Optimization Platform Research Articles

Multidisciplinary Optimization of a Mixed-flow Impeller with 140 Parameters and its Shapley Additive Explanations

Abstract In recent years, we have made several improvements to the geometric parameterization method, the surrogate model method, and the sampling method, with the goal of making the traditional surrogate model-based optimization method applicable to aerodynamic optimization of hundreds of parameters with reasonable computational cost. However, increasing the number of control parameters raises two additional issues. First, the impeller geometry becomes too complex to ensure the required mechanical performance. Second, the optimization mechanism becomes difficult to understand with too many parameters. To address the first issue, this paper builds a multidisciplinary optimization platform to achieve the optimization of a large flow coefficient mixed-flow impeller under 140 control parameters, resulting in a significant improvement in both aerodynamic and mechanical performance. To address the latter, a novel machine learning interpretation tool, Shapley Additive Explanations (SHAP), is introduced in this paper. Using this methodology, the contribution of all 140 parameter values in the final optimal impeller to each aspect of the performance improvement is presented in this paper, providing the first in-depth understanding of the intricate mechanisms involved in the multidisciplinary optimization of hundreds of control parameters.

Unveiling Intrinsic Bulk Photovoltaic Effect in Atomically Thin ReS2.

The bulk photovoltaic effect (BPVE) offers a promising avenue to surpass the efficiency limitations of current solar cell technology. However, disentangling intrinsic and extrinsic contributions to photocurrent remains a significant challenge. Here, we fabricate high-quality, lateral devices based on atomically thin ReS2 with minimal contact resistance, providing an optimal platform for distinguishing intrinsic bulk photovoltaic signals from other extrinsic photocurrent contributions originating from interfacial effects. Our devices exhibit large bulk photovoltaic performance with intrinsic responsivities of ∼1 mA/W in the visible range, without the need for external tuning knobs such as strain engineering. Our experimental findings are supported by theoretical calculations. Furthermore, our approach can be extrapolated to investigate the intrinsic BPVE in other noncentrosymmetric van der Waals materials, paving the way for a new generation of efficient light-harvesting devices.

Decision Support Model for Selecting the Optimal Blockchain Oracle Platform: An Evaluation of Key Factors

Smart contract-based applications are executed in a blockchain environment, and they cannot directly access data from external systems, which is required for the service provision of these applications. Instead, smart contracts use agents known as blockchain oracles to collect and provide data feeds to the contracts. The functionality and compatibility with smart contract applications need to be considered when selecting the best-fit oracle platform. As the number of oracle alternatives and their features increases, the decision-making process becomes increasingly complex. Selecting the wrong or sub-optimal oracle is costly and may lead to severe security risks. This paper provides a decision support model for the oracle selection problem. The model supports smart contract decision-makers in selecting a secure, cost-effective, and feasible oracle platform for their applications. We interviewed oracle co-founders and smart contracts experts to refine and validate the decision model. Two real-world smart contract application case studies were used to evaluate the model. Our model prioritises and suggests more than one possible oracle platform based on the developer's required criteria, security assessment, and cost analysis. Moreover, this guided decision model serves to reveal issues that may go unnoticed if done haphazardly, reduce decision-making efforts, and provide a cost-effective solution.

Tailoring the Electronic Structure and Properties of Graphdiyne by Cyano Groups.

Two-dimensional (2D) materials, such as 2D carbon-based systems, have been recently the subject of intense studies, thanks to their optoelectronic properties and promising electronic performances. 2D carbon-based materials such as graphdiyne (GDY) represent an optimal platform for tuning the optoelectronic properties via precise chemical functionalization. Here, we report a synthetic strategy to precisely introduce cyano groups into the 2D GDY backbone in order to tune the electronic properties of GDY. Three kinds of cyano-modified GDY have been synthesized, namely, bearing one cyano group (CNGDY), two CN in meta (m-CNGDY), and two in para (p-CNGDY) positions. A variety of experimental data as well as first-principles calculations allowed us to elucidate the role of the cyano groups in tuning the structural and functional properties of GDYs. We found that an increase in the number of cyano groups reduces the interlayer spacing between GDY layers, increases the lithium adsorption amount, as well as impacts the lithium diffusion rate, while changes in meta- or para-position impact the energy band gap.

