Search results for: cell morphology prediction

Authors: Cedric Leong, Parth Desai, Parth Patel

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The purpose of this project was to develop a neural network based on qualitative team data to predict alliance scores to determine winners of matches in the FIRST Robotics Competition (FRC). The game for the competition changes every year with different objectives and game objects, however the idea was to create a prediction system which can be reused year by year using some of the statistics that are constant through different games, making our system adaptable to future games as well. Aerial Assist is the FRC game for 2014, and is played in alliances of 3 teams going against one another, namely the Red and Blue alliances. This application takes any 6 teams paired into 2 alliances of 3 teams and generates the prediction for the final score between them.

Keywords: artifical neural network, prediction system, qualitative team data, FIRST Robotics Competition (FRC)

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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: W. Baumgartner, M. Welti, N. Hild, S. C. Hess, W. J. Stark, G. Meier Bürgisser, P. Giovanoli, J. Buschmann

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Perfusion bioreactors are used to solve problems in tissue engineering in terms of sufficient nutrient and oxygen supply. Such problems especially occur in critical size grafts because vascularization is often too slow after implantation ending up in necrotic cores. Biominerizable and biocompatible nanocomposite materials are attractive and suitable scaffold materials for bone tissue engineering because they offer mineral components in organic carriers – mimicking natural bone tissue. In addition, human adipose derived stem cells (ASCs) can potentially be used to increase bone healing as they are capable of differentiating towards osteoblasts or endothelial cells among others. In the present study, electrospun nanocomposite disks of poly-lactic-co-glycolic acid and amorphous calcium phosphate nanoparticles (PLGA/a-CaP) were seeded with human ASCs and eight disks were stacked in a bioreactor running with normal culture medium (no differentiation supplements). Under continuous perfusion and uniaxial cyclic compression, load-displacement curves as a function of time were assessed. Stiffness and energy dissipation were recorded. Moreover, stem cell densities in the layers of the piled scaffold were determined as well as their morphologies and differentiation status (endothelial cell differentiation, chondrogenesis and osteogenesis). While the stiffness of the cell free constructs increased over time caused by the transformation of the a-CaP nanoparticles into flake-like apatite, ASC-seeded constructs showed a constant stiffness. Stem cell density gradients were histologically determined with a linear increase in the flow direction from the bottom to the top of the 3.5 mm high pile (r2 > 0.95). Cell morphology was influenced by the flow rate, with stem cells getting more roundish at higher flow rates. Less than 1 % osteogenesis was found upon osteopontin immunostaining at the end of the experiment (9 days), while no endothelial cell differentiation and no chondrogenesis was triggered under these conditions. All ASCs had mainly remained in their original pluripotent status within this time frame. In summary, we have fabricated a critical size bone graft based on a biominerizable bone-biomimetic nanocomposite with preserved stiffness when seeded with human ASCs. The special feature of this bone graft was that ASC densities inside the piled construct varied with a linear gradient, which is a good starting point for tissue engineering interfaces such as bone-cartilage where the bone tissue is cell rich while the cartilage exhibits low cell densities. As such, this tissue-engineered graft may act as a bone-cartilage interface after the corresponding differentiation of the ASCs.

Keywords: bioreactor, bone, cartilage, nanocomposite, stem cell gradient

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Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh

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Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.

Keywords: feature selection, neural network, particle swarm optimization, software fault prediction

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Authors: Yingjeng James Li, Yun Jyun Ou, Chih Chi Hsu, Chiao-Chih Hu

