Search results for: cell morphology prediction

Authors: Emhimed Saffor

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In this paper, the problem of edge detection in digital images is considered. Three methods of edge detection based on mathematical morphology algorithm were applied on two sets (Brain and Chest) CT images. 3x3 filter for first method, 5x5 filter for second method and 7x7 filter for third method under MATLAB programming environment. The results of the above-mentioned methods are subjectively evaluated. The results show these methods are more efficient and satiable for medical images, and they can be used for different other applications.

Keywords: CT images, Matlab, medical images, edge detection

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Authors: Maassoumeh Bemani Naeini

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Studies on interlanguage have long been engaged in describing the phenomenon of variation in SLA. Pursuing the same goal and particularly addressing the role of linguistic features, this study describes the use of Persian morphology in the interlanguage of two adult English-speaking learners of Persian L2. Taking the general approach of a combination of contrastive analysis, error analysis and interlanguage analysis, this study focuses on the identification and prediction of some possible instances of transfer from English L1 to Persian L2 across six elicitation tasks aiming to investigate whether any of contextual features may variably influence the learners’ order of morpheme accuracy in the areas of copula, possessives, articles, demonstratives, plural form, personal pronouns, and genitive cases.  Results describe the existence of task variation in the interlanguage system of Persian L2 learners.

Keywords: English L1, Interlanguage Analysis, Persian L2, SLA variation

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Authors: Anne-Lena Kampen, Øivind Kure

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Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: central machine learning, embedded machine learning, energy consumption, local machine learning, wireless sensor networks, WSN

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Authors: Wen-Hsi Lee, C.G. Kao

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In this study, Cu paste was prepared and printed with narrow line screen printing process on polycrystalline Si solar cell which has already finished the back Al printing and deposition of double anti-reflection coatings (DARCs). Then, two-step firing process was applied to sinter the front electrode and obtain the ohmic contact between front electrode and solar cell. The first step was in air atmosphere. In this process, PbO-based glass frit etched the DARCs and Ag recrystallized at the surface of Si, constructing the preliminary contact. The second step was in reducing atmosphere. In this process, CuO reduced to Cu and sintered. Besides, Ag nanoparticles recrystallized in the glass layer at interface due to the interactions between H2, Ag and PbO-based glass frit and the volatility of Pb, constructing the ohmic contact between electrode and solar cell. By experiment and analysis, reaction mechanism in each stage was surmised, and it was also proven that ohmic contact and good sheet resistance for front electrode could both be obtained by applying newly-invented paste and process.

Keywords: front electrode, solar cell, ohmic contact, screen printing, paste

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Authors: Mansoureh Naderipour, Susan Bastani, Mohammad Fazel Zarandi

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Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach.

Keywords: social network, link prediction, granular computing, type-2 fuzzy sets

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Authors: Sharmi Mukherjee, Anindita Chakraborty

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Cellular irradiation incites complex responses including arrest of cell cycle progression. This article accentuates the effects of radiation on cell cycle status of radiation non-targeted cells. Human Hepatoma HepG2 cells were exposed to increasing doses of γ radiations (1, 2, 4, 6 Gy) and their cell culture media was transferred to non-targeted HepG2 cells cultured in other Petri plates. These radiation non-targeted cells cultured in the ICCM (Irradiated cell conditioned media) were the bystander cells on which cell cycle analysis was performed using flow cytometry. An apparent decrease in the distribution of bystander cells at G0/G1 phase was observed with increased radiation doses upto 4 Gy representing a linear relationship. This was accompanied by a gradual increase in cellular distribution at G2/M phase. Interestingly the number of cells in G2/M phase at 1 and 2 Gy irradiation was not significantly different from each other. However, the percentage of G2 phase cells at 4 and 6 Gy doses were significantly higher than 2 Gy dose indicating the IC50 dose to be between 2 and 4 Gy. Cell cycle arrest is an indirect indicator of genotoxic damage in cells. In this study, bystander stress signals through the cell culture media of irradiated cells disseminated the radiation induced DNA damages in the non-targeted cells which resulted in arrest of the cell cycle progression at G2/M phase checkpoint. This implies that actual radiation biological effects represent a penumbra with effects encompassing a larger area than the actual beam. This article highlights the existence of genotoxic damages as bystander effects of γ rays in human Hepatoma cells by cell cycle analysis and opens up avenues for appraisal of bystander stress communications between tumor cells. Contemplation of underlying signaling mechanisms can be manipulated to maximize damaging effects of radiation with minimum dose and thus has therapeutic applications.

