Developed Model Research Articles

QSAR modelling of enzyme inhibition toxicity of ionic liquid based on chaotic spotted hyena optimization algorithm

ABSTRACT Ionic liquids (ILs) have attracted considerable interest due to their unique properties and prospective uses in various industries. However, their potential toxicity, particularly regarding enzyme inhibition, has become a growing concern. In this study, a QSAR model was proposed to predict the enzyme inhibition toxicity of ILs. A dataset of diverse ILs with corresponding toxicity data against three enzymes was compiled. Molecular descriptors that capture the physicochemical, structural, and topological properties of the ILs were calculated. To optimize the selection of descriptors and develop a robust QSAR model, the chaotic spotted hyena optimization algorithm, a novel nature-inspired metaheuristic, was employed. The proposed algorithm efficiently searches for an optimal subset of descriptors and model parameters, enhancing the predictive performance and interpretability of the QSAR model. The developed model exhibits excellent predictive capability, with high classification accuracy and low computation time. Sensitivity analysis and molecular interpretation of the selected descriptors provide insights into the critical structural features influencing the toxicity of ILs. This study showcases the successful application of the chaotic spotted hyena optimization algorithm in QSAR modelling and contributes to a better understanding of the toxicity mechanisms of ILs, aiding in the design of safer alternatives for industrial applications.

Validity and Effectiveness of STEAM-Based Food Microbiology Electronic Booklet to Improve Critical Thinking Skills of Biology Students

Objective: This research and development aims to determine the validity and effectiveness of STEAM-based food microbiology electronic booklets based on the assessment of validators and the results of student critical thinking skills tests. Method: This research is an R&D study using the ADDIE development model. The developed product was tested on students using the One Group Pretest-Posttest research design. The validity test was carried out by giving a questionnaire to the validator, and the effectiveness test was carried out by giving a test in the form of 20 fill-in questions to 15 Biology students. Results: The results of this study are that STEAM-based electronic booklets are very feasible to use as teaching materials and learning media and are effective in teaching food microbiology because they can improve students' critical thinking skills. This study is recommended to carry out STEAM-based electronic booklet development innovations in other food microbiology materials. Novelty: The novelty of this study lies in the research variables, which focus on the validity and effectiveness of food microbiology electronic booklets integrated with the STEAM approach to obtain teaching materials that encourage students to be active in learning activities.

Design Of Simulation Application System For Corporate Income Tax

The design of the corporate income tax simulation application system aims to provide an effective and efficient tool for companies in calculating income tax liabilities in accordance with applicable tax regulations. The research method used is to start identifying problems through literature studies related to corporate taxes and interviews with users. Then analyze the needs related to the required features, security, performance and ease of use. The development system used is the waterfall model method. The waterfall model method is one of the software development models in the SDLC (Sequencial Development Life Cycle) model. Waterfall models are often also called linear sequence models or classic life flows. Key features developed include an intuitive user interface, flexibility in handling companies of various sizes, and strict data security to protect sensitive financial information. With a comprehensive design and focusing on user needs, this application is expected to be a reliable solution in supporting corporate income tax management.

Molecular Interactions Governing the Rat Aryl Hydrocarbon Receptor Activities of Polycyclic Aromatic Compounds and Predictive Model Development

Polycyclic aromatic compounds (PACs) exhibit rat aryl hydrocarbon receptor (rAhR) activities, leading to diverse biological or toxic effects. In this study, the key amino residues and molecular interactions that govern the rAhR activity of PACs were investigated using in silico strategies. The homology model of rAhR was first docked with 90 PACs to yield complexes, and the results of the molecular dynamics simulations of 16 typical complexes showed that the binding energies of the complexes range from −7.37 to −26.39 kcal/mol. The major contribution to the molecular interaction comes from van der Waals forces, and Pro295 and Arg316 become the key residues involved in most complexes. Two QSAR models were further developed to predict the rAhR activity of PACs (in terms of log IEQ for PACs without halogen substitutions and log%-TCDD-max for halogenated PACs). Both models have good predictive ability, robustness, and extrapolation ability. Molecular polarizability, electronegativity, size, and nucleophilicity are identified as the important factors affecting the rAhR activity of PACs. The developed models could be employed to predict the rAhR activity of other reactive PACs. This work provides insight into the mechanisms and interactions of the rAhR activity of PACs and assists in the assessment of their fate and risk in organisms.