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A fuel cell is a device that produces electric power by reacting fuel and oxidant electrochemically. There is no pollution produced from a fuel cell if hydrogen is employed as the fuel. Therefore, a fuel cell is considered as a zero emission device and is a source of green power. A membrane electrode assembly (MEA) is the key component of a fuel cell. It is, therefore, beneficial to develop MEAs with high performance. In this study, an MEA for proton exchange membrane fuel cell (PEMFC) was prepared from a 15-micron thick reinforced PEM. The active area of such MEA is 25 cm2. Carbon supported platinum (Pt/C) was employed as the catalyst for both anode and cathode. The platinum loading is 0.6 mg/cm2 based on the sum of anode and cathode. Commercially available carbon papers coated with a micro porous layer (MPL) serve as gas diffusion layers (GDLs). The original thickness of the GDL is 250 μm. It was compressed down to 163 μm when assembled into the single cell test fixture. Polarization curves were taken by using eight different test conditions. At our standard test condition (cell: 70 °C; anode: pure hydrogen, 100%RH, 1.2 stoic, ambient pressure; cathode: air, 100%RH, 3.0 stoic, ambient pressure), the cell current density is 1250 mA/cm2 at 0.6 V, and 2400 mA/cm2 at 0.4 V. At self-humidified condition and cell temperature of 55 °C, the cell current density is 1050 mA/cm2 at 0.6 V, and 2250 mA/cm2 at 0.4 V. Hydrogen crossover rate of the MEA is 0.0108 mL/min*cm2 according to linear sweep voltammetry experiments. According to the MEA’s Pt loading and the cyclic voltammetry experiments, the Pt electrochemical surface area is 60 m2/g. The ohmic part of the impedance spectroscopy results shows that the membrane resistance is about 60 mΩ*cm2 when the MEA is operated at 0.6 V.

Keywords: fuel cell, membrane electrode assembly, proton exchange membrane, reinforced

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Authors: Shittu Ahmed Tajudeen

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This study examines student-teachers’ attitude and intention towards cell-phone use for learning. The study involves one hundred and ninety (190) trainee teachers in one of the Institutes of Education in Nigeria. The data of the study was collected through a questionnaire on a rating of seven point likert-type Scale. The data collected was used to test the hypothesized model of the study using Structural Equation Modeling approach. The finding of the study revealed that Perceived Usefulness (PU), Perceived Ease of Use (PEU), Subjective Norm (SN) and Attitude significantly influence students’ intention towards adoption of cell-phone for learning. The study showed that perceived ease of use stands to be the strongest predictor of cell-phone use. The model of the study exhibits a good-fit with the data and provides an explanation on student- teachers’ attitude and intention towards cell-phone for learning.

Keywords: cell-phone, adoption, structural equation modeling, technology acceptance model

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Authors: S. E. Mohmad-Saberi, W. Song, N. Oliver, M. Adrian, T.C. Hsu, A. Darbyshire

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Biodegradable polyurethane (PU) has emerged as a potential material to promote repair and regeneration of damaged/diseased tissues in heart valve regeneration due to its excellent biomechanical profile. Understanding the effects of sterilization on their properties is vital since they are more sensitive and more critical of porous structures compared to bulk ones. In this study, the effects of low concentration of hydrogen peroxide (H₂O₂) solution sterilization has been investigated to determine whether the procedure would be efficient and non-destructive to porous three-dimensional (3D) elastomeric nanocomposite, polyhedral oligomeric silsesquioxane-terminated poly (ethylene-diethylene glycol succinate-sebacate) urea-urethane (POSS-EDSS-PU) scaffold. All the samples were tested for sterility following sterilization using phosphate buffer saline (PBS) as control and 5 % v/v H₂O₂ solution. The samples were incubated in tryptic soy broth for the cultivation of microorganisms under agitation at 37˚C for 72 hours. The effects of the 5 % v/v H₂O₂ solution sterilization were evaluated in terms of morphology, chemical and mechanical properties using scanning electron microscopy (SEM), Fourier transform infrared (FTIR) and tensile tester apparatus. Toxicity effects of the 5 % v/v H₂O₂ solution decontamination were studied by in vitro cytotoxicity test, where the cellular responses of human dermal fibroblast (HDF) were examined. A clear, uncontaminated broth using 5 % v/v H₂O₂ solution method indicated efficient sterilization after 3 days, while the non-sterilized control shows clouding broth indicated contamination. The morphology of 3D POSS-EDSS-PU scaffold appeared to have similar morphology after sterilization with 5 % v/v H₂O₂ solution regarding of pore size and surface. FTIR results show that the sterilized samples and non-sterilized control share the same spectra pattern, confirming no significant alterations over the surface chemistry. For the mechanical properties of the H₂O₂ solution-treated scaffolds, the tensile strain was not significantly decreased, however, become significantly stiffer after the sterilization. No cytotoxic effects were observed after the 5 % v/v H₂O₂ solution sterilization as confirmed by cell viability assessed by Alamar Blue assay. The results suggest that low concentration of 5 % v/v hydrogen peroxide solution can be used as an alternative method for sterilizing biodegradable 3D porous scaffold with micro/nano-architecture without structural deformation. This study provides the understanding of the sterilization effects on biomechanical profile and cell proliferation of 3D POSS-EDSS-PU scaffolds.

