{"title":"Mathematical Model in Air Pollution with Area Source","authors":"Dr. B.B. Chattopadhyay, Shibajee Singha Deo","doi":"10.2139/ssrn.3653343","DOIUrl":"https://doi.org/10.2139/ssrn.3653343","url":null,"abstract":"A steady state two-dimensional atmospheric advection- diffusion numerical model of area source air pollution is presented. This model takes into account the actual form of variable settling velocity and eddy-diffusivity profile. Here the influence of settling velocity must be taken into account for the study of atmosphere dispersion. Therefore in the present analysis the two dimensional steady state dispersion of air pollutants over an area source under the settling effect has been investigated. The results obtained are compared with the known results and are found in close agreement.","PeriodicalId":283911,"journal":{"name":"Bioengineering eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131208942","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}
S. Park, Joon Yeong Park, Y. Ji, Hyun Jin Ju, B. Min, M. Kim
{"title":"An Injectable Click-Crosslinked Hyaluronic Acid Hydrogel Modified with a BMP-2 Mimic Peptide as a Bone Tissue Engineering Scaffold","authors":"S. Park, Joon Yeong Park, Y. Ji, Hyun Jin Ju, B. Min, M. Kim","doi":"10.2139/ssrn.3622648","DOIUrl":"https://doi.org/10.2139/ssrn.3622648","url":null,"abstract":"An injectable, click-crosslinking (Cx) hyaluronic acid (HA) hydrogel scaffold modified with a bone morphogenetic protein-2 (BMP-2) mimetic peptide (BP) was prepared for bone tissue engineering applications. The injectable click-crosslinking HA formulation was prepared from HA-tetrazine (HA-Tet) and HA-cyclooctene (HA-TCO). The Cx-HA hydrogel scaffold was prepared simply by mixing HA-Tet and HA-TCO. The Cx-HA hydrogel scaffold was stable for a longer period than HA both in vitro and in vivo, which was verified via in-vivo fluorescence imaging in real time. BP acted as an osteogenic differentiation factor for human dental pulp stem cells (hDPSCs). After its formation in vivo, the Cx-HA scaffold provided an excellent environment for the hDPSCs, and the biocompatibility of the hydrogel scaffold with tissue was excellent. Like traditional BMP-2, BP induced the osteogenic differentiation of hDPSCs in vitro. The physical properties and injectability of the chemically loaded BP for the Cx-HA hydrogel (Cx-HA-BP) were nearly identical to those of the physically loaded BP hydrogels and the Cx-HA-BP formulation quickly formed a hydrogel scaffold in vivo. The chemically loaded hydrogel scaffold retained the BP for over a month. The Cx-HA-BP hydrogel was better at inducing the osteogenic differentiation of loaded hDPSCs, because it prolonged the availability of BP. In summary, we successfully developed an injectable, click-crosslinking Cx-HA hydrogel scaffold to prolong the availability of BP for efficient bone tissue engineering.","PeriodicalId":283911,"journal":{"name":"Bioengineering eJournal","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127651976","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}
Brianna M. Roux, M. Vaicik, Binita Shreshta, S. Montelongo, Katerina Stojkova, Feipeng Yang, T. Guda, A. Çinar, E. Brey
{"title":"In Vitro and in Vivo Evaluation of Vascular Networks Generated from iPSC-Derived Endothelial Cells","authors":"Brianna M. Roux, M. Vaicik, Binita Shreshta, S. Montelongo, Katerina Stojkova, Feipeng Yang, T. Guda, A. Çinar, E. Brey","doi":"10.2139/ssrn.3618767","DOIUrl":"https://doi.org/10.2139/ssrn.3618767","url":null,"abstract":"Vascularization is critical for the survival of engineered tissues post implantation. It has been previously shown that biomaterials containing preformed networks can anastomose to host vasculature following implantation. However, the optimal source of cells for vascularization for clinical use remains elusive. In this study, vascular networks were generated from endothelial cells derived from human induced pluripotent stem cells (iPSCs). Network formation by iPSC-ECs within fibrin gels was investigated in a mesenchymal stem cell (MSC) co-culture spheroid model. Statistical design of experiments (DOE) techniques were applied to identify optimal conditions for vessel-like network formation. The prevascularized units were then combined with hydroxyapatite nanoparticles to develop a vascularized composite hydrogel that was implanted in a rodent critical sized cranial defect model. Immunohistological staining for human-specific CD31 at week 1 indicated the presence and maintenance of the implanted vessels. Erythrocytes in the vessel lumen further suggests anastomosis of vessels with host vasculature. At week 8, isolectin staining indicated functionality of the human implanted vessels. There was a slight increase in bone volume in prevascularized scaffolds compared to MSC-only scaffolds. However, a pronounced increased in bone regeneration with prevascularization was not observed. These results show that prevascularized scaffolds can be generated from ECs derived from iPSC and that the networks survive and inosculate with the host post implantation in a bone model.","PeriodicalId":283911,"journal":{"name":"Bioengineering eJournal","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129576166","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}
{"title":"Detection of Malaria Using Machine Learning","authors":"H. Thakkar, P. Thakker, P. Pede, N. Shah","doi":"10.2139/ssrn.3606136","DOIUrl":"https://doi.org/10.2139/ssrn.3606136","url":null,"abstract":"According to the WHO 2018 report, there were approx. 228 million cases worldwide and the estimated number of deaths stood 405000. Malaria is a life-threatening, hazardous disease brought about by parasites that are transmitted to individuals through the bites of infected mosquitoes. Malaria should be considered a potential medical emergency. Delay in diagnosis and treatment is a leading cause of death in malaria patients. Malaria can be suspected on the basis of physical findings and symptoms in any patient. Laboratorians may lack experience with malaria and neglect to identify parasites while examining blood smears under the microscope. Automation of the diagnosis process will ensure accurate diagnosis of the disease and hence may deliver reliable results to resource-scarce areas.","PeriodicalId":283911,"journal":{"name":"Bioengineering eJournal","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126073687","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}
{"title":"A Comparative Study between Simulation of Machine Learning and Extreme Learning Techniques on Breast Cancer Diagnosis","authors":"Rahul Reddy Nadikattu","doi":"10.2139/ssrn.3615092","DOIUrl":"https://doi.org/10.2139/ssrn.3615092","url":null,"abstract":"Breast Cancer is a developing and most normal disease among ladies around the globe. Breast malignancy is an uncontrolled and exorbitant development of abnormal cells in the Breast because of hereditary, hormonal, and way of life factors. During the starting stages, the tumor is restricted to the Breast, and in the latter part, it can spread to lymph hubs in the armpit and different organs like the liver, bones, lungs, and cerebrum. At the point when the bosom disease spreads too different pieces of the body, it is going to metastasize. The sickness is repairable in the beginning periods, yet it is identified in later stages, which is the fundamental driver for the passing of such a large number of ladies in this entire world. Clinical tests led in medical clinics for deciding the malady are a lot of costly, just as tedious as well. The answer to counter this is by directing early and exact findings for quicker treatment, and accomplishing such exactness in a limited capacity to focus time demonstrates troublesome with existing techniques. In this paper, we look at changed AI and neural system calculations to foresee malignant growth in beginning times, intending to save the patient's life. Wisconsin Breast Cancer (WBC) data set from the UCI AI vault has been utilized. Various calculations were looked in particular Support Vector Machine Classification (SVM), K-Nearest Neighbor Classification (KNN), Decision tree Classification (DT), Random Forest Classification (RF) and Extreme Learning Machine (ELM) and they thought about based on precision and handling time taken by each. The outcomes show that an extreme learning machine gives the best outcome for both the ideal models.","PeriodicalId":283911,"journal":{"name":"Bioengineering eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129059326","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}
Anjali Tripathi, Upasana Singh, G. Bansal, Rishabh Gupta, A. Singh
{"title":"A Review on Emotion Detection and Classification using Speech","authors":"Anjali Tripathi, Upasana Singh, G. Bansal, Rishabh Gupta, A. Singh","doi":"10.2139/ssrn.3601803","DOIUrl":"https://doi.org/10.2139/ssrn.3601803","url":null,"abstract":"The paper reviews about “emotion detection using vocal audios”. The vocals mainly constitute of the speech which is determined by the signals. Emotion recognition from the speech is an old and challenging problem in the field of artificial intelligence. In this paper, the recent developments on sentiment analysis using speech and different problems related to the same have been presented. The main challenge of the speech detection model is the classification of different emotions using the emotion detection model. So to choose an appropriate classification model is vital. Different types of features of emotional speech data and extraction techniques concerned with them are described in this paper along with the previous work review. The applicability of the various classification techniques has also been reviewed. The analysis has also been performed on different ML techniques for speech emotion recognition accuracy in different languages’.","PeriodicalId":283911,"journal":{"name":"Bioengineering eJournal","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115001154","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}
Gladys A Emechebe, Francis O. Obiweluozor, In-Seok Jeong, Park June Kyu, C. Park, Cheol-Sang Kim
{"title":"Structurally Reinforced Biodegradable Antithrombotic Small-Caliber Vascular Grafts Immobilized with VEGF to Accelerate Endothelialization: When 3D Printing Meets Electrospun Fiber","authors":"Gladys A Emechebe, Francis O. Obiweluozor, In-Seok Jeong, Park June Kyu, C. Park, Cheol-Sang Kim","doi":"10.2139/ssrn.3563934","DOIUrl":"https://doi.org/10.2139/ssrn.3563934","url":null,"abstract":"The major challenge of commercially available vascular substitutes come from their limitations in terms of good mechanical strength and host remodeling. To date, tissue-engineered and synthetic grafts have not translated well to clinical trials when looking at small diameters. We conceptualized a cell-free structurally reinforced biodegradable vascular graft recapitulating the anisotropic feature of native blood vessel by using nanofibrous scaffold that will gradually degrade systematically to yield a neo-vessel, facilitated by an immobilized bioactive molecule-vascular endothelial growth factor (VEGF). The nanotopographic cue of the device is capable to directs host cell infiltration. We evaluated the burst pressure, Histology, hemocompatibility, compression test and mechanical analysis of the new graft. Hence, we proposed that future long-term studies of this technology on porcine models due to their similar vasculature regeneration to humans is needed prior to clinical translation. This acellular off-the-shelf approach will mark a paradigm shift from the current dominant focus on cell incorporation in vascular tissue engineering thus strongly influencing regenerative medicine as we move forward in this new decade.","PeriodicalId":283911,"journal":{"name":"Bioengineering eJournal","volume":"90 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132766200","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}
{"title":"Implement a Proper Nutrition Model for Athletes Using the Linear Optimization Model","authors":"H. Eghbali","doi":"10.2139/ssrn.3568367","DOIUrl":"https://doi.org/10.2139/ssrn.3568367","url":null,"abstract":"Purpose: According to the previous studies, an athlete's required calory must be achieved through a healthy, carbohydrate-rich, low-fat and protein-rich diet. The focus of this study is to apply this diet by the use of optimizing the linear programming problem.<br><br>Material and Methods: A 24 years old boy with 22.7 kg/m2 body mass index(BMI) spending 2 hours fun swimming, was selected for this research. Afterward by the use of library resources , minimum and maximum of required calory (about 3000 kcal) and nutrients was determined. Maximizing the amount of calory and minimizing fat intake are the objectives of linear programming. The maximum and minimum amount of nutrients. to solve this problem an appropriate computational software matlab was used.<br><br>Results: After solving nutrition model , a quantitative values of each food was acquired. This quantitative values is considered as an originator of an optimized diet upon maximizing calory and reducing fat intake. The amount of daily intake from various nutritive food was achieved by an appropriate application. <br><br>Conclusion: According to the research findings, we can express that by the use of linear programming to optimize the diet the quantitative data of nutrients in eating schedule is acquired. Consequently, we will observe increase of calory and fat reduction by considering nutrition and food variety in course meals.<br>","PeriodicalId":283911,"journal":{"name":"Bioengineering eJournal","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126147402","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}
{"title":"Bioplastics from Agricultural Wastes","authors":"P. A. Ramamoorthy, M. Karthikeyan","doi":"10.2139/ssrn.3564039","DOIUrl":"https://doi.org/10.2139/ssrn.3564039","url":null,"abstract":"BioPlastics such as PLA has a few drawbacks among them incompatible with existing recycling stream and hence classified as “unrecyclable” in many countries; not truly biodegradable in natural conditions since it requires high temperature to decompose (>58oC); high impact to the environment for it’s high carbon footage production process; and competing to our food production for taking the corps as it’s feed-stock. FPCTM presented in this paper resolves all the above difficulties by using agricultural waste which contains fiber as it’s main ingredient, mixed with proprietary CompatiblizerTM which is converted starch without adding any man-made chemicals, so FPCTM is inherently biodegradable and compostable, yet FPCTM can be mixed with almost any plastics in any percentage, making it exhibits no harm to the existing recycling system, such characteristics also make FPCTM to be an excellent binder to create new material from various recycled plastics including ocean plastic waste and textile waste. Products using 100% FPCTM are not only biodegradable & compostable, but also a truly circular bio-economy fashion without competing with our food source, while significantly reduce air pollution because the agricultural waste would otherwise be burned off; and in the meantime create high value since the processing of biomass is not targeted to obtained low-value calories through burning, but the replacement of petro-chemical products without causing long-term burden to our land and ocean.","PeriodicalId":283911,"journal":{"name":"Bioengineering eJournal","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114634058","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}
A. Shakya, Ayushman Ramola, Yash Tandon, A. Vidyarthi
{"title":"A Matrix-based Mathematical Model for Redundant Data Reduction from DICOM Images","authors":"A. Shakya, Ayushman Ramola, Yash Tandon, A. Vidyarthi","doi":"10.2139/ssrn.3545074","DOIUrl":"https://doi.org/10.2139/ssrn.3545074","url":null,"abstract":"In the era of the 21st century, there are many Nations who are not able to provide proper medical facilities for their citizens, as proper medical facilities require a large amount of investment and support. Here we have proposed a hybrid model of the digital image in communication and medicine (DICOM) image compression for the hospitals of rural India in which important information from a diagnostic point of view and non-important information can be kept together in the same image. As we are aware of the fact that DICOM images require large storage space so it is important to reduce the property of the DICOM images so that they can be easily stored, transmitted and operated wherever it is required. In this research work, we have obtained 60.83 % compression by using the proposed technique.","PeriodicalId":283911,"journal":{"name":"Bioengineering eJournal","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115117351","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}