Developed Model Research Articles

Kinetic modeling of methane dehydroaromatization over Mo/ZSM-5 catalysts

We propose a novel kinetic model for the methane dehydroaromatization (MDA) reaction over the Mo/ZSM-5 catalyst to express the practical behavior of the catalytic reaction. Unlike existing MDA kinetic models, we introduced a deactivation model involving carbon deposit formation to simulate the more realistic behavior of the MDA reaction. The proposed kinetic model integrated the “apparent kinetic model,” which focuses on detectable components, and the “micro-kinetic model,” which incorporates the acidic properties and active sites of the catalyst. To validate this model, we conducted fixed-bed experiments across a wide range of operating conditions, including temperature, gas velocity, and metal loading. Compared with experimental data, our model predictions exhibited a remarkable error of 5 %. Specifically, by leveraging the relationship between the deactivation behavior and carbon deposit formation, the model accurately predicted the CH4 conversion rates, component yields, and coke production throughout the reaction. This model sheds light on catalytic behavior during carbon deposit generation under diverse operating conditions, contributing to a comprehensive understanding of the MDA reaction mechanism. The developed kinetic model can be applied to estimate reactor performance across various scenarios. By providing a kinetic model that incorporates information regarding the catalytic properties of Mo/ZSM-5 and the apparent gas concentration, our study offers a potent tool for estimating practical reactor performance and advancing MDA catalyst development.

Adapting Self-Regulated Strategy Development Model to Teach Deaf Learners English Writing Skills

Adapting Self-Regulated Strategy Development Model to Teach Deaf Learners English Writing Skills

A decision framework for improving the service quality of charging stations based on online reviews and evolutionary game theory

With “charging anxiety” gradually replacing “range anxiety” as the major obstacle for consumers to purchase electric vehicles (EVs), the quantity-driven rather than quality-driven charging station development model barely meets the development of the EV market. It is of great practical significance that a comprehensive and in-depth insight into charging stations’ customer requirements (CRs) to uncover their pain points and improvement measures. Therefore, this study develops a decision framework for improving EV charging service quality based on quality function deployment (QFD). First, CRs are extracted based on charging station online reviews and classified by the revised importance performance analysis (IPA) method to identify the charging service’s main highlights and pain points. Then, the process of achieving consensus among experts on evaluating the correlation between CRs and service design requirements (DRs) is considered as an evolutionary game of coalition, with a meritocratic Fermi rule considering affinities (MFA) being introduced. Finally, the importance of DRs is determined by combining the Shapley value and risk aversion theory. The results indicate that regulation and convenience are the main highlights of charging stations to satisfy EV users, while reliability and assurance are primary pain points. The charging station operators should prioritize their limited resources on providing efficient customer and maintenance services, installing charging stations with international standards, and regularly inspecting and updating charging infrastructures. This study is beneficial for charging station operators to understand what customers want and how to satisfy them.

Kinetic Modeling for BT200 to Predict the Level of Plasma-Derived Coagulation Factor VIII in Humans.

Lack of Factor VIII (FVIII) concentrates is one of limiting factors for Hemophilia A prophylaxis in resource-limited countries. Rondaptivon pegol (BT200) is a pegylated aptamer and has been shown to elevate the level of von Willebrand Factor (VWF) and FVIII in previous studies. A population pharmacokinetic model for BT200 was built and linked to the kinetic models of VWF and FVIII based on reasonable assumptions. The developed PK/PD model for BT200 described the observed kinetic of BT200, VWF, and FVIII in healthy volunteers and patients with mild-to-moderate hemophilia A from two clinical trials. The developed model was evaluated using an external dataset in patients with severe hemophilia A taking recombinant FVIII products. The developed and evaluated PK/PD model was able to describe and predict concentration-time profiles of BT200, VWF, and FVIII in healthy volunteers and patients with hemophilia A. Concentration-time profiles of FVIII were then predicted following coadministration of plasma-derived FVIII concentrate and BT200 under various dosing scenarios in virtual patients with severe hemophilia A. Plasma-derived products, that contain VWF, are more accessible in low-resource countries as compared to their recombinant counterparts. The predicted time above 1 and 3 IU/dL FVIII in one week was compared between scenarios in the absence and presence of BT200. A combination dose of 6 mg BT200 once weekly plus 10 IU/kg plasma-derived FVIII twice weekly maintained similar coverage to a 30 IU/kg FVIII thrice weekly dose in absence of BT200, representing only 22% of the FVIII dose per week.