Keywords: biodegradable, hydrogen peroxide solution, POSS-EDSS-PU, sterilization

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Authors: M. Chavez, H. Juarez, M. Pacio, O. Portillo

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PbS chemical bath heterojunction sollar cells have shown significant improvements in performance. Here we demonstrate a solar cell based on the heterojunction formed between PbS layer and PbS:Bi3+ thin films that are deposited via solution process at 40°C. The device achieve an current density of 4 mA/cm2. The simple and low-cost deposition method of PbS:Bi3+ films is promising for the fabrication.

Keywords: PbS doped, Bismuth, solar cell, thin films

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Authors: Ajayi Olusola Olajide, Alonge Olaide Moses

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Predicting the outcome of soccer matches poses an interesting challenge for which it is realistically impossible to successfully do so for every match. Despite this, there are lots of resources that are being expended on the correct prediction of soccer matches weekly, and all over the world. Soccer Match Result Prediction System Model (SMRPSM) is a system that is proposed whereby the results of matches between two soccer teams are auto-generated, with the added excitement of giving users a chance to test their predictive abilities. Soccer teams from different league football are loaded by the application, with each team’s corresponding manager and other information like team location, team logo and nickname. The user is also allowed to interact with the system by selecting the match to be predicted and viewing of the results of completed matches after registering/logging in.

Keywords: predicting, soccer match, outcome, soccer, matches, result prediction, system, model

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Authors: Tran Hung Tra, Hao Dinh Duong, Masakazu Okazaki

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Copper 1100 and aluminum 1050 plates with a thickness of 5.0 mm are butt-joint using friction stir welding. The tool offset is linearly varied along the welding path. Two welding regimes, using the same linear tool offset but in opposite directions, are applied for fabricating two Cu/Al plates. The material flow is dominated by both tool offset and offset history. The intermetallic compounds layer and interface morphology in each welded plate are formed in a different manner. As a result, the bonding strength and fracture behavior between two welded plates are significantly distinct. The role of interface morphology on fracture behavior is analyzed by the finite element method.

Keywords: Cu/Al dissimilar welding, offset history, interface morphology, intermetallic compounds, strength and fracture

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Authors: Shital Suresh Borse, Vijayalaxmi Kadroli

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E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.

Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN

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Authors: Ross Lee, Pritpal Singh, Andrew Jester

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As the world transitions to a more sustainable energy economy, the deployment of energy storage technologies is expected to increase to develop a more resilient grid system. However, current technologies are associated with various environmental and safety issues throughout their entire lifecycle; therefore, new battery technology is necessary for grid applications to curtail these risks. Biological cells, such as human neurons and electrolytes in the electric eel, can serve as a more sustainable design template for a new bio-inspired (i.e., biomimetic) battery. Within biological cells, an electrochemical gradient across the cell membrane forms the membrane potential, which serves as the driving force for ion transport into/out of the cell, akin to the charging/discharging of a battery cell. This work serves as the first step to developing such a biomimetic battery cell, starting with the fabrication and characterization of ion-selective membranes to facilitate ion transport through the cell. Performance characteristics (e.g., cell voltage, power density, specific energy, roundtrip efficiency) for the cell under investigation are compared to incumbent battery technologies and biological cells to assess the readiness level for this emerging technology. Using a Na⁺-Form Nafion-117 membrane, the cell in this work successfully demonstrated behavior similar to human neurons; these findings will inform how cell components can be re-engineered to enhance device performance.

Keywords: battery, biomimetic, electrolytes, human neurons, ion-selective membranes, membrane potential

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Authors: Cheng-Cao Sun, Shu-Jun Li, Cuili Yang, Yongyong Xi, Liang Wang, Feng Zhang, De-Jia Li