Targeting Alzheimer's disease with novel dual-function 3,5-diaryl-4,5-dihydro-1H-pyrazole-1-carbothioamide derivatives

In the field of medicinal chemistry, the versatility of the thiosemicarbazone scaffold makes it a promising platform for the development of next-generation pharmaceuticals. In this paper the thiosemicarbazone scaffold was explored to obtain novel series of derivatives: a) thiosemicarbazones 15–31, and 33 containing a linear thiosemicarbazone scaffold, b) 34–38 and 44–64 containing pyrazoline ring, and c) 39–43 containing the dihydropyrimidine cycle. Among these, compounds 21, 23, 26, 33–35, 37, 38, 44, 57, 61, and 62 demonstrated no significant cytotoxic effects on HDFa cells at concentrations up to 500 μg/mL. Importantly, compounds 21, 23, 26, 33, 34, 35, and 37 exhibited significant protective effects against neurotoxicity induced by beta-amyloid peptide (1-42) in differentiated SHSY-5Y cell cultures. Enzymatic assays targeting BACE1 and AChE revealed modest inhibitory activity in compounds 21, 23, and 34, 37, respectively. The identification of compounds with inhibitory effects and neuroprotective activity against beta-amyloid peptide (1-42) offers a platform for further optimization and refinement of these compounds to enhance their potency and selectivity.

Along-track deployment control of space tether system for SAR-GMTI mission

Global, 24/7, and all-weather Synthetic Aperture Radars (SARs) are optimal platforms for Ground Moving Target Indication (GMTI) missions, and the tether constraint provides a stable mechanic connection for such configurations. To fulfill the requirements of such missions, the Space Tether System (STS) must be deployed to horizontal positions to form the necessary along-track interference baseline, which is unstable relative to traditional vertical positions and has not received adequate focus. To deal with this problem, this study focuses on the deployment control of the STS to the unstable horizontal positions. Firstly, the properties of the STS at the horizontal position are analyzed, and a synthetic criterion of measurement error is defined based on the observation principle of the GMTI mission. Secondly, two deployment control strategies are proposed, and corresponding desired trajectories are generated by considering two occasions respectively. In the end, considering the instability of horizontal positions, an adaptive closed-loop controller is designed utilizing the backstepping method to address gravitational moment and other disturbances. Simulations demonstrate that the system can successfully attain the desired horizontal positions under both deployment strategies, and the designed controller can quickly track trajectories under initial state errors and external disturbances.

Application of digital twin for industrial process control: A case study of gauge-looper-tension optimized control in strip hot rolling

Background During the hot rolling process, the performance of most control systems gradually degrades due to equipment aging and changing process conditions. However, existing gauge-looper-tension control method remain restricted by a lack of intelligent parameter maintenance strategies. Methods To address this challenge and enhance the smart manufacturing capabilities of strip hot rolling, based on the digital twin method, this paper proposes a data-driven optimized control method for the gauge-looper-tension system of strip hot rolling. First, a hot rolling process model is constructed based on a digital twin method to serve as an evaluation and optimization platform. Subsequently, relevant data are collected to calculate the Hurst index for identifying the performance of the controller during the rolling process. Additionally, for controllers with poor Hurst index values, the crayfish optimization algorithm is employed for adjusting controller parameters to maximum the Hurst index. Results A real case of hot rolling steel production was used to validate the proposed data-driven optimized control method. Experimental results demonstrate that the proposed evaluation method can effectively recognize the state of gauge-looper-tension controller. Moreover, after optimizing the controller parameters through crayfish optimization algorithm (COA), the value of Hurst index showed significant improvement. Conclusions The proposed digital twin -based optimized control method effectively enhance the manufacturing capability and maintain strategy of hot rolling steel production. Through the proposed method, the Hurst index of gauge-looper-tension system increasing from 0.574 to 0.862.

An In Vitro Platform for Pharmacokinetic Quantification and Optimization of Cerebrospinal Fluid Filtration and Drug Circulation

