Developed Model Research Articles

ТЕОРЕТИЧНЕ ДОСЛІДЖЕННЯ ТЕПЛОВИХ ПРОЦЕСІВ НА ВУГЛЕЦЕВИХ ЕЛЕКТРОДАХ В РЕЗУЛЬТАТІ ДІЇ ПЛАЗМИ ПРИ ГЕНЕРАЦІЇ НАНОСТРУКТУР У ВАКУУМНІЙ ДУЗІ

A mathematical model has been refined to determine the thermophysical and thermomechanical processes on electrodes during the plasma formation of nanostructures. The model takes into account the effects of electrode spots, evaporation, sputtering, and thermal stresses in the electrode bodies. Calculations of temperature distribution on the surfaces of the graphite cathode and anode were carried out, considering the conditions necessary for obtaining nanostructures. An analysis of the thermophysical processes on the surfaces of the graphite cathode and anode during the transition to the working regime was conducted. The stability of the electrodes during plasma generation of nanostructures was determined by changes in the geometry of the electrodes. Calculations of the temperature fields on the end surface of the graphite cathode showed that with a continuous increase in the cathode surface temperature, the nature of its distribution does not change fundamentally. Calculation of temperature fields along the radius of the graphite cathode at different moments in time during the transition to the working regime showed a slight impact of evaporation on the change in the cathode's geometry. Determining the temperature fields along the generatrix of the anode showed the greatest impact of evaporation on the small area of the anode closest to the cathode. The dependencies of the acting stresses on temperature for the graphite cathode and anode were obtained. Studies of the dynamics of changes in thermal stresses on the electrodes during the formation of nanostructures in a plasma environment indicate that the values of thermal stresses are far from the material's strength limit. A theoretical study of the thermophysical and thermomechanical processes on the graphite cathode was carried out and compared with experimental measurements. The calculation of the electrodes' lifespan during the creation of carbon nanostructures in a plasma environment was 2.52∙105 s. The experimental lifespan of the graphite cathode is 2.88∙105 s, which is quite close to the calculated value. The coincidence of the obtained theoretical and experimental results indicates the viability of the developed model. The article may be of interest when designing equipment for obtaining nanostructures in a plasma environment and for further research on the physical parameters of electrodes.

Drug–drug interactions between letermovir and tacrolimus in Japanese renal transplant recipients simulated using a physiologically based pharmacokinetic model

Letermovir (LET) is a novel antiviral agent recently approved for cytomegalovirus (CMV) prophylaxis of renal transplant patients in Japan. However, its interactions with tacrolimus (TAC), an important immunosuppressant, remain ambiguous, warranting careful evaluation considering the unique genetic and physiological characteristics of Japanese patients. Therefore, in this study, we aimed to investigate the drug–drug interactions between LET and extended-release TAC (ER-TAC) in Japanese renal transplant patients via physiologically based pharmacokinetic (PBPK) modeling. We developed PBPK models for LET and TAC, including a new model for ER-TAC, using the Simcyp simulator. We also created a virtual Japanese post-transplant population by incorporating physiological parameters specific to Japanese patients, including CYP3A5 genotypes. Our model accurately predicted the pharmacokinetics of both immediate-release and ER-TAC co-administered with LET. In the Japanese population, LET significantly increased ER-TAC exposure, with the effect varying by CYP3A5 genotype. For CYP3A5*1 carrier, the area under the curve ratio ranged from 2.33 to 2.53, while for CYP3A5*3/*3 carriers, it ranged from 2.82 to 2.86. The maximum concentration ratio was approximately 1.50 across all groups. Our findings suggest reducing the ER-TAC dose by approximately 57–60% for CYP3A5*1 carrier and 65% for CYP3A5*3/*3 carriers when co-administered with LET for Japanese renal transplant patients. Moreover, the developed model incorporating population-specific factors, such as hematocrit values and CYP3A5 genotype frequencies, is a valuable tool to evaluate complex drug interactions and guide the dosing strategies for LET and TAC in Japanese patients. Overall, this study expands the application of PBPK modeling in transplant pharmacology, contributing to the development of effective immunosuppressive strategies for Japanese renal transplant patients.