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Hsa-miRNA-326 (miR-326) has recently been discovered having anticancer efficacy in different organs. However, the role of miR-326 on non-small cell lung cancer (NSCLC) is still ambiguous. In this study, we investigated the role of miR-326 on the development of NSCLC. The results indicated that miR-326 was significantly down-regulated in primary tumor tissues and very low levels were found in NSCLC cell lines. Ectopic expression of miR-326 in NSCLC cell lines significantly suppressed cell growth as evidenced by cell viability assay, colony formation assay and BrdU staining, through inhibition of cyclin D1, cyclin D2, CDK4, and up-regulation of p57(Kip2) and p21(Waf1/Cip1). In addition, miR-326 induced apoptosis, as indicated by concomitantly with up-regulation of key apoptosis protein cleaved caspase-3, and down-regulation of anti-apoptosis protein Bcl2. Moreover, miR-326 inhibited cellular migration and invasiveness through inhibition of matrix metalloproteinases (MMP)-7 and MMP-9. Further, oncogene CCND1 was revealed to be a putative target of miR-326, which was inversely correlated with miR-326 expression in NSCLC. Taken together, our results demonstrated that miR-326 played a pivotal role on NSCLC through inhibiting cell proliferation, migration, invasion, and promoting apoptosis by targeting oncogenic CCND1.

Keywords: hsa-miRNA-326 (miR-326), cyclin D1, non-small cell lung cancer (NSCLC), proliferation, apoptosis

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Authors: Pejman Hosseiniun, Rose Shayeghi, Iman Rahbari, Mohamad Reza Kalhor

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CNFET has emerged as an alternative material to silicon for high performance, high stability and low power SRAM design in recent years. SRAM functions as cache memory in computers and many portable devices. In this paper, a new SRAM cell design based on CNFET technology is proposed. The proposed SRAM cell design for CNFET is compared with SRAM cell designs implemented with the conventional CMOS and FinFET in terms of speed, power consumption, stability, and leakage current. The HSPICE simulation and analysis show that the dynamic power consumption of the proposed 8T CNFET SRAM cell’s is reduced about 48% and the SNM is widened up to 56% compared to the conventional CMOS SRAM structure at the expense of 2% leakage power and 3% write delay increase.

Keywords: SRAM cell, CNFET, low power, HSPICE

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Authors: Chonmapat Torasa

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This paper presents the performance of electricity generation and consumption from solar generator installed at Rajabhat Suan Sunandha’s learning center in Samutsongkram. The result from the experiment showed that solar cell began to work and distribute the current into the system when the solar energy intensity was 340 w/m2, starting from 8:00 am to 4:00 pm (duration of 8 hours). The highest intensity read during the experiment was 1,051.64w/m2. The solar power was 38.74kWh/day. The electromotive force from solar cell averagely was 93.6V. However, when connecting solar cell with the battery charge controller system, the voltage was dropped to 69.07V. After evaluating the power distribution ability and electricity load of tested solar cell, the result showed that it could generate power to 11 units of 36-wattfluorescent lamp bulbs, which was altogether 396W. In the meantime, the AC to DC power converter generated 3.55A to the load, and gave 781VA.

Keywords: solar cell, solar-cell power generating system, computer, systems engineering

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Authors: Chang-Hui Shen, Paulina Konarzewska

