River and lake dredging projects inevitably produce significant quantities of wastewater and sediment. This accumulation results in dredged soil with high moisture content, characterized by low strength, rendering it unsustainable for use. To facilitate environmentally friendly utilization of wastewater and sediment, solidifying agents and basalt fibers are introduced to solidify the wastewater within the dredged sediment. This process transforms the wastewater, sediment, solidifying agents, and basalt fibers into a novel, strengthened material. This transformation allows for their application as stabilized soil for engineering endeavors. Indoor experiments and scanning electron microscope analyses were performed to examine the deformation characteristics of fiber-stabilized soil and analyze its micro-mechanisms. Research findings suggest that as the curing age increases, the curing agent’s reaction becomes more comprehensive. Fibers have the potential to ameliorate soil damage. The proposed binary-medium model’s applicability and accuracy were validated through the analysis of triaxial test results employing the reinforcement principle. These findings establish a theoretical foundation for the resourceful utilization of wastewater and sediment. Full article

The planning, regulation and effectiveness of the product design process depend on various characteristics. Recently, bio-inspired collective intelligence approaches have been applied in this process in order to create more appealing product forms and optimize the design process. In fact, the use of neural network models in product form design analysis is a complex process, in which the type of network has to be determined, as well as the structure of the network layers and the neurons in them; the connection coefficients, inputs and outputs have to be explored; and the data have to be collected. In this paper, an impulsive discrete fractional neural network modeling approach is introduced for product design analysis. The proposed model extends and complements several existing integer-order neural network models to the generalized impulsive discrete fractional-order setting, which is a more flexible mechanism to study product form design. Since control and stability methods are fundamental in the construction and practical significance of a neural network model, appropriate impulsive controllers are designed, and practical Mittag-Leffler stability criteria are proposed. The Lyapunov function strategy is applied in providing the stability criteria and their efficiency is demonstrated via examples and a discussion. The established examples also illustrate the role of impulsive controllers in stabilizing the behavior of the neuronal states. The proposed modeling approach and the stability results are applicable to numerous industrial design tasks in which multi-agent systems are implemented. Full article

Due to the rapid development of high-speed trains, the service safety of vehicle body materials and structures has become a focal point in transport and impact engineering. Numerical simulations on the collision resistance of vehicle materials and structures are crucial for the safety assessment and optimal structural design of high-speed trains but have not been fully investigated due to the lack of damage model parameters. This study focuses on the Johnson-Cook (J-C) constitutive and damage-fracture models of a typical vehicle material, Q345C steel. A series of mechanical tests are conducted on the Q345C steel, including the quasi-static and dynamic compression/tension tests, quasi-static tension tests at different temperatures, and fracture tests along different stress paths, using the material test system and the split Hopkinson pressure/tension bar. Then, the parameters of the Johnson-Cook constitutive and damage-fracture models are calibrated based on the experimental results. In terms of the damage parameters related to stress paths, a new method of combining experiments and simulations is proposed to obtain the real, local fracture strains of the Q345C steel samples. This method allows the measurements of equivalent plastic strain and stress triaxiality histories under nonlinear stress paths, which are hardly accessible from individual experiments, and facilitates the accurate calibration of stress-path-related damage parameters. In addition, a high-speed plate penetration test is used to validate the J-C parameters, which can be directly implemented in the commercial finite element software Abaqus. The projectile trajectories from the simulation and experiment agree well with each other, demonstrating the reliability of the model parameters for impact scenarios and the efficiency of the experimental procedures utilized for calibration. Full article

In response to the global megatrends of digitalization and transportation automation, Turku University of Applied Sciences has developed a test platform to advance autonomous maritime operations. This platform includes the unmanned surface vessel eM/S Salama and a remote operations center, both of which are detailed in this article. The article highlights the importance of collecting and annotating multi-modal sensor data from the vessel. These data are vital for developing deep learning algorithms that enhance situational awareness and guide autonomous navigation. By securing relevant data from maritime environments, we aim to enhance the autonomous features of unmanned surface vessels using deep learning techniques. The annotated sensor data will be made available for further research through open access. An image dataset, which includes synthetically generated weather conditions, is published alongside this article. While existing maritime datasets predominantly rely on RGB cameras, our work underscores the need for multi-modal data to advance autonomous capabilities in maritime applications. Full article

