Adaptive Tool Research Articles

Carbon footprint calculating for fruit processing and storage activities

Food production plays a significant role in greenhouse gas emissions. Addressing these issues in agriculture and production requires strategies that consider regional and national contexts while ensuring food security. There is no universal solution for agro-processing sector; thus, research and adaptable tools must be employed based on local conditions. The research were focused on analysis of fruit paste production technology, refrigerated storage and transport. As a result, a calculating carbon footprint method for these processes was developed. Conclusions of this research can be of great value to agri-food industry, enabling producers to make more informed decisions about energy efficiency and reducing greenhouse gas emissions. This makes it possible to move toward more sustainable and environmentally friendly production, while ensuring high quality products throughout their shelf life.

Data-adaptive hybrid control for power quality improvement using H-bridge circuit

The extraction of fundamental current and controlling the H-bridge circuit, called shunt active power filter (SAPF), for power quality support have always been major research concerns. The effectiveness of a SAPF depends on its fundamental component estimation. In this context, empirical mode decomposition (EMD) is applied to SAPF operations due to its effectiveness in complex signal analysis. Being a data-driven, adaptive tool, EMD decomposes the distorted nonlinear signal into signal- and noise-dominated signals, called intrinsic mode functions (IMFs). However, its exploitation has been hindered by its mode mixing issue. As a remedy, a second-order generalized integrator (SOGI) is integrated with the EMD approach to extract the required fundamental active component of distorted load current. Thus, this work investigates the effect of an EMD-based SOGI hybrid control approach in extracting the fundamental active component of distorted load current. The MATLAB/Simulink results demonstrate the effectiveness of the proposed hybrid control strategy for nonlinear load current generated by the diode bridge rectifier. Furthermore, the simulated results are validated through a real-time simulation result using the OPAL-RT OP4510 test bench. Results are analyzed under sinusoidal and distorted voltage scenarios at the point of common coupling. The simulation results showed that the proposed hybrid control approach provides better active filtering efficiency, support for reactive power, and improved total harmonic distortion, which meets the IEEE 1547-2018 standard.

Experimental & numerical investigations of ultra-high-speed dynamics of optically induced droplet cavitation in soft materials

Perfluorocarbon (PFC) droplets represent a novel class of phase-shift contrast agent with a promise in applications in biomedical and bioengineering fields. PFC droplets undergo a fast liquid-gas transition upon exposure to acoustic or optical triggering, offering a potential adaptable and versatile tool as contrast agent in diagnostics imaging and localized drug delivery vehicles in therapeutics systems. In this paper, we utilize advanced imaging techniques to investigate ultra-high-speed inertial dynamics and rectified quasi-static (low-speed) diffusion evolution of optically induced PFC droplet vaporization within three different hydrogels, each of different concentrations, examining effects such as droplet size and PFC core on bubble dynamics and material viscoelastic properties. Gelatin hydrogels reveal concentration-dependent impacts on bubble expansion and material elasticity. Embedding PFC droplets in gelatin increases internal pressure, resulting in higher equilibrium radius and continuous bubble growth during quasi-static evolution. Similar trends are observed in fibrin and polyacrylamide matrices, with differences in bubble behavior attributed to matrix properties and droplet presence. Interestingly, droplet size exhibits minimal impact on bubble expansion during inertial dynamics but influences quasi-static evolution, with larger droplets leading to continuous growth beyond 60 seconds. Furthermore, the core composition of PFC droplets significantly affects bubble behavior, with higher boiling point droplets exhibiting higher maximum expansion and faster quasi-static dissolution rates. Overall, the study sheds light on the intricate interplay between droplet characteristics, matrix properties, and multi-timescale bubble dynamics, offering valuable insights into their behavior within biomimetic hydrogels.

Design and Practice of Virtual Experimental Scenes Integrating Computer Vision and Image Processing Technologies

In this work, we introduce a novel framework, GAN-based Image Processing (GAN-IP), to design and manipulate digital experimental settings that effectively combine computer vision and image processing technology. Using the skills of Generative Adversarial Networks (GANs), GAN-IP creates and complements virtual scenes and affords rich, adaptive surroundings for analysing and creating computationally smart and perceptive algorithms. GAN-IP solves the pressing troubles of variability and absence of data through synthesising realistic pictures and scenarios, enabling simulations of the diverse environments in which computer vision structures have to function. Our approach improves the fidelity and sort of digital scenes and introduces a way to mechanically alter and evoke a pleasant image, enabling more accurate and powerful computer vision and prescient models. Through extensive experimentation, GAN-IP demonstrates remarkable improvements in the performance of computer vision tasks, including object detection, segmentation, and recognition in complicated virtual environments. This research lays the foundation for future studies in this field and provides an adaptive tool for researchers and practitioners to simulate and test superior computer imaginative and prescient image processing technologies.