Keywords: bystander effect, cell cycle, genotoxic damage, hepatoma

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Authors: Zeineb Seboui, Samar Dabbabi

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In this paper, we study the performance of Cu₂ZnSnS₄ (CZTS) based solar cell. In our knowledge, it is for the first time that the FTO/ZnO:Co/CZTS structure is simulated using the SILVACO-Atlas 2D simulation. Cu₂ZnSnS₄ (CZTS), ZnO:Co and FTO (SnO₂:F) layers have been deposited on glass substrates by the spray pyrolysis technique. The extracted physical properties, such as thickness and optical parameters of CZTS layer, are considered to create a new input data of CZTS based solar cell. The optimization of CZTS electron affinity and thickness is performed to have the best FTO/ZnO: Co/CZTS efficiency. The use of CZTS absorber layer with 3.99 eV electron affinity and 3.2 µm in thickness leads to the higher efficiency of 16.86 %, which is very important in the development of new technologies and new solar cell devices.

Keywords: CZTS solar cell, characterization, electron affinity, thickness, SILVACO-atlas 2D simulation

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Authors: Gunasekaran Raja, Rajakumar Arul, Kottilingam Kottursamy, Ramkumar Jayaraman, Sathya Pavithra, Swaminathan Venkatraman

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Wireless Interoperability for Microwave Access (WiMAX) utilizes the IEEE 802.1X mechanism for authentication. However, this mechanism incurs considerable delay during handoffs. This delay during handoffs results in service disruption which becomes a severe bottleneck. To overcome this delay, our article proposes a key caching mechanism based on user path prediction. If the user mobility follows that path, the user bypasses the normal IEEE 802.1X mechanism and establishes the necessary authentication keys directly. Through analytical and simulation modeling, we have proved that our mechanism effectively decreases the handoff delay thereby achieving fast authentication.

Keywords: authentication, authorization, and accounting (AAA), handoff, mobile, user path prediction (UPP) and user pattern

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Authors: Alieh Farshbaf

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Introduction: Current anti-retroviral drugs have some restrictions for treatment of HIV-1 infection. The efficacy of retroviral drugs is not same in different infected patients and the virus rebound from latent reservoirs after stopping them. Recently, the engineering of stem cells and gene therapy provide new approaches to eliminate some drug problems by induction of resistance to HIV-1. Literature review: Up to now, AIDS-restriction genes (ARGs) were suitable candidate for gene and cell therapies, such as cc-chemokine receptor-5 (CCR5). In this manner, CCR5 provide effective cure in Berlin and Boston patients by inducing of HIV-1 resistance with allogeneic stem cell transplantation. It is showed that Zinc Finger Nuclease (ZFN) could induce HIV-1 resistance in stem cells of infected patients by homologous recombination or non-end joining mechanism and eliminate virus loading after returning the modified cells. Then, gene modification by HIV restriction factors, as TRIM5, introduced another gene candidate for HIV by interfering in infection process. These gene modifications/editing provided by stem cell futures that improve treatment in refractory disease such as HIV-1. Conclusion: Although stem cell transplantation has some complications, but in compare to retro-viral drugs demonstrated effective cure by elimination of virus loading. On the other hand, gene therapy is cost-effective for an infected patient than retroviral drugs payment in a person life-long. The results of umbilical cord blood stem cell transplantation showed that gene and cell therapy will be applied easier than previous treatment of AIDS with high efficacy.

Keywords: stem cell, AIDS, gene modification, cell engineering

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Authors: Kanda Wongwailikhit

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Copper (I) oxide microparticles with the morphology of cubic and hollow sphere were synthesized with the assistance of a surfactant as the shape controller. Both particles were then subjected to a study of the catalytic activity and the results of shape effects of catalysts on rate of catalytic reaction was observed. The decolorizing reaction of crystal violet and sodium hydroxide was chosen and the decrease of reactant with respect to time was measured using a spectrophotometer. The result revealed that morphology of the crystal had no effect on the catalytic activity for the crystal violet reaction but contributed to total surface area predominantly.

Keywords: copper (I) oxide, catalytic activity, crystal violet

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Authors: M. Maleczek, Leszek Bogdan, Kazimierz Drabczyk, Agnieszka Iwan

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Crystalline silicon (Si) solar cells are the main product in the market among the various photovoltaic technologies concerning such advantages as: material richness, high carrier mobilities, broad spectral absorption range and established technology. However, photovoltaic technology on the stiff substrates are heavier, more fragile and less cost-effective than devices on the flexible substrates to be applied in special applications. The main goal of our work was to incorporate silicon solar cells into various fabric, without any change of the electrical and mechanical parameters of devices. This work is realized for the GEKON project (No. GEKON2/O4/268473/23/2016) sponsored by The National Centre for Research and Development and The National Fund for Environmental Protection and Water Management. In our work, the polyamide or polyester fabrics were used as a flexible substrate in the created devices. Applied fabrics differ in tensile and tear strength. All investigated polyamide fabrics are resistant to weathering and UV, while polyester ones is resistant to ozone, water and ageing. The examined fabrics are tight at 100 cm water per 2 hours. In our work, commercial silicon solar cells with the size 156 × 156 mm were cut into nine parts (called single solar cells) by diamond saw and laser. Gap and edge after cutting of solar cells were checked by transmission electron microscope (TEM) to study morphology and quality of the prepared single solar cells. Modules with the size of 160 × 70 cm (containing about 80 single solar cells) were created and investigated by electrical and mechanical methods. Weight of constructed module is about 1.9 kg. Three types of solar cell architectures such as: -fabric/EVA/Si solar cell/EVA/film for lamination, -backsheet PET/EVA/Si solar cell/EVA/film for lamination, -fabric/EVA/Si solar cell/EVA/tempered glass, were investigated taking into consideration type of fabric and lamination process together with the size of solar cells. In investigated devices EVA, it is ethylene-vinyl acetate, while PET - polyethylene terephthalate. Depend on the lamination process and compatibility of textile with solar cell an efficiency of investigated flexible silicon solar cells was in the range of 9.44-16.64 %. Multi folding and unfolding of flexible module has no impact on its efficiency as was detected by Instron equipment. Power (P) of constructed solar module is 30 W, while voltage about 36 V. Finally, solar panel contains five modules with the polyamide fabric and tempered glass will be produced commercially for different applications (dual use).

