Pub Date : 2023-09-30DOI: 10.3390/computation11100190
Meynard Austria, Jon Patrick Garcia, Alvin Caparanga, Lemmuel Tayo, Bonifacio Doma
Polymerase chain reaction (PCR) technique is one of the molecular methods in amplifying DNA for the detection of malaria. However, the collection and transportation of samples and the processing and dissemination of results via conventional PCR, especially when used for routine clinical practice, can hamper the technique’s sensitivity and specificity. The rampancy of such disease in the Philippines is aggravated by the limited supply of medical machinery and the poor economic state of the country; thus, the need to innovate a device for the early detection of malaria is necessary. With that, this study focuses on designing a microfluidic device that will mimic the function of a conventional genus-specific PCR based on the 18S rRNA gene to detect malaria parasites (Plasmodium falciparum) at low-grade parasitemia. The design was intended to be portable, accessible, and economical, which none from past literature has dealt with specifically for malaria detection. This in silico design is a first in the country specially crafted for such reasons. The proposed device was developed and simulated using ANSYS software for Computational Fluid Dynamics (CFD) analyses. The simulation shows that adding loops to the design increases its relative deviation but minimally compared to having only a straight path design. This indicates that looping is acceptable in designing a microfluidic device to minimize chip length. It was also found that increasing the cross-sectional area of the fluid path decreases the efficiency of the design. Lastly, among the three materials utilized, the chip made of polypropylene is the most efficient, with a relative deviation of 0.94 compared to polycarbonate and polydimethylsiloxane, which have relative deviations of 2.78 and 1.92, respectively. Future researchers may mesh the 44-cycle microfluidic chip due to the limitations of the software used in this study, and other materials, such as biocomposites, may be assessed to broaden the application of the design.
{"title":"Designing Microfluidic PCR Chip Device Using CFD Software for the Detection of Malaria","authors":"Meynard Austria, Jon Patrick Garcia, Alvin Caparanga, Lemmuel Tayo, Bonifacio Doma","doi":"10.3390/computation11100190","DOIUrl":"https://doi.org/10.3390/computation11100190","url":null,"abstract":"Polymerase chain reaction (PCR) technique is one of the molecular methods in amplifying DNA for the detection of malaria. However, the collection and transportation of samples and the processing and dissemination of results via conventional PCR, especially when used for routine clinical practice, can hamper the technique’s sensitivity and specificity. The rampancy of such disease in the Philippines is aggravated by the limited supply of medical machinery and the poor economic state of the country; thus, the need to innovate a device for the early detection of malaria is necessary. With that, this study focuses on designing a microfluidic device that will mimic the function of a conventional genus-specific PCR based on the 18S rRNA gene to detect malaria parasites (Plasmodium falciparum) at low-grade parasitemia. The design was intended to be portable, accessible, and economical, which none from past literature has dealt with specifically for malaria detection. This in silico design is a first in the country specially crafted for such reasons. The proposed device was developed and simulated using ANSYS software for Computational Fluid Dynamics (CFD) analyses. The simulation shows that adding loops to the design increases its relative deviation but minimally compared to having only a straight path design. This indicates that looping is acceptable in designing a microfluidic device to minimize chip length. It was also found that increasing the cross-sectional area of the fluid path decreases the efficiency of the design. Lastly, among the three materials utilized, the chip made of polypropylene is the most efficient, with a relative deviation of 0.94 compared to polycarbonate and polydimethylsiloxane, which have relative deviations of 2.78 and 1.92, respectively. Future researchers may mesh the 44-cycle microfluidic chip due to the limitations of the software used in this study, and other materials, such as biocomposites, may be assessed to broaden the application of the design.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136342799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-21DOI: 10.3390/computation11090187
Arpiruk Hokpunna
We present an interface-splitting algorithm (ITS) for solving diagonally dominant tridiagonal systems in parallel. The construction of the ITS algorithm profits from bidirectional links in modern networks, and it only needs one synchronization step to solve the system. The algorithm trades some necessary accuracy for better parallel performance. The accuracy and the performance of the ITS algorithm are evaluated on four different parallel machines of up to 2048 processors. The proposed algorithm scales very well, and it is significantly faster than the algorithm used in ScaLAPACK. The applicability of the algorithm is demonstrated in the three-dimensional simulations of turbulent channel flow at Reynolds number 41,430.
{"title":"Interface Splitting Algorithm: A Parallel Solution to Diagonally Dominant Tridiagonal Systems","authors":"Arpiruk Hokpunna","doi":"10.3390/computation11090187","DOIUrl":"https://doi.org/10.3390/computation11090187","url":null,"abstract":"We present an interface-splitting algorithm (ITS) for solving diagonally dominant tridiagonal systems in parallel. The construction of the ITS algorithm profits from bidirectional links in modern networks, and it only needs one synchronization step to solve the system. The algorithm trades some necessary accuracy for better parallel performance. The accuracy and the performance of the ITS algorithm are evaluated on four different parallel machines of up to 2048 processors. The proposed algorithm scales very well, and it is significantly faster than the algorithm used in ScaLAPACK. The applicability of the algorithm is demonstrated in the three-dimensional simulations of turbulent channel flow at Reynolds number 41,430.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136235469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-18DOI: 10.3390/computation11090185
Simone Brogi, Vincenzo Calderone
In April 2020, during the last pandemic health emergency, we launched a Special Issue hosted by Computation—section Computational Biology, entitled “Computation to Fight SARS-CoV-2 (COVID-19)” [...]
{"title":"Computation to Fight SARS-CoV-2 (COVID-19)","authors":"Simone Brogi, Vincenzo Calderone","doi":"10.3390/computation11090185","DOIUrl":"https://doi.org/10.3390/computation11090185","url":null,"abstract":"In April 2020, during the last pandemic health emergency, we launched a Special Issue hosted by Computation—section Computational Biology, entitled “Computation to Fight SARS-CoV-2 (COVID-19)” [...]","PeriodicalId":52148,"journal":{"name":"Computation","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135154033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Acquiring accurate tire–pavement interaction information is crucial for pavement mechanical analysis and pavement maintenance. This paper combines the tire finite element model (FEM) and response surface methodology (RSM) to obtain tire–pavement interaction information and to analyze the pavement structure response under different loading conditions. A set of experiments was initially designed through the Box–Behnken design (BBD) method to obtain input and output variables for RSM calibration. The resultant RSM was evaluated accurately using the analysis of variance (ANOVA) approach. Then, tire loading simulations were conducted under different magnitudes of static loading using the optimal parameter combination obtained from the RSM. The results show that the deviations between the simulations and the real test results were mostly below 5%, validating the effectiveness of the tire FEM. Additionally, three different dynamic conditions—including free rolling, full brake, and full traction—were simulated by altering the tire rolling angle and translational velocities. Finally, the pavement mechanical response under the three rolling conditions was analyzed based on the tire–pavement contact feature.
{"title":"Tire–Pavement Interaction Simulation Based on Finite Element Model and Response Surface Methodology","authors":"Qingtao Zhang, Lingxiao Shangguan, Tao Li, Xianyong Ma, Yunfei Yin, Zejiao Dong","doi":"10.3390/computation11090186","DOIUrl":"https://doi.org/10.3390/computation11090186","url":null,"abstract":"Acquiring accurate tire–pavement interaction information is crucial for pavement mechanical analysis and pavement maintenance. This paper combines the tire finite element model (FEM) and response surface methodology (RSM) to obtain tire–pavement interaction information and to analyze the pavement structure response under different loading conditions. A set of experiments was initially designed through the Box–Behnken design (BBD) method to obtain input and output variables for RSM calibration. The resultant RSM was evaluated accurately using the analysis of variance (ANOVA) approach. Then, tire loading simulations were conducted under different magnitudes of static loading using the optimal parameter combination obtained from the RSM. The results show that the deviations between the simulations and the real test results were mostly below 5%, validating the effectiveness of the tire FEM. Additionally, three different dynamic conditions—including free rolling, full brake, and full traction—were simulated by altering the tire rolling angle and translational velocities. Finally, the pavement mechanical response under the three rolling conditions was analyzed based on the tire–pavement contact feature.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135154035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-14DOI: 10.3390/computation11090183
None Kainat, Sana Gul, Qaisar Ali, Momin Khan, Munir Ur Rehman, Mohammad Ibrahim, Abdullah F. AlAsmari, Fawaz Alasmari, Metab Alharbi
In our current investigation, we employed a B12N12 nanocage to extract paracetamol from water utilizing a DFT approach. We explored three distinct positions of paracetamol concerning its interaction with the B12N12 nanocage, designated as complex-1 (BNP-1), complex-2 (BNP-2), and complex-3 (BNP-3), under both aqueous and gaseous conditions. The optimized bond distances exhibited strong interactions between the nanocage and the paracetamol drug in BNP-1 and BNP-3. Notably, BNP-1 and BNP-3 displayed substantial chemisorption energies, measuring at −27.94 and −15.31 kcal/mol in the gas phase and −30.69 and −15.60 kcal/mol in the aqueous medium, respectively. In contrast, BNP-2 displayed a physiosorbed nature, indicating weaker interactions with values of −6.97 kcal/mol in the gas phase and −4.98 kcal/mol in the aqueous medium. Our analysis of charge transfer revealed significant charge transfer between the B12N12 nanocage and paracetamol. Additionally, a Quantum Theory of Atoms in Molecules (QTAIM) analysis confirmed that the O─B bond within BNP-1 and BNP-3 exhibited a strong covalent and partial bond, encompassing both covalent and electrostatic interactions. In contrast, the H─N bond within BNP-2 displayed a weaker hydrogen bond. Further investigation through Noncovalent Interaction (NCI) and Reduced Density Gradient (RDG) analyses reinforced the presence of strong interactions in BNP-1 and BNP-3, while indicating weaker interactions in BNP-2. The decrease in the electronic band gap (Eg) demonstrated the potential of B12N12 as a promising adsorbent for paracetamol. Examining thermodynamics, the negative values of ∆H (enthalpy change) and ∆G (Gibbs free energy change) pointed out the exothermic and spontaneous nature of the adsorption process. Overall, our study underscores the potential of B12N12 as an effective adsorbent for eliminating paracetamol from wastewater.
{"title":"Theoretical Modeling of B12N12 Nanocage for the Effective Removal of Paracetamol from Drinking Water","authors":"None Kainat, Sana Gul, Qaisar Ali, Momin Khan, Munir Ur Rehman, Mohammad Ibrahim, Abdullah F. AlAsmari, Fawaz Alasmari, Metab Alharbi","doi":"10.3390/computation11090183","DOIUrl":"https://doi.org/10.3390/computation11090183","url":null,"abstract":"In our current investigation, we employed a B12N12 nanocage to extract paracetamol from water utilizing a DFT approach. We explored three distinct positions of paracetamol concerning its interaction with the B12N12 nanocage, designated as complex-1 (BNP-1), complex-2 (BNP-2), and complex-3 (BNP-3), under both aqueous and gaseous conditions. The optimized bond distances exhibited strong interactions between the nanocage and the paracetamol drug in BNP-1 and BNP-3. Notably, BNP-1 and BNP-3 displayed substantial chemisorption energies, measuring at −27.94 and −15.31 kcal/mol in the gas phase and −30.69 and −15.60 kcal/mol in the aqueous medium, respectively. In contrast, BNP-2 displayed a physiosorbed nature, indicating weaker interactions with values of −6.97 kcal/mol in the gas phase and −4.98 kcal/mol in the aqueous medium. Our analysis of charge transfer revealed significant charge transfer between the B12N12 nanocage and paracetamol. Additionally, a Quantum Theory of Atoms in Molecules (QTAIM) analysis confirmed that the O─B bond within BNP-1 and BNP-3 exhibited a strong covalent and partial bond, encompassing both covalent and electrostatic interactions. In contrast, the H─N bond within BNP-2 displayed a weaker hydrogen bond. Further investigation through Noncovalent Interaction (NCI) and Reduced Density Gradient (RDG) analyses reinforced the presence of strong interactions in BNP-1 and BNP-3, while indicating weaker interactions in BNP-2. The decrease in the electronic band gap (Eg) demonstrated the potential of B12N12 as a promising adsorbent for paracetamol. Examining thermodynamics, the negative values of ∆H (enthalpy change) and ∆G (Gibbs free energy change) pointed out the exothermic and spontaneous nature of the adsorption process. Overall, our study underscores the potential of B12N12 as an effective adsorbent for eliminating paracetamol from wastewater.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135487977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-14DOI: 10.3390/computation11090184
Abdulaziz Sharahy, Zaid Sawlan
This work aims to estimate temperature-dependent thermal conductivity and heat capacity given measurements of temperature and heat flux at the boundaries. This estimation problem has many engineering and industrial applications, such as those for the building sector and chemical reactors. Two approaches are proposed to address this problem. The first method uses an integral approach and a polynomial approximation of the temperature profile. The second method uses a numerical solver for the nonlinear heat equation and an optimization algorithm. The performance of the two methods is compared using synthetic data generated with different boundary conditions and configurations. The results demonstrate that the integral approach works in limited scenarios, whereas the numerical approach is effective in estimating temperature-dependent thermal properties. The second method is also extended to account for noisy measurements and a comprehensive uncertainty quantification framework is developed.
{"title":"Estimation of Temperature-Dependent Thermal Conductivity and Heat Capacity Given Boundary Data","authors":"Abdulaziz Sharahy, Zaid Sawlan","doi":"10.3390/computation11090184","DOIUrl":"https://doi.org/10.3390/computation11090184","url":null,"abstract":"This work aims to estimate temperature-dependent thermal conductivity and heat capacity given measurements of temperature and heat flux at the boundaries. This estimation problem has many engineering and industrial applications, such as those for the building sector and chemical reactors. Two approaches are proposed to address this problem. The first method uses an integral approach and a polynomial approximation of the temperature profile. The second method uses a numerical solver for the nonlinear heat equation and an optimization algorithm. The performance of the two methods is compared using synthetic data generated with different boundary conditions and configurations. The results demonstrate that the integral approach works in limited scenarios, whereas the numerical approach is effective in estimating temperature-dependent thermal properties. The second method is also extended to account for noisy measurements and a comprehensive uncertainty quantification framework is developed.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"358 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134913816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-14DOI: 10.3390/computation11090182
Oleksandr Liubimov, Ihor Turkin, Vladimir Pavlikov, Lina Volobuyeva
As a subclass of nanosatellites, CubeSats have changed the game’s rules in the scientific research industry and the development of new space technologies. The main success factors are their cost effectiveness, relative ease of production, and predictable life cycle. CubeSats are very important for training future engineers: bachelor’s and master’s students of universities. At the same time, using CubeSats is a cost-effective method of nearest space exploration and scientific work. However, many issues are related to efficient time-limited development, software and system-level quality assurance, maintenance, and software reuse. In order to increase the flexibility and reduce the complexity of CubeSat projects, this article proposes a “hybrid” development model that combines the strengths of two approaches: the agile-a-like model for software and the waterfall model for hardware. The paper proposes a new computing platform solution, “Falco SBC/CDHM”, based on Microchip (Atmel) ATSAMV71Q21 with improved performance. This type of platform emphasizes low-cost space hardware that can compete with space-grade platforms. The paper substantiates the architecture of onboard software based on microservices and containerization to break down complex software into relatively simple components that undergraduates and graduates can handle within their Master’s studies, and postgraduates can use for scientific space projects. The checking of the effectiveness of the microservice architecture and the new proposed platform was carried out experimentally, involving the time spent on executing three typical algorithms of different algorithmic complexities. Algorithms were implemented using native C (Bare-metal) and WASM3 on FreeRTOS containers on two platforms, and performance was measured on both “Falco” and “Pi Pico” by Raspberry. The experiment confirmed the feasibility of the complex application of the “hybrid” development model and microservices and container-based architecture. The proposed approach makes it possible to develop complex software in teams of inexperienced students, minimize risks, provide reusability, and thus increase the attractiveness of CubeSat student projects.
{"title":"Agile Software Development Lifecycle and Containerization Technology for CubeSat Command and Data Handling Module Implementation","authors":"Oleksandr Liubimov, Ihor Turkin, Vladimir Pavlikov, Lina Volobuyeva","doi":"10.3390/computation11090182","DOIUrl":"https://doi.org/10.3390/computation11090182","url":null,"abstract":"As a subclass of nanosatellites, CubeSats have changed the game’s rules in the scientific research industry and the development of new space technologies. The main success factors are their cost effectiveness, relative ease of production, and predictable life cycle. CubeSats are very important for training future engineers: bachelor’s and master’s students of universities. At the same time, using CubeSats is a cost-effective method of nearest space exploration and scientific work. However, many issues are related to efficient time-limited development, software and system-level quality assurance, maintenance, and software reuse. In order to increase the flexibility and reduce the complexity of CubeSat projects, this article proposes a “hybrid” development model that combines the strengths of two approaches: the agile-a-like model for software and the waterfall model for hardware. The paper proposes a new computing platform solution, “Falco SBC/CDHM”, based on Microchip (Atmel) ATSAMV71Q21 with improved performance. This type of platform emphasizes low-cost space hardware that can compete with space-grade platforms. The paper substantiates the architecture of onboard software based on microservices and containerization to break down complex software into relatively simple components that undergraduates and graduates can handle within their Master’s studies, and postgraduates can use for scientific space projects. The checking of the effectiveness of the microservice architecture and the new proposed platform was carried out experimentally, involving the time spent on executing three typical algorithms of different algorithmic complexities. Algorithms were implemented using native C (Bare-metal) and WASM3 on FreeRTOS containers on two platforms, and performance was measured on both “Falco” and “Pi Pico” by Raspberry. The experiment confirmed the feasibility of the complex application of the “hybrid” development model and microservices and container-based architecture. The proposed approach makes it possible to develop complex software in teams of inexperienced students, minimize risks, provide reusability, and thus increase the attractiveness of CubeSat student projects.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134913807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-12DOI: 10.3390/computation11090181
Haja-Sherief N. Musthafa, Jason Walker, Talal Rahman, Alvhild Bjørkum, Kamal Mustafa, Dhayalan Velauthapillai
Due to their excellent properties, triply periodic minimal surfaces (TPMS) have been applied to design scaffolds for bone tissue engineering applications. Predicting the mechanical response of bone scaffolds in different loading conditions is vital to designing scaffolds. The optimal mechanical properties can be achieved by tuning their geometrical parameters to mimic the mechanical properties of natural bone. In this study, we designed gyroid scaffolds of different user-specific pore and strut sizes using a combined TPMS and signed distance field (SDF) method to obtain varying architecture and porosities. The designed scaffolds were converted to various meshes such as surface, volume, and finite element (FE) volume meshes to create FE models with different boundary and loading conditions. The designed scaffolds under compressive loading were numerically evaluated using a finite element method (FEM) to predict and compare effective elastic moduli. The effective elastic moduli range from 0.05 GPa to 1.93 GPa was predicted for scaffolds of different architectures comparable to human trabecular bone. The results assert that the optimal mechanical properties of the scaffolds can be achieved by tuning their design and morphological parameters to match the mechanical properties of human bone.
{"title":"In-Silico Prediction of Mechanical Behaviour of Uniform Gyroid Scaffolds Affected by Its Design Parameters for Bone Tissue Engineering Applications","authors":"Haja-Sherief N. Musthafa, Jason Walker, Talal Rahman, Alvhild Bjørkum, Kamal Mustafa, Dhayalan Velauthapillai","doi":"10.3390/computation11090181","DOIUrl":"https://doi.org/10.3390/computation11090181","url":null,"abstract":"Due to their excellent properties, triply periodic minimal surfaces (TPMS) have been applied to design scaffolds for bone tissue engineering applications. Predicting the mechanical response of bone scaffolds in different loading conditions is vital to designing scaffolds. The optimal mechanical properties can be achieved by tuning their geometrical parameters to mimic the mechanical properties of natural bone. In this study, we designed gyroid scaffolds of different user-specific pore and strut sizes using a combined TPMS and signed distance field (SDF) method to obtain varying architecture and porosities. The designed scaffolds were converted to various meshes such as surface, volume, and finite element (FE) volume meshes to create FE models with different boundary and loading conditions. The designed scaffolds under compressive loading were numerically evaluated using a finite element method (FEM) to predict and compare effective elastic moduli. The effective elastic moduli range from 0.05 GPa to 1.93 GPa was predicted for scaffolds of different architectures comparable to human trabecular bone. The results assert that the optimal mechanical properties of the scaffolds can be achieved by tuning their design and morphological parameters to match the mechanical properties of human bone.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135885445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-08DOI: 10.3390/computation11090180
Nishant Chauhan, Byung-Jae Choi
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental condition in children and is characterized by challenges in maintaining attention, hyperactivity, and impulsive behaviors. Despite ongoing research, we still do not fully understand what causes ADHD. Electroencephalography (EEG) has emerged as a valuable tool for investigating ADHD-related neural patterns due to its high temporal resolution and non-invasiveness. This study aims to contribute to diagnostic accuracy by leveraging EEG data to classify children with ADHD and healthy controls. We used a dataset containing EEG recordings from 60 children with ADHD and 60 healthy controls. The EEG data were captured during cognitive tasks and comprised signals from 19 channels across the scalp. Our primary objective was to develop a machine learning model capable of distinguishing ADHD subjects from controls using EEG data as discriminatory features. We employed several well-known classifiers, including a support vector machine, random forest, decision tree, AdaBoost, Naive Bayes, and linear discriminant analysis, to discern distinctive EEG patterns. To further enhance classification accuracy, we explored the impact of regional data on the classification outcomes. We arranged the EEG data according to the brain regions from which they were derived (namely frontal, temporal, central, parietal, and occipital) and examined their collective effects on the accuracy of our classifications. Notably, we considered combinations of three regions at a time and found that certain combinations led to enhanced accuracy. Our findings underscore the potential of EEG-based classification in distinguishing children with ADHD from healthy controls. The Naive Bayes classifier yielded the highest accuracy (84%) when applied to specific region combinations. Moreover, we evaluated the classification performance based on hemisphere-specific EEG data and found promising results, particularly when using the right hemisphere region channels.
{"title":"Regional Contribution in Electrophysiological-Based Classifications of Attention Deficit Hyperactive Disorder (ADHD) Using Machine Learning","authors":"Nishant Chauhan, Byung-Jae Choi","doi":"10.3390/computation11090180","DOIUrl":"https://doi.org/10.3390/computation11090180","url":null,"abstract":"Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental condition in children and is characterized by challenges in maintaining attention, hyperactivity, and impulsive behaviors. Despite ongoing research, we still do not fully understand what causes ADHD. Electroencephalography (EEG) has emerged as a valuable tool for investigating ADHD-related neural patterns due to its high temporal resolution and non-invasiveness. This study aims to contribute to diagnostic accuracy by leveraging EEG data to classify children with ADHD and healthy controls. We used a dataset containing EEG recordings from 60 children with ADHD and 60 healthy controls. The EEG data were captured during cognitive tasks and comprised signals from 19 channels across the scalp. Our primary objective was to develop a machine learning model capable of distinguishing ADHD subjects from controls using EEG data as discriminatory features. We employed several well-known classifiers, including a support vector machine, random forest, decision tree, AdaBoost, Naive Bayes, and linear discriminant analysis, to discern distinctive EEG patterns. To further enhance classification accuracy, we explored the impact of regional data on the classification outcomes. We arranged the EEG data according to the brain regions from which they were derived (namely frontal, temporal, central, parietal, and occipital) and examined their collective effects on the accuracy of our classifications. Notably, we considered combinations of three regions at a time and found that certain combinations led to enhanced accuracy. Our findings underscore the potential of EEG-based classification in distinguishing children with ADHD from healthy controls. The Naive Bayes classifier yielded the highest accuracy (84%) when applied to specific region combinations. Moreover, we evaluated the classification performance based on hemisphere-specific EEG data and found promising results, particularly when using the right hemisphere region channels.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136362376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-07DOI: 10.3390/computation11090179
G. U. Nnachi, Y. Hamam, Coneth Graham Richards
The electrical energy demand increase does evolve rapidly due to several socioeconomic factors such as industrialisation, population growth, urbanisation and, of course, the evolution of modern technologies in this 4th industrial revolution era. Such a rapid increase in energy demand introduces a huge challenge into the power system, which has paved way for network operators to seek alternative energy resources other than the conventional fossil fuel system. Hence, the penetration of renewable energy into the electricity supply mix has evolved rapidly in the past three decades. However, the grid system has to be well planned ahead to accommodate such an increase in energy demand in the long run. Transmission Network Expansion Planning (TNEP) is a well ordered and profitable expansion of power facilities that meets the expected electric energy demand with an allowable degree of reliability. This paper proposes a DC TNEP model that minimises the capital costs of additional transmission lines, network reinforcements, generator operation costs and the costs of renewable energy penetration, while satisfying the increase in demand. The problem is formulated as a mixed integer linear programming (MILP) problem. The developed model was tested in several IEEE test systems in multi-period scenarios. We also carried out a detailed derivation of the new non-negative variables in terms of the power flow magnitudes, the bus voltage phase angles and the lines’ phase angles for proper mixed integer variable decomposition techniques. Moreover, we intend to provide additional recommendations in terms of in which particular year (within a 20 year planning period) can the network operators install new line(s), new corridor(s) and/or additional generation capacity to the respective existing power networks. This is achieved by running incremental period simulations from the base year through the planning horizon. The results show the efficacy of the developed model in solving the TNEP problem with a reduced and acceptable computation time, even for large power grid system.
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