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Cell homeostasis is regulated by vacuolar activity and it has been shown that lipid composition of the vacuole plays an important role in vacuolar function. The major phosphoinositide species present in the vacuolar membrane include phosphatidylinositol 3,5-biphosphate (PI(3,5)P₂) which is generated from PI(3)P controlled by Fab1p. Deletion of FAB1 gene reduce the synthesis of PI(3,5)P₂ and thus result in enlarged or fragmented vacuoles, with neutral vacuolar pH due to reduced vacuolar H⁺-ATPase activity. These mutants also exhibited poor growth at high extracellular pH and in the presence of CaCl₂. Conversely, VPS34 regulates the synthesis of PI(3)P from phosphatidylinositol (PI), and the lack of Vps34p results in the reduction of vacuolar activity. Although the cellular observations are clear, it is still unknown about the molecular mechanism between the phospholipid biosynthesis pathway and vacuolar activity. Since both VPS34 and FAB1 are important in vacuolar activity, we hypothesize that the molecular mechanism of vacuolar function might be regulated by the transcriptional regulators of phospholipid biosynthesis. In this study, we study the role of the major phospholipid biosynthesis transcription factor, INO2, in the regulation of vacuolar activity. We first performed qRT-PCR to examine the effect of Ino2p on the expression of VPS34 and FAB1. Our results showed that VPS34 was upregulated in the presence of inositol for both WT and ino2Δ cells. However, FAB1 was only upregulated significantly in ino2Δ cells. This indicated that Ino2p might be the negative regulator for FAB1 expression. Next, growth sensitivity experiment showed that WT, vma3Δ, and ino2Δ grew well in growth medium buffered to pH 5.5 containing 10 mM CaCl₂. As cells were switched to growth medium buffered to pH 7 containing CaCl₂ WT, ino2Δ and opi1Δ showed growth reduction, whereas vma3Δ was completely nonviable. As the concentration of CaCl₂ was increased to 60 mM, ino2Δ cells showed moderate growth reduction compared to WT. This result suggests that ino2Δ cells have better vacuolar activity. Microscopic analysis and vacuolar acidification were employed to further elucidate the importance of INO2 in vacuolar homeostasis. Analysis of vacuolar morphology indicated that WT and vma3Δ cells displayed vacuoles that occupied a small area of the cell when grown in media buffered to pH 5.5. Whereas, ino2Δ displayed fragmented vacuoles. On the other hand, all strains grown in media buffered to pH 7, exhibited enlarged vacuoles that occupied most of the cell’s surface. This indicated that the presence of INO2 may play negative effect in vacuolar morphology when cells are grown in media buffered to pH 5.5. Furthermore, vacuolar acidification assay showed that only vma3Δ cells displayed notably less acidic vacuoles as cells were grown in media buffered to pH 5.5 and pH 7. Whereas, ino2Δ cells displayed more acidic pH compared to WT at pH7. Taken together, our results demonstrated the molecular mechanism of the vacuolar activity regulated by the phospholipid biosynthesis transcription factors Ino2p. Ino2p negatively regulates vacuolar activity through the expression of FAB1.

Keywords: vacuole, phospholipid, homeostasis, Ino2p, FAB1

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Authors: Daniel Nieto, Ramiro Couceiro

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Microfluidic chips have demonstrated their significant application potentials in microbiological processing and chemical reactions, with the goal of developing monolithic and compact chip-sized multifunctional systems. Heat generation and thermal control are critical in some of the biochemical processes. The paper presents a laser direct-write technique for rapid prototyping and manufacturing of microheater chips and its applicability for perfusion cell culture outside a cell incubator. The aim of the microheater is to take the role of conventional incubators for cell culture for facilitating microscopic observation or other online monitoring activities during cell culture and provides portability of cell culture operation. Microheaters (5 mm × 5 mm) have been successfully fabricated on soda-lime glass substrates covered with aluminum layer of thickness 120 nm. Experimental results show that the microheaters exhibit good performance in temperature rise and decay characteristics, with localized heating at targeted spatial domains. These microheaters were suitable for a maximum long-term operation temperature of 120ºC and validated for long-time operation at 37ºC. for 24 hours. Results demonstrated that the physiology of the cultured SW480 adenocarcinoma of the colon cell line on the developed microheater chip was consistent with that of an incubator.

Keywords: laser microfabrication, microheater, bioengineering, cell culture

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Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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Authors: Rodrigo Aguiar, Adelino Ferreira

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Road traffic accidents are the leading cause of unnatural death and injuries worldwide, representing a significant problem of road safety. In this context, the use of artificial intelligence with advanced machine learning techniques has gained prominence as a promising approach to predict traffic accidents. This article investigates the application of machine learning algorithms to develop traffic accident frequency prediction models. Models are evaluated based on performance metrics, making it possible to do a comparative analysis with traditional prediction approaches. The results suggest that machine learning can provide a powerful tool for accident prediction, which will contribute to making more informed decisions regarding road safety.

Keywords: machine learning, artificial intelligence, frequency of accidents, road safety

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Authors: Rachid El Aidani, Phuong Nguyen-Tri, Toan Vu-Khanh

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This study intends to show the influence of the hydrolytic degradation on the properties of the e-PTFE/NOMEX® membranes used in fire-protective clothing. The modification of water vapour permeability, morphology and chemical structure was examined by MOCON Permatran, electron microscopy scanning (SEM), and ATR-FTIR, respectively. A decrease in permeability to water vapour of the aged samples was observed following closure of transpiration pores. Analysis of fiber morphology indicates the appearance of defects at the fibers surface with the presence of micro cavities as well as the of fibrils. ATR-FTIR analysis reveals the presence of a new absorption band attributed to carboxylic acid terminal groups generated during the amide bond hydrolysis.