Keywords: flexible devices, mechanical properties, silicon solar cells, textiles

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Authors: Tao Chen, ShiHua Liu, JiWei Zhang

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Assembly of the proton exchange membrane fuel cells (PEMFC) has a very important influence on its performance and efficiency. The various components of PEMFC stack are usually locked and fixed by bolts. Locking bolt will cause the deformation of the bipolar plate and the other components, which will affect directly the deformation degree of the integral parts of the PEMFC as well as the performance of PEMFC. This paper focuses on the object of three-cell stack of PEMFC. Finite element simulation is used to investigate the deformation of bipolar plate caused by quantity and layout of bolts, bolt locking pressure, and bolt locking sequence, etc. Finally, we made a conclusion that the optimal combination packaging scheme was adopted to assemble the fuel cell stack. The scheme was in use of 3.8 MPa locking pressure imposed on the fuel cell stack, type Ⅱ of four locking bolts and longitudinal locking method. The scheme was obtained by comparatively analyzing the overall displacement contour of PEMFC stack, absolute displacement curve of bipolar plate along the given three paths in the Z direction and the polarization curve of fuel cell. The research results are helpful for the fuel cell stack assembly.

Keywords: bipolar plate, deformation, finite element simulation, fuel cell, locking bolt

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Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

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In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

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Authors: Tanushree Jaitly, Shailendra Gupta, Leila Taher, Gerold Schuler, Julio Vera

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Genomics-based personalized medicine is a promising approach to fight aggressive tumors based on patient's specific tumor mutation and expression profiles. A remarkable case is, dendritic cell-based immunotherapy, in which tumor epitopes targeting patient's specific mutations are used to design a vaccine that helps in stimulating cytotoxic T cell mediated anticancer immunity. Here we present a computational pipeline for epitope-based personalized cancer vaccines using patient-specific haplotype and cancer mutation profiles. In the workflow proposed, we analyze Whole Exome Sequencing and RNA Sequencing patient data to detect patient-specific mutations and their expression level. Epitopes including the tumor mutations are computationally predicted using patient's haplotype and filtered based on their expression level, binding affinity, and immunogenicity. We calculate binding energy for each filtered major histocompatibility complex (MHC)-peptide complex using docking studies, and use this feature to select good epitope candidates further.

Keywords: cancer immunotherapy, epitope prediction, NGS data, personalized medicine

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Authors: S. Ghosh, L. Ramos, A. N. Kouamé, A.-L. Teillout, H. Remita

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Catalytic materials have attracted continuous attention due to their promising applications in a variety of energy and environmental applications including clean energy, energy conversion and storage, purification and separation, degradation of pollutants and electrochemical reactions etc. With the advanced synthetic technologies, polymer nanostructures and nanocomposites can be directly synthesized through soft template mediated approach using swollen hexagonal mesophases and modulate the size, morphology, and structure of polymer nanostructures. As an alternative to conventional catalytic materials, one-dimensional PDPB polymer nanostructures shows high photocatalytic activity under visible light for the degradation of pollutants. These photocatalysts are very stable with cycling. Transmission electron microscopy (TEM), and AFM-IR characterizations reveal that the morphology and structure of the polymer nanostructures do not change after photocatalysis. These stable and cheap polymer nanofibers and metal polymer nanocomposites are easy to process and can be reused without appreciable loss of activity. The polymer nanocomposites formed via one pot chemical redox reaction with 3.4 nm Pd nanoparticles on poly(diphenylbutadiyne) (PDPB) nanofibers (30 nm). The reduction of Pd (II) ions is accompanied by oxidative polymerization leading to composites materials. Hybrid Pd/PDPB nanocomposites used as electrode materials for the electrocatalytic oxidation of ethanol without using support of proton exchange Nafion membrane. Hence, these conducting polymer nanofibers and nanocomposites offer the perspective of developing a new generation of efficient photocatalysts for environmental protection and in electrocatalysis for fuel cell applications.

Keywords: conducting polymer, swollen hexagonal mesophases, solar photocatalysis, electrocatalysis, water depