Search results for: artificial cell

Authors: Ainoa Guinart, Maria Korpidou, Daniel Doellerer, Cornelia Palivan, Ben L. Feringa

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Stimuli responsive systems arise from the need to meet unsolved needs of current molecular drugs. Our study presents the design of a delivery system with high spatiotemporal control and tuneable release profiles. We study the incorporation of a hydrophobic synthetic molecular motor into PDMS-b-PMOXA block copolymer vesicles to create a self-assembled system. We prove their successful incorporation and selective activation by low powered visible light (λ 430 nm, 6.9 mW). We trigger the release of a fluorescent dye with high release efficiencies over sequential cycles (up to 75%) with the ability to turn on and off the release behaviour on demand by light irradiation. Low concentrations of photo-responsive units are proven to trigger release down to 1 mol% of molecular motor. Finally, we test our system in relevant physiological conditions using a lung cancer cell line and the encapsulation of an approved drug. Similar levels of cell viability are observed compared to the free-given drugshowing the potential of our platform to deliver functional drugs on demand with the same efficiency and lower toxicity.

Keywords: molecular motor, polymer, drug delivery, light-responsive, cancer, selfassembly

Procedia PDF Downloads 137

Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: Elena Petersen, Inna Kornienko, Svetlana Guryeva, Sergey Simakov

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In vitro organoid cultivation requires the simultaneous provision of necessary vascularization and nutrients perfusion of cells during organoid development. However, many aspects of this problem are still unsolved. The functionality of vascular network intergrowth is limited during early stages of organoid development since a function of the vascular network initiated on final stages of in vitro organoid cultivation. Therefore, a microchannel network should be created in early stages of organoid cultivation in hydrogel matrix aimed to conduct and maintain minimally required the level of nutrients perfusion for all cells in the expanding organoid. The network configuration should be designed properly in order to exclude hypoxic and necrotic zones in expanding organoid at all stages of its cultivation. In vitro vascularization is currently the main issue within the field of tissue engineering. As perfusion and oxygen transport have direct effects on cell viability and differentiation, researchers are currently limited only to tissues of few millimeters in thickness. These limitations are imposed by mass transfer and are defined by the balance between the metabolic demand of the cellular components in the system and the size of the scaffold. Current approaches include growth factor delivery, channeled scaffolds, perfusion bioreactors, microfluidics, cell co-cultures, cell functionalization, modular assembly, and in vivo systems. These approaches may improve cell viability or generate capillary-like structures within a tissue construct. Thus, there is a fundamental disconnect between defining the metabolic needs of tissue through quantitative measurements of oxygen and nutrient diffusion and the potential ease of integration into host vasculature for future in vivo implantation. A model is proposed for growth prognosis of the organoid perfusion based on joint simulations of general nutrient diffusion, nutrient diffusion to the hydrogel matrix through the contact surfaces and microchannels walls, nutrient consumption by the cells of expanding organoid, including biomatrix contraction during tissue development, which is associated with changed consumption rate of growing organoid cells. The model allows computing effective microchannel network design giving minimally required the level of nutrients concentration in all parts of growing organoid. It can be used for preliminary planning of microchannel network design and simulations of nutrients supply rate depending on the stage of organoid development.

Keywords: 3D model, consumption model, diffusion, spheroid, tissue organoid

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Authors: O. Gsib, U. Peirera, C. Egles, S. A. Bencherif

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In skin regenerative medicine, one of the critical issues is to produce a three-dimensional scaffold with optimized porosity for dermal fibroblast infiltration and neovascularization, which exhibits high mechanical properties and displays sufficient wound healing characteristics. In this study, we report on the synthesis and characterization of macroporous sequential interpenetrating polymer networks (IPNs) combining skin wound healing properties of fibrin with the excellent physical properties of polyethylene glycol (PEG). Fibrin fibers serve as a provisional biologically active network to promote cell adhesion and proliferation while PEG provides the mechanical stability to maintain the entire 3D construct. After having modified both PEG and Serum Albumin (used for promoting enzymatic degradability) by adding methacrylate residues (PEGDM and SAM, respectively), Fibrin/PEGDM-SAM sequential IPNs were synthesized as follows: Macroporous sponges were first produced from PEGDM-SAM hydrogels by a freeze-drying technique and then rehydrated by adding the fibrin precursors. Environmental Scanning Electron Microscopy (ESEM) and Confocal Laser Scanning Microscopy (CLSM) were used to characterize their microstructure. Human dermal fibroblasts were cultivated during one week in the constructs and different cell culture parameters (viability, morphology, proliferation) were evaluated. Subcutaneous implantations of the scaffolds were conducted on five-week old male nude mice to investigate their biocompatibility in vivo. We successfully synthesized interconnected and macroporous Fibrin/PEGDM-SAM sequential IPNs. The viability of primary dermal fibroblasts was well maintained (above 90%) after 2 days of culture. Cells were able to adhere, spread and proliferate in the scaffolds suggesting the suitable porosity and intrinsic biologic properties of the constructs. The fibrin network adopted a spider web shape that covered partially the pores allowing easier cell infiltration into the macroporous structure. To further characterize the in vitro cell behavior, cell proliferation (EdU incorporation, MTS assay) is being studied. Preliminary histological analysis of animal studies indicated the persistence of hydrogels even after one-month post implantation and confirmed the absence of inflammation response, good biocompatibility and biointegration of our scaffolds within the surrounding tissues. These results suggest that our Fibrin/PEGDM-SAM IPNs could be considered as potential candidates for dermis regenerative medicine. Histological analysis will be completed to further assess scaffold remodeling including de novo extracellular matrix protein synthesis and early stage angiogenesis analysis. Compression measurements will be conducted to investigate the mechanical properties.