Innovative approaches to the maintenance and repair of biomedical devices in resource-limited settings

This review paper examines innovative approaches to maintaining and repairing biomedical devices in resource-limited settings, emphasizing the critical role these devices play in healthcare delivery. It addresses the challenges healthcare facilities face in these regions, such as the lack of spare parts, limited technical expertise, and harsh environmental conditions. The paper highlights several innovative strategies, including using locally sourced materials, developing low-cost, adaptable tools, remote support systems, and targeted training programs for local technicians. These approaches significantly improve device functionality, reduce downtime, and enhance the reliability and availability of essential medical equipment. By fostering collaboration between local technicians and external experts and building local capacity, these strategies contribute to better patient care and overall healthcare delivery. The paper also discusses prospects and recommendations for sustaining these innovations to strengthen healthcare systems in resource-constrained environments.

Evolutionary Role of the Female Orgasm: Insights into Mate Choice and Beyond.

The female orgasm remains a subject of extensive debate within evolutionary sciences, primarily due to the absence of a consensus regarding its adaptive function. Some hypotheses propose that it could function as a mechanism for mate selection, possibly linked to reproductive strategies. Studies have observed that lesbian women tend to experience orgasms more frequently than straight women, suggesting a potential link to advantageous partner characteristics. We explored the connection between the female orgasm and mate selection, aiming to ascertain its role as an adaptive tool for mate choice. A total of 939 sexually active Brazilian women (Mage = 28.3years) engaged in committed relationships participated by completing the Marital Empathy Questionnaire, the Female Sexual Function Index, and evaluations of their partners' attributes. Analysis using structural equation models revealed that higher orgasm scores were positively associated with perceptions of partner kindness, intelligence, good health, physical attractiveness, and empathy. However, the small effect sizes of these associations warrant caution in their interpretation, and no significant association was found for relationship duration, financial prospects, dominance, and masculinity/femininity. Additionally, no differences were found between women in same-sex and other-sex relationships regarding orgasm frequency and its association with partner traits. The findings partially support the mate-choice theory, encompassing both sire-choice and pair-bond hypotheses, suggesting that female orgasm is positively associated with some partner attributes related to genetic quality and the capability for emotional connection and resource investment. Therefore, female orgasm may offer information about the partner that might not be primarily accessed and contribute to relationship maintenance.

Optimizing crop seeding rates on organic grain farms using on farm precision experimentation

Organic agriculture is often regarded as less damaging to the environment than conventional agriculture, though at the expense of lower yields. Field-specific precision agriculture may benefit organic production practices given the inherent need of organic farmers to understand spatiotemporal variation on large-scale fields. Here the primary research question is whether on-farm precision experimentation (OFPE) can be used as an adaptive management methodology to efficiently maximize farmer net returns using variable cover crop and cash crop seeding rates. Inputs of cash crop seed and previous-year green manure cover crop seed were experimentally varied on five different farms across the Northern Great Plains from 2019 to 2022. Experiments provided data to model the crop yield response, and subsequently net return, in response to input (seeding) rates plus a suite of other spatially explicit data from satellite sources. New, field-specific spatially explicit optimum input rates were generated to maximize net return including temporal variation in economic variables. Inputs were spatially optimized and using simulations it was found that the optimization strategies consistently out-performed other strategies by reducing inputs and increasing yields, particularly for non-tillering crops. By adopting site specific management, the average increase in net return for all fields was $50 ha−1. These results showed that precision agriculture technologies and remote sensing can be utilized to provide organic farmers powerful adaptive management tools with a focus on within-field spatial variability in response to primary input drivers of economic return. Continued OFPE for seeding rate optimization will allow quantification of temporal variability and subsequent probabilistic recommendations.

First reported human use of wireless laparoscopic system: is it ready for prime time?