МОДЕЛЬ НЕПРЕРЫВНОГО ТРАНСПОРТНОГО ПОТОКА БЕСПИЛОТНЫХ АВТОМОБИЛЕЙ ПРИ ДВИЖЕНИИ НА СЕРПАНТИНЕ С ВИРАЖАМИ С УЧЕТОМ СРЕДНЕЙ СКОРОСТИ ДВИЖУЩИХСЯ ВПЕРЕДИ АВТОМОБИЛЕЙ

The paper proposes a new model of continuous traffic flow of unmanned autonomous cars when travelling on a serpentine with curves, taking into accountthe average speed of the cars ahead. The review of existing traffic flow models, in particular, the models of following the leader, such as the optimal speed model, generalised traffic model, model of total velocity difference is carried out. It is noted that these models do not take into account the peculiarities of traffic on serpentines with turns. On the basis of the existing models, a new model of continuous traffic flow has been developed, the principal difference of which is the consideration of the transverse slope of the road (turn) when travelling on a serpentine. The model takes into account the action of forces on the vehicle, including gravity, driving force and centripetal force. The prospects of using the developed model in the conditions of using intelligent transport systems, when the information about the average speed of vehicles moving ahead is transmitted over the network, are shown. Th proposed model allows to take into account the transverse slope of the road on curvilinear serpentine sections when calculating speed modes, to adequately assess the carrying capacity and identify potentially dangerous sections for optimisation of design decisions when creating unmanned transport.

Estimating Rainfall Intensity Using an Image-Based Convolutional Neural Network Inversion Technique for Potential Crowdsourcing Applications in Urban Areas

High-quality rainfall data are essential in many water management problems, including stormwater management, water resources management, and more. Due to the high spatial–temporal variations, rainfall measurement could be challenging and costly, especially in urban areas. This could be even more challenging in tropical regions with their typical short-duration and high-intensity rainfall events, as some of the undeveloped or developing countries in those regions lack a dense rain gauge network and have limited resources to use radar and satellite readings. Thus, exploring alternative rainfall estimation methods could be helpful to back up some shortcomings. Recently, a few studies have examined the utilisation of citizen science methods to collect rainfall data as a complement to the existing rain gauge networks. However, these attempts are in the early stages, and limited works have been published on improving the quality of such data. Therefore, this study focuses on image-based rainfall estimation with potential usage in citizen science. For this, a novel convolutional neural network (CNN) model is developed to predict rainfall intensity by processing the images captured by citizens (e.g., by smartphones or security cameras) in an urban area. The developed model is merely a complementary sensing tool (e.g., better spatial coverage) to the existing rain gauge network in an urban area and is not meant to replace it. This study also presents one of the most extensive datasets of rain image data ever published in the literature. The estimated rainfall data by the proposed CNN model of this study using images captured by surveillance cameras and smartphone cameras are compared with observed rainfall by a weather station and exhibit strong R2 values of 0.955 and 0.840, respectively.

Risk Prediction Models for Adverse Drug Reactions and Adverse Drug Events in Older Adults – A Systematic Review and Meta-analysis