Keywords: hydrolytic ageing, moisture membrane, water vapor permeability, morphology

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Authors: E. Gandomkar, S. Sabbaghi

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In this paper, the effects of variation synthesized methods on morphology and size of silica nanostructure via modifying sol-gel and precipitation method have been investigated. Meanwhile, resulting products have been characterized by particle size analyzer, scanning electron microscopy (SEM), X-ray Diffraction (XRD) and Fourier transform infrared (FT-IR) spectra. As result, the shape of SiO2 with sol-gel and precipitation methods was spherical but with modifying sol-gel method we have been had nanolayer structure.

Keywords: modified sol-gel, precipitation, nanolayer, Na2SiO3, nanoparticle

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Authors: Mayuva Youngsabanant, Suphaphorn Rabiab, Hatairuk Tungkasen, Nongnuch Gumlungpat, Mayuree Pumipaiboon

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The porcine follicular fluid proteins (pFF) of healthy small size ovarian follicles (1-3 mm in diameters) of Large White pig ovaries were collected by sterile technique. They were used for testing the effect on cell viability and characterization of Vero cell lines using MTT assay. Two hundred microliter of round shape Vero cell lines were culture in 96 well plates with DMEM for 24 h. After that, they were attachment to substrate and some changed into fibroblast shape and spread over the surface after culture for 48 h. Then, Vero cell lines were treated with pFF at concentration of 2, 4, 20, 40, 200, 400, 500, and 600 µg proteins/mL for 24 h. Yields of the best results were analyzed by using one-way ANOVA. MTT assay reviewed an increasing in percentage of viability of Vero cell lines indicated that at concentration of 400-600 µg proteins/mL showed higher percentage of viability (115.64 ± 6.95, 106.91 ± 5.27 and 116.73 ± 20.15) than control group. They were significantly different from the control group (p < 0.05) but lower than the positive control group (DMEM with 10% heat treated fetal bovine serum). Cell lines showed normal character in fibroblast elongate shape after treated with pFF except in high concentration of pFF. This result implies that pFF of small size ovarian follicle at concentration of 400-600 µg proteins/mL could be optimized concentration for using as a supplement in Vero cell line culture medium to promote cell viability instead of growth hormone from fetal bovine serum. This merit could be applied in other cell biotechnology researches. Acknowledgements: This work was funded by a grant from Silpakorn University and Faculty of Science, Silpakorn University, Thailand.

Keywords: cell viability, porcine follicular fluid, MTT assay, Vero cell line

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Authors: Sathish Sundar Dhilip Kumar, Nicolette Houreld, Heidi Abrahamse

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Silver nanoparticles (AgNPs) are classified as metal-based nanomaterials and have received considerable attention globally for wound healing and tissue engineering applications. Naturally available materials are a significant source of medicinal products to treat numerous diseases; polysaccharides are among them. Polysaccharides are non-toxic, safe, and inexpensive, and it has good biocompatibility and biodegradability. Most polysaccharides are shown to have a positive effect on wound healing processes, including chitosan and gum tragacanth. The present study evaluated the improvement of cellular wound healing by nanosilver-loaded polysaccharide-based biomaterial (CGT-NS) in WS1 cells. The physicochemical properties of prepared CGT-NS were studied using different characterization techniques, and it exhibited better stability and swelling properties in various pH conditions. Surface morphology was studied using scanning electron microscopy, and it revealed the porous morphology of the synthesized CGT-NS. The synthesized biomaterial displayed acceptable antibacterial properties against Gram-positive and Gram-negative bacterial strains, and it may prevent infection. The biocompatibility of the synthesized CGT-NS biomaterial was studied in WS1 cells, where it may lead to promote increased cell adhesion and proliferation properties. Thus, the CGT-NS biomaterial has good potential as a biomaterial in wound healing applications.

Keywords: biomaterial, wound healing, nano, silver nanoparticles

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Authors: Chih-Chia Lin, Ching-Ying Huang, Cheng-Hong Liu, Wen-Lin Wang

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A complete fuel cell stack comprises several single cells with end plates, bipolar plates, gaskets and membrane electrode assembly (MEA) components. Electrons generated from cells are conducted through bipolar plates. The amount of cells' components increases as the stack voltage increases, complicating the fuel cell assembly process and mass production. Stack assembly error influence cell performance. PEM fuel cell stack importing laser welding technique could eliminate transverse deformation between bipolar plates to promote stress uniformity of cell components as bipolar plates and MEA. Simultaneously, bipolar plates were melted together using laser welding to decrease interface resistance. A series of experiments as through-plan and in-plan resistance measurement test was conducted to observe the laser welding effect. The result showed that the through-plane resistance with laser welding was a drop of 97.5-97.6% when the contact pressure was about 1MPa to 3 MPa, and the in-plane resistance was not significantly different for laser welding.

