Computer-based Model Research Articles

Integrating technology in teaching and learning practices: students’ competencies

Technology usage in teaching and learning is not a new pedagogical practice and the benefits of its adoption are noted in the literature. However, an area that is often neglected when integrating technology into teaching and learning is the competency level of the would-be learners or students. This study investigated student competency levels based on factors such as their prior exposure to computers and the availability of facilitating conditions such as human or technical support. The study adopted a descriptive approach and was quantitative in nature. Data was collected from 368 students by means of a questionnaire. Descriptive statistics were obtained through quantitative analysis and the computer-based assessment acceptance model (CBAAM) was adopted. The results showed that the provisioning of facilitating conditions in a technology-integrated academic environment positively influences student competency in the use of technology. Furthermore, results showed that prior exposure to computers significantly impacts student competency levels in such an environment.

Waste reduction via image classification algorithms: beyond the human eye with an AI-based vision

Modern manufacturing is the world's largest and most automated industrial sector. The rise of Industry 4.0 technologies such as Big Data, Internet of Things (IoT) devices, and Machine Learning has enabled a better connection with machines and factory systems. Data harvesting allowed for a more seamless and comprehensive implementation of the knowledge-based decision-making process. New models that provide a competitive edge must be created by combining the Lean paradigm with the new technologies of Industry 4.0. This paper presents novel computer-based vision models for automated detection and classification of damaged packages from intact packages. In high-volume production environments, the package manual inspection process through the human eye consumes inordinate amounts of time poring over physical packages. Our proposed three different computer-based vision approaches detect damaged packages to prevent them from moving to shipping operations that would otherwise incur waste in the form of wasted operating hours, wasted resources and lost customer satisfaction. The proposed approaches were carried out on a data set consisting of package images and achieved high precision, accuracy, and recall values during the training and validation stage, with the resultant trained YOLO v7 model.

Developing Computer Course Models Based on Learning Management System for Early Children Education Teachers

Course and training institutions as a nonformal education unit organized for people who need knowledge, skills, life skills, and attitudes for self-development, professional development, work, independent business, and/or continuing education to a higher level. Currently, the world is faced with the phenomenon of digital disruption, which is a situation shown by the movement of the industrial world or job competition that is no longer linear. In the field of courses and training, the current era of disruption has also led to online course and training services that can be accessed via the service provider’s web/page. These service providers are not in the form of educational units, but several experts in their fields have joined forces with several experts in information and communication technology to create courses and training services that can be accessed through electronic devices such as computers, laptops, and communication devices. One of the development of courses and training in the field of information and communication technology is based on learning management system (LMS)—a webbased application system that allows instructors and/or students to share material, submit, and return assignments, and communicate online. Results of research and development of computer-based course models and training that have been tested shows that the level of practicality of this model is very good according to the instructor, course, and training organizers. Results of course learning and computer-based training can improve the skills of early childhood education teachers in the office application computer course program.
 Keywords: non-formal education, courses and training, learning management system, early childhood education teachers

Ergonomic investigations on novel dynamic postural estimator using blaze pose and transfer learning

The aim is to develop a computer-based assessment model for novel dynamic postural evaluation using RULA. The present study proposed a camera-based, three-dimensional (3D) dynamic human pose estimation model using ‘BlazePose’ with a data set of 50,000 action-level-based images. The model was investigated using the Deep Neural Network (DNN) and Transfer Learning (TL) approach. The model has been trained to evaluate the posture with high accuracy, precision, and recall for each output prediction class. The model can quickly analyse the ergonomics of dynamic posture online and offline with a promising accuracy of 94.12%. A novel dynamic postural estimator using blaze pose and transfer learning is proposed and assessed for accuracy. The model is subjected to a constant muscle loading factor and foot support score that could evaluate one person with good image clarity at a time. Practitioner summary: A detailed investigation of dynamic work postures is largely missing in the literature. Experimental analysis has been performed using transfer learning, BlazePose, and RULA action levels. An overall accuracy of 94.12% is achieved for dynamic postural assessment.

