a fully differentiable pipeline and the use of deep learning techniques may allow the simultaneous optimization of all design parameters. In this white paper, we lay down our plans for the design of a modular and versatile modeling tool for the end-to-end optimization of complex instruments for particle physics experiments as well as industrial and medical applications that share the detection of radiation as their basic ingredient. We consider a selected set of use cases to highlight the specific needs of different applications.

Dynamically coupling system dynamics and SWAT+ models using Tinamït: application of modular tools for coupled human–water system models

Abstract. Participatory water resource management requires modeling techniques that are accurate and flexible yet stakeholder-friendly. While different modeling frameworks offer advantages and disadvantages, system dynamics (SDs) models have seen sustained use as a stakeholder-friendly approach for participatory water resource modeling. Physically based models (e.g., SWAT+) have seen sustained use to model the hydrological components of water systems. Proposed as a way to combine the relative strengths of both modeling paradigms, model coupling allows researchers to, for example, build participatory SD models with stakeholders, while delegating the hydrological components of the overall model to an external hydrological model. Recently developed to facilitate model coupling, the Tinamït Python package presents an extensible, outward-facing application programming interface (API). It allows for the development of extensions (wrappers) that expand compatibility with different physically based models. However, no watershed hydrological model has yet been connected to this API. In the present study, a socket and JavaScript Object Notation (JSON)-based communication protocol was developed with the goal of facilitating the coupling of models written in languages such as Fortran. This novel protocol served to develop a Tinamït-compatible wrapper for the hydrological model SWAT+, allowing it to be coupled to human–water SD models. The novel coupling protocol was then applied to a case study of Tanzania's Usa river catchment. This approach provides the modeler with the benefits of both physically based and SD models, thereby allowing the detection of potentially far-reaching effects of policy-makers' decisions.

A decision support tool for e-waste recycling operations using the hen-and-chicks bio-inspired optimization metaheuristic

E-waste from end-of-life electrical and electronic devices is one of the fastest growing waste streams from households and businesses. E-waste recycling yields environmental sustainability and economic benefits. Due to continuous changes in e-waste types and compositions, recycling businesses face challenges to optimize their operational configuration to achieve better economic and environmental performance. To help e-waste recyclers mitigate this problem, we have developed a modular decision support tool called the Comprehensive Manufacturing Assessment Tool (CMAT) that can simulate both e-waste recycling operations and economics. This tool can give valuable insights regarding the profitability of the entire operation and different e-waste types. In addition, a new bio-inspired metaheuristic optimization algorithm, hen-and-chicks optimization (HACO), was developed to assign manpower to different workstations to maximize operational efficiencies. According to the results of our case study, laptops, desktops, and computer peripherals are the three electronic waste products that produce the most profit. Our examination of the sensitivity of material prices shows that the price of steel has the most significant influence on total profit, because it is the most widely used material in the majority of electronic devices. We have released the decision support tool as open-source software under a general public license. It could be customized for other recycling industries beyond e-waste to achieve business sustainability by making their operations more efficient.

Delivering the next generation of cancer immunotherapies with RNA

Decades of oncologic clinical use have demonstrated that cancer immunotherapy provides unprecedented therapeutic benefits. Tragically, only a minority of patients respond to existing immunotherapies. RNA lipid nanoparticles have recently emerged as modular tools for immune stimulation. Here, we discuss advancements in RNA-based cancer immunotherapies and opportunities for improvement.

BarleyExpDB: an integrative gene expression database for barley

BackgroundRNA-sequencing (RNA-seq) has been widely used to study the dynamic expression patterns of transcribed genes, which can lead to new biological insights. However, processing and analyzing these huge amounts of histological data remains a great challenge for wet labs and field researchers who lack bioinformatics experience and computational resources.ResultsWe present BarleyExpDB, an easy-to-operate, free, and web-accessible database that integrates transcriptional profiles of barley at different growth and developmental stages, tissues, and stress conditions, as well as differential expression of mutants and populations to build a platform for barley expression and visualization. The expression of a gene of interest can be easily queried by searching by known gene ID or sequence similarity. Expression data can be displayed as a heat map, along with functional descriptions as well as Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Proteins Families Database, and Simple Modular Architecture Research Tool annotations.ConclusionsBarleyExpDB will serve as a valuable resource for the barley research community to leverage the vast publicly available RNA-seq datasets for functional genomics research and crop molecular breeding.

Pan-cancer classification of single cells in the tumour microenvironment

Single-cell RNA sequencing can reveal valuable insights into cellular heterogeneity within tumour microenvironments (TMEs), paving the way for a deep understanding of cellular mechanisms contributing to cancer. However, high heterogeneity among the same cancer types and low transcriptomic variation in immune cell subsets present challenges for accurate, high-resolution confirmation of cells’ identities. Here we present scATOMIC; a modular annotation tool for malignant and non-malignant cells. We trained scATOMIC on >300,000 cancer, immune, and stromal cells defining a pan-cancer reference across 19 common cancers and employ a hierarchical approach, outperforming current classification methods. We extensively confirm scATOMIC’s accuracy on 225 tumour biopsies encompassing >350,000 cancer and a variety of TME cells. Lastly, we demonstrate scATOMIC’s practical significance to accurately subset breast cancers into clinically relevant subtypes and predict tumours’ primary origin across metastatic cancers. Our approach represents a broadly applicable strategy to analyse multicellular cancer TMEs.