Keywords: PEM fuel cell, laser welding, through-plan, in-plan, resistance

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Authors: Sindhu S Nair, Atul Thakur, Preeti Thakur, Trukhanov Alex

Abstract:

Perovskite-based absorbing materials that are organic, inorganic, or hybrid have gained interest as an appealing candidate for the development of solar cell devices. Lead-based perovskites are among the most promising materials, but their application is plagued with toxicity and stability concerns. Most of the perovskite solar cell consists of conventional (n-i-p) structure with organic or inorganic charge transport materials. The commercial application of such device is limited due to higher J-V hysteresis and the need for high temperature during fabrication. This numerical analysis primarily directs to investigate the performance of various inorganic lead-free valency ordered double perovskite absorber materials and to develop an inverted perovskite solar cell device structure. Simulation efforts using SCAPS-1D was carried out with various organic and inorganic charge transport materials with absorber layer materials, and their performance has been evaluated for various factors of thickness, absorber thickness, absorber defect density, and interface defect density to achieve the optimized structure.

Keywords: perovskite materials, solar cell, inverted solar cell, inorganic perovskite solar cell materials, cell efficiency

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Authors: Cheng-Cao Sun, Shu-Jun Li, Cuili Yang, Yongyong Xi, Liang Wang, Feng Zhang, De-Jia Li

Abstract:

MicroRNAs (miRNAs) act as key regulators of multiple cancers. Hsa-miR-329 (miR-329) functions as a tumor suppressor in some malignancies. However, its role on lung cancer remains poorly understood. In this study, we investigated the role of miR-329 on the development of lung cancer. The results indicated that miR-329 was decreased in primary lung cancer tissues compared with matched adjacent normal lung tissues and very low levels were found in a non-small cell lung cancer (NSCLC) cell lines. Ectopic expression of miR-329 in lung cancer cell lines substantially repressed cell growth as evidenced by cell viability assay, colony formation assay and BrdU staining, through inhibiting cyclin D1, cyclin D2, and up-regulatiing p57(Kip2) and p21(WAF1/CIP1). In addition, miR-329 promoted NSCLC cell apoptosis, as indicated by up-regulation of key apoptosis gene cleaved caspase-3, and down-regulation of anti-apoptosis gene Bcl2. Moreover, miR-329 inhibited cellular migration and invasiveness through inhibiting matrix metalloproteinases (MMP)-7 and MMP-9. Further, oncogene MET was revealed to be a putative target of miR-329, which was inversely correlated with miR-329 expression. Furthermore, down-regulation of MET by siRNA performed similar effects to over-expression of miR-329. Collectively, our results demonstrated that miR-329 played a pivotal role in lung cancer through inhibiting cell proliferation, migration, invasion, and promoting apoptosis by targeting oncogenic MET.

Keywords: hsa-miRNA-329(miR-329), MET, non-small cell lung cancer (NSCLC), proliferation, apoptosis

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Authors: N. A. Kazemi Sefat, M. M. Mohammadi, J. Hadjati, S. Talebi, M. Ajami, H. Daneshvar

Abstract:

Colorectal cancer metastases result in a significant number of cancer related deaths. Histone deacetylase (HDAC) inhibitors induce growth arrest and apoptosis in a variety of human cancer cells. Sodium butyrate (SB) is a short chain fatty acid, belongs to HDAC inhibitors which is released in the colonic lumen as a consequence of fiber fermentation. In this study, we are about to assess the effect of sodium butyrate on HCT116 human colorectal carcinoma cell line. The viability of cells was measured by microscopic morphologic study and MTT assay. After 48 hours, treatments more than 10 mM lead to cell injury in HCT116 by increasing cell granulation and decreasing cell adhesion (p>0.05). After 72 hours, treatments at 10 mM and more lead to significant cell injury (p<0.05). Our results may suggest that the gene expression which is contributed in cell proliferation and apoptosis has been changed under pressure of HDAC inhibition.