Computer-Based Mechanobiological Fracture Healing Model Predicts Non-Union of Surgically Treated Diaphyseal Femur Fractures.

As non-unions are still common, a predictive assessment of healing complications could enable immediate intervention before negative impacts for the patient occur. The aim of this pilot study was to predict consolidation with the help of a numerical simulation model. A total of 32 simulations of patients with closed diaphyseal femoral shaft fractures treated by intramedullary nailing (PFNA long, FRN, LFN, and DePuy Synthes) were performed by creating 3D volume models based on biplanar postoperative radiographs. An established fracture healing model, which describes the changes in tissue distribution at the fracture site, was used to predict the individual healing process based on the surgical treatment performed and full weight bearing. The assumed consolidation as well as the bridging dates were retrospectively correlated with the clinical and radiological healing processes. The simulation correctly predicted 23 uncomplicated healing fractures. Three patients showed healing potential according to the simulation, but clinically turned out to be non-unions. Four out of six non-unions were correctly detected as non-unions by the simulation, and two simulations were wrongfully diagnosed as non-unions. Further adjustments of the simulation algorithm for human fracture healing and a larger cohort are necessary. However, these first results show a promising approach towards an individualized prognosis of fracture healing based on biomechanical factors.

The Evolution of Historic Agroforestry Landscape in the Northern Apennines (Italy) and Its Consequences for Slope Geomorphic Processes

Historic agricultural practices have played a dominant role in shaping landscapes, creating a heritage which must be understood and conserved from the perspective of sustainable development. Agroforestry (i.e., the practice of combining trees with agriculture or livestock) has existed since ancient times in European countries, and it has been recognised as one of the most resilient and multifunctional cultural landscapes, providing a wide range of economic, sociocultural, and environmental benefits. This research explores aspects of the history, physical characteristics, decline, and current state of conservation of historic agroforestry systems on the Northern Apennines in Italy, using an interdisciplinary approach combining archival sources, landscape archaeology, dendrochronology, and GIS analysis. Furthermore, through computer-based modelling, this research aims to evaluate how the abandonment of this historic rural land-use strategy impacted slope geomorphic processes over the long term. The importance of environmental values attached to traditional rural landscapes has received much attention even beyond the heritage sector, justifying the definition of transdisciplinary approaches necessary to ensure the holistic management of landscapes. Through the integration of the Unit Stream Power-Based Erosion Deposition (USPED) equation with landscape archaeological data, the paper shows how restoring the historic agroforestry landscape could significantly mitigate soil mass movements in the area. Thus, the interdisciplinary workflow proposed in this study enables a deep understanding of both the historical evolution of agroforestry systems and its resulting effects for cumulative soil erosion and deposition in the face of climate change.

Disturbing Effect of Intra-Tissue Temperature Sensors in Pre-Clinical Experimental Studies of Radiofrequency Cardiac Ablation: A Computer-Based Modeling Study

Background: Preclinical studies on radiofrequency (RF) cardiac ablation (RFCA) use very small temperature sensors in specific positions in the tissue subjected to RF heating. Despite the sensors’ small size, the proximity to the ablation electrode and the extremely high thermal gradient around the electrode means that the presence of the temperature sensors could distort the temperatures recorded. Our objective was to assess the thermal impact of intra-tissue temperature sensors during RFCA. Methods: 3D RFCA models were built including different temperature sensors based on fiber optics and T-type thermocouples. Constant power ablation was simulated for 10 s. Results: The results showed that the disturbance caused by the presence of the T-type thermocouples was considerably greater (one order of magnitude) than that caused by the optical fibers. The closer the sensor was to the ablation electrode, the greater the greater the disturbance was and the more it increased with time in sensors more than 3 mm deep. The fiber optic measurements always slightly underestimated (<0.2 °C) the tissue temperature that would exist without the sensors, while the disturbance caused by the T-type thermocouples did not always result in underestimation but depended on the depth of the sensors parallel to the catheter. Conclusions: The presence of thermocouples inserted into the tissue close to the RF ablation electrode involves a disturbance that could affect the measured temperature value, although it does not substantially alter the shape and size of the thermal lesion. Optical fibers cause much less disturbance, possibly due to the absence of internal metal parts that favor heat conduction.

Enhancement of CO2 viscosity prediction using advanced intelligent methods: Application to carbon capture and storage

As the concept of CO2 capture and storage has gained traction, some recent efforts have been made to build an accurate model for CO2 viscosity prediction, which is an important element in CO2 pipeline design and metering calculations. The present study focuses on the application of eleven computer-based models. There are a few important differences between this study and others that have utilized machine learning to determine CO2 viscosity. This study is the most comprehensive investigation of this issue to date, using eleven intelligent models; unlike most of the literature models, the density of CO2 is not used as an input parameter in the models; the best model's results are compared with the most recent experimentally derived correlations; it was shown that machine learning approaches not previously employed in studies outperform the model previously used in the literature; and instead of employing classic evolutionary approaches, two newly discovered optimization techniques (i.e., BAT and GOA) were applied. The performance of decision trees and random forest techniques is better than that of previously introduced best models for CO2 viscosity prediction, such as multi-layer perceptron, radial basis function, and adaptive neuro-fuzzy inference systems, according to the results of this paper, which rank decision trees and random forest algorithms as the first and second-best algorithms among eleven methodologies studied. The final result of the decision trees method outperformed a current and most updated correlation for CO2 viscosity prediction so far, as seen in various charts.

Evaluation of the pattern of fracture formation from trauma to the human mandible with finite element analysis. Part 2: The corpus and the angle regions.

Although the mandible is the largest and strongest bone of the facial skeleton, it is frequently broken. The fracture location in the mandible depends on the biomechanical features, direction and angle of the trauma, and masticatory muscles. This study aimed to evaluate the stresses caused by trauma to the corpus and angle regions from different angles. After computer-based mandible models were created using finite element analysis, a force of 2000 Newton(N) was simulated with the mouth open or closed to the corpus and the angle. To the corpus: at 90° (Model 1) in the lateromedial direction, 45° (Model 2) in the lateromedial-inferosuperior direction, and 90° (Model 3) in the inferosuperior direction. To angle: 90° (Model 4) in the lateromedial direction and 45° (Model 5) in the lateromedial-inferosuperior direction. The resulting stress intensity was assessed using FEA. Following the simulated forces, the maximum stress in the mandible occurred in the condylar region, except in Model 3 (Left(L)Corpus2[36 megapascals(MPa)]) in the mouth-closed condition. After traumas in Model 1 (open-mouth: LCondyle2[547 MPa]) and Model 4 (closed-mouth: LCondyle2[607 MPa]), higher stress values occurred in the condyle. In the mouth open-closed state, there was no significant stress change in the condyle region in Model 1 (open-mouth: LCondyle2[547 MPa], closed-mouth:LCondyle2[546 MPa]) or in Model 2 (open mouth: Right(R)Condyle2[431 MPa], closed-mouth:LCondyle2[439 MPa]). In Model 3, lower stress values occurred in the closed-mouth rather than the open-mouth (LCondyle1[167 MPa]) state. In Models 4 and 5, the stress values increased in the mouth-closed condition compared with the mouth-open condition. Stress in the mandible is affected by the location of the trauma and the angle of incidence of the blow. In trauma to both the corpus and the angle, the most common area to be fractured is the condyle.

Evaluation and Comparison of Stress in Divergent and Convergent Collar Designs of Implants With Different Bone Densities: A Finite Element Study.

The failure and the success rate of an implant depends on biomechanical factors, esthetics and painless sterile implant surgery conditions, out of which stresses applied to the bone and its surrounding, bone-implant interface, material characteristics of the implant used and the strength of the bone and its surrounding are the important factors. This study aimed to evaluate the stress distribution of divergent collar design (DCD)and convergent collar design (CCD) implants placing them in four different densities of the bone (D1, D2, D3 and D4).The evaluation of the stress distribution of DCDand CCD was performed using the 3D finite element method (FEM), by placing them in four different bone densities.In addition to this, a comparison of the effect of DCD and CCD in terms of stressdistribution in the bone was also done. The softwareused to process the geometric characteristics of the missing first molar in the mandibular section were Ansys, version 19.2, CATIA, version 5, and Solidworks (Dassault Systèmes). Using these software, three models were designed and successfully restored using an all-ceramic crown implant. The first model was a geometric modelof the first molar mandibular bone section, the second model was a cylindrical implant (4x10mm) with a DCD and CCD, and the third model had titanium alloy (Ti-6Al-4V) properties incorporated into the implant. The D1 bone model showed the lowest stress concentration compared to D2, D3, D4. The DCD showed the lower stress and strain concentrations as compared to the CCD in the contiguous crestal bone in all the densities of the bone in both vertical and lateral or oblique loadings. The DCD with the D1 bone showed the least stress concentration around the crestal bone region. The results of this study also showed that the maximum von Mises stress was observed in the crestal region or the neck of the implant for both the convergent and divergent collar implant designs in all the four densities of the bone. Before a patient trial of a new implant design or a new implant material, finite element analysis (FEA) gives us a clear picture of what will be the patient bone response when an implant will be placed and loaded. FEA also gives us an opportunity to test a new implant material without putting a patient at risk. In this study, four different types of bone were incorporated with two different implant collar designs. Each implant assembly was subjected to vertical as well as oblique forces. The response of each bone type for the titanium alloy implant was recorded. A color-coded response for the magnitude and the location of the maximum stress received by the bone was observed.Maximum stresses were seen in the crestal region. As this is a computer-based model, dynamic loading was not possible. This study provided us with the possible outcome in patients under a static load. Further studies can be conducted invivo to record dynamic loading responses as well as long-time loading responses.

Pharmacometrics: A New Era of Pharmacotherapy and Drug Development in Low- and Middle-Income Countries.

Pharmacotherapy, in many cases, is practiced at a suboptimal level of performance in low- and middle-income countries (LMICs) although stupendous amounts of data are available regularly. The process of drug development is time-consuming, costly, and is also associated with loads of hurdles related to the safety concerns of the compounds. This review was conducted with the objective to emphasize the role of pharmacometrics in pharmacotherapy and the drug development process in LMICs for rational drug therapy. Pharmacometrics is widely applied for the rational clinical pharmacokinetic (PK) practice through the population pharmacokinetic (popPK) modeling and physiologically based pharmacokinetic (PBPK) modeling approach. The scope of pharmacometrics practice is getting wider day by day with the untiring efforts of pharmacometricians. The basis for pharmacometrics analysis is the computer-based modeling and simulation of pharmacokinetics/pharmacodynamics (PK/PD) data supplemented by characterization of important aspects of drug safety and efficacy. Pharmacometrics can be considered an invaluable tool not only for new drug development with maximum safety and efficacy but also for dose optimization in clinical settings. Due to the convenience of using sparse and routine patient data, a significant advantage exists in this regard for LMICs which would otherwise lag behind in clinical trials.

Evaluation of the pattern of fracture formation from trauma to the human mandible with finite element analysis. Part 1: Symphysis region.

The mandible is the largest, strongest bone in the maxillofacial region. When a fracture occurs in the mandible, its location depends on several factors: the direction of the trauma, the angle of the trauma, masticatory muscles and the quality of the bone. The aim of this study was to evaluate the stresses caused by trauma to the symphysis region from different angles. Computer-based mandible models were created, and a 2000 N force was applied to the symphysis at three different angles using finite element analysis. Six trauma situations were simulated with the mouth open or closed. Forces were applied to the symphysis at 90° (Model 1) in the anteroposterior direction, 45° (Model 2) in the anteroposterior-inferosuperior direction and 90° (Model 3) in the inferosuperior direction, when the mouth was open or closed. The resulting stress intensity was assessed using finite element analysis. As a result of trauma applied to the symphysis region, maximum stresses were found where the impact originated and at the condyle region (Model 2, open mouth: condyle 1 [1172 MPa]). The open mouth position caused higher stress values than the closed mouth position (Model 2, open mouth: condyle 1 [1172 MPa]; closed mouth: symphysis 4 [82 MPa]). The Model 2, open-mouth state (Model 2, open mouth: condyle 1 [1172 MPa]) sustained higher stresses than all the other models. The stress values in the mandible were affected by the force applied to the symphysis region, the angle of impact arrival and the open or closed state of the mouth. Keeping the mouth closed at the time of trauma reduced the stress value. A closed mouth during trauma directed at the symphysis reduced the possibility of mandible fractures.

Net zero climate remediations and potential terminal depletion of global critical metal resources: A synoptic geological perspective

• Climate change accords led to widespread acceptance of Net Zero by 2060 targets. • Critical metals depletion making low carbon technology production impossible. • Climate change in geological perspective is slow incremental not catastrophic. • A reset in Net Zero ambitions should be made for the future. Over the past two decades, concerns about anthropogenic CO 2 emissions have led to computer-based climate models of the consequences, first on global warming and then on more general climate change. The more extremes of these models have been used to engender concerns about climate events that could be catastrophic for global populations even though natural climate change has always been incremental with only periodic large volcanic eruptions producing short-term catastrophic changes due to massive additions of aerosols to the atmosphere. Climate change accords have led to widespread acceptance of Net Zero by 2060 targets. However, indicative modelling of the nexus between clean energy and the critical metals required for low carbon solar and wind technologies and electric vehicles and their chargers indicates that many metals, particularly Co, Ni, Cu, Se, Ag, Cd, In, Te, and Pt, may be severely to terminally depleted by 2060, making further low carbon technology production impossible. Mineral exploration and currently unmined deposits with high risk factors are only likely to be able to replace these non-renewable metals at lower grades in more inaccessible or deeper mines, leading to even further increases in conventional energy for mining and metallurgy and consequent cost of the low carbon technology revolution. There is no current indication that recycling can replace the critical metal stocks. The heterogeneous global distribution of both mineral deposits containing the critical metals and production points could become a geopolitical issue if global security declines. These factors combined with the slow incremental, rather than catastrophic, changes related to climate change, suggest that a reset in Net Zero ambitions should be made to consider a more multicomponent plan for the future that involves a balanced portfolio of least polluting energy sources that do not cause serious depletion of affordable metal resources for the future. Graphical Abstract. .

A Review on Recent Approaches on Molecular Docking Studies of Novel Compounds Targeting Acetylcholinesterase in Alzheimer Disease.

Alzheimer's disease (AD), a neurodegenerative brain disorder that affects millions of people worldwide, is characterized by memory loss and cognitive decline. Low levels of acetylcholine and abnormal levels of beta-amyloid, T protein aggregation, inflammation, and oxidative stress, have been associated with AD, and therefore, research has been oriented towards the cholinergic system and primarily on acetylcholinesterase (AChE) inhibitors. In this review, we are focusing on the discovery of AChE inhibitors using computer-based modeling and simulation techniques, covering the recent literature from 2018-2022. More specifically, the review discusses the structures of novel, potent acetylcholinesterase inhibitors and their binding mode to AChE, as well as the physicochemical requirements for the design of potential AChE inhibitors.

SIMPLACE—a versatile modelling and simulation framework for sustainable crops and agroecosystems

AbstractAgricultural system analysis has considerably evolved over the last years, allowing scientists to quantify complex interactions in crops and agroecosystems. Computer-based models have become a central tool for such analysis, using formulated mathematical representations (algorithms) of different biophysical processes to simulate complex system’s behaviour. Nevertheless, the current large variety of algorithms in combination with nonstandardization in their use limits rapid and rigorous model improvement and testing. This is particularly important because contextualization is a key aspect used to formulate the appropriate model structure for a specific research question, framing a clear demand for ‘next generation’ models being modular and flexible. This paper aims to describe the Scientific Impact assessment and Modelling PLatform for Advanced Crop and Ecosystem management (SIMPLACE), which has been developed over the last decade to address the various aforementioned issues and support appropriate model formulations and interoperability. We describe its main technical implementation and features to develop customized model solutions that can be applied to a number of cropping systems with high flexibility, performance and transparency. A brief review of exemplary applications of SIMPLACE is provided covering the different topics, crops and cropping systems, spatial scales and geographies. We stress that standardized documentation of modules, variables ontology and data archives are key requirements to maintain and assist model development and reproducibility. The increasing demand for more complex, diversified and integrated production systems (e.g. intercropping, livestock-grazing, agroforestry) and the associated impacts on sustainable food systems also require the strong collaboration of a multidisciplinary community of modellers and stakeholders.