A highly fluorescent and readily accessible all-organic photosensitizer model for advancing image-guided cancer PDT.

The potential of using image-guided photodynamic therapy (ig-PDT) for cancer, especially with highly biocompatible fluorescent agents free of heavy atoms, is well recognized. This is due to key advantages related to minimizing adverse side effects associated with standard cancer chemotherapy. However, this theragnostic approach is strongly limited by the lack of synthetically-accessible and easily-modulable chemical scaffolds, enabling the rapid design and construction of advanced agents for clinical ig-PDT. In fact, there are still very few ig-PDT agents clinically approved. Herein we report a readily accessible, easy-tunable and highly fluorescent all-organic small photosensitizer, as a model design for accelerating the development and translation of advanced ig-PDT agents for cancer. This scaffold is based on BODIPY, which assures high fluorescence, accessibility, and ease of performance adaptation by workable chemistry. The optimal PDT performance of this BODIPY dye, tested in highly resistant pancreatic cancer cells, despite its high fluorescent behavior, maintained even after fixation and cancer cell death, is based on its selective accumulation in mitochondria. This induces apoptosis upon illumination, as evidenced by proteomic studies and flow cytometry. All these characteristics make the reported BODIPY-based fluorescent photosensitizer a valuable model for the rapid development of ig-PDT agents for clinical use.

Proof of a LOD prediction model with orthogonal PAT methods in continuous wet granulation and drying

Real-time monitoring of critical quality attributes, such as residual water in granules after drying which can be determined through loss-on-drying (LOD), during wet granulation and drying is essential in continuous manufacturing. Near-infrared (NIR) spectroscopy has been widely used as process analytical technology (PAT) for in-line LOD monitoring. This study aims to develop and apply a model for predicting the LOD based on process parameters. Additionally, the efficacy of an orthogonal PAT approach using NIR and mass balance (MB) for a vibrating fluidized bed dryer (VFBD) is demonstrated. An in-house-built, cost-effective NIR sensor was utilized for measurements and exhibited good correlation compared to standard method via infrared drying. The combination of NIR and MB, as independent methods, has demonstrated their applicability. A good correlation, with a Pearson r above 0.99, was observed for LOD up to 16 % (w/w). The use of an orthogonal PAT method mitigated the risk of false process adaption. In some experiments where the NIR sensor might have been covered by powder and therefore did not measure accurately, LOD monitoring via MB remained feasible. The developed model effectively predicted LOD or process parameters, resulting in an R2 of 0.882 and a RMSE of 0.475 between predicted and measured LOD using the standard method.

Surgical step recognition in laparoscopic distal gastrectomy using artificial intelligence: a proof-of-concept study.

Laparoscopic distal gastrectomy (LDG) is a difficult procedure for early career surgeons. Artificial intelligence (AI)-based surgical step recognition is crucial for establishing context-aware computer-aided surgery systems. In this study, we aimed to develop an automatic recognition model for LDG using AI and evaluate its performance. Patients who underwent LDG at our institution in 2019 were included in this study. Surgical video data were classified into the following nine steps: (1) Port insertion; (2) Lymphadenectomy on the left side of the greater curvature; (3) Lymphadenectomy on the right side of the greater curvature; (4) Division of the duodenum; (5) Lymphadenectomy of the suprapancreatic area; (6) Lymphadenectomy on the lesser curvature; (7) Division of the stomach; (8) Reconstruction; and (9) From reconstruction to completion of surgery. Two gastric surgeons manually assigned all annotation labels. Convolutional neural network (CNN)-based image classification was further employed to identify surgical steps. The dataset comprised 40 LDG videos. Over 1,000,000 frames with annotated labels of the LDG steps were used to train the deep-learning model, with 30 and 10 surgical videos for training and validation, respectively. The classification accuracies of the developed models were precision, 0.88; recall, 0.87; F1 score, 0.88; and overall accuracy, 0.89. The inference speed of the proposed model was 32 ps. The developed CNN model automatically recognized the LDG surgical process with relatively high accuracy. Adding more data to this model could provide a fundamental technology that could be used in the development of future surgical instruments.

Pengembangan Media Pembelajaran Berbasis Power Point Interaktif Pada Materi Sistem Pencernaan Manusia Kelas XI

The purpose of this study is to develop Power Point -based interactive learning media on digestive system material that is valid, practical, and effective. This research is development research using the Research and Development (R&D) development model. This research was carried out in class XI. The instrument used is a validation questionnaire which includes aspects of content feasibility (material), language feasibility, and design feasibility (media), student response questionnaires and learning outcomes. The data analysis in this study was carried out descriptively on all the data obtained. The results of the analysis show that the learning media is also very practical to be used by students. Based on the results of the study, it can be concluded that the media developed is suitable for use in the learning process of the digestive system

Risk assessment models for development of carpal tunnel syndrome: clinical, anthropometric, and neuromuscular ultrasound predictors

BackgroundCarpal tunnel syndrome (CTS) is the most common entrapment neuropathy with multifactorial etiologies. We intended in this case–control study to identify, out of a comprehensive set of risk factors, the relatively important ones and develop a quantitative risk assessment model for this disorder. It was also legitimate to define the hazard of those factors in a dose-related manner and the acceptable safe limit especially for work-related stresses.ResultsAge and female predominance were comparable between the 60 patients (89 hands with electrophysiologically confirmed CTS) and 50 controls (100 hands). Occupation of the studied sample varied between housewives only, employed housewives, and manual workers with a distribution that differed significantly between patients and controls. Significantly higher body mass index (BMI) and mean wrist depth were found in patients than controls. Wrist ratio (clinically or sonographically) was significantly squarer in patients than controls. Overall workload and number of hours spent daily performing work with repeated hand movements or awkward hand position were significantly higher among patients than controls.ROC curves were constructed for wrist measurements and occupational stresses. Cut-off points of wrist ratio and internal carpal tunnel ratio (by ultrasound) to discriminate subjects with CTS were > 0.68 and ≤ 1.854, respectively. The best cut-off value for number of hours spent daily performing work with repeated hand movements was 3 h/ day. As for working with awkward hand position or cold exposure, cut-off value was 0.6 h/day for both.Two logistic regression models were conducted to investigate nonoccupational and occupational predictors of CTS. The independent predictors concluded from the first model were BMI, positive family history of CTS, wrist ratio, and decrease grip strength. As for the occupational model, predictors were tasks requiring awkward hand position and cold exposure.ConclusionOccupational risk assessment by clinical, anthropometric, and ultrasonographic measurement should be used in professions requiring repetitive or awkward hand movements, so that in overweight persons with square wrists appropriate workplace setup measures or assistive technology at work or home could be taken to prevent or decrease the impact of work hazards or help choose individuals with low risk for appropriate jobs.

Factors affecting bond behavior between ECC and steel rebars

Engineered cementitious composites (ECC) have attracted significant attention, in the civil engineering domain, due to their appealing characteristics. A main factor governing ECC’s performance is the steel-to-concrete bond behavior. However, there is yet dire need to mend the knowledge gap in this venue. This study aims to investigate the influence of the ECC associated traits onto the aforementioned bond behavior: compressive strength, bonded length-to-rebar ratio, rebar diameter, ECC cover thickness (and confinement level around steel rebar at bonded length region). To fulfill this purpose, eight beam-end specimens were prepared and tested. Results showed that (i) ECC compressive strength had the greatest impact on the ultimate bond stress; followed by (ii) the bonded length-to-diameter ratio, and (iii) the cover thickness (whilst adding steel stirrups). The latter’s performance was marginal. In descending order, the influence amounted to 16.5 %, 12 % and 3.5 %, respectively, for a variant range of input-parameter change. As regards the failure mode: the superior tensile properties of ECC led to the occurrence of a pull-out scheme rather than the anticipated splitting mode of failure. This diminished the role of cover thickness and stirrups, in this regards. Finally, new models are developed to predict the bond-slip behavior for ECC-to-steel rebar. The developed models demonstrated adequate agreement with experimental results.

Study on the Design Scheme of Vehicle Flow Lines in Unilateral Agglomerative Open Service Area

In recent years, with the introduction of the strategy to strengthen the country’s transportation infrastructure and the continuous implementation of new economic development models such as integrating transportation with tourism, various open service areas integrating highway service areas with local tourism have emerged nationwide. Examples include the Yangcheng Lake service area in Jiangsu and the Lengshui service area in Chongqing. This paper focuses on the design example of the Dazu Stone Carving service area on the Chongqing section of the Yurong Expressway, comprehensively considering factors such as construction scale, terrain conditions, and local urban planning. It analyzes and studies the traffic flow design of unilateral agglomerative open service areas around two vehicle traffic conversion links: between the main expressway and the service area, and between the service area and local roads. The aim is to provide a case study reference for similar projects.

Investigation of the dynamic characteristics of the pneumatic-mechanical drive of the installation movements of machine mechanisms

The creation of new and improvement of existing machines and mechanisms requires the development of drive engineering and the creation of new drive systems capable of competing with currently known circuit solutions. Under these conditions, the creation of combined pneumatic-mechanical drives is an important scientific and technical task. The purpose of this work is to increase the speed at a given accuracy of auxiliary movements of the target mechanisms of technological machines by creating a pneumatic-mechanical drive with improved energy and dynamic characteristics. The technical solution of a positioning pneumatic-mechanical drive of executive movements of technological equipment is presented, mathematical and computer models are developed. In this case, the method of solving the differential equation in the SimInTech program is used. As a result, an oscillogram of transients is obtained. The developed models allow for dynamic analysis of pneumatic-mechanical systems.

Emergence of information processing in biological systems and the origin of life

ABSTRACT As every life form is composed of cells, elements of consciousness, namely memory and sentience, must be grounded in mechanisms that are integral to unicellular organisms. Earlier studies indicated that cellular cytoskeletal structures consisting of excitable, flexible, and oscillating polymers such as microtubules, along with quantum events, are potentially responsible for information processing and thus consciousness. This work attempts to solve the unknown, that is, how, at the spark of life, the phenomenon of cellular information processing first appears. This study posits that the spatially distributed wave energy of the molecules of an incepting cell interacts with space and generates a rotating bioinformation field, forming a vortex. This vortex, the local energy maximum, whose inbound and outbound energy fluxes represent signal reception and dispersal, is a critical step in the spark of life responsible for information storage, and with incremental wave superpositions, exhibits information processing. The vorticity of the rotating field is computed, and the obtained field characteristics indicated the emergence of a prebiotic complex to initiate information processing. Furthermore, the developed system model explains how perturbations from the environment are converted into response signals for the emanation of sense, locomotion, nutrition, and asexual reproduction, the fundamental evolutionary building blocks of prokaryotes. Further research directions include explaining how the energy potential available in the bio-information field and the vortex leads to the first formation of genetic material, emergence of cytoskeleton, and extension of bio-information field to multi-cellular organisms.

Multi-Target In-Silico modeling strategies to discover novel angiotensin converting enzyme and neprilysin dual inhibitors

Cardiovascular diseases, including heart failure, stroke, and hypertension, affect 608 million people worldwide and cause 32% of deaths. Combination therapy is required in 60% of patients, involving concurrent Renin–Angiotensin–Aldosterone-System (RAAS) and Neprilysin inhibition. This study introduces a novel multi-target in-silico modeling technique (mt-QSAR) to evaluate the inhibitory potential against Neprilysin and Angiotensin-converting enzymes. Using both linear (GA-LDA) and non-linear (RF) algorithms, mt-QSAR classification models were developed using 983 chemicals to predict inhibitory effects on Neprilysin and Angiotensin-converting enzymes. The Box-Jenkins method, feature selection method, and machine learning algorithms were employed to obtain the most predictive model with ~ 90% overall accuracy. Additionally, the study employed virtual screening of designed scaffolds (Chalcone and its analogues, 1,3-Thiazole, 1,3,4-Thiadiazole) applying developed mt-QSAR models and molecular docking. The identified virtual hits underwent successive filtration steps, incorporating assessments of drug-likeness, ADMET profiles, and synthetic accessibility tools. Finally, Molecular dynamic simulations were then used to identify and rank the most favourable compounds. The data acquired from this study may provide crucial direction for the identification of new multi-targeted cardiovascular inhibitors.

Modelling width of the spectral component of a gas-turbine engine gearbox output shaft speed

Gearbox is the most stressed component in an aircraft gas-turbine engine. This implies the need for finding ways to monitor its technical condition. Practice shows that the most efficient method is vibration-based diagnostics. However, this method requires the use of sophisticated measurement systems and highly skilled personnel. This paper shows that errors of gear coupling manufacture and assembly, characteristics of machine operating mode, design factors, frequency modulation of the carrier of the engine rotor speed in the stationary mode of its operation, and wear of teeth flanks determine the width of the spectral component of the gearbox output shaft speed. Using the results obtained from the developed model of the width of gear tooth spectral component, ratios for width of the spectral component of the signal of the “standard” tachometric speed sensor of the gearbox output shaft speed and the corresponding spectral component of its vibration were obtained. Models for repaired and newly manufactured gearboxes and gearboxes with tooth flank wear were proposed. This allowed the development of a number of new diagnostic indicators of a defect. Several examples of the use of these new diagnostic indicators are given for the gearbox of one of turbo-prop engines. The results obtained provide an opportunity to assess the gearbox technical condition in operation.

Development model for assessing the structural complexity of programs

Development model for assessing the structural complexity of programs

Development model for assessing the structural complexity of programs

The research is devoted to the estimation the structural complexity of programs. The algorithm of finding cyclomatic routes for program executions is described. By now, two directions of obtaining estimates for the complexity estimates in software modules have been defined: structural and statistical. Both directions connect the value of program complexity with the labor intensity related to their development. The structural complexity of program modules is determined by the number of interacting components, the number and complexity of links between them. The complexity of a program's behavior depends to a large extent on the set of routes through which it is executed. The complexity metric obtained from these positions allows us to determine estimates of the cost of designing the program as a whole, as well as to identify the modules that are likely to contain the most errors, especially the logical ones.

Oxygen uptake efficiency plateau is unaffected by fitness level - the NOODLE study

BackgroundEndurance athletes (EA) are an emerging population of focus for cardiovascular health. The oxygen uptake efficiency plateau (OUEP) is the levelling-off period of ratio between oxygen uptake (VO2) and ventilation (VE). In the cohort of EA, we externally validated prediction models for OUEP and derived with internal validation a new equation.Methods140 EA underwent a medical assessment and maximal cycling cardiopulmonary exercise test. Participants were 55% male (N = 77, age = 21.4 ± 4.8 years, BMI = 22.6 ± 1.7 kg·m− 2, peak VO2 = 4.40 ± 0.64 L·min− 1) and 45% female (N = 63, age = 23.4 ± 4.3 years, BMI = 22.1 ± 1.6 kg·m− 2, peak VO2 = 3.21 ± 0.48 L·min− 1). OUEP was defined as the highest 90-second continuous value of the ratio between VO2 and VE. We used the multivariable stepwise linear regression to develop a new prediction equation for OUEP.ResultsOUEP was 44.2 ± 4.2 mL·L− 1 and 41.0 ± 4.8 mL·L− 1 for males and females, respectively. In external validation, OUEP was comparable to directly measured and did not differ significantly. The prediction error for males was − 0.42 mL·L− 1 (0.94%, p = 0.39), and for females was + 0.33 mL·L− 1 (0.81%, p = 0.59). The developed new prediction equation was: 61.37–0.12·height (in cm) + 5.08 (for males). The developed model outperformed the previous. However, the equation explained up to 12.9% of the variance (R = 0.377, R2 = 0.129, RMSE = 4.39 mL·L− 1).ConclusionOUEP is a stable and transferable cardiorespiratory index. OUEP is minimally affected by fitness level and demographic factors. The predicted OUEP provided promising but limited accuracy among EA. The derived new model is tailored for EA. OUEP could be used to stratify the cardiorespiratory response to exercise and guide training.

Optimization of Hydrochemical Leaching Process of Kaolinite Fraction of Bauxite with Response Surface Methodology

A technology for the hydrochemical processing of the kaolinite fraction of bauxite has been developed, and it involves preliminary chemical activation in a sodium bicarbonate solution and alkaline leaching in a recycled high-modulus solution with the addition of an active form of calcium oxide. Chemical activation allows for the transformation of the difficult-to-explore kaolinite phase to form easily soluble phases of dawsonite, sodium hydroaluminosilicate and bemite. An active, finely dispersed form of calcium oxide was obtained as a result of CaO quenching in Na2SO4 solution at elevated temperature and pressure. Using a central composite design (CCD) via response surface methodology (RSM), the technological leaching mode was achieved. The influence on the leaching process was studied by adjusting the CaO/SiO2 ratio, temperature, alkaline solution concentration and duration. It was found that the determining factors are the concentration of the leaching solution and the temperature. At a stable CaO/SiO2 ratio, a combination of these two factors determines the duration of the process to achieve the predicted degree of recovery. The results of experiments carried out using the developed model of the leaching process confirmed the validity of the calculated indicators, with an error of 2.01%. In an optimal technological mode at a Na2O leaching solution concentration of 260 g/L, a temperature of 260 °C, a CaO/SiO2 ratio of 1.5 and a leaching time of 5 h, the extraction of Al2O3 into the solution was 89.7%, which is close to the value of 87.9% predicted by the model.

Forecasting urban passenger transportation emissions: a green and new energy approach

ABSTRACT Passenger transportation significantly contributes to urban carbon dioxide emission. Decreasing these emissions is essential to achieving low-carbon development. This research focused on Xi’an City to enhance previous research works by considering factors such as road greening, online ride-hailing, and use of vehicles with new energy sources. Using system dynamics method, a carbon dioxide emission prediction model was developed for urban passenger transportation in Xi’an. The developed model estimated total emissions from 2012 to 2021 and projected carbon dioxide emission reduction plans through six different scenarios for the time period of 2023 to 2032. The analysis identified private cars as the main contributors to carbon emission in urban passenger transportation. Single scenario simulations indicated that passenger traffic in Xi’an would not achieve carbon emission peak by 2030, but multi-scenario simulations showed it would. Specific recommendations for carbon emission reduction in urban passenger transportation were provided, focusing on travel patterns, energy sources, and promotion of green initiatives.