Abstract Background Adverse drug reactions (ADRs) and adverse drug events (ADEs) are common and result in significant morbidity, mortality and healthcare costs. As the world’s population ages, the consumption of medications and healthcare will increase. Models predicting ADR risks in older adults have previously been found to lack reliability and validity. The aim of this systematic review and meta-analysis is to provide an updated, comprehensive quality assessment and analysis of ADR-risk prediction tools in older adults. Methods Standard computerised-databases and citations were searched (2012 to 2023) to identify relevant peer-reviewed studies. Studies which developed and/or validated an ADR/ADE prediction model for use in older adults were included. Four studies from a previous systematic review were also included. The TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) guidelines were used to evaluate each of the included studies. Random effects models were used to derive a pooled discrimination estimate (area under the receiver operation curve; AUROC) for model development studies and model validation studies. The prediction model risk of bias assessment tool (PROBAST) was applied to evaluate bias. Results Five out of 11,481 titles, plus four previous studies, met all inclusion criteria and underwent TRIPOD evaluation. Meta-analysis resulted in a favourable pooled AUROC 0.75 (95% CI 0.57, 0.87; I-squared= 96.65%) for model development studies and 0.70 (95% CI 0.57, 0.80; I-squared= 90.53%) for model validation studies but there was substantial heterogeneity. Studies had poor adherence (range 32-50%; median 44%; IQR 11.5%) to TRIPOD guidelines. The overall risk of bias was high for all included studies. Conclusion Seven risk prediction models were identified, all exhibiting poor adherence to TRIPOD guidelines which may question the investigational rigor of the studies and their usability. This underscores the need for the development of a validated, robust and reliable tool worthy of implementation and testing in a real-world setting.

Quantification and sensitivity assessment of Chinese provincial ecological compensation in the perspective of carbon deficit redistribution

The ecological compensation mechanism is a tool for managing regional development and promoting the green economy. This paper proposes a revised model for carbon emissions and absorption based on IPCC, then analyses the spatial and temporal variations of carbon emissions, absorption, and deficit in 31 provinces of China from 2001 to 2019. A model was developed to redistribute carbon deficits and compensate for ecological imbalances, with the aim of eliminating background differences between regions. The concept of ecological compensation sensitivity was proposed, and a redundancy analysis (RDA) was conducted to detect possible influencing factors. Results indicate that: (1) The carbon deficits were relatively substantial in the centre and developed coastal regions, which were the subject regions of China’s ecological compensation. Meanwhile, the northwest and southwest regions were the object regions of ecological compensation, and the compensated object regions tended to extend towards the southeast. The majority of compensated subject areas are generally less sensitive than compensated object regions. (2) The graph of carbon deficit volume over time shows that China’s two carbon targets are closely aligned. The distribution of China’s ecological compensation amounts follows the pattern of provincial economic development levels, with higher compensation amounts concentrated in the central and coastal regions. There is a positive correlation between GDP, year, and population size with carbon emission and carbon deficit. Additionally, there is a positive correlation between year, region, and carbon absorption. (3) This compensation model can strongly incentivise the compensation subject area to proactively adjust its economic development model to cope with the significant compensation pressure. Additionally, it can fully encourage the compensation recipient area to continue adhering to the green economic development model. The conclusions of the study hold significant reference value for promoting the development of a green, low-carbon economy.

French Language Learning Media Based on Project-Based Learning Assisted by the Pear Deck Application

The purpose of this research is to determine (1) the feasibility of learning media assisted by the Pear Deck application based on project-based learning (PjBL). (2) determine the effectiveness of PjBL-based learning media. The research method is R&D using the Borg and Gall development models. This research was conducted in class XI SMAN 1 Lubuk Pakam, totaling 28 students. The research subjects are material experts, media experts, and design experts. The research results show that: (1) the learning material expert test criteria are very good (94%); (2) the learning media expert test criteria are very good (93%); and (3) the learning design expert test criteria are very good (94%). The results of submitting a hypothesis can prove that: (1) learning media assisted by the PjBL-based Pear Deck application is suitable for use (2) The learning media assisted by the PjBL-based Pear Deck application is effective to use. The average effectiveness of students' French learning outcomes in using the PjBL-based Pear Deck Application in the experiment class was 86.42%, and the average effectiveness of the average effectiveness of students who used picture and book learning media in the control class was 49.5%. The posttest results obtained a value of Tcount = 7.08 at a significant level of α = 0.05, with dk 27 obtaining Ttable = 1.674, so that Tcount > Ttable, namely 7.08 > 1.674. The use of learning media assisted by the PjBL-based Pear Deck application is very feasible and effective.