Effects of different spatial and precipitation input data on swat-derived catchment features

Computer-based mathematical models are used in water management research to represent ecological problems, simulate different processes, deal with such problems and support their solution. Such studies require an interdisciplinary approach that is both user-friendly and comprehensive to integrate all of the processes that occur in nature. The use of available hydrological models requires a model setup with a reasonable level of data quality and quantity to represent catchment features to emphasize the distinctive local character of ecosystems. One of the models that comply with such requirements is the Soil and Water Assessment Tool (SWAT). This paper aims to address the possible impact of different spatial and precipitation input data on the catchment features by using SWAT for the case study of the floodplain located within the Danube River Basin in Serbia. The objective was to evaluate the impact of digital elevation models, land use, and soil types with different resolutions (1) SRTM and ASTER (30 m), TanDEM-X (12.5 m), (2) CORINE and GlobCover land use databases, and (3) FAO/UNESCO world soil map and digitized soil map of Vojvodina Province on catchment delineation. The research was conducted alongside the analysis of precipitation, using data from the CFSR, CarpatClim, and the national yearbooks. Regarding the spatial data, the results indicate that the high-resolution data need to be adjusted for this area, while the ASTER layer is suitable at an acceptable level for further modeling in SWAT. Interpolated precipitation data are better to use due to their higher resolution (10km) and the heterogeneous distribution of rain gauge stations.

The Dilemma between Reducing the Thermal Stress in the Industrial Spaces and Ergonomics Arrangement in Low- and Middle-income Countries

Thermal heat stress is a leading cause of numerous occupational diseases that disturb worker performance and work quality and, in extreme circumstances, can result in death. When employees are exposed to severely hot or cold thermal settings, thermal discomfort is listed as one of the leading reasons for discontent in the job. Given the time individuals spend at work, studies assessing the comfort of the thermal environment are becoming increasingly relevant. However, most industrial spaces in low- and middle-income countries are designed without considering the workers' thermal comfort, which leads to an unmeasured decrease in productivity and many health considerations. This research aims to provide a methodology for developing the indoor thermal comfort of the workers in industrial spaces by optimizing the workers’ ergonomics, activity profiles, and building shell without implementing any mechanical cooling systems, which is not usual in low- and middle-income areas. The methodology is based on building a computer-based model on the Design Builder simulation tool based on current measures of temperature, humidity, wet-bulb temperature, air speed over each window, and indoor surface temperatures. Then, three different scenarios were built to optimize the indoor ergonomics of the factory in the first scenario, and the building shell in the second scenario, the activity profiles of the workers in the third scenario to become correspond with the NOISH criteria of maximum metabolic rate for each WBGT. After that, each scenario's results were associated with the workers' thermal sensation and air temperatures, which correlated the ergonomics of industrial spaces and the thermal comfort of workers there. The results of each scenario simulation were represented by horizontal and vertical sections of the air temperature and Percentage of People's Discomfort (PPD). Each scenario’s results referred to a decrease in the air temperature and PPD; however, all the scenarios combined decreased the PPD to around 50% for most of the measured working stations. The research concluded a methodology of optimizing any industrial space thermal performance without implementing any active ventilation techniques, which is considered the usual form of any industrial space in Egypt and most low and middle-income countries. Therefore, the presented methodology applies to most industrial spaces that face the dilemma of decreased productivity due to indoor thermal heat loads that affect the workers.