Abstract Background: Modification of cerebrospinal fluid (CSF) transport dynamics is an expanding method for treating central nervous system injury and diseases. One application of this route is to modify the distribution of solutes in the CSF, however few tools currently exist for this purpose. The present study describes the use of a subject-specific in-vitro CSF phantom to perform a parametric evaluation of the Neurapheresis? CSF Management System (NP) for both CSF filtration and intrathecal drug circulation. Methods: An in-vitro CSF phantom was constructed which included realistic anatomy for the complete subarachnoid space. This platform was configured to test multiple parametric modifications of a dual-lumen catheter and filtration system. Calibrated mapping of tracer distribution and area under the curve (AUC) measurements were used to compare filtration and intrathecal-circulation schemes using the NP device versus the clinical standards of care. Results: The NP device showed potential advantages over lumbar drain (LD) for clearance of simulated subarachnoid hemorrhage, especially in the spinal canal. Use of the NP device in combination with simulated intracerebroventricular drug infusion (ICV) resulted in an increased extent and uniformity of tracer spread compared to ICV alone. Conclusion: NP improved clearance of simulated subarachnoid hemorrhage compared to LD and increased uniformity of tracer concentration via simulated ICV, providing support for NP use in these scenarios. The in-vitro CSF phantom system presented here quantitatively described the effects of parametric boundary modification on solute distribution in the intrathecal space.

Reactivity Profiling for High-Yielding Ynamine-Tagged Oligonucleotide Click Chemistry Bioconjugations.

The Cu-catalyzed azide-alkyne cycloaddition (CuAAC) reaction is a key ligation tool used to prepare bioconjugates. Despite the widespread utility of CuAAC to produce discrete 1,4-triazole products, the requirement of a Cu catalyst can result in oxidative damage to these products. Ynamines are superior reactive groups in CuAAC reactions and require lower Cu loadings to produce 1,4-triazole products. This study discloses a strategy to identify optimal reaction conditions for the formation of oligodeoxyribonucleotide (ODN) bioconjugates. First, the surveying of reaction conditions identified that the ratio of Cu to the choice of reductant (i.e., either sodium ascorbate or glutathione) influences the reaction kinetics and the rate of degradation of bioconjugate products. Second, optimized conditions were used to prepare a variety of ODN-tagged products and ODN-protein conjugates and compared to conventional CuAAC and Cu-free azide-alkyne (3 + 2)cycloadditions (SPAAC), with ynamine-based examples being faster in all cases. The reaction optimization platform established in this study provides the basis for its wider utility to prepare CuAAC-based bioconjugates with lower Cu loadings while maintaining fast reaction kinetics.

Acoustic evaluation of voice signal distortion by videoconferencing platforms and devices used in telepractice for cleft palate.

The usefulness and effectiveness of telepractice have been reported in recent years. Treatment of cleft palate patients with compensatory articulation is based on perceptual identification. Telepractice using videoconferencing platforms causes voice signal distortion and impacts auditory-perceptual perception. This study aimed acoustically examine voice signal distortion and determine the optimal videoconferencing platforms, in addition to the phonemes that can be discriminated with the same quality as in face-to-face interactions. ATR503 with 50 phoneme-balanced Japanese speech sentences was used as a reference corpus. Four videoconferencing platforms, -Zoom, Cisco Webex, Skype, and Google Meet, -and five devices, -iPhone, Android, iPad Air, Windows, and MacBook Pro were used as transmission conditions to examine voice signal distortions with the objective measure log-spectral distortion (LSD). Tukey's test was conducted to evaluate the degree of consonant distortion related to voicings (voiceless and voiced), places of articulation (bilabial, alveolar, alveolo-palatal, palatal, velar, labial-velar, and glottal), and manners of articulation (plosive, fricative, affricate, tap or flap, nasal, and approximant). With statistically significant differences, voiced, bilabial, labial-velar, nasal, and plosive consonants exhibited smaller distortions. In contrast, voiceless, alveolo-palatal, fricative, and affricate consonants exhibited larger distortions. Google Meet exhibited the lowest distortion among videoconferencing platforms and MacBook exhibited the lowest distortion among devices. This study provides significant insights into the telepractice strategies with the appropriate videoconferencing platform and device, and useful settings for cleft palate patients with compensatory articulations with respect to acoustics.

Rethinking internationalization of higher education for society from an outside-in perspective

ABSTRACT Amid increasing criticism of the internationalization of higher education (IoHE) for its Anglo-centric tendencies, there has been discussion of the need to reconsider the rationales for and approaches to IoHE. Specifically it has been argued that there is an urgent need to focus IOHE more sharply on addressing the many complex and persistent issues faced by local and global communities. As part of the discussion, a new model of IoHE, ‘internationalisation of higher education for society’ (IHES) has been proposed by prominent scholars in the field. This paper seeks to make a positive contribution to the discussion of IHES. Our aim is to refine the concept by integrating an ‘outside-in’ perspective, a viewpoint currently missing from the existing conceptualization of IHES. The paper answers three unique research questions: 1) What are the implications of contemporary societal transitions for IoHE? 2) How can universities use their internationalization activities to more effectively facilitate societal transformations? 3) What are the implications of reforming the rationales of IoHE from the perspective of university–society relations? We highlight that collaborations in higher education between East Asian and Nordic countries offer an optimal platform to explore and promote the potential of a new paradigm of IoHE.

Mass customization using hybrid manufacturing and smart assembly: An optimal configuration and platform design approach

Hybrid Manufacturing (HM) and smart assembly stand as pivotal pillars in advanced smart manufacturing systems, offering manufacturers highly efficient and adaptable solutions for manufacturing. This paper delves into the configuration of a production line that integrates HM and assembly stages, each comprising multiple cells, with each cell housing one or more parallel stations. The objective is to manufacture a family of final assemblies, leveraging the platform concept to defer mass customization to later stages and thereby minimize processing costs. A mathematical programming model is proposed to identify the optimal configuration for such production lines, considering constraints such as an allowable capital cost and machine availabilities. In addition, the precedence, inclusion, and seclusion restrictions imposed on the part family are considered. The proposed mathematical programming model aims to delineate which HM features are processed in the part platform cell versus those processed in the mass customization (part variants) cells. Simultaneously, the model determines the components (variants from the HM stage) of final assemblies processed in the assembly platform cell, as well as components assembled or disassembled in the final assembly cells. Furthermore, the model seeks to determine the required number of stations in each cell to meet periodic demand. The overall objective of the model is to minimize the capital and the processing cost. A detailed case study illustrates the effectiveness of the proposed configuration approach and mathematical model. The proposed model is solvable in a few seconds by using commercial solvers.

Study on the Internal Flow Characteristics of High Flowrate Emergency Drainage Series-parallel Pump

Abstract Floods have become the main natural disaster threatening the safety of peoples lives and property. It is of great significance to develop high flow emergency drainage equipment. An innovative structure of pumps with high flow rate and multiple operating conditions is proposed in this paper to achieve series and parallel operation. It established an automatic optimization platform that integrates functions such as 3D modeling, mesh generation, computational fluid dynamics, and scheme optimization, and developed an efficient hydraulic model for a volute mixed flow pump combining flow field diagnostic techniques. The research results indicate that the inlet distortion of the secondary stage pump is the main cause of pump performance loss for both series and parallel operation condition. The third-generation vortex identification method was used to diagnose the internal flow of the pump under two operating conditions and control strategies were proposed. The final optimization scheme show that the pump can reach 1800 m3/h with a head of 9.6m and efficiency of 80% in parallel operation condition. In series operation condition, the pump can reach 900 m3/h with a head of 18.3m and an efficiency of 75.3%.

Evaluation of Recombinant Antibody Production Efficiency in CHO Cells with Sleeping Beauty Transposon Vector System

Chinese hamster ovary (CHO) mammalian cell lines are widely used as cell platforms in biopharmaceutical productions. Different transfection systems are employed for the integration of the target gene cassette into the cell genome and have limitations, such as (i) the integration region in the genome, (ii) the size of the target cassette, and (iii) long selection periods for stable expression. Transposon systems can be utilized to overcome the limitations mentioned in the efficient production of commercially significant recombinant proteins. This study aims to demonstrate the differences in production potential and selection periods by using a specially designed vector system for random genome integration in CHODG44 DHFR -/- cells and the Sleeping Beauty (SB) transposon system. In this context, the optimal transfer ratio between the donor and the helper plasmid was determined for the most efficient co-transfection in the SB transposon system. According to the results, the pools obtained using the SB transposon system had titers ranging from 1300 to 2600 mg/L in 13-day fed-batch studies, while the pool obtained using the random transfer system had a titer of 0.056 mg/L. Additionally, stable cell pools obtained using the transposon system underwent selection in a short period of 52 days, compared to over 100 days for the pool obtained through random transfer. Considering all these results together, it is demonstrated that stable CHO pools obtained using the optimal SB transposon system can achieve high-efficiency monoclonal antibody production in a short period, making it an optimal production platform in the biopharmaceutical field.

SQL2FPGA: Automated Acceleration of SQL Query Processing on Modern CPU-FPGA Platforms

Today’s big data query engines are constantly under pressure to keep up with the rapidly increasing demand for faster processing of more complex workloads. In the past few years, FPGA-based database acceleration efforts have demonstrated promising performance improvement with good energy efficiency. However, few studies target the programming and design automation support to leverage the FPGA accelerator benefits in query processing. Most of them rely on the SQL query plan generated by CPU query engines and manually map the query plan onto the FPGA accelerators, which is tedious and error-prone. Moreover, such CPU-oriented query plans do not consider the utilization of FPGA accelerators and could lose more optimization opportunities. In this article, we present SQL2FPGA, an FPGA accelerator-aware compiler to automatically map SQL queries onto the heterogeneous CPU-FPGA platforms. Our SQL2FPGA front-end takes an optimized logical plan of an SQL query from a database query engine and transforms it into a unified operator-level intermediate representation. To generate an optimized FPGA-aware physical plan, SQL2FPGA implements a set of compiler optimization passes to (1) improve operator acceleration coverage by the FPGA, (2) eliminate redundant computation during physical execution, and (3) minimize data transfer overhead between operators on the CPU and FPGA. Furthermore, it also leverages machine learning techniques to predict and identify the optimal platform, either CPU or FPGA, for the physical execution of individual query operations. Finally, SQL2FPGA generates the associated query acceleration code for heterogeneous CPU-FPGA system deployment. Compared to the widely used Apache Spark SQL framework running on the CPU, SQL2FPGA—using two AMD/Xilinx HBM-based Alveo U280 FPGA boards and Ver.2020 AMD/Xilinx FPGA overlay designs—achieves an average performance speedup of 10.1x and 13.9x across all 22 TPC-H benchmark queries in a scale factor of 1 GB (SF1) and 30 GB (SF30), respectively. While evaluated on AMD/Xilinx Alveo U50 FPGA boards, SQL2FPGA using Ver. 2022 AMD/Xilinx FPGA overlay designs also achieve an average speedup of 9.6x at SF1 scale factor.

Dissimilar soliton molecule formed by dissipative pulses in a single-mode mode-locked fiber laser

Soliton molecules, or also known as optical bound states, are the most representative example of solitons’ particle nature and have given birth to diverse light-matter analogies. Despite detailed research on regular bound states, the soliton molecule synthesis of dissimilar pulses has rarely been reported. Here, soliton molecules formed by dissimilar dissipative solitons are demonstrated in a single-mode mode-locked fiber laser, with an in-depth analysis of their evolution dynamics. This novel bound state features pulse trapping between two ultrafast vector pulses with distinct pulse properties including energy, duration, and chirp, leading to unique temporal and spectral profiles. This laser provides an optimal platform for studying complex interactions between different types of dissipative solitons. The findings here can provide new degrees of freedom for the generation of optical soliton molecules and can fuel applications in optical information processing, metrology, and spectroscopy.

Comparative Analysis of Topology Optimization Platforms for Additive Manufacturing of Robot Arms

Recently, CAD environments have integrated topology optimization (TO) tools, enabling rapid development and manufacturing of parts with optimized mechanical properties. However, different CAD platforms incorporate TO differently, making a comparative analysis necessary. This study aims to systematically compare the efficiency, material usage, and design quality of five commonly used CAD/TO platforms when applied to the topology optimization of a six degrees of freedom robotic arm. The objective is to identify the key differences in how these platforms influence the final design and manufacturing outcomes. Practical validation of results is provided by printing and assembling optimized components into a fully functional robotic arm. Our findings indicate differences in optimization efficiency, material usage, and print time between analyzed platforms. Strengths and weaknesses of each platform are indicated and recommendations for optimization parameters are provided.

Innovating Civil Engineering: Strategies for Fostering Stakeholder Engagement in the Circular Economy

Sustainability and circular economy principles are increasingly important in civil engineering, as highlighted by the United Nations Environmental Programme in 2023 the construction activities represented 36% of global energy use in 2020. However, the sector's focus on reducing operational carbon overshadows the need for addressing embodied carbon from materials like cement, steel, and aluminium. To address this, a shift towards incentivizing all supply chain stakeholders and cultivating collaborative models is necessary. This research provides an initial scoping for the development of the Lithuanian Construction Materials Reuse Optimization (LSEPO) platform, a pioneering regional initiative fostering a marketplace for reused building materials. Such platforms are recognized for their potential to overcome sustainability barriers by utilizing digital technologies for efficient data management and stakeholder collaboration. Our research identifies a significant gap in the existing literature concerning effective stakeholder engagement strategies critical for the success of such platforms. To bridge this gap, we employed a three-tiered methodological approach: firstly, a semi-structured literature analysis delved into existing stakeholder engagement strategies within the circular economy. This review highlighted a fragmented understanding of incentives and collaboration dynamics across different sectors. Secondly, a content analysis of global material exchange and circular construction platforms provided insights into best practices, showcasing successful communication methods, innovative incentive models, and robust collaboration frameworks. Lastly, integrating these findings, our study proposes a conceptual stakeholder engagement framework tailored for social innovation in civil engineering, more specifically Lithuanian Construction Materials Reuse Optimization (LSEPO). Practical implications of our findings underscore the necessity for platforms like LSEPO to incorporate adaptive engagement strategies that are context-sensitive and inclusive, facilitating a broad spectrum of stakeholder inputs. The study demonstrates that effective stakeholder engagement goes beyond traditional communication methods; it requires a systemic integration of technological innovation and incentive alignment to promote sustained participation and collaboration. By providing a comprehensive foundation for the development of the LSEPO platform, this research not only aims to advance it as a beacon of social innovation and environmental stewardship within the civil engineering sector but also sets a benchmark for future initiatives aiming to embed circular economy principles effectively.

An integrated optimization method for the damper placements, shape and size of truss structures

This work extends the application of the approximation concept in dynamic topology optimization for truss structures. The corresponding problem contains both continuous and discrete variables, encompassing damper placements, truss shape and cross-sectional area. First, the utilization of a branched multipoint approximation (BMA) function establishes sequential approximation problems that also involve such mixed variables, marking its innovative application in dynamic optimization. Then, a modified genetic algorithm (GA) is used to optimize discrete variables. To enhance convergence stationarity, the concept of ‘adjacent individuals’ is proposed to control the degree of difference in topology configuration between initial population members and the current optimal. Additionally, adjustments to the sequence-based crossover process ensure compliance with damper quantity constraints. Examples demonstrate that the introduction of adjacent individuals is beneficial to convergence stationarity, and the shape change of the truss increases the mode damping ratio by more than 20%. The created optimization platform can also tackle other mixed variables optimization problems.

Structured multicellular intestinal spheroids (SMIS) as a standardized model for infection biology

Background3D cell culture models have recently garnered increasing attention for replicating organ microarchitecture and eliciting in vivo-like responses, holding significant promise across various biological disciplines. Broadly, 3D cell culture encompasses organoids as well as single- and multicellular spheroids. While the latter have found successful applications in tumor research, there is a notable scarcity of standardized intestinal models for infection biology that mimic the microarchitecture of the intestine. Hence, this study aimed to develop structured multicellular intestinal spheroids (SMIS) specifically tailored for studying molecular basis of infection by intestinal pathogens.ResultsWe have successfully engineered human SMIS comprising four relevant cell types, featuring a fibroblast core enveloped by an outer monolayer of enterocytes and goblet cells along with monocytic cells. These SMIS effectively emulate the in vivo architecture of the intestinal mucosal surface and manifest differentiated morphological characteristics, including the presence of microvilli, within a mere two days of culture. Through analysis of various differentiation factors, we have illustrated that these spheroids attain heightened levels of differentiation compared to 2D monolayers. Moreover, SMIS serve as an optimized intestinal infection model, surpassing the capabilities of traditional 2D cultures, and exhibit a regulatory pattern of immunological markers similar to in vivo infections after Campylobacter jejuni infection. Notably, our protocol extends beyond human spheroids, demonstrating adaptability to other species such as mice and pigs.ConclusionBased on the rapid attainment of enhanced differentiation states, coupled with the emergence of functional brush border features, increased cellular complexity, and replication of the intestinal mucosal microarchitecture, which allows for exposure studies via the medium, we are confident that our innovative SMIS model surpasses conventional cell culture methods as a superior model. Moreover, it offers advantages over stem cell-derived organoids due to scalability and standardization capabilities of the protocol. By showcasing differentiated morphological attributes, our model provides an optimal platform for diverse applications. Furthermore, the investigated differences of several immunological factors compared to monotypic monolayers after Campylobacter jejuni infection underline the refinement of our spheroid model, which closely mimics important features of in vivo infections.