Keywords: fibrin, hydrogels for dermal reconstruction, polyethylene glycol, semi-interpenetrating polymer network

Procedia PDF Downloads 237

Authors: H. Bouaziz, M. Sefi, J. de Lapuente, M. Borras, N. Zeghal

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Although arsenic trioxide has been the subject of toxicological research, in vitro cytotoxicity and genotoxicity studies using relevant cell models and uniform methodology are not well elucidated. Hence, the aim of the present study was to evaluate the cytotoxicity and genotoxicity induced by arsenic trioxide in human keratinocytes (HaCaT) using the MTT [3-(4, 5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] and alkaline single cell gel electrophoresis (Comet) assays, respectively. Human keratinocytes were treated with different doses of arsenic trioxide for 4 h prior to cytogenetic assessment. Data obtained from the MTT assay indicated that arsenic trioxide significantly reduced the viability of HaCaT cells in a dose-dependent manner, showing a IC50 value of 34.18 ± 0.6 µM. Data generated from the comet assay also indicated a significant dose-dependent increase in DNA damage in HaCaT cells associated with arsenic trioxide exposure. We observed a significant increase in comet tail length and tail moment, showing an evidence of arsenic trioxide -induced genotoxic damage in HaCaT cells. This study confirms that the comet assay is a sensitive and effective method to detect DNA damage caused by arsenic.

Keywords: arsenic trioxide, cytotoxixity, genotoxicity, HaCaT

Procedia PDF Downloads 258

Authors: Kuan Yin Hsiao, Shyh Ming Kuo, Yi Jhen Wu, Chin Wen Chuang, Chuen-Fu Lin, Wei-qing Yang, Han Hsiang Huang

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Anti-tumor effects of natural products, like compounds from marine sponges and soft corals, have been investigated for decades. Polymeric nanoparticles prepared from biodegradable and biocompatible molecules, such as Hyaluronan (HA), Chitosan (CHI) and gelatin have been widely studied. Encapsulation of anti-cancer therapies by the biopolymeric nanoparticles in drug delivery system is potentially capable of improving the therapeutic effects and attenuating their toxicity. In the current study, the anti-bladder cancer effects of heteronemin extracted from the sponge Hippospongia sp. with or without HA and CHI nanoparticle encapsulation were assessed and evaluated in vitro. Results showed that IC50 (half maximal inhibitory concentration) of heteronemin toward T24 human bladder cancer cell viability is approximately 0.18 µg/mL. Both plain and HA nanoparticles-encapsulated heteronemin at 0.2 and 0.4 µg/mL significantly reduced T24 cell viability (P<0.001) while HA nanoparticles-encapsulated heteronemin showed weaker viability-inhibitory effects on L929 fibroblasts compared with plain heteronemin at the identical concentrations. HA and CHI nanoparticles-encapsulated heteronemin exhibited significantly stronger inhibitory effects against migration of T24 human bladder cancer cell than those exerted by plain heteronemin at the same concentrations (P<0.001). The flow cytometric results showed that 0.2 µg/mL HA and CHI nanoparticles-encapsulated heteronemin induced higher early apoptosis rate than that induced by plain heteronemin at the same concentration. These results show that HA and CHI nanoparticle encapsulation is able to elevate anti-migratory and apoptosis-inducing effects exerted by heteronemin against bladder cancer cells in vitro. The in vivo anti-bladder cancer effects of the compound with or without HA/CHI nanoparticle encapsulation will be further investigated and examined using murine tumor models. The data obtained from this study will extensively evaluate of the anti-bladder cancer effects of heteronemin as well as HA/CHI-encapsulated heteronemin and pave a way to develop potential bladder cancer treatment.

Keywords: heteronemin, nanoparticles, hyaluronan, chitosan, bladder cancer

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Authors: Gebregziabher Brhane Berhe, Wei-Nien Su, Bing Joe Hwang

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A new lithium-ion battery is configured by coupling sulfurized carbon anode and high voltage LiNi₀.₅Mn₁.₅O₄ (LNMO) cathode. The anode is derived from sulfurized polyacrylonitrile (S-C(PAN)). Severe capacity fading usually becomes unavoidable due to the oxidative decomposition of solvents, primarily when a conventional carbonate electrolyte with 1 M lithium hexafluorophosphate (LiPF6) is employed. Fluoroethylene carbonate (FEC), ethyl methyl carbonate (EMC), and 1, 1, 2, 2-Tetrafluoroethyl-2, 2, 3, 3-tetrafluoropropyl ether (TTE) are formulated as the best electrolyte (3:2:5 in vol. ratio) for this new high-voltage lithium-ion battery to mitigate this capacity fading and improve the adaptability of the S-C(PAN) and LNMO. The discharge capacity of a full cell made with 1 M lithium hexafluorophosphate (LiPF6) in FEC/EMC/TTE (3:2:5) electrolyte reaches 688 mAh g⁻¹ at a rate of 2 C, while 19 mAh g⁻¹ for the control electrolyte. X-ray photoelectron spectroscopy (XPS) results confirm that the fluorinated electrolyte effectively stabilizes both surfaces of S-C(PAN) and LNMO in the full cell. Compared to the control electrolyte, the developed electrolyte enhances the cyclic stability and rate capability of both half cells (Li//S-C(PAN and Li//LiNi₀.₅Mn₁.₅O₄) and S-C(PAN)//LiNi₀.₅Mn₁.₅O₄ full cells.

Keywords: fluorinated electrolyte, high voltage, lithium-ion battery, polyacrylonitrile

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Authors: Zheni S. Stefanova, Kandethody M. Ramachandran

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With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.