Keywords: colorectal cancer, sodium butyrate, cytotoxicity, MTT

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Authors: Busra Balli, Tuncay Dikici, Mustafa Toparli

Abstract:

Titanium and its alloys have been used extensively over the past 25 years as biomedical materials in orthopedic and dental applications because of their good mechanical properties, corrosion resistance, and biocompatibility. It is known that the surface properties of titanium implants can enhance the cellular response and play an important role in Osseo integration. The rate and quality of Osseo integration in titanium implants are related to their surface properties. The purpose of this investigation was to evaluate the effect of sandblasting and acid etching on surface morphology, roughness, the wettability of titanium. The surface properties will be characterized by scanning electron microscopy and contact angle and roughness measurements. The results show that surface morphology, roughness, and wettability were changed and enhanced by these treatments.

Keywords: dental implant, etching, surface modifications, surface morphology, surface roughness

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Authors: Jingjing Huang, Nengwei Li, Guanghua Wei, Jiabin You, Chao Wang, Junliang Zhang

Abstract:

In this work, molecular dynamics (MD) simulation is applied to analyze the mass transport process in the cathode of proton exchange membrane fuel cell (PEMFC), of which all types of molecules situated in the cathode is considered. a reasonable and effective MD simulation process is provided, and models were built and compared using both Materials Studio and LAMMPS. The mass transport is one of the key issues in the study of proton exchange membrane fuel cells (PEMFCs). In this report, molecular dynamics (MD) simulation is applied to analyze the influence of Nafion ionomer distribution and Pt nano-particle size on mass transport process in the cathode. It is indicated by the diffusion coefficients calculation that a larger quantity of Nafion, as well as a higher equivalent weight (EW) value, will hinder the transport of oxygen. In addition, medium-sized Pt nano-particles (1.5~2nm) are more advantageous in terms of proton transport compared with other particle sizes (0.94~2.55nm) when the center-to-center distance between two Pt nano-particles is around 5 nm. Then mass transport channels are found to be formed between the hydrophobic backbone and the hydrophilic side chains of Nafion ionomer according to the radial distribution function (RDF) curves. And the morphology of these channels affected by the Pt size is believed to influence the transport of hydronium ions and, consequently the performance of PEMFC.

Keywords: cathode catalytic layer, mass transport, molecular dynamics, proton exchange membrane fuel cell

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Authors: Aliaa M. Issa, Mahmoud N. ElRouby, Sahar A. S. Ahmad, Mahmoud M. El-Merzabani

Abstract:

Sider honey is a type of honey produced by bees feeding on the nectar of Sider tree, Ziziphus spina-christi (L) Desf . Honey is an effective agent for preventing, inhibiting and treating the growth of human and animal cancer cell lines in vitro and in vivo. The aim of the present study was to evaluate the impact of different dilutions from crude Sider honey and different duration times of exposure on the growth of six tumor cell lines (human cervical cancer cell line, HeLa; human hepatocellular carcinoma cell line, HepG-2; human larynx carcinoma cell line, Hep-2; brain tumor cell line, U251) as well as one animal cancerous cell line (Ehrlich ascites carcinoma cells line, EAC) and one normal cell line, Homo sapiens, human, (WISH) CCL-25. Different concentrations and treatment durations with Sider honey were tested on the growth of several cancer cell lines types. Histopathological changes in the tumor masses, animal survival, apoptosis and necrosis of the used cancer cell lines (using flow cytometry) were evaluated. Sider honey was administers either to the tumor mass itself by intratumoral injection or via drinking water. One-way ANOVA test was used for the analysis of (the means + standard error) of the optical density obtained from the Elisa reader and flow cytometry. The study revealed that different concentrations of Sider honey affected the growth patterns of all the studied cancer cell lines as well as their histopathological changes, and it depended on the cell line nature and the concentration of honey used. It is obvious that the relative animal survival percentage (bearing Ehrlich ascites carcinoma, EAC cells) was proportionally increased with the increase in the used honey concentrations. The study of apoptosis and necrosis using the flow cytometry technique emphasized the viability results. In conclusion, Sider honey was effective as antitumor agent, in the used concentrations.

Keywords: antitumor, honey, sider, tumor cell lines

Procedia PDF Downloads 482