Monitoring and Optimization of Potato Growth Dynamics under Different Nitrogen Forms and Rates Using UAV RGB Imagery

The temporal dynamics of canopy growth are closely related to the accumulation and distribution of plant dry matter. Recently, unmanned aerial vehicles (UAVs) equipped with various sensors have been increasingly adopted in crop growth monitoring. In this study, two potato varieties were used as materials, and treated with different combinations of nitrogen forms (nitrate and ammonium) and application rates (0, 150, and 300 kg ha−1). A canopy development model was then constructed using low-cost time-series RGB imagery acquired by UAV. The objectives of this study were to quantify the variation in canopy development parameters under different nitrogen treatments and to explore the model parameters that represent the dynamics of plant dry matter accumulation, as well as those that contribute significantly to yield. The results showed that, except for the thermal time to canopy senescence (t2), other parameters of the potato canopy development model exhibited varying degrees of variation under different nitrogen treatments. The model parameters were more sensitive to nitrogen forms, such as ammonium and nitrate, than to application rates. The integral area (At) under the canopy development curve had a direct effect on plant dry matter accumulation (path coefficient of 0.78), and the two were significantly positively correlated (Pearson correlation coefficient of 0.93). Integral area at peak flowering (AtII) was significantly correlated with yield for both single and mixed potato varieties, having the greatest effect on yield (total effect of 1.717). In conclusion, UAV-acquired time-series RGB imagery could effectively quantify the variation of potato canopy development parameters under different nitrogen treatments and monitor the dynamic changes in plant dry matter accumulation. The regulation of canopy development parameters is of great importance and practical value for optimizing nitrogen management strategies and improving yield.

Increasing the size and coverage of protected areas will not be enough for effective biodiversity conservation

KEY POLICY INSIGHTS Socio-economic issues must be addressed simultaneously to agree in theoretical issues for the management of extant and new protected areas. An increase in the area covered by protected areas does not guarantee biodiversity conservation. The global development model, based on economic growth, is the major impediment to biodiversity conservation.

What can we learn from one-to-one trials in Instructional design? A case from module development

The one-to-one trial phase within the instructional design development model has frequently been neglected in prior research. This stage should provide much in-depth insight considering its nature, which is in-depth face-to-face data collection between designers and participants. In this study, we aim to analyze a particular instance of module development during the one-to-one trial phase. This study is part of the media development stage with the ADDIE model (Analyze, Design, Develop, Implement, and Evaluate) at the implementation stage. We used quantitative data collection through scoring and qualitative data through interviews with six participants involved in the one-to-one trial. The findings revealed that students provided critical feedback on two aspects of the module, particularly its design appeal and suitability for independent learning, aligning with an average participant score of 3 on a 1-5 scale. These results provide an overview that one-to-one as a foundation and initiation for a broader trial plays an essential role in providing a starting point for an implementation where quantitative and qualitative data provide holistic insight.

Modeling the Influence of Thermal Phenomena in Inductors and Capacitors on the Characteristics of the SEPIC Converter

The paper presents the results of measurements and calculations of the SEPIC converter characteristics, taking into account thermal phenomena in semiconductor devices and passive elements. Compact electrothermal models of the MOSFET transistor, diode, capacitor, and inductor are proposed. Parasitic phenomena are also included in these models. The form of the developed models and the method of determining the values of their parameters are presented. The correctness of the formulated models was verified experimentally. Calculations and measurements of the characteristics of SEPIC converters containing inductors with ferromagnetic cores made of different materials were carried out. The obtained results of the investigations are discussed, and the range of applicability of the formulated models is described. It was shown that, at the considered operating conditions at an ambient temperature equal to 22 °C, the temperature of capacitors can exceed 40 °C, whereas the temperatures of inductors can even reach 50 °C.