Keywords: cyber security, intrusion prevention, optimal policy, Q-learning

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Authors: Lindy Adoma Dampare, Marina Aferiba Tandoh

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Sickle cell disease (SCD) is an inherited blood disorder that mostly affects individuals in sub-Saharan Africa. Nutritional deficiencies have been well established in SCD patients. In Ghana, studies have revealed the prevalence of malnutrition, especially amongst children with SCD and hence the need to develop an evidence-based comprehensive nutritional therapy for SCD to improve their nutritional status. The aim of the study was to develop and assess the effect of a nutrition education material on the nutritional status of SCD patients in Ghana. This was a pre-post interventional study. Patients between the ages of 2 to 60 years were recruited from the Tema General Hospital. Following a baseline nutrition knowledge (NK), beliefs, sanitary practice and dietary consumption pattern assessment, a twice-monthly nutrition education was carried out for 3 months, followed by a post-intervention assessment. Nutritional status of SCD patients was assessed using a 3-days dietary recall and anthropometric measurements. Nutrition education (NE) was given to SCD adults and caregivers of SCD children. Majority of the caregivers (69%) and SCD adult (82%) at baseline had low NK. The level of NK improved significantly in SCD adults (4.18±1.83 vs. 10.00±1.00, p<0.001) and caregivers (5.58 ± 2.25 vs.10.44± 0.846, p<0.001) after NE. Increase in NK improved dietary intake and dietary consumption pattern of SCD patients. Significant increase in weight (23.2±11.6 vs. 25.9±12.1, p=0.036) and height (118.5±21.9 vs. 123.5±22.2, p=0.011) was observed in SCD children at post intervention. Stunting (10.5% vs. 8.6%, p=0.62) and wasting (22.1% vs. 14.4%, p=0.30) reduced in SCD children after NE although not statistically significant. Reduction (18.2% vs. 9.1%) in underweight and an increase (18.2% vs. 27.3%) in overweight SCD adults was recorded at post intervention. Fat mass remained the same while high muscle mass increased (18.2% vs. 27.3%) at post intervention in SCD adult. Anaemic status of SCD patients improved at post intervention and the improvement was statistically significant amongst SCD children. Nutrition education improved the NK of SCD caregivers and adults hence, improving the dietary consumption pattern and nutrient intake of SCD patients. Overall, NE improved the nutritional status of SCD patients. This study shows the potential of nutrition education in improving the nutritional knowledge, dietary consumption pattern, dietary intake and nutritional status of SCD patients, and should be further explored.

Keywords: sickle cell disease, nutrition education, dietary intake, nutritional status

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Authors: Paul Hernandez-Herrera, Fernando Montoya, Juan Manuel Rendon, Alberto Darszon, Gabriel Corkidi

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Intracellular calcium ([Ca2+]i) regulates sperm motility. The analysis of [Ca2+]i has been traditionally achieved in two dimensions while the real movement of the cell takes place in three spatial dimensions. Due to optical limitations (high speed cell movement and low light emission) important data concerning the three dimensional movement of these flagellated cells had been neglected. Visualizing [Ca2+]i in 3D is not a simple matter since it requires complex fluorescence microscopy techniques where the resulting images have very low intensity and consequently low SNR (Signal to Noise Ratio). In 4D sequences, this problem is magnified since the flagellum oscillates (for human sperm) at least at an average frequency of 15 Hz. In this paper, a novel approach to extract the flagellum’s center-line in 4D stacks is presented. For this purpose, an iterative algorithm based on the fast-marching method is proposed to extract the flagellum’s center-line. Quantitative and qualitative results are presented in a 4D stack to demonstrate the ability of the proposed algorithm to trace the flagellum’s center-line. The method reached a precision and recall of 0.96 as compared with a semi-manual method.

Keywords: flagellum, minimal path, segmentation, sperm

Procedia PDF Downloads 287

Authors: Christopher R. Triggle, Hong Ding, Khaled Machaca, Gnanapragasam Arunachalam

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The antidiabetic drug, metformin, has been in clinical use for over 50 years and remains the first choice drug for the treatment of type two diabetes. In addition to its effectiveness as an oral anti-hyperglycaemic drug metformin also possesses vasculoprotective effects that are assumed to be secondary to its ability to reduce insulin resistance and control glycated hemoglobin levels; however, recent data from our laboratory indicate that metformin also has direct vasoprotective effects that are mediated, at least in part, via the anti-ageing gene, SIRT1. Diabetes is a major risk factor for the development of cardiovascular disease (CVD) and it is also well established that tobacco use further enhances the risk of CVD; however, it is not known whether treatment with metformin can offset the negative effects of diabetes and tobacco use on cardiac function. The current study was therefore designed to investigate 1: the effects of hyperglycaemia (HG) either alone or in the presence of elevated fatty acids (palmitate) and nicotine on the protein expression levels of the deacetylase sirtuin 1 (the protein product of SIRT1), anti-apoptotic Bcl-2, pro-apoptotic BIM and the pro-apoptotic, tumour suppressor protein, acetylated p53 in cardiomyocytes. 2: the ability of metformin to prevent the detrimental effects of HG, palmitate and nicotine on cardiomyocyte survival. Cell culture protocols were designed using a rat cardiomyocyte cell line, H9c2, either under normal glycaemic (NG) conditions of 5.5mM glucose, or hyperglycaemic conditions (HG) of 25mM glucose with, or without, added palmitate (250μM) or nicotine (1.0mM) for 24h. Immuno-blotting was used to detect the expression of sirtuin 1, Bcl-2, BIM, acetylated (Ac)-p53, p53 with β-actin used as the reference protein. Exposure to HG, palmitate, or nicotine alone significantly reduced expression of sirtuin1, Bcl-2 and raised the expression levels of acetylated p53 and BIM; however, the combination of HG, palmitate and nicotine had a synergistic effect to significantly suppress the expression levels of sirtuin 1 and Bcl-2, but further enhanced the expression of Ac-p53, and BIM. The inclusion of 1000μM, but not 50μM, metformin in the H9c2 cell culture protocol prevented the effects of HG, palmitate and nicotine on the pro-apoptotic pathways. Collectively these data indicate that metformin, in addition to its anti-hyperglycaemic and vasculoprotective properties, also has direct cardioprotective actions that offset the negative effects of hyerglycaemia, elevated free fatty acids and nicotine on cardiac cell survival. These data are of particular significance for the treatment of patients with diabetes who are also smokers as the inclusion of metformin in their therapeutic treatment plan should help reduce cardiac-related morbidity and mortality.

Keywords: apoptosis, cardiac muscle, diabetes, metformin, nicotine

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Authors: Saman Khan, Imrana Naseem

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Copper is an essential trace element required for pro-angiogenic co-factors including vascular endothelial growth factor (VEGF). Elevated levels of copper are found in various types of cancer including prostrate, colon, breast, lung and liver for angiogensis and metastasis. Therefore, targeting copper via copper-specific chelators in cancer cells can be developed as effective anticancer treatment strategy. In continuation of our pursuit to design and synthesize copper chelators, herein we opted for a reaction to incorporate di-(2-picolyl) amine in 3-(bromoacetyl) coumarin (parent backbone) for the synthesis of complex 1. We evaluated lipid peroxidation, protein carbonylation, ROS generation, DNA damage and consequent apoptosis by complex 1 in exogenously added Cu(II) in human peripheral lymphocytes (simulate malignancy condition). Results showed that Cu(II)-complex 1 interaction leads to cell proliferation inhibition, apoptosis, ROS generation and DNA damage in human lymphocytes, and these effects were abrogated by cuprous chelator neocuproine and ROS scavengers (thiourea, catalase, SOD). This indicates that complex 1 cytotoxicity is due to redox cycling of copper to generate ROS which leads to pro-oxidant cell death in cancer cells. To further confirm our hypothesis, using the rat model of diethylnitrosamine (DEN) induced hepatocellular carcinoma; we showed that complex 1 mediates DNA breakage and cell death in isolated carcinoma cells. Membrane permeant copper chelator, neocuproine, and ROS scavengers inhibited the complex 1-mediated cellular DNA degradation and apoptosis. In summary, complex 1 anticancer activity is due to its copper chelation capability. These results will provide copper chelation as an effective targeted cancer treatment strategy for selective cytotoxic action against malignant cells without affecting normal cells.

Keywords: cancer treatment, copper chelation, ROS generation, DNA damage, redox cycling, apoptosis

Procedia PDF Downloads 293

Authors: Fahimeh Palizban, Farshad Noravesh, Amir Hossein Saeidian, Mahya Mehrmohamadi

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In the recent decade, the emergence of liquid biopsy has significantly improved cancer monitoring and detection. Dying cells, including those originating from tumors, shed their DNA into the blood and contribute to a pool of circulating fragments called cell-free DNA. Accordingly, identifying the tissue origin of these DNA fragments from the plasma can result in more accurate and fast disease diagnosis and precise treatment protocols. Open chromatin regions are important epigenetic features of DNA that reflect cell types of origin. Profiling these features by DNase-seq, ATAC-seq, and histone ChIP-seq provides insights into tissue-specific and disease-specific regulatory mechanisms. There have been several studies in the area of cancer liquid biopsy that integrate distinct genomic and epigenomic features for early cancer detection along with tissue of origin detection. However, multimodal analysis requires several types of experiments to cover the genomic and epigenomic aspects of a single sample, which will lead to a huge amount of cost and time. To overcome these limitations, the idea of predicting OCRs from WGS is of particular importance. In this regard, we proposed a computational approach to target the prediction of open chromatin regions as an important epigenetic feature from cell-free DNA whole genome sequence data. To fulfill this objective, local sequencing depth will be fed to our proposed algorithm and the prediction of the most probable open chromatin regions from whole genome sequencing data can be carried out. Our method integrates the signal processing method with sequencing depth data and includes count normalization, Discrete Fourie Transform conversion, graph construction, graph cut optimization by linear programming, and clustering. To validate the proposed method, we compared the output of the clustering (open chromatin region+, open chromatin region-) with previously validated open chromatin regions related to human blood samples of the ATAC-DB database. The percentage of overlap between predicted open chromatin regions and the experimentally validated regions obtained by ATAC-seq in ATAC-DB is greater than 67%, which indicates meaningful prediction. As it is evident, OCRs are mostly located in the transcription start sites (TSS) of the genes. In this regard, we compared the concordance between the predicted OCRs and the human genes TSS regions obtained from refTSS and it showed proper accordance around 52.04% and ~78% with all and the housekeeping genes, respectively. Accurately detecting open chromatin regions from plasma cell-free DNA-seq data is a very challenging computational problem due to the existence of several confounding factors, such as technical and biological variations. Although this approach is in its infancy, there has already been an attempt to apply it, which leads to a tool named OCRDetector with some restrictions like the need for highly depth cfDNA WGS data, prior information about OCRs distribution, and considering multiple features. However, we implemented a graph signal clustering based on a single depth feature in an unsupervised learning manner that resulted in faster performance and decent accuracy. Overall, we tried to investigate the epigenomic pattern of a cell-free DNA sample from a new computational perspective that can be used along with other tools to investigate genetic and epigenetic aspects of a single whole genome sequencing data for efficient liquid biopsy-related analysis.

Keywords: open chromatin regions, cancer, cell-free DNA, epigenomics, graph signal processing, correlation clustering

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Authors: M. Abou-Amouna, A. Radwan, L. Al-kuwari, A. Hammuda, K. Al-Khalifa

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There is growing concern over increasing incidences of road accidents and consequent loss of human life in Qatar. In light to the future planned event in Qatar, World Cup 2022; Qatar should put into consideration the future deaths caused by road accidents, and past trends should be considered to give a reasonable picture of what may happen in the future. Qatar roads should be arranged and paved in a way that accommodate high capacity of the population in that time, since then there will be a huge number of visitors from the world. Qatar should also consider the risk issues of road accidents raised in that period, and plan to maintain high level to safety strategies. According to the increase in the number of road accidents in Qatar from 1995 until 2012, an analysis of elements affecting and causing road accidents will be effectively studied. This paper aims to identify and criticize the factors that have high effect on causing road accidents in the state of Qatar, and predict the total number of road accidents in Qatar 2022. Alternative methods are discussed and the most applicable ones according to the previous researches are selected for further studies. The methods that satisfy the existing case in Qatar were the multiple linear regression model (MLR) and artificial neutral network (ANN). Those methods are analyzed and their findings are compared. We conclude that by using MLR the number of accidents in 2022 will become 355,226 accidents, and by using ANN 216,264 accidents. We conclude that MLR gave better results than ANN because the artificial neutral network doesn’t fit data with large range varieties.

Keywords: road safety, prediction, accident, model, Qatar

Procedia PDF Downloads 259

Authors: Sang-Myung Jung, Jeong Hyun Ju, Gwang Heum Yoon, Hwa Sung Shin

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Central nervous system (CNS) consists of neuronal cell and supporting cells. Astrocytes are the most common supporting cells and play roles in metabolism between neurons and blood vessel. For this function, engineered astrocytes have been studied as a therapeutic source for CNS injury. In neural tissue engineering, nanofiber has been suggested as an effective scaffold for providing structure and mechanical properties influencing physiology. Cellulose acetate (CA) has been investigated for material to fabricate scaffold because of its biocompatibility, biodegradability and fine thermal stability. In this research, CA nanofiber was modified via heat treatment and its effect on astrocyte activity was evaluated. Adhesion and viability of astrocyte were increased in proportion to stiffness. Additionally, expression of GFAP, a marker of astrocyte activation, was increased via stiffness of scaffold. This research suggests a simple modification method to change stiffness of CA nanofiber and shows cellular behavior affecting stiffness of three-dimensional scaffold independently. For the results, we highlight that the stiffness is a factor to regulate astrocyte activity.

Keywords: astrocyte, cellulose acetate, cell therapy, stiffness of scaffold

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Authors: A. Alvaredo , R. Guzman De Villoria, P. Castell, Juan P. Fernandez-Blazquez

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Since graphene was discovered in 2004, has been considered as superb material, due to its outstanding mechanical, electrical and thermal properties. Graphene has been incorporated as reinforcement in several high performance polymers in order to obtain a good balance of properties and to get new properties as thermal or electric conductivity. As well known, the properties of semicrystalline polymer and its composites depends heavily on degree of crystallinity. In this context, our research group has studied the crystallization behavior from amorphous state of PEEK/GNP composites. The monitoring of cold crystallization processes studied by time-resolved simultaneous wide-angle X-ray scattering (WAXS) and small-angle X-ray scattering (SAXS). These techniques allowed to get an extremely relevant information about the evolution of the morphology of the PEEK/GNP composites. In addition, the thermal evolution of cold crystallization was followed by differential scanning calorimetry (DSC) as well. The experimental results showed changes in crystallization kinetics and c parameter unit cell when adding graphene. The main aim of this work is to produce PEEK/GNP composites and characterize their morphology, unit cell parameters and crystallization kinetic.

Keywords: PEEK, graphene, synchrotron, cold crystallization

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Authors: Mariangela Viviani, Daniele Germano, Simone Colace, Agostino Forestiero, Giuseppe Papuzzo, Sara Laurita

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Nowadays, people spend most of their time in closed environments, in offices, or at home. Therefore, secure and highly livable environmental conditions are needed to reduce the probability of aerial viruses spreading. Also, to lower the human impact on the planet, it is important to reduce energy consumption. Heating, Ventilation, and Air Conditioning (HVAC) systems account for the major part of energy consumption in buildings [1]. Devising systems to control and regulate the airflow is, therefore, essential for energy efficiency. Moreover, an optimal setting for thermal comfort and air quality is essential for people’s well-being, at home or in offices, and increases productivity. Thanks to the features of Artificial Intelligence (AI) tools and techniques, it is possible to design innovative systems with: (i) Improved monitoring and prediction accuracy; (ii) Enhanced decision-making and mitigation strategies; (iii) Real-time air quality information; (iv) Increased efficiency in data analysis and processing; (v) Advanced early warning systems for air pollution events; (vi) Automated and cost-effective m onitoring network; and (vii) A better understanding of air quality patterns and trends. We propose AIR SAFE, an IoT-based infrastructure designed to optimize air quality and thermal comfort in indoor environments leveraging AI tools. AIR SAFE employs a network of smart sensors collecting indoor and outdoor data to be analyzed in order to take any corrective measures to ensure the occupants’ wellness. The data are analyzed through AI algorithms able to predict the future levels of temperature, relative humidity, and CO₂ concentration [2]. Based on these predictions, AIR SAFE takes actions, such as opening/closing the window or the air conditioner, to guarantee a high level of thermal comfort and air quality in the environment. In this contribution, we present the results from the AI algorithm we have implemented on the first s et o f d ata c ollected i n a real environment. The results were compared with other models from the literature to validate our approach.

Keywords: air quality, internet of things, artificial intelligence, smart home

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Authors: M. Yadegari, M. Nourbakhsh, N. Arbabzadeh

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The skeletal system injuries are of major importance. In addition, it is recommended to use materials for hard tissue repair in open or closed fractures. It is important to use complex minerals with a beneficial effect on hard tissue repair, stimulating cell growth in the bone. Materials that could help avoid bone fracture inflammatory reaction and speed up bone fracture repair are of utmost importance in the treatment of bone fractures. Similar to minerals, the inner eggshell membrane consists of carbohydrates, lipids, proteins with the high pH, high calcium absorptive capacity and with faster bone fracture repair ability. In the present radiographic survey, eggshell-derived bone graft substitutes were used for bone defect repair in 8 dog tibia, measuring bone density on the day of implant placement and 30 and 60 days after placement. In fact, the result of this study shows the difference in bone growth and misshapen bones between treatment and control sites. Cell growth was adequate in treatment sites and misshapen bones were less frequent here than in control sites.

Keywords: bone repair, eggshell powder, implant, radiography

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Authors: Edgar Ochoa, G. Torres-Villasenor

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Superplastic deformation is shown by materials with a fine grain size, usually less than 10 μm, when they are deformed within the strain rate range 10-5 10-1 s-1 at temperatures greater than 0.5Tm, where Tm is the melting point in Kelvin. According to the constitutive equation for superplastic flow, refinement of the grain size would be expected to increase the optimum strain rate and decrease the temperature required for superplastic flow. Ribbons of eutectic Ag-Cu and Bi-Cd alloys were manufactured by using a single roller melt-spinning technique to obtain a fine grain structure for later test in superplastic regime. The eutectics ribbons were examined by scanning electron microscopy and X-Ray diffraction, and the grain size was determined using the image analysis software ImageJ. The average grain size was less than 1 μm. Tensile tests were carried out from 10-4 to 10-1 s-1, at room temperature, to evaluate the superplastic behavior. The largest deformation was shown by the Bi-Cd eutectic ribbons, Ɛ=140 %, despite that these ribbons have a hexagonal unit cell. On the other hand, Ag-Cu eutectic ribbons have a minor grain size and cube unit cell, however they showed a lower deformation in tensile test under the same conditions than Bi-Cd ribbons. This is because the Ag-Cu grew in a strong cube-cube orientation relationship.

Keywords: eutectic ribbon, fine grain, superplastic deformation, cube-cube orientation

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Authors: Osung Im, Neha Yadav, Eui Hoon Lee, Joong Hoon Kim

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Artificial Neural Network (ANN) approach is commonly used in lots of fields for forecasting. In water resources engineering, forecast of water level or inflow of reservoir is useful for various kind of purposes. Due to advantages of ANN, many papers were written for inflow prediction in river networks, but in this study, ANN is used in urban sewer networks. The growth of severe rain storm in Korea has increased flood damage severely, and the precipitation distribution is getting more erratic. Therefore, effective pump operation in pump station is an essential task for the reduction in urban area. If real time inflow of pump station reservoir can be predicted, it is possible to operate pump effectively for reducing the flood damage. This study used ANN model for pump station reservoir inflow prediction using upstream sewer depth data. For this study, rainfall events, sewer depth, and inflow into Banpo pump station reservoir between years of 2013-2014 were considered. Feed – Forward Back Propagation (FFBF), Cascade – Forward Back Propagation (CFBP), Elman Back Propagation (EBP) and Nonlinear Autoregressive Exogenous (NARX) were used as ANN model for prediction. A comparison of results with ANN model suggests that ANN is a powerful tool for inflow prediction using the sewer depth data.

Keywords: artificial neural network, forecasting, reservoir inflow, sewer depth

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Authors: Hemad Zareiforoush, Saeed Minaei, Ahmad Banakar, Mohammad Reza Alizadeh

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The quality inspection of rice (Oryza sativa L.) during its various processing stages is very important. In this research, an artificial intelligence-based model coupled with computer vision techniques was developed as a decision support system for qualitative grading of rice grains. For conducting the experiments, first, 25 samples of rice grains with different levels of percentage of broken kernels (PBK) and degree of milling (DOM) were prepared and their qualitative grade was assessed by experienced experts. Then, the quality parameters of the same samples examined by experts were determined using a machine vision system. A grading model was developed based on fuzzy logic theory in MATLAB software for making a relationship between the qualitative characteristics of the product and its quality. Totally, 25 rules were used for qualitative grading based on AND operator and Mamdani inference system. The fuzzy inference system was consisted of two input linguistic variables namely, DOM and PBK, which were obtained by the machine vision system, and one output variable (quality of the product). The model output was finally defuzzified using Center of Maximum (COM) method. In order to evaluate the developed model, the output of the fuzzy system was compared with experts’ assessments. It was revealed that the developed model can estimate the qualitative grade of the product with an accuracy of 95.74%.

Keywords: machine vision, fuzzy logic, rice, quality

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Authors: Yi Sun, George Ed Rainger, Steve P. Watson

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Background: Beyond the classical roles in haemostasis and thrombosis, platelets are important in the initiation and development of various thrombo-inflammatory diseases. In atherosclerosis and deep vein thrombosis, for example, platelets bridge monocytes with endothelium and form heterotypic aggregates with monocytes in the circulation. This can alter monocyte phenotype by inducing their activation, stimulating adhesion and migration. These interactions involve cell surface receptor-ligand pairs on both cells. This list is likely incomplete as new interactions of importance to platelet biology are continuing to be discovered as illustrated by our discovery of PEAR-1 binding to FcεR1α. Results: We have developed a highly sensitive avidity-based assay to identify novel extracellular interactions among 126 recombinantly-expressed platelet cell surface and secreted proteins involved in platelet aggregation. In this study, we will use this method to identify novel platelet-monocyte interactions. We aim to identify ligands for orphan receptors and novel partners of well-known proteins. Identified interactions will be studied in preliminary functional assays to demonstrate relevance to the inflammatory processes supporting atherogenesis. Conclusions: Platelet-monocyte interactions are essential for the development of thromboinflammatory disease. Up until relatively recently, technologies only allow us to limit our studies on each individual protein interaction at a single time. These studies propose for the first time to study the cell surface platelet-monocyte interactions in a systematic large-scale approach using a reliable screening method we have developed. If successful, this will likely to identify previously unknown ligands for important receptors that will be investigated in details and also provide a list of novel interactions for the field. This should stimulate studies on developing alternative therapeutic strategies to treat vascular inflammatory disorders such as atherosclerosis, DVT and sepsis and other clinically important inflammatory conditions.

Keywords: membrane proteins, large-scale screening, platelets, recombinant expression

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Authors: A. M. Raseona, D. M. Barry, T. L. Nedambale

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Preservation of semen is an important process to ensure that semen quality is sufficient for assisted reproductive technology. This study evaluated the effectiveness of different extenders to preserve Nguni bull semen stored at controlled room temperature 24 °C for three days, as an alternative to frozen-thawed semen straws used for artificial insemination. Semen samples were collected from two Nguni bulls using an electro-ejaculator and transported to the laboratory for evaluation. Pooled semen was aliquot into three extenders Triladyl, Ham’s F10 and M199 at a dilution ratio of 1:4 then stored at controlled room temperature 24 °C. Sperm motility was analysed after 0, 24, 48 and 72 hours. Morphology and viability were analysed after 72 hours. The study was replicated four times and data was analysed by analysis of variance (ANOVA). Triladyl showed higher viability percentage and consistent total motility for three days. Ham’s F10 showed higher progressive motility compared to the other extenders. There was no significant difference in viability between Ham’s F10 and M199. No significant difference was also observed in total abnormality between the two Nguni bulls. In conclusion, Nguni semen can be preserved in Triladyl or Ham’s F10 and M199 culture media stored at 24 °C and stay alive for three days. Triladyl proved to be the best extender showing high viability and consistency in total motility as compared to Ham’s F10 and M199.

Keywords: bull semen, artificial insemination, Triladyl, Ham’s F10, M199, viability

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Authors: John K. Avor, Choong-Koo Chang

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The transfer of electrical loads at power generation stations from Standby Auxiliary Transformer (SAT) to Unit Auxiliary Transformer (UAT) and vice versa is through a fast bus transfer scheme. Fast bus transfer is a time-critical application where the transfer process depends on various parameters, thus transfer schemes apply advance algorithms to ensure power supply reliability and continuity. In a nuclear power generation station, supply continuity is essential, especially for critical class 1E electrical loads. Bus transfers must, therefore, be executed accurately within 4 to 10 cycles in order to achieve safety system requirements. However, the main problem is that there are instances where transfer schemes scrambled due to inaccurate interpretation of key parameters; and consequently, have failed to transfer several critical loads from UAT to the SAT during main generator trip event. Although several techniques have been adopted to develop robust transfer schemes, a combination of Artificial Neural Network and Fuzzy Systems (Neuro-Fuzzy) has not been extensively used. In this paper, we apply the concept of Neuro-Fuzzy to determine plant operating mode and dynamic prediction of the appropriate bus transfer algorithm to be selected based on the first cycle of voltage information. The performance of Sequential Fast Transfer and Residual Bus Transfer schemes was evaluated through simulation and integration of the Neuro-Fuzzy system. The objective for adopting Neuro-Fuzzy approach in the bus transfer scheme is to utilize the signal validation capabilities of artificial neural network, specifically the back-propagation algorithm which is very accurate in learning completely new systems. This research presents a combined effect of artificial neural network and fuzzy systems to accurately interpret key bus transfer parameters such as magnitude of the residual voltage, decay time, and the associated phase angle of the residual voltage in order to determine the possibility of high speed bus transfer for a particular bus and the corresponding transfer algorithm. This demonstrates potential for general applicability to improve reliability of the auxiliary power distribution system. The performance of the scheme is implemented on APR1400 nuclear power plant auxiliary system.

Keywords: auxiliary power system, bus transfer scheme, fuzzy logic, neural networks, reliability

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Authors: Ali Bayram, Remzi Yiğiter

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Objective: Alzheimer's disease (AD), the most common cause of dementia, is a progressive neurodegenerative disease. At present, diagnosis of AD is rather late in the disease. Therefore, we attempted to find peripheral biomarkers for the early diagnosis of AD. Herein, we conducted a study to investigate the unc-51 like autophagy activating kinase-1 (ULK1) mRNA expression levels in human peripheral blood mononuclear cells from patients with Alzheimer's disease. Method: To determine whether ULK1 gene expression are altered in AD patients, we measured their gene expression in human peripheral blood cell in 50 patients with AD and 50 age and gender matched healthy controls by quantitative real-time PCR technique. Results: We found that both ULK1 gene expression in peripheral blood cell were significantly decreased in patients with AD as compared with controls (p <0.05). Lower levels of ULK1 gene expression were significantly associated with the increased risk for AD. Conclusions: Serine/threonine-protein kinase involved in autophagy in response to starvation. Acts upstream of phosphatidylinositol 3-kinase PIK3C3 to regulate the formation of autophagophores, the precursors of autophagosomes. Part of regulatory feedback loops in autophagy: acts both as a downstream effector and negative regulator of mammalian target of rapamycin complex 1 (mTORC1) via interaction with RPTOR. Activated via phosphorylation by AMPK and also acts as a regulator of AMPK by mediating phosphorylation of AMPK subunits PRKAA1, PRKAB2, and PRKAG1, leading to negatively regulate AMPK activity. May phosphorylate ATG13/KIAA0652 and RPTOR; however such data need additional evidences. Plays a role early in neuronal differentiation and is required for granule cell axon formation. Alzheimer is the most common neurodegenerative disease. Our results provide useful information that the ULK1 gene expression is decreased in the neurodegeneration and AD patients with, indicating their possible systemic involvement in AD.

Keywords: Alzheimer’s sisease, ULK1, mRNA expression, RT-PCR

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Authors: Hyunjung Lim, Jeonghun Nam, Hyuk Choi

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High-throughput separation is an essential technique for cancer research and diagnosis. Here, we propose a viscoelastic microfluidic device for sheathless, high-throughput isolation of circulating tumor cells (CTCs) from white blood cells. Here, we demonstrate a viscoelastic method for separation and concentration of CTCs using closed-loop microfluidics. Our device is a rectangular straight channel with a low aspect ratio. Also, to achieve high-efficiency, high-throughput processing, we used a polymer solution with low viscosity. At the inlet, CTCs and white blood cells (WBCs) were randomly injected into the microchannel. Due to the viscoelasticity-induced lateral migration to the equilibrium positions, large CTCs could be collected from the side outlet while small WBCs were removed at the center outlet. By recirculating the collected CTCs from the side outlet back to the sample reservoir, continuous separation and concentration of CTCs could be achieved with high separation efficiency (~ 99%). We believe that our device has the potential to be applied in resource-limited clinical settings.

Keywords: circulating tumor cell, closed-loop microfluidics, concentration, separation, viscoelastic fluid

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Authors: Dimitriya A. Mihaylova, Zlatka V. Valkova-Jarvis, Georgi L. Iliev

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One possible approach for maintaining the security of communication systems relies on Physical Layer Security mechanisms. However, in wireless time division duplex systems, where uplink and downlink channels are reciprocal, the channel estimate procedure is exposed to attacks known as pilot contamination, with the aim of having an enhanced data signal sent to the malicious user. The Shifted 2-N-PSK method involves two random legitimate pilots in the training phase, each of which belongs to a constellation, shifted from the original N-PSK symbols by certain degrees. In this paper, legitimate pilots’ offset values and their influence on the detection capabilities of the Shifted 2-N-PSK method are investigated. As the implementation of the technique depends on the relation between the shift angles rather than their specific values, the optimal interconnection between the two legitimate constellations is investigated. The results show that no regularity exists in the relation between the pilot contamination attacks (PCA) detection probability and the choice of offset values. Therefore, an adversary who aims to obtain the exact offset values can only employ a brute-force attack but the large number of possible combinations for the shifted constellations makes such a type of attack difficult to successfully mount. For this reason, the number of optimal shift value pairs is also studied for both 100% and 98% probabilities of detecting pilot contamination attacks. Although the Shifted 2-N-PSK method has been broadly studied in different signal-to-noise ratio scenarios, in multi-cell systems the interference from the signals in other cells should be also taken into account. Therefore, the inter-cell interference impact on the performance of the method is investigated by means of a large number of simulations. The results show that the detection probability of the Shifted 2-N-PSK decreases inversely to the signal-to-interference-plus-noise ratio.

Keywords: channel estimation, inter-cell interference, pilot contamination attacks, wireless communications

Procedia PDF Downloads 219

Authors: K. J. Keerthi, Vasundhara Kamineni, A. Ravi Shanker, T. Rammurthy, A. Vijaya Lakshmi, Q. Hasan

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Pancreatic β-cells are the predominant insulin-producing cell types within the Islets of Langerhans and insulin is the primary hormone which regulates carbohydrate and fat metabolism. Apoptosis of β-cells or insufficient insulin production leads to Diabetes Mellitus (DM). Current therapy for diabetes includes either medical management or insulin replacement and regular monitoring. Replacement of β- cells is an attractive treatment option for both Type-1 and Type-2 DM in view of the recent paper which indicates that β-cells apoptosis is the common underlying cause for both the Types of DM. With the development of Edmonton protocol, pancreatic β-cells allo-transplantation became possible, but this is still not considered as standard of care due to subsequent requirement of lifelong immunosuppression and the scarcity of suitable healthy organs to retrieve pancreatic β-cell. Fetal pancreatic cells from abortuses were developed as a possible therapeutic option for Diabetes, however, this posed several ethical issues. Hence, in the present study Mesenchymal stem cells (MSCs) were differentiated into insulin producing cells which were isolated from Human Umbilical cord (HUC) tissue. MSCs have already made their mark in the growing field of regenerative medicine, and their therapeutic worth has already been validated for a number of conditions. HUC samples were collected with prior informed consent as approved by the Institutional ethical committee. HUC (n=26) were processed using a combination of both mechanical and enzymatic (collagenase-II, 100 U/ml, Gibco ) methods to obtain MSCs which were cultured in-vitro in L-DMEM (Low glucose Dulbecco's Modified Eagle's Medium, Sigma, 4.5 mM glucose/L), 10% FBS in 5% CO2 incubator at 37°C. After reaching 80-90% confluency, MSCs were characterized with Flowcytometry and Immunocytochemistry for specific cell surface antigens. Cells expressed CD90+, CD73+, CD105+, CD34-, CD45-, HLA-DR-/Low and Vimentin+. These cells were differentiated to β-cells by using H-DMEM (High glucose Dulbecco's Modified Eagle's Medium,25 mM glucose/L, Gibco), β-Mercaptoethanol (0.1mM, Hi-Media), basic Fibroblast growth factor (10 µg /L,Gibco), and Nicotinamide (10 mmol/L, Hi-Media). Pancreatic β-cells were confirmed by positive Dithizone staining and were found to be functionally active as they released 8 IU/ml insulin on glucose stimulation. Isolating MSCs from usually discarded, abundantly available HUC tissue, expanding and differentiating to β-cells may be the most feasible cell therapy option for the millions of people suffering from DM globally.

Keywords: diabetes mellitus, human umbilical cord, mesenchymal stem cells, differentiation

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

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Authors: Mohanad Alhabo, Li Zhang, Naveed Nawaz

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In this paper, a non-cooperative game method is formulated where all players compete to transmit at higher power. Every base station represents a player in the game. The game is solved by obtaining the Nash equilibrium (NE) where the game converges to optimality. The proposed method, named Power Efficient Handover Game Theoretic (PEHO-GT) approach, aims to control the handover in dense small cell networks. Players optimize their payoff by adjusting the transmission power to improve the performance in terms of throughput, handover, power consumption and load balancing. To select the desired transmission power for a player, the payoff function considers the gain of increasing the transmission power. Then, the cell selection takes place by deploying Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). A game theoretical method is implemented for heterogeneous networks to validate the improvement obtained. Results reveal that the proposed method gives a throughput improvement while reducing the power consumption and minimizing the frequent handover.

Keywords: energy efficiency, game theory, handover, HetNets, small cells

Procedia PDF Downloads 128