Venom peptides have evolved to target a wide range of membrane proteins through diverse mechanisms of action and structures, providing promising therapeutic leads for diseases, including pain, epilepsy, and cancer, as well as unique probes of ion channel structure-function. In this work, a high-throughput FLIPR window current screening assay on T-type Ca_V3.2 guided the isolation of a novel peptide named ω-Buthitoxin-Hf1a from scorpion Hottentotta franzwerneri crude venom. At only 10 amino acid residues with one disulfide bond, it is not only the smallest venom peptide known to target T-type Ca_Vs but also the smallest structured scorpion venom peptide yet discovered. Synthetic Hf1a peptides were prepared with C-terminal amidation (Hf1a-NH₂) or a free C-terminus (Hf1a-OH). Electrophysiological characterization revealed Hf1a-NH₂ to be a concentration-dependent partial inhibitor of Ca_V3.2 (IC₅₀ = 1.18 μM) and Ca_V3.3 (IC₅₀ = 0.49 μM) depolarized currents but was ineffective at Ca_V3.1. Hf1a-OH did not show activity against any of the three T-type subtypes. Additionally, neither form showed activity against N-type Ca_V2.2 or L-type calcium channels. The three-dimensional structure of Hf1a-NH₂ was determined using NMR spectroscopy and used in docking studies to predict its binding site at Ca_V3.2 and Ca_V3.3. As both Ca_V3.2 and Ca_V3.3 have been implicated in peripheral pain signaling, the analgesic potential of Hf1a-NH₂ was explored in vivo in a mouse model of incision-induced acute post-surgical pain. Consistent with this role, Hf1a-NH₂ produced antiallodynia in both mechanical and thermal pain. Full article

Ulcerative colitis (UC) is a chronic intestinal ailment which cannot be completely cured. The occurrence of UC has been on the rise in recent years, which is highly detrimental to patients. The effectiveness of conventional drug treatment is limited. The long-term usage of these agents can lead to substantial adverse effects. Therefore, the development of a safe and efficient dietary supplement is important for the prevention of UC. Echinacea purpurea polysaccharide (EPP) is one of the main bioactive substances in Echinacea purpurea. EPP has many favorable effects, such as antioxidative, anti-inflammatory, and antitumor effects. However, whether EPP can prevent or alleviate UC is still unclear. This study aims to analyze the effect and mechanism of EPP on UC in mice using a 3% dextran sulfate sodium (DSS)-induced UC model. The results showed that dietary supplementation with 200 mg/kg EPP significantly alleviated the shortening of colon length, weight loss, and histopathological damage in DSS-induced colitis mice. Mechanistically, EPP significantly inhibits the activation of the TLR4/NF-κB pathway and preserves the intestinal mechanical barrier integrity by enhancing the expression of claudin-1, ZO-1, and occludin and reducing the loss of goblet cells. Additionally, 16S rRNA sequencing revealed that EPP intervention reduced the abundance of Bacteroides, Escherichia–Shigella, and Klebsiella; the abundance of Lactobacillus increased. The results of nontargeted metabonomics showed that EPP reshaped metabolism. In this study, we clarified the effect of EPP on UC, revealed the potential function of EPP, and supported the use of polysaccharide dietary supplements for UC prevention. Full article

This study represents an advancement in the field of composite material engineering, focusing on the synthesis of composite materials derived from porous hydroxyapatite via surface modification employing cucurbit[n]urils, which are highly promising macrocyclic compounds. The surface modification procedure entailed the application of cucurbit[n]urils in an aqueous medium onto the hydroxyapatite surface. A comprehensive characterization of the resulting materials was undertaken, employing analytical techniques including infrared (IR) spectroscopy and scanning electron microscopy (SEM). Subsequently, the materials were subjected to rigorous evaluation for their hemolytic effect, anti-inflammatory properties, and cytotoxicity. Remarkably, the findings revealed a notable absence of typical hemolytic effects in materials incorporating surface-bound cucurbit[n]urils. This observation underscores the potential of these modified materials as biocompatible alternatives. Notably, this discovery presents a promising avenue for the fabrication of resilient and efficient biocomposites, offering a viable alternative to conventional approaches. Furthermore, these findings hint at the prospect of employing supramolecular strategies involving encapsulated cucurbit[n]urils in analogous processes. This suggests a novel direction for further research, potentially unlocking new frontiers in material engineering through the exploitation of supramolecular interactions. Full article