ObjectiveDuring the advent of laparoscopy, surgeons directly explored the abdominal cavity with a telescope-like device through a small incision. Since then, numerous technological advances have transformed minimally invasive surgery (MIS). Yet, in our wireless world, various devices crowd the surgical field, with long wires and light sources posing fall and fire risks. The primary objective of this study was to analyze the first reported human use of a novel wireless laparoscopy system or WLS (ArthroFree™, Lazurite®, Cleveland, Ohio).MethodsThe utility and convenience of the WLS was assessed via two avenues: (1) by analyzing surgical outcomes from first human use and (2) by surveying healthcare professionals regarding its quality and utility.ResultsEighteen patients (mean age 44.2, 83.3% female, mean BMI 33.4) underwent operations with the WLS. Operations included gynecologic and general surgical procedures. There were no intraoperative or postoperative complications, and no conversions to traditional laparoscopy or laparotomy. Mean operating time was 71.94 ± 20.41 min, and estimated blood loss was minimal. Survey results revealed varied individual experiences. Strengths included adequate illumination, improved ergonomics, and simplicity of setup and ease of operation. One respondent criticized the image resolution. Feedback indicated an overall positive impact, and 67% of respondents supported inclusion of the device at their facility. Moreover, its deployment in resource-limited settings abroad has demonstrated its efficacy in global surgery, indicating its potential in various healthcare environments.ConclusionsThis is the first reported human use of a novel WLS. Clinical results supported efficiency and safety of the technology. The successful deployment of the WLS in diverse surgical environments, including resource-limited settings, highlights its potential as a universally adaptable tool in global surgery. This report represents a strong first step toward a wireless operating room with the promise of redefining surgical standards as well as bridging gaps in surgical care worldwide.Graphical abstract

A versatile microbial platform as a tunable whole-cell chemical sensor.

Biosensors are used to detect and quantify chemicals produced in industrial microbiology with high specificity, sensitivity, and portability. Most biosensors, however, are limited by the need for transcription factors engineered to recognize specific molecules. In this study, we overcome the limitations typically associated with traditional biosensors by engineering Pseudomonas putida for whole-cell sensing of a variety of chemicals. Our approach integrates fluorescent reporters with synthetic auxotrophies within central metabolism that can be complemented by target analytes in growth-coupled setups. This platform enables the detection of a wide array of structurally diverse chemicals under various conditions, including co-cultures of producer cell factories and sensor strains. We also demonstrate the applicability of this versatile biosensor platform for monitoring complex biochemical processes, including plastic degradation by either purified hydrolytic enzymes or engineered bacteria. This microbial system provides a rapid, sensitive, and readily adaptable tool for monitoring cell factory performance and for environmental analyzes.

The Role of e-Learning During Martial Law: The Ukrainian Experience

The research aim is to reveal the role of e-learning during Martial law by the example of Ukrainian experience. It focuses on the following objectives: to outline the advantages and challenges of e-learning; to describe the peculiarities of implementation of e-learning at the different levels of education; to analyse teaching methods used to integrate e-learning; and to develop the recommendations to implement e-learning. The systemic literature review was carried out to provide an objective summary of the current topic. All sources were published between March, 2022 and May, 2024. The literature focused on e-learning in Ukraine or similar conflict-affected areas. All articles were available in English or Ukrainian. To analyse the data, the synthesis method was applied. The findings proved that e-learning became an important tool during emergencies, providing continuity in education. It was explained that e-learning is introduced at primary, secondary, and higher levels of education. It includes synchronous and asynchronous models. Certain teaching methods are used to implement e-learning effectively. They relate to interactive simulations, multimedia content, gamification, discussion forums, and personalized learning. These methods, combined, create a dynamic e-learning environment that enhances students’ educational outcomes, particularly during emergencies. The implementation of e-learning in Ukraine during Martial law requires careful consideration of the recommendations: enhancement of digital infrastructure, adoption of flexible learning, formation of digital literacy, support of mental health, using interactive methods, increase of content quality, regular assessment, encouragement of positive teacher-student interaction, implementation of adaptive learning tools, and protection of students and educators' data. The research outcomes on the role of e-learning during Martial law can be used for the development of strategic plan of implementation of e-learning tools within the learning process in the regions affected by war or other emergencies. Also, the study can contribute to future educational practices, encouraging the development of more innovative learning solutions.

Floodplain Restoration and Its Effects on Summer Water Temperature and Macroinvertebrates in Whychus Creek, Oregon (USA)

ABSTRACTStream restoration is a proposed climate adaptation tool; however, outcomes of floodplain restoration on stream temperature have been debated. Despite a growing number of studies that investigated water temperature in restored streams, few have quantified temperature variations in new habitat types created by restored hydrogeomorphic processes to explore the effects on aquatic macroinvertebrates. We evaluated the hypotheses: (1) restoration increases habitat diversity, (2) habitat diversity increases water temperature variability, and (3) restoration increases the diversity of macroinvertebrate assemblage and temperature associations. In August 2021, we collected environmental data to describe the aquatic habitats, water temperature and quality (continuous and discrete), and macroinvertebrates in 40 riffle, pool, and off‐channel sites in a stream being restored, Whychus Creek, Oregon, USA. Our study is a site comparison of three reaches—one restored in 2012, another restored in 2016, and an unrestored (control) that will soon undergo restoration. Evaluations of the hypotheses show: (1) Habitat diversity in restored reaches is effectively three types of aquatic habitats versus only one in the control (riffles), (2) water temperature variability in habitats created by restoration (off‐channel) is high and low, and suggest a range of hyporheic connectivity and flow paths are present, and (3) restoration created a different macroinvertebrate assemblage, with 16 additional taxa in off‐channel habitats, and the range in macroinvertebrate thermal optima is approximately doubled when off‐channel macroinvertebrate thermal optima are accounted for. Our results support the idea that floodplain restoration creates more diverse thermal conditions and different macroinvertebrate communities in restored stream reaches.

Scientometric analysis of cover crop management: Trends, networks, and future directions

This research paper presents a comprehensive scientometric analysis of English articles from the Scopus database regarding the topic of cover crop management from 1956 to March 2024. Through the analysis of the annual production trend, total production, a co-occurrence network of keywords, co-authorship networks, and co-citation networks, the data was mapped and visualized using VOSviewer and Bibliometrix software. There was an exponential increase in publications from 1991 onwards. The predominant subject was Agricultural and Biological Sciences and the most relevant journals, authors, and documents were related to this topic. Additionally, the most productive country was the United States, but in terms of article production per surface area, other countries, such as Switzerland and The Netherlands, evidence the great weight of cover crop management in these countries. The identified research topics were related to the application of different crops as cover crops and the effects on different cultivars, also soil quality improvement, and fertilization and nutrient efficiency. An emerging research topic was found to be the usefulness of cover crops as effective tools for climate change adaptation and mitigation strategies in agriculture. Future research in the field of cover crop management could be directed towards climate-adaptive cover crop species and varieties, the use of technological innovations for cover crop monitoring, and management and analysis of the economic and social impacts of cover crop adoption.

Eco-Spatial Indices as an Effective Tool for Climate Change Adaptation in Residential Neighbourhoods—Comparative Study

Eco-Spatial Indices as an Effective Tool for Climate Change Adaptation in Residential Neighbourhoods—Comparative Study

The influence of the CommonLit platform on the development of reading skills as an academic reinforcement for A2 students

Ecuador, a country of privileges due to its geographical location, has varied socio-ideological and cultural influences that significantly impact the learning and acquisition of a foreign language. Few students are aware of the importance of English. However, many do not feel a real interest in or the need to use the language in their daily activities in a society where they only try to cover a momentary requirement. The complexity of mastering a new language like English is even worse because learners have to face environmental, and emotional difficulties, as reflected in the quantitative study carried out, which suggests energizing their learning acquisition using the qualitative method that promotes their voluntary interest in reading comprehension, as stated by a survey and class observation carried out in the First “A” of Accountancy at the Isabel de Godin Educative Unit in Riobamba. Therefore, the implementation of the CommonLit platform will determine academic progress and reading proficiency as the main tool to improve their reading skills by addressing challenges according to different levels of English proficiency. In this sense, with the platform's interactive activities, adaptive learning tools, and variety of interesting information, participants' reading abilities significantly improve, according to the findings. Therefore, the CommonLit platform is a useful tool for students who intend to achieve A2 in their reading development since it enhances the academic level and cultivates an enduring enjoyment for reading.

393 The role of on-animal sensors in understanding feed intake, behavior, and performance of grazing livestock

Abstract Intake by grazing animals is difficult to reliably measure in the field, particularly in more diverse grazing systems where pastures vary greatly across time and space in resource availability, which in turn leads to greater variation in animal time budgets and intake patterns. Advances in remote livestock monitoring (e.g., on-animal sensors, walk -over-weighing), and advanced analytics such as machine learning algorithms can contribute to the development of robust, adaptable tools for better understanding of animal performance and behavior in grazing systems. Many existing tools for predicting livestock production require estimates of feed intake, and while estimates based on forage sward characteristics have been developed and used for temperate, relatively homogenous pastures, they are less well defined for more diverse rangelands. These diverse pastures are more difficult to characterize due to their greater variation in quantity and quality; consequently, animal selectivity is greater in more variable pastures. However, such feedback loops between pasture diversity and animal behavior may not yet be adequately represented in biophysical models. On-animal sensors such as accelerometers and GPS devices can be used to develop new ways of assessing relative intake by providing accurate estimates of animal location and behavior profiles, such as the use of machine learning algorithms to detect how much time is spent grazing, walking, ruminating, or resting. Measurements of animal behavior could then be combined with other animal-based methods such as walk-over-weighing and fecal NIR to improve estimates of intake and production for a wide range of extensive grazing environments. Sensor-derived measurements of animal movement could also be used to improve estimates of the energetic costs of grazing, thereby improving estimates of energy available for growth. As an example, data on recent activity and paddock use from on-animal sensors could be entered into a model to estimate current feeding requirements, then combined with weather and pasture quality forecasts. The ensuing baseline could then be used to explore the potential variability of these projections and generate a range for possible expected performance over the next month or season. This approach could be repeated over time, and animal performance and behavior measures used to update model estimates and improve forward projections. These methods could also be used in conjunction with estimates of animal energy requirements to provide real-time prediction of relative feed intake, which would provide a step-change in modelling livestock production in extensive grazing systems. For these approaches to be successful, additional calibration data are needed across a wide variety of environments and species, and the tools must be cost-effective to implement. In summary, on-animal measurements provide an adaptable, data-driven approach that could be integrated with existing tools to improve our understanding of feed intake, behavior, and performance of grazing animals.

Gender and climate resilience: A study probing the agricultural adherent behavior through climate information services in southern Punjab

Climate change poses a significant threat to agriculture, with gender dynamics playing a critical role in influencing adaptive behaviors. Despite this, there remains a notable gap in addressing gender-specific factors in climate change adherent behaviors within the agricultural sector, especially in the Asian Regions. Pakistan's agriculture, particularly in underdeveloped regions, is highly vulnerable to climate change impacts. Climate information is predominantly disseminated through vernacular media, which serves as a crucial tool for adaptation. To fill the gap in this tapestry, a study conducted in the district of Rahim Yar Khan in southern Punjab, Pakistan, proposes a conceptual framework grounded in existing theories and literature to examine agricultural adherence to climate information services (CIS) and highlight the potential of digital media in promoting climate-resilient behaviors among agricultural workers. To ensure the robustness of the results, a cross-sectional research design was employed, integrating a broad survey that traversed on a gender basis within this underdeveloped precinct. A probability sampling technique, specifically systematic random sampling, was utilized to gather responses from 200 respondents related to farming and yielding through a closed-ended questionnaire. The study found that over half of the participants, irrespective of gender, recognized climate change as a significant concern for agriculture. Notably, females exhibited a higher level of awareness compared to their male counterparts. Local media emerged as the primary source of climate information for both genders. Post-CIS exposure, notable behavioral changes were observed, underscoring the critical role of CIS in managing climate change risks. The findings highlight significant gender differences and stress the importance of gender-responsive approaches in delivering climate information services to ensure equitable engagement and effective management of climate change risks in agriculture. The research also suggests theoretical and social implications, along with practical recommendations for policy and practice.