Electrothermal Modeling of Photovoltaic Modules for the Detection of Hot-Spots Caused by Soiling

Solar energy plays a major role in the transition to renewable energy. To ensure that large-scale photovoltaic (PV) power plants operate at their full potential, their monitoring is essential. It is common practice to utilize drones equipped with infrared thermography (IRT) cameras to detect defects in modules, as the latter can lead to deviating thermal behavior. However, IRT images can also show temperature hot-spots caused by inhomogeneous soiling on the module’s surface. Hence, the method does not differentiate between defective and soiled modules, which may cause false identification and economic and resource loss when replacing soiled but intact modules. To avoid this, we propose to detect spatially inhomogeneous soiling losses and model temperature variations explained by soiling. The spatially resolved soiling information can be obtained, for example, using aerial images captured with ordinary RGB cameras during drone flights. This paper presents an electrothermal model that translates the spatially resolved soiling losses of PV modules into temperature maps. By comparing such temperature maps with IRT images, it can be determined whether the module is soiled or defective. The proposed solution consists of an electrical model and a thermal model which influence each other. The electrical model of Bishop is used which is based on the single-diode model and replicates the power output or consumption of each cell, whereas the thermal model calculates the individual cell temperatures. Both models consider the given soiling and weather conditions. The developed model is capable of calculating the module temperature for a variety of different weather conditions. Furthermore, the model is capable of predicting which soiling pattern can cause critical hot-spots.

Integrated bioprocessing and genetic strategies to enhance soluble expression of anti-HER2 immunotoxin in E. Coli

Immunotoxins are widely applied for cancer therapy. However, bacterial expression of immunotoxins usually leads to the formation of insoluble and non-functional recombinant proteins. This study was aimed to improve soluble expression of a novel anti-HER2 immunotoxin under the regulation of the trc promoter in Escherichia coli by optimization of the cultivation conditions using response surface methodology (RSM). To conduct RSM, four cultivation variables (i.e., inducer concentration, post-induction time, post-induction temperature, and medium recipe), were selected for statistical characterization and optimization using the Box-Behnken design and Design Expert software. Based on the developed model using the Box-Behnken design, the optimal cultivation conditions for soluble expression of anti-HER2 immunotoxin were determined to be 0.1 mM IPTG for induction in the LB medium at 33 °C for 18 h. The expressed immunotoxin was successfully purified using affinity chromatography with more than 90% purity and its bioactivity was confirmed using cell-based ELISA. Technical approach developed in this study can be generally applied to enhance the production yield and quality of recombinant proteins using E. coli as the gene expression system.

Research on the Development Model of Computer Course Resources in Vocational Colleges Based on the Integration of Industry and Education

China is currently experiencing a critical period of development in vocational education from a scale-based approach to a content-based approach. The integration of industry and education is considered the main theme of vocational education reform, and one of its core issues is curriculum construction. The traditional reform of computer courses has a series of problems in terms of matching the structure with talent training goals, matching the content with professional job requirements, and integrating the evaluation system with professional development. To address this challenge, this article focuses on the construction of integrated curriculum resources between industry and education, with student ability cultivation as the core, and is committed to strengthening the deep connection between talent cultivation and enterprise development. To this end, we have explored and proposed a development model for industry education integration courses based on the concept of "school enterprise coeducation - practical majors - industry connectivity - zero distance docking", in order to solve many problems faced by traditional computer course reform and promote vocational education to move towards a more connotation rich development stage.

The Forecasting Model of the Impact of Shopping Centres in Urban Areas on the Generation of Traffic Demand

The increase in traffic caused by new development affects the change in traffic conditions on the surrounding roads, and shopping centres are significant traffic generators. The development of local travel generation rates and their characteristics for individual land uses from the aspect of traffic demand is a reliable way to plan traffic in order to come up with preventive solutions to traffic problems, that is, prevention of possible negative consequences on traffic conditions in the street network occurring due to the construction of shopping centres. One of the main aims of this paper is to develop a model for objective assessment of the generated traffic demand for significant changes in land use, such as the construction of shopping centres in medium-sized towns. All these would be steps in the right direction for the promotion of reliable traffic planning and adoption of TIA for every new development before a decision regarding the change in land purpose has been made. This kind of process still has not been established systematically in either Bosnia and Herzegovina and the Republic of Serbia, or in surrounding countries. This paper focuses on the formulation of a model for determining the volume of traffic generated by shopping centres in medium-sized towns in two countries of the Southeast Europe region. The survey was conducted in eight different locations (cities) where there are shopping centres with common facilities. The analysis showed that the number of visitors and vehicles attracted by the shopping centre zone can be determined by a model based on a linear regression analysis. The analysis included exploring several different factors of trip generation in shopping centres, including the relationship between trip generation and combinations of several independent variables. The verification of the model was conducted in real conditions of the traffic flow generated by a shopping centre which was not the analysis subject when forming the forecasting model. In this way, the validity of the proposed model is credibly assessed. The developed model can be applied in the procedures of planning the construction of shopping centres in medium-sized cities in the Republic of Serbia and Bosnia and Herzegovina, and wider, in the region of Southeast Europe, in order to estimate the volume of generated traffic demand, that is, its impact on the conditions of traffic on the surrounding traffic network.