A model-based approach to addressing energy demand in sustainable urban systems

Sustainable cities address their citizens’ environmental, social, economic, cultural, and institutional needs in an integrated manner. In order to successfully transform urban systems in this context, key enabling technologies must be investigated that can facilitate such changes. In addition, computer-based modeling approaches for analyzing the benefits of such technologies for urban organizations and activities are highly desirable. In this paper, we propose a model-based approach to address sustainable urban environments that employs green edge computing technology to meet the energy and digital service requirements of urban systems. By utilizing the solar energy potential of urban roofs, this technology can be adapted to meet the crucial demands for power arising from digital activity in various urban contexts. As a result of its unique features, the proposed modeling framework is a valuable analysis tool for assisting decision-making to improve the quality of urban systems.

Pengembangan Aplikasi E-Learning Akuntansi Sektor Publik dengan Metode Prototyping

The development of computer-based learning models (e-learning) is so rapid. In Indonesia, various universities have implemented e-learning for their students. In addition, in- general, there are many e-learning applications that offer learning packages that can be used by learners. However, the learning packages offered to the general public are still limited (some are paid). With the enthusiasm to succeed the independent learning policy launched by the government, the researcher proposes an e-learning application that presents material on public sector accounting. This public sector accounting e-learning application can be used for free by anyone, anytime, anywhere with any teacher.Given that users of public sector accounting e-learning are all levels of Indonesian society whose needs are difficult to identify, there will be a big challenge in developing e-learning that suits user needs. Therefore, the development of public sector accounting e-learning is proposed using the prototyping method. The system development steps consist of planning, analysis, design and implementation stages. In the analysis stage, the researcher develops an initial prototype and analyzes user needs by submitting a survey to get the level of user wawsatisfaction as measured by the Customer Satisfaction Index method and explores user needs.This study shows that the curriculum-based prototype of e-learning Public Sector Accounting provides a level of user satisfaction (Customer Satisfaction Index) which can be categorized into excellent criteria, which is 90.52%. In addition, based on a survey on the initial prototype, many students want learning media in the form of slides, videos and practice questions.

The Isoleucine at Position 118 in Transmembrane 2 Is Responsible for the Selectivity of Xamoterol, Nebivolol, and ICI89406 for the Human β1-Adrenoceptor.

Known off-target interactions frequently cause predictable drug side-effects (e.g., β1-antagonists used for heart disease, risk β2-mediated bronchospasm). Computer-aided drug design would improve if the structural basis of existing drug selectivity was understood. A mutagenesis approach determined the ligand-amino acid interactions required for β1-selective affinity of xamoterol and nebivolol, followed by computer-based modeling to provide possible structural explanations. 3H-CGP12177 whole cell binding was conducted in Chinese hamster ovary cells stably expressing human β1, β2, and chimeric β1/β2-adrenoceptors (ARs). Single point mutations were investigated in transiently transfected cells. Modeling studies involved docking ligands into three-dimensional receptor structures and performing molecular dynamics simulations, comparing interaction frequencies between apo and holo structures of β1 and β2-ARs. From these observations, an ICI89406 derivative was investigated that gave further insights into selectivity. Stable cell line studies determined that transmembrane 2 was crucial for the β1-selective affinity of xamoterol and nebivolol. Single point mutations determined that the β1-AR isoleucine (I118) rather than the β2 histidine (H93) explained selectivity. Studies of other β1-ligands found I118 was important for ICI89406 selective affinity but not that for betaxolol, bisoprolol, or esmolol. Modeling studies suggested that the interaction energies and solvation of β1-I118 and β2-H93 are factors determining selectivity of xamoterol and ICI89406. ICI89406 without its phenyl group loses its high β1-AR affinity, resulting in the same affinity as for the β2-AR. The human β1-AR residue I118 is crucial for the β1-selective affinity of xamoterol, nebivolol, and ICI89406 but not all β1-selective compounds. SIGNIFICANCE STATEMENT: Some ligands have selective binding affinity for the human β1 versus the β2-adrenoceptor; however, the molecular/structural reason for this is not known. The transmembrane 2 residue isoleucine I118 is responsible for the selective β1-binding of xamoterol, nebivolol, and ICI89406 but does not explain the selective β1-binding of betaxolol, bisoprolol, or esmolol. Understanding the structural basis of selectivity is important to improve computer-aided ligand design, and targeting I118 in β1-adrenoceptors is likely to increase β1-selectivity of drugs.