Video Content Analysis for Detection of Road Traffic Congestion Pattern: An Optimized YOLOv8 Based Approach

This paper presents a new approach to Video Content Analysis (VCA) with a specific focus on detecting and analyzing road traffic congestion patterns. The implemented methodology deploys the YOLOv8 (You Only Look Once) object detection framework, which has been optimized to accurately and efficiently identify road traffic objects within video streams. The primary goal is to improve traditional VCA systems by capturing and understanding complex road congestion scenarios. This research develops a customized YOLO model optimized specifically for road traffic analysis. The optimization process addresses the challenges inherent in real-world traffic scenarios including variations in lighting conditions, diverse vehicle types and dynamic traffic flow patterns. The developed model seeks to enable robust and real-time detection of congestion-related events such as heavy congestion and normal congestion thereby contributing to improved traffic management and overall road safety. Moreover, the paper explores the integration of advanced techniques for congestion pattern analysis including vehicle detection, tracking, and counting. The combination of these features facilitates a comprehensive understanding of traffic dynamics and congestion evolution over time. The proposed approach is trained and evaluated on benchmark datasets and real-world video footage to assess its performance. Experimental results demonstrate the effectiveness of the optimized YOLOv8-based approach in accurately detecting and analyzing road traffic congestion patterns. The system exhibits promising capabilities in handling diverse and challenging scenarios thereby serving as a valuable tool for intelligent transportation systems, urban planning and traffic management. This research significantly contributes to the advancement of video-based traffic analysis, providing a robust solution for monitoring and mitigating congestion-related challenges on road networks.

Predicting vertical ground reaction force characteristics during running with machine learning

Running poses a high risk of developing running-related injuries (RRIs). The majority of RRIs are the result of an imbalance between cumulative musculoskeletal load and load capacity. A general estimate of whole-body biomechanical load can be inferred from ground reaction forces (GRFs). Unfortunately, GRFs typically can only be measured in a controlled environment, which hinders its wider applicability. The advent of portable sensors has enabled training machine-learned models that are able to monitor GRF characteristics associated with RRIs in a broader range of contexts. Our study presents and evaluates a machine-learning method to predict the contact time, active peak, impact peak, and impulse of the vertical GRF during running from three-dimensional sacral acceleration. The developed models for predicting active peak, impact peak, impulse, and contact time demonstrated a root-mean-squared error of 0.080 body weight (BW), 0.198 BW, 0.0073 BW ⋅ seconds, and 0.0101 seconds, respectively. Our proposed method outperformed a mean-prediction baseline and two established methods from the literature. The results indicate the potential utility of this approach as a valuable tool for monitoring selected factors related to running-related injuries.

Development and Evaluation of an AI-Based Chatbot for Preventing Social Media Addiction: A Waterfall Model Approach

The rapid growth of social media has transformed interaction and communication patterns, but it has also led to the rise of social media addiction, particularly among teenagers and young adults. This addiction, marked by compulsive usage and negative impacts on mental health and daily life, necessitates effective interventions. This research explores the development and evaluation of an AI-based chatbot designed to mitigate social media addiction by employing cognitive and behavioural strategies. The study utilizes the Waterfall model—a structured, sequential approach—in the chatbot’s development, encompassing stages from needs analysis to maintenance. The chatbot’s effectiveness was assessed through rigorous testing and user feedback. The methodology included problem analysis, system design, implementation, testing, and iterative improvements. A comprehensive needs analysis identified the psychological and behavioural factors contributing to social media addiction, leading to the design of a prototype chatbot integrated with AI for dynamic content adaptation and real-time feedback. The implementation phase focused on coding and system integration, followed by rigorous testing using Black Box Testing and the System Usability Scale (SUS) to ensure functionality and user-friendliness. Results indicate that the chatbot significantly reduced social media addiction scores, with a mean decrease from 55.21 to 50.17, supported by a highly significant p-value of <0.0001. User satisfaction was high, particularly regarding ease of use and information quality. However, user engagement declined over time, highlighting the need for ongoing content updates and feature enhancements. This study contributes to the field by providing insights into the application of the Waterfall model in AI chatbot development and offers a scalable solution for addressing social media addiction, with implications for future digital interventions in mental health.

Analysis of the Theory of Al-Maqāṣid asy-Syarī'ah in Sustainable Economic Development

Sustainable economic development has emerged as a critical challenge in our increasingly globalised world, where environmental degradation and social inequities pose significant threats to future prosperity. The urgency of this issue is underscored by recent reports indicating that over 1 billion people still live in extreme poverty, while climate change continues to exacerbate existing vulnerabilities. In this context, the theory of Al-Maqāṣid asy-Syarī'ah provides a relevant framework for addressing these multifaceted challenges, as it focuses on the preservation of human welfare and the promotion of social justice. Central to this theory are the principles of maslahah, which advocate for actions that yield the greatest benefit for society, thereby aligning economic activities with ethical and moral values. This article seeks to analyse the application of Al-Maqāṣid asy-Syarī'ah in the realm of sustainable economic development, underscoring its potential to foster holistic community welfare. Employing a qualitative methodology, this study will delve into pertinent literature, elucidate the research methods employed, and present the findings that emerge from the analysis. It is anticipated that the insights gleaned from this research will illuminate the significance of integrating Islamic principles into sustainable economic practices, ultimately contributing to a more equitable and environmentally sound future. By recognising the interconnectedness of economic, social, and environmental factors, we can pave the way for a development model that is not only sustainable but also just and inclusive.

Методический подход к согласованию стратегических приоритетов государственной региональной политики развития старопромышленных регионов Российской Федерации

The formation of strategic priorities of the state regional policy for the development of old-industrial regions is complicated by the multiplicity of its actors and the need to coordinate spatial and sectoral priorities of regulatory impact. The article presents a methodological approach to coordinating the priorities of spatial and sectoral development of old industrial regions in the format of a scheme reflecting the logic and sequence of actions aimed at achieving strategic goals of regional development in accordance with the strategic national priorities of the Russian Federation. The methodological approach was tested on the example of the Saratov region, one of the old industrial regions of Russia with growth potential within the framework of the industrial development model. The necessity of using two approaches in the coordination process is justified: the first should be used to achieve the strategic priorities of the federal Center in a coordinated manner, on the one hand, and the old industrial regions and enterprises and organizations of the "industrial core", on the other (coordination "vertically"); the second — in order to coordinate the regional priorities of spatial and sectoral development of the old industrial region (horizontal alignment). Proposals are presented for the formation of a list of agreed priorities for the spatial and sectoral development of the Saratov region, the implementation of which will contribute to the transformation of the region into a point of growth of the national economy of Russia.

Design and Development Model of a Web Accessibility Ecosystem

The article examines issues of web accessibility ecosystems for people with special needs. Methods, models, accessibility standards, and technologies related to the structure, design, and functionality of the web accessibility ecosystem are studied. The stages of developing an accessibility ecosystem are explored. The accessibility of the design, functionalities, structure, and content of a particular ecosystem are presented. Several themes for the design of the system with an emphasis on its accessibility for blind users are explored and analyzed. UX/UI design and the ontological model of accessibility, used in the implementation of the model of the ecosystem and its elements, are studied. A web accessibility ecosystem model has been developed, compliant with the Web Content Accessibility Guidelines and based on semantic technologies. Other qualities of this model are easy access to information resources on the topic of accessibility, convenience for users with different needs, and the possibility of expansion and enrichment in the future.

The effects of herding and dispersal behaviour on the evolution of cooperation on complete networks

Evolutionary graph theory has considerably advanced the process of modelling the evolution of structured populations, which models the interactions between individuals as pairwise contests. In recent years, these classical evolution models have been extended to incorporate more realistic features, e.g. multiplayer games. A recent series of papers have developed a new evolutionary framework including structure, multiplayer interactions, evolutionary dynamics, and movement. However, so far, the developed models have mainly considered independent movement without coordinated behaviour. Although the theory underlying the framework has been developed and explored in various directions, several movement mechanisms have been produced which characterise coordinated movement, for example, herding. By embedding these newly constructed movement distributions, within the evolutionary setting of the framework, we demonstrate that certain levels of aggregation and dispersal benefit specific types of individuals. Moreover, by extending existing parameters within the framework, we are not only able to develop a general process of embedding any of the considered movement distributions into the evolutionary setting on complete graphs but also analytically produce the probability of fixation of a mutant on a complete N-sized network, for the multiplayer Public Goods and Hawk–Dove games. Also, by applying weak selection methods, we extended existing previous analyses on the pairwise Hawk–Dove Game to encompass the multiplayer version considered in this paper. By producing neutrality and equilibrium conditions, we show that hawks generally do worse in our models due to the multiplayer nature of the interactions.

Method of Maximizing F-Synergistic Value in IT Development Projects for Self-Managed Organizations

The article is devoted to the formulation of the method of maximizing the F-synergistic value of IT development projects of a project-oriented organization, which was developed within the syncretic methodology of project management. The application of the proposed method is considered in the field of IT development projects of organizations involved in infrastructure restoration projects of Ukraine. The directions of scientific research in the field of value-oriented project management are analyzed. The previously unsolved part of the scientific problem is highlighted. Objects of value analysis in a project-oriented organization carrying out IT development were identified, among which stellarator projects were highlighted. A model for determining the value of a separate component of the system is presented. The concept of F-synergistic value is defined. Such a value is proposed to be calculated through the aggregate value of three clusters that create synergistic effects both within themselves (first-order value) and among themselves (second-order value). The clusters included: "IT + people" cluster, "projects + operational activity" cluster, "methodology + environment" cluster. Models for determining the value of a separate cluster and the aggregate F-synergistic value are proposed. Variations in the selection of weighting factors for evaluating value criteria are considered. Within the syncretic methodology, a method of maximizing the F-synergistic value of IT development of a project-oriented company is proposed. The model of 27 scenarios of the dynamics of the change of the multipliers of synergy of three clusters is presented. In the corresponding tables for each scenario, a hypothesis is put forward regarding the reasons for such dynamics for each scenario, as well as a model of further IT development of a project-oriented company in response to such reasons. According to the results of the development of the method of maximizing the F-synergistic value of IT development projects of a project-oriented organization guided by syncretic methodology, directions for improving the activities of such organizations were determined. An extended SWOT analysis of the proposed method was conducted. Conclusions based on the research are formulated, prospects for further research in the chosen direction are outlined.

CO2 gas-liquid equilibrium study and machine learning analysis in MEA-DMEA blended amine solutions

The combination of primary and tertiary amines represents a promising approach to improve sorbent performance in CO2 capture by enhancing absorption efficiency and reducing regeneration energy. This study focuses on investigating the absorption performance of binary mixtures of ethanolamine (MEA) and N,N-dimethylethanolamine (DMEA) at temperatures between 298–323 K and CO2 partial pressures between 5–60 kPa. The species generated during the absorption were analyzed using 13C NMR spectroscopy, to clarify the intricate role of MEA and DMEA in the capture process. A developed excess property model for MEA-DMEA, based on excess CO2 loading, predicted equilibrium CO2 solubility data with an average absolute relative deviation (AARD) of 1.6 %. Additionally, the machine learning models XGBoost, RBFNN, and SVR were applied, providing AARD values between 0.86 % and 1.28 %, demonstrating strong agreement between experimental and predicted outcomes. These comprehensive findings enhance our understanding of mixed amines’ mechanisms and practical applications, contributing to ongoing research development.