Modeling and forecasting biogas production from anaerobic digestion process for sustainable resource energy recovery

Anaerobic digestion (AD) is one of the most extensively accepted processes for organic waste cleanup, and production of both bioenergy and organic fertilizer. Numerous mathematical models have been conceived for modeling the anaerobic process.In this study, a new modified dynamic mathematical model for the simulation of the biochemical and physicochemical processes involved in the AD process for biogas production was proposed. The model was validated, and a sensitivity analysis based on the OAT approach (one-at-a-time) was carried out as a screening technique to identify the most sensitive parameters. The model was developed by updating the bio-chemical framework and including more details concerning the physico-chemical process. The fraction XP was incorporated into the model as a particulate inert product arising from biomass decay (inoculum). New components were included to distinguish between the substrate and inoculum, and a surface-based kinetics was used to model the substrate disintegration. Additionally, the sulfate reduction process and hydrogen sulfide production have been included. The model was validated using data extracted from the literature. The model's ability to generate accurate predictions was testified using statistical metrics. The model exhibited excellent performance in forecasting the parameters related to the biogas process, with measurements falling within a reasonable error margin. The relative absolute error (rAE) and root mean square error (RMSE) were both less than 5 %, indicating a high ability of the current model in comparison with the literature. Additionally, the scatter index (SI) was below 10 %, and the Nash-Sutcliffe efficiency (NES) approached one, which affirms the model's accuracy and reliability. Finally, the model was applied to investigate the performances of the AD of food waste (FW). The findings of this study support the robustness of the developed model and its applicability as a virtual platform to evaluate the efficiency of the AD treatment and to forecast biogas production and its quality, CO2 emission, and energy potential across various organic solid waste types.

The Impact of Eco-tourism on the Local Economy of Kuruva Dweep, Wayanad: A Study of the Industry's Contribution to GDP and Sustainable Development

ABSTRACT The study examines the economic and environmental effects of eco-tourism in Kuruva Dweep, Wayanad, with a focus on its impact on local livelihoods and sustainability. Eco-tourism, considered a sustainable development model, has drawn more tourists to Kuruva Dweep, resulting in economic benefits such as job opportunities and increased income for local communities. However, this growth has raised concerns about environmental degradation and the region's long-term sustainability. Through surveys, descriptive statistics, and regression analysis, the study investigates the link between eco-tourism, its economic impact, and environmental consequences. The findings indicate a strong positive correlation between eco-tourism and local economic growth, but also reveal significant environmental challenges such as littering, resource overuse, and habitat disruption. The study concludes that while eco-tourism holds promise for sustainable development, stricter environmental management and greater community involvement are crucial to balance economic gains with ecological preservation. The study provides recommendations to encourage responsible tourism and ensure the long-term sustainability of Kuruva Dweep.

Analysis of the food crisis in the new era

Under the new development model of "dual circulation," it is essential to ensure absolute food security and to nip potential risks in the bud regarding food production and supply issues. In the face of extreme natural environments and a complex international situation, timely emergency measures should be taken and appropriate preparations should be made. To this end, this paper proposes the following suggestions on how to ensure China's food security: First, focus on agricultural production to enhance the overall production capacity and ensure a sustainable food supply. Second, break through key technologies such as "bottleneck" grain breeding and selection, and agricultural machinery equipment, using technological innovation and information exchange as means to achieve large-scale development of grain production. Third, from the perspectives of agricultural and industrial production, pay attention to the issue of food quality and safety. Fourth, in terms of grain import and grain reserve settings, consider both unblocking the grain path and hiding grain among the people.