NIR-II light-activated and Cu nanocatalyst-enabled bioorthogonal reaction in living systems for efficient tumor therapy

Bioorthogonal reaction refers to chemical reactions that occur within a biological system without interfering the normal biochemical process, offering the unprecedented versatility in engineering chemical reactions within cells. However, the precise regulation of bioorthogonal reaction in living systems is mired by the complexity of the physiological environment and the toxicity of catalysts. Herein, considering the deeper tissue penetration and reduced phototoxicity compared to visible light and ultraviolet, a second near infrared (NIR-II) light-activated Cu-based bioorthogonal reaction is developed to achieve precise spatiotemporal control and effective switching for Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC) mediated chemical transformations in tumor, reducing the off-target effects. The catalytic activity of Cu catalyst through valence state interconversion between Cu(II) and Cu(I) can be precisely regulated in a reversible manner under NIR-II light irradiation-induced photoelectron transfer, which controls the extent of desired drug synthesis in bioorthogonal reaction. Meanwhile, the adverse effects of Cu(I) can be substantially mitigated within normal tissues due to their oxygen-rich condition. By utilizing NIR-II light and oxygen level, the Cu bioorthogonal catalyst achieves a balance between catalytic activity and biocompatibility. The ability to achieve precise spatiotemporal control and reversible catalysis makes this NIR-II light-mediated CuAAC platform an efficient and adaptable tool for bioorthogonal chemistry in living systems.

Future Climate Projections and Uncertainty Evaluations for Frost Decay Exposure Index in Norway

To implement the geographical and future climate adaptation of building moisture design for building projects, practitioners need efficient tools, such as precalculated climate indices to assess climate loads. Among them, the Frost Decay Exposure Index (FDEI) describes the risk of freezing damage for clay bricks in facades. Previously, the FDEI has been calculated for 12 locations in Norway using 1961–1990 measurements. The purpose of this study is both updating the FDEI values with new climate data and future scenarios and assessing how such indices may be suitable as a climate adaptation tool in building moisture safety design. The validity of FDEI as an expression of frost decay potential is outside the scope of this study. Historical data from the last normal period as well as future estimated climate data based on 10 different climate models forced by two emission scenarios (representative concentration pathways 4.5 and 8.5) have been analyzed. The results indicate an overall decline in FDEI values on average, due to increased winter temperatures leading to fewer freezing events. Further, the variability between climate models and scenarios necessitates explicit uncertainty evaluations, as single climate model calculations may result in misleading conclusions due to high variability between models.

Transcending traditional metrics: Evaluating school leadership effectiveness through emotional intelligence and qualitative instruments

This paper examines the integration of school leaders' emotional intelligence and qualitative instruments into commonly used metrics for measuring school leadership effectiveness. Traditionally, these metrics rely heavily on questionnaires to assess leadership effectiveness. However, a weakness of these metrics is their excessive reliance on numerical data, which overlooks the qualitative dimensions of leadership. This study utilises Trait Emotional Intelligence Theory and Team Emotional Intelligence as units of analysis to redefine school leadership assessment. To make sense of the related literature and theories used in the study, an integrative literature review was employed as the methodological approach. The findings indicate that emotional intelligence significantly contributes to leadership effectiveness. The study also reveals that leaders who are self-aware of their emotional composition and its impact are more effective than those who are not. Furthermore, the results suggest that leaders who are cognisant and responsive to the emotional dynamics of their teams benefit from enhanced team cohesion, collaboration, and goal attainment. The study emphasises the importance of incorporating adaptable qualitative tools alongside quantitative instruments to accurately measure leadership effectiveness. Thus, this study adds to the existing literature by proposing a theoretically informed and adaptable framework that integrates an emotional intelligence construct and qualitative instruments for assessing school leadership effectiveness.

Unlocking Grid Flexibility: Leveraging Mobility Patterns for Electric Vehicle Integration in Ancillary Services

The electrification of mobility has introduced considerable challenges to distribution networks due to varying demand patterns in both time and location. This underscores the need for adaptable tools to support strategic investments, grid reinforcement, and infrastructure deployment. In this context, the present study employs real-world datasets to propose a comprehensive spatial–temporal energy model that integrates a traffic model and geo-referenced data to realistically evaluate the flexibility potential embedded in the light-duty transportation sector for a given study region. The methodology involves assessing traffic patterns, evaluating the grid impact of EV charging processes, and extending the analysis to flexibility services, particularly in providing primary and tertiary reserves. The analysis is geographically confined to the Lombardy region in Italy, relying on a national survey of 8.2 million trips on a typical day. Given a target EV penetration equal to 2.5%, corresponding to approximately 200,000 EVs in the region, flexibility bands for both services are calculated and economically evaluated. Within the modeled framework, power-intensive services demonstrated significant economic value, constituting over 80% of the entire potential revenues. Considering European markets, the average marginal benefit for each EV owner is in the order of 10 € per year, but revenues could be higher for sub-classes of users better fitting the network needs.