Acausal Fuel Cell Simulation Model for System Integration Analysis in Early Design Phases

Hydrogen technologies have the potential to reduce aviation’s CO2 emissions but come with many challenges. This paper introduces a scalable hydrogen fuel cell model tailored for system integration analysis in early aircraft design phases. The model focuses on Proton Exchange Membrane Fuel Cells (PEMFCs) and is based on thermodynamic equations and empirical data to simulate performance under different ambient and operating conditions; it also includes a simplified model of the Balance of Plant (BOP) systems and is implemented in OpenModelica. The model performance is validated through a comparison of the simulated polarization curves with real datasheet data. A case study highlights the peculiarities of this model by studying the sizing of the fuel cell stacks for a modified ATR 72 aircraft. The developed model effectively supports the early design exploration of the aircraft with a greater level of detail for system integration studies, essential to better explore the potential of aircraft featuring hydrogen-based power systems.

Influence of a new controlled voltage regulator on the current and voltage non-sinusoidality of a power supply system

This work evaluates the influence of a new controlled voltage regulator on the current and voltage non-sinusoidality in different sections of a power supply system during smooth (discrete) voltage regulation on the high-voltage side of a shop transformer. The MatLab software application was used to develop a block-modular model for a transformer substation with the proposed controlled voltage regulator and measurement modules. The developed model was used to investigate the current and voltage non-sinusoidality in different parts of a power supply system when stabilizing the voltage at the consumer end at a given level. The study was carried out using a shop transformer with a capacity of 1 MV∙A and a voltage of 6/0.4 kV under an active-inductive character of the load with the load current phase angle of φ=45 deg. The obtained results confirm that, due to the extended functional capabilities of the proposed technical solution, the voltage at consumers is maintained at a given level under high technical and economic performance. When the network voltage is reduced by 5% and the activeinductive load current is increased by 35%, the proposed device was shown to create voltage non-sinusoidality. The voltage non-sinusoidality value does not exceed the permissible domestic and international norms. In addition, the proposed device is capable of maintaining the voltage at the consumer end at a given level. The obtained integral characteristic of voltage stabilization shows that the application of the proposed technical solution instead of the existing mechanical voltage regulator of the “switching without excitation” type allows the nominal voltage at the busbar of the switchgear to be retained. Further research will investigate voltage stabilization at consumers with simultaneous compensation of reactive power for complex improvement of technical and economic indicators of power supply systems under the conditions of unstable supply voltage and load current.

Optimal Configuration of Modular Strongrooms Using Multi-Attribute Decision Making

In this paper, we show that it is possible to obtain an optimal configuration variant of Modular Strongrooms (MSR) that satisfies the individual requirements of customers and is most economically advantageous for manufacturers. A model of the automatic configuration system for configuring MSR type MODULPRIM was developed, integrating the procedures for generating product variants, choosing the optimal configuration, and designing detailed products and technological processes. The developed model’s importance lies in its ability to automatically select the optimal configuration from a set of possible configurations on a multidisciplinary basis. The problem of choosing was solved by integrating the Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods from the group of Multi-Attribute Decision Making (MADM). Validation of the proposed model was performed on eight examples of Modular Strongrooms type MODULPRIM 5 and showed great opportunities to improve efficiency and effectiveness in the process of innovative product development, as well as to obtain a product configuration with significantly improved quality. The proposed model has a high degree of flexibility and universality; thus, it can be further upgraded and integrated into a company’s business system.

8053 A Ligand-Based Differentiation Protocol for Human Induced Pluripotent Stem Cells Recapitulates Granulosa Cell Development and Induces Steroidogenic Pathway Genes

Abstract Disclosure: H. Kubo: None. M.M. Laronda: None. Sex determination is a developmental process that defines the gonad as a testis or ovary, and influences sex hormone production. While key signaling events are well conserved across mammals, there can be differences between species. Therefore, there is a need to develop a human model to fully understand this critical process in humans. We have developed a ligand-based differentiation protocol for human induced pluripotent stem cells (hiPSCs) to generate granulosa-like cells (GLCs). Additionally, hiPSC-derived GLCs could become the foundation for a cell-based hormone replacement therapy that recapitulates cyclicity, physiologic levels of hormones, and production of peptide hormones that are not included in currently available hormone replacement therapies. We aim to gain further understanding of the key factors and culture conditions necessary for functional GLCs that produce ovarian hormones, which includes maintained expression of FOXL2. We used our monolayer differentiation protocol that includes WNT-agonist CHIR99021 treatment for 2 days, followed by a combination treatment of BMP4, FST, and DKK1-inhibitor Gallocyanine for 3 days. We have tested our protocol on three different hiPSC lines: IISH2i-BM9s, STiPS-A3, and STiPS-A6. Expression of pluripotency marker POU5F1 is reduced during differentiation, while expression of the intermediate mesoderm markers PAX2, LHX1, and WT1 and bipotential gonad marker GATA4 peak at day 2. Peak expression of the bipotential gonad marker NR5A1 occurred at day 2 in the STiPS-A6 cells, but at day 5 in IISH2i-BM9 and STiPS-A3 cells. Interestingly, FOXL2 expression peaks at day 2 in all three lines and drops by day 5. In the IISH2i-BM9s, FOXL2 protein peaks at day 2 by Jess Western while there is the highest percentage of FOXL2-positive cells at day 5 by immunofluorescence. In murine granulosa cells, FOXL2 maintenance depends on NR5A2. NR5A2 expression drops in the GLCs, which suggests that NR5A2 loss may be preventing FOXL2 maintenance. Additionally, as FOXL2 is required for expression of aromatase and HSD17B1, we are using this model to interrogate NR5A2 upstream of FOXL2 and control hormone production. CYP19A1 and HSD17B1 along with AMH are induced during this differentiation protocol, suggesting these GLCs can be steroidogenic and produce peptide hormones. Additionally, scRNA-seq analysis of the GLCs is underway to identify types of granulosa cells produced by this protocol. Future directions include optimizing GLC culture conditions to generate hormones and to test if NR5A2 inhibitors alter FOXL2 expression. Put together, the data suggests that cells differentiated with our protocol show promise as a human model of ovarian development and a foundation for a personalized cell-based hormone replacement therapy. This work is supported by the NIH/NICHD R01HD104683 (MML), HuBMAP U01HD110336 (MML), and Gesualdo Family Research Scholar (MML). Presentation: 6/2/2024

Ecosystem model of development of the unmanned aircraft systems industry

The article analyzes the structural transformations of Russian industry in the context of external constraints and the need to ensure technological sovereignty in high-tech industries. The scientific hypothesis of the work is the assumption of the importance of cross-sectoral coordination of subjects of industrial policy in order to develop the production of critical products. The digital industrial ecosystem of the unmanned aircraft systems (UAS) industry is considered as an object of research. The purpose of the research is to develop the foundations of the structure of the ecosystem model of the development of the UAS industry and substantiate the feasibility of its application in the interests of improving high-tech industries of the Russian Federation. The article offers the author’s interpretations of the concepts of “digital industrial ecosystem” and “cross-industry ecosystem”, substantiates the principles of functioning of the ecosystem model and its architecture. An ecosystem model of the development of the UAS industry was developed, including management bodies, technical infrastructure, organizational and economic tools, technological clusters and a network of participants. The main distinguishing features of the proposed model from the existing ones are: the distribution of ecosystem management bodies that ensure the autonomy of management at all horizontal and hierarchical levels of its organization; the ecosystem is considered as an instrument of the mechanism of strategic development of high-tech industries involved in the creation of civil-purpose UAS, and provides cross-industry interaction of participants in order to accelerate the development of industrial production and the formation of the UAS market. The ecosystem management model will ensure the possession of up-to-date data of actual and planned indicative evaluation indicators of the state and development of the industry on a time scale close to real, based on the principle of digital transparency.

8468 Development And Characterisation Of Three-Dimensional Cell Culture Models Of Adrenocortical Carcinoma

Abstract Disclosure: S. Feely: None. N. Mullen: None. P. Donlon: None. C. Hantel: None. M.C. dennedy: None. Adrenocortical carcinoma (ACC) is a rare malignancy carrying a poor prognosis and limited treatment options. Surgical resection is the only option for cure; but unsuitable for advanced disease. Mitotane is the approved medical therapy, but associated with treatment resistance and adverse effects. Newer therapies, such as immune checkpoint inhibitors, have limited success. Development of improved therapies is limited by current pre-clinical disease models. No available model reflects the tumour micro-environment. Three-dimensional (3D) cell culture models are increasingly used in cancer research (6), with a paucity of developed models in ACC. In the current study, we developed novel 3D models of ACC using a type-1 collagen matrix. We then characterised these as representative ACC disease models . 3D cell culture models of ACC were optimised by embedding ACC cell lines, MUC-1, HAC15 and H295R within a type-1 Collagen matrix at differing cell numbers. Expression of type-1 collagen in ACC primary tumours was determined using immunohistochemistry (n=4). Cell viability for each model was assessed by evaluating sytox blue staining by Flow Cytometry. Metabolic activity of ACC cells within the matrix was determined using AlamarBlue staining. Prolferative activity was assessed using Ki67. Steroidogenesis was evaluated by measuring cortisol, aldosterone and androstenedione using LC-MS/MS.. Expression of CYP11B1, CYP11B2 CYP17, and StAR was measured using RT-qPCR. Type 1 collagen is strongly expressed in ACC tumour microenvironment. MUC-1, H295R and HAC15 cells were successfully cultured in a type 1 collagen matrix. MUC-1 cells cultured in the collagen matrix remain viable throughout the period of experimentation with optimum viability between 14 and 21 days. H295R cells also remain viable with optimum viability at an earlier stage of 7-14 days. HAC15 cells demonstrate high resilience in 3D cell culture with maximum viability throughout the entire period of experimentation up to 21 days. All three models increase their metabolic and proliferative activity over time. All three steroids are expressed by all three models with an increase in aldosterone secretion observed in 3D HAC15 and H295R models compared to monolayer (p>0.001) at days 7 and 14. All models express key steroidogenic enzymes. 3D ACC cell culture models were developed successfully using collagen type 1 abundant in ACC. Typical characteristics of the ACC tumour environment included (i) the presence of live and necrotic cells (ii) high metabolic activity and proliferation, reflective of cell turnover.. Capacity of cells to spread and proliferate within the 3D cell culture models was limited by available collagen substrate. Steroidogenic capacity was demonstrated in 3D cell culture. This model therefore retained key characteristics of ACC and shows promise as an animal-sparing, pre-clinical model. Presentation: 6/1/2024

Energy Demand Estimation in Turkey According to Road and Rail Transportation: Walrus Optimizer and White Shark Optimizer Algorithm-Based Model Development and Application

Transport energy demand (TED) forecasting is a crucial issue for countries like Turkey that are dependent on external resources. The accuracy and effectiveness of these forecasts are extremely important, especially for the strategies and plans to be developed. With this in mind, different forms of forecasting models were developed in the present study using the Walrus Optimizer (WO) and White Shark Optimizer (WSO) algorithms to estimate Turkey’s energy consumption related to road and railway transportation modes. Additionally, another objective of this study was to examine the impacts of different transport modes on energy demand. To investigate the effect of demand distribution among transport modes on energy consumption, model parameters such as passenger-kilometers (P-km), freight-kilometers (F-km), carbon dioxide emissions (CO2), gross domestic product (GDP), and population (POP) were utilized in the development of the models. It was found that the WO algorithm outperformed the WSO algorithm and was the most suitable method for energy demand forecasting. All the developed models demonstrated a better performance level than those reported in previous studies, with the best performance achieved by the semi-quadratic model developed with the WO, showing a 0.95% MAPE value. Projections for energy demand up to the year 2035 were established based on two different scenarios: the current demand distribution among transport modes, and a demand shift from road to rail transportation. It is anticipated that the proposed energy demand models will serve as an important guide for effective planning and strategy development. Moreover, the findings suggest that a balanced distribution among transport modes will have a positive impact on transport energy and will result in lower energy requirements.

Identification and Spatial Characterization of suburban areas in Chengdu

As transitional territories where urban and rural functions interpenetrate, suburban areas have multiple values such as recreation, ecology, agriculture and landscape. Promoting their benign development is the key to realizing global sustainable development of urban and rural areas. Planning control is based on precisely defining the spatial extent of suburban areas, and understanding suburban area differentiation and its driving forces scientifically is a key component in raising the bar for focused planning. However, there are currently few research on fine-scale quantitative identification of suburban regions because of their spatial complexity, ambiguous boundaries, and structural dynamic features. Based on this, this paper develops a multi-dimensional identification index system for suburban areas by using multi-source big data and remote sensing information technology, employs the random forest model and the K-Medoids clustering algorithm, identifies the distribution of suburban areas and their subdivided types, analyzes spatial differentiation characteristics, and conducts empirical research using Chengdu City as an example. The findings demonstrate that: (1) The majority of suburban areas in Chengdu City are concentrated in groups or belts surrounding the urban centers of various districts and counties, and the higher the functional class of a district or county, the denser the distribution of suburban areas. (2)The distribution pattern of suburban areas in Chengdu basically conforms to its planned urban hierarchy system.(3)Urban-oriented, suburban-interacted and rural-oriented suburban areas have their own characteristics in land use level, economic development and regional population characteristics.(4)Regional openness, government behavior, social development and geographical location are the core driving factors of spatial differentiation of suburban areas in Chengdu, and the interaction between urban and rural systems, the flow of social resources and the transformation of development models are the spatial mapping dimensions that affect its differentiation.(5)Chengdu can draw up detailed regulatory planning of suburban units to standardize and guide the overall development of suburban areas. In support of the global sustainable development goals, this study offers a methodology for precisely and impartially defining suburban areas, assisting in the implementation of integrated urban-rural development globally.

Ultrasonic Non-Destructive Testing of Accelerated Carbonation Cured-Eco-Bricks

This study aimed to investigate the behavior of accelerated carbonation-cured laboratory specimens using the ultrasonic non-destructive testing (UNDT) method and compare the results with the destructive testing (DT) method. The materials used in the study included a blend of lime kiln dust and ground granulated blast furnace slag (LKD-GBFS) wastes, natural fine aggregate (sand), and alternative fine aggregates from waste tires. The chemical analysis of the LKD and GBFS samples highlighted them as suitable alternatives to OPC, hence their utilization in the study. A 60:40 (LKD-GBFS) blending ratio and a 1:2 mix design (one part LKD-GBFS blend and two part sand) was considered. The natural fine aggregate was partially replaced with fine waste tire rubber crumbs (TRCs) in stepped increments of 0, 5, and 10% by the volume of the sand. The samples produced were cured using three curing regimens: humid curing (HC), accelerated carbonation curing (ACC) with no water curing (NWC) afterwards, and water curing after carbonation (WC). From the results, an exponential model was developed, which showed a direct correlation between the UNDT and DT results. The developed model is a useful tool that can predict the CS of carbonated samples when cast samples are unavailable. Lastly, a total CO2 uptake of 15,912 g (15.9 kg) was recorded, which underscores ACC as a promising curing technique that can be utilized in the construction industry. This technique will bring about savings in terms of the time required to produce masonry units while promoting a change in the basic assumptions of a safer and cleaner environment.