Displacement mapping is a computer graphics technique that enables the design of components with regularly or randomly textured surfaces that can be quickly materialized on a three-dimensional (3D) printer when needed. This approach is, in principle, more flexible, faster, and more economical compared to conventional texturing methods, but the accuracy of the texture depends heavily on the parameters used. The purpose of this study is to demonstrate how to produce a surface-textured part using polygonal (mesh) modeling software and a photopolymerizable resin and to develop a universal methodology to predict the dimensional accuracy of the model file log combined with a resin 3D printer. The printed components were characterized on a scanning confocal microscope. In the setup used in this study, the mesh size had to be reduced to 10% of the smallest feature size, and the textured layer had to be heavily (×4.5) overexposed to achieve the desired accuracy. As a practical application, two functional stamps with a regular (honeycomb) and a random texture, respectively, were successfully manufactured. The insights gained will be of great benefit for quickly and cost-effectively producing components with innovative patterns and textures for a variety of hobby, industrial, and biomedical applications. Full article

To promote the development of the ‘Bamboo as a Substitute for Steel’ proposal, rotary cut bamboo veneers were applied to prepare a kind of high-strength laminated bamboo composite, which was achieved through the hot press molding method in this study. Orthogonal experiments of L9 (3³) were performed, with hot-pressing temperature, pressure, and time considered as three influencing factors. Physical properties like density and moisture content, and mechanical properties like modulus of rupture (MOR), modulus of elasticity (MOE), shear strength, and compressive strength were tested for the samples. It can be obtained from the results of range analysis and ANOVA that higher density and lower moisture content were correlated with higher mechanical strength. Within the selected range of tested factors, a hot-pressing temperature and time of 150 °C and 10 min can contribute to higher density and lower moisture content, and the combination of 150 °C and 50 MPa can produce greater mechanical strength. In the thickness direction, the laminated bamboo composites displayed a notable compressed structure. Full article

In cluttered electromagnetic environments, radar is often disturbed by varied clutter, making target detection challenging. Therefore, achieving effective clutter suppression is crucial for radar target detection. However, traditional clutter suppression methods face three key challenges: (1) significant degradation in target signal detection performance when the clutter’s Doppler spectrum completely masks the target signal; (2) heavy reliance on prior knowledge for optimal performance; and (3) inherent signal energy loss during clutter suppression. To address these challenges, we propose a clutter suppression scheme based on blind source separation (BSS). Initially, the scheme utilizes parallel principal skewness analysis (PPSA) to process the echo signals in the range domain, which helps in identifying the position of moving targets. Subsequently, PPSA is applied once more to process the moving targets in the Doppler domain, allowing for the precise determination of their relative velocities. Subsequently, we evaluate the scheme’s performance with simulated and real data, comparing it with traditional clutter suppression methods and other BSS techniques. The results confirm the effectiveness of the scheme in clutter suppression. Full article

We studied various fund investing options in the circular economy sector. We found that most circular economy mutual funds and exchange-traded funds charge higher fees and take higher risks than their benchmarks. However, they appear to have underperformed their benchmarks during their short existence so far. Most of these funds are rated as sustainable and low-carbon funds. Investors keen on circular economy startups may consider private equity/venture capital funds, but most of these funds are exclusive to institutional and accredited investors. Full article

The application of centrifugal compressors is extensive in industries such as aerospace and energy. The blade is the primary factor affecting the aerodynamic performance of compressors. In this paper, the aerodynamic performance of a centrifugal compressor with leaned and bowed 3D blades is investigated. The spanwise section profiles of the blade in the circumferential direction are deflected at different angles, resulting in four compressors with distinct leaned and bowed 3D blades based on the original model. There is a significant change in isentropic efficiency of the modified models under design conditions. Specifically, models 1, 3, and 4 experienced an increase of 0.97%, 1.04%, and 0.79%, respectively, while model 2 experienced a decrease of 0.70%. The profile of the blade tip and 50% spanwise section are shifted towards the suction surface, resulting in a geometric structure where the blade is concave towards the pressure surface. This structure gradually lifts the flow from the blade root to the blade tip downstream to the outlet area of the flow channel, reducing the load on the trailing edge of the blade and making the flow more closely aligned with the blade. At the same time, the larger radial velocity gradient near the blade tip suppresses the backflow on the shroud side, making the flow at the impeller outlet more stable. The outlet velocity of the impeller is more evenly distributed along the spanwise and circumferential directions, which improves the flow at the inlet of the diffuser and enhances the efficiency of the diffuser. Due to the high spanwise height of the leading edge of the blade, this bowed blade structure has little effect on the spanwise curvature upstream of the blade, resulting in negligible influence on the flow of the upstream channel. Full article

Low-carbon electricity and heat production is essential for keeping the decarbonization targets and climate mitigation goals. Thus, an accurate understanding of the potential environmental impacts constitutes a key aspect not only for the reduction in greenhouse gas emissions but also for other environmental categories. Life cycle assessment allows us to conduct an overall evaluation of a given process or system through its whole lifetime across various environmental indicators. This study focused on construction, operation and maintenance, and end-of-life phases, which were analyzed based on the ReCiPe 2016 method. Within this work, authors assessed the environmental performance of one of the renewable energy sources—Enhanced Geothermal Systems, which utilize supercritical carbon dioxide as a working fluid to produce electricity and heat. Heat for the process is extracted from hot, dry rocks, typically located at depths of approximately 4–5 km, and requires appropriate stimulation to enable fluid flow. Consequently, drilling and site preparation entail significant energy and material inputs. This stage, based on conducted calculations, exhibits the highest global warming potential, with values between 5.2 and 30.1 kgCO₂eq/MWh_el, corresponding to approximately 65%, 86%, and 94% in terms of overall impacts for ecosystems, human health, and resources categories, respectively. Moreover, the study authors compared the EGS impacts for the Polish and Norwegian conditions. Obtained results indicated that due to much higher electricity output from the Norwegian plant, which is sited offshore, the environmental influence remains the lowest, at a level of 11.9 kgCO₂eq/MWh_el. Polish cases range between 38.7 and 54.1 kgCO₂eq/MWh_el of global warming potential in terms of electricity production. Regarding power generation only, the impacts in the case of the Norwegian facility are two to five times lower than for the installation in the Polish conditions. Full article

Underwater acoustic (UWA) channel prediction technology, as an important topic in UWA communication, has played an important role in UWA adaptive communication network and underwater target perception. Although many significant advancements have been achieved in underwater acoustic channel prediction over the years, a comprehensive summary and introduction is still lacking. As the first comprehensive overview of UWA channel prediction, this paper introduces past works and algorithm implementation methods of channel prediction from the perspective of linear, kernel-based, and deep learning approaches. Importantly, based on available at-sea experiment datasets, this paper compares the performance of current primary UWA channel prediction algorithms under a unified system framework, providing researchers with a comprehensive and objective understanding of UWA channel prediction. Finally, it discusses the directions and challenges for future research. The survey finds that linear prediction algorithms are the most widely applied, and deep learning, as the most advanced type of algorithm, has moved this field into a new stage. The experimental results show that the linear algorithms have the lowest computational complexity, and when the training samples are sufficient, deep learning algorithms have the best prediction performance. Full article

The general population’s assessment and perception of a city can be influenced by its skyline, which is one of its representatives. This paper uses semantic segmentation and exploratory factor analysis to conduct a study from two different perspectives, aiming to analyse the development and current situation of the skyline of Hefei’s political and cultural new district. By collecting pictures of the skyline of the New Administrative and Cultural District, the New Administrative and Cultural District of Hefei’s skyline is being studied for overall changes using the semantic segmentation method, and to evaluate the quality of the skyline in various years, the entropy weight–TOPSIS is employed. Through the literature investigation and creation status of the new political and cultural district, the index system is scientifically formulated to conduct a questionnaire survey, and its reliability and validity are tested. This study is conducted with exploratory factor analysis of factors that are vital in the city skyline. The results of this study show that (1) after the semantic segmentation of the pictures, it is found that the proportion of buildings and the proportion of vegetation are both rising; the proportion of buildings tends to level off after 2018, and the proportion of vegetation shows a uniform increase. In the relative proximity ranking, the overall trend is increasing, and the skyline is ranked first in 2024. (2) Two variables were identified based on the findings of the exploratory factor analysis: ‘skyline value’ and ‘neighbourhood ecological quality’. The results of this study show that the skyline of Hefei’s New Administrative and Cultural District in 2024 is the best overall, and that the skyline of the New Administrative and Cultural District has developed into one of the city images of Hefei, and that its optimisation can be considered in terms of the “quality of the surrounding ecological environment”. Full article

In a previous study, we assessed the efficiency of reducing either traffic or industrial emissions on various ozone metrics for several cities in Europe, based on the Air Control Toolbox surrogate model. Here, we perform various model parametrisation sensitivity analyses in order to assess the robustness of our results. We find that increasing the model resolution has a limited impact on the ozone response to emission changes when focusing on concentration peaks but strongly changes the response of the ozone daily mean with a switch to a titration regime for all zones with significant nitrogen oxide (NO_x) emissions. The impact of pollution imported from outside the simulation domain was also studied and we show that if the first lever for action on ozone peaks remains as the reduction of local and regional emissions, in order to achieve higher levels of reduction, it is necessary to act at a European level. We also explore more up-to-date temporal profiles and sectoral emission speciation and find a shift towards a more NO_x-limited regime in a number of cities. Overall, these sensitivity tests show that most of the differences are simulated in cities with high NO_x emissions and little solar radiation but do not change the overall conclusions that were previously obtained. Full article

Sewage sludge and red mud, as common industrial waste, have become a research hotspot in the field of achieving carbon peaking and carbon neutrality, reducing carbon emissions, and solving environmental problems. However, their treatment and disposal have always been a difficult problem in the environmental field. Utilizing these two materials for thermal energy storage can not only improve energy utilization efficiency but also further reduce carbon emissions during their treatment process, providing a new approach for sustainable development in the industrial sector. This article summarizes the research progress for the resource recovery of sewage sludge and red mud for direct thermal energy recovery and composite phase change energy storage. After proper treatment, sludge and red mud can be directly used as energy storage materials. In addition, sludge and red mud can be combined with phase change materials to prepare composite materials with an excellent energy storage performance. This composite has broad application prospects in fields such as solar energy utilization and building energy efficiency. However, there are still some challenges and issues in this resource recovery and utilization, such as potential environmental pollution during the treatment process, the long-term stability of energy storage materials, and cost-effectiveness, which require further research and resolution. The purpose of this paper is to evaluate the potential of sewage sludge and red mud as energy storage materials, to explore their feasibility and advantages in practical applications, and to reveal the research progress, technical challenges, and future development directions of these two materials in the field of thermal energy storage. Full article

Induction healing technology can effectively repair microcracks in asphalt mixtures and is a promising maintenance technology for asphalt pavements. However, it requires the addition of steel wool fibers to asphalt mixtures and cannot be directly used to repair existing pavements. In order to improve the practicality of the induction healing technology, this article designs a wearing course asphalt mixture with induction healing function that is going to be paved above the existing road surface. The AC-10 asphalt wearing course for induction heating was prepared by adding steel fiber (SF). Analysis of the overall temperature of the surface revealed the unevenness of the temperature distribution, and the healing properties were investigated through protective heating that controlled the maximum temperature of the upper surface. The results show that the addition of SF can improve the high-temperature stability, low-temperature and intermediate-temperature crack resistance, and moisture stability of asphalt wearing courses; however, it has adverse effects on volumetric performance and skid resistance. The heating temperature increases with the increase in SF content, but higher maximum temperature heating rate causes worse heating uniformity and lower healing effect. The maximum heating rate of the sample with 10% SF reaches 3.92 °C/s, while its heating rate at minimum temperature is similar to that of the sample with 6% SF, which is only 0.7 °C/s, indicating the worst heating uniformity. The best healing effect occurs when the maximum temperature of the upper surface reaches 160 °C. The recommended optimal SF content is 6% of the asphalt volume. The asphalt mixture with 6% SF has an appropriate volume performance, moisture stability, and skid resistance; additionally, it has the best high-temperature stability, as well as low-temperature and intermediate-temperature crack resistance. Meanwhile, it also has uniform temperature distribution and efficient healing efficiency. Full article

The United Nations Sustainable Development Goals (SDGs) agenda has stated the importance of green investment. Energy-related green investment involves intricate economic behavior and ecological objectives. Green investment definitely requires agile decisions, e.g., rule-based decisions, to respond to changes outside the country. The identification of significant rules with numerous result features and the assurance of the stability and robustness of the rules in decision-making are crucial for green energy investment. The rough set (RS) methodology works well for processing qualitative data that are difficult to examine with traditional statistical methods in order to induce decision rules. The RS methodology starts with the analysis of the limits of discernibility of a subset of objects belonging to the domain to induce rules. However, traditional RS methods cannot incrementally generate rules with outcome features when new objects are added, which frequently occurs in green energy investment with the inclusion of big data. In this paper, an intelligent RS approach is proposed. This approach effectively identifies the rules that either stay the same or are altered based on four classified cases after a new object is introduced; it is novel because it can deal with a complicated investment environment by imposing multiple outcome features, specifically when it is required to flexibly extract new decision rules via adding new data sets. Full article

Phthalate esters (PAEs) are a group of chemicals used to improve the flexibility and durability of plastics. The chemical properties and the resistance to high temperatures promote their degradation and release into the environment. Food and beverages can be contaminated by PAEs through the migration from packaging material because they are not covalently bound to plastic and also via different kinds of environmental sources or during processing. For instance, alcoholic drinks in plastic containers are a particular risk, since the ethanol contained provides a good solubility for PAEs. According to its role as an endocrine disruptor compound and its adverse effects on the liver, kidney, and reproductive and respiratory systems, the International Agency on Research Cancer (IARC) classified di-(2-ethylhexyl) phthalate (DEHP) as a possible human carcinogen. For this reason, to control human exposure to PAEs, many countries prohibited their use in food as non-food substances. For example, in Europe, the Commission Regulation (EU) 2018/2005 restricts the use of DEHP, dibutyl phthalate (DBP), benzyl butyl phthalate (BBP), and diisobutyl phthalate (DiBP) to a concentration equal to or below 0.1 by weight in plasticizers in articles used by consumers or in indoor areas. There are reports from the US Food and Drug Administration (FDA) that some beverages (and food as well), particularly fruit juices, contain high levels of phthalates. In some cases, the deliberate adulteration of soft drinks with phthalate esters has been reported. This paper would like to show the difficulties of performing PAE analysis in beverage matrices, in particular alcoholic beverages, as well as the main solutions provided for quality control in the industrial branches. Full article

The fact is that hundreds of holes are drilled in the assembly process of furniture sets, so intelligent drilling is a key element in maximizing efficiency. Increasing the feed rate or the cutting speed in materials characterized by a higher machinability index is necessary. Smart drilling, that is, the real-time adjustment of the cutting parameters, requires the evolution of cutting process variables. In addition, it is necessary to control and adjust the processing parameters in real time. Machinability is one of the most important technological properties in the machining process, enabling the determination of the material’s susceptibility to machining. One of the machinability indicators is the unit cutting resistance. This article proposes a method of material identification using the short-time Fourier transform in order to automatically adjust cutting parameters during drilling based on force signals, cutting torque and acceleration signals. In the tests, four types of wood-based materials were used as the processed material: medium-density fiberboard, chipboard, plywood board and high-pressure laminate. Holes with a diameter of 10 mm were drilled in the test materials, with variable feed rate, cutting speed and thickness of cutting layer. An innovative method for determining the value of unit cutting resistance was proposed. The results obtained were used to determine the machinability index. Based on the test results, it was shown that both the selected signal measures in the time and frequency domains and the unit cutting resistance are constant for a given material of a workpiece and do not depend on the drilling process parameters. In this article, the methodology is proposed, which can be used as an intelligent technique to support the drilling process to detect the material being machined using data from sensors installed on the machine tool. The work proposes the fundamentals for material identification based on the analysis of force signals and the magnitude of force derivatives. The proposed methodology shows effectiveness, which proves that it can be used in intelligent drilling processes. Hybrid wood-based material structures consisting of different materials are becoming more and more common in building structures for strength, economic and environmental reasons. Due to the difference in the machinability of interconnected materials, cutting parameters must be optimized in real time during machining. Currently, with the rapid development of Industry 4.0, the on-line identification of parameters is becoming necessary to improve the process flow in industrial reality. The proposed methodology can be used as an intelligent technique to support the drilling process in order to detect the material being processed using data from sensors installed on the machine tool. Full article

This article offers a fresh interpretation of the intended impact of 2 Cor 6:14–7:1 on the group formation of the Corinthian Christ community. To achieve this interpretation, it will first determine the most likely social reference of the term οἱ ἄπιστοι. Secondly, it will describe a methodological tool from the Social Identity Approach that will help to visualise how groups are formed and reformed when the context changes. Finally, it will apply this tool to determine how 2 Cor 6:14–7:1 affected the boundaries of the Christ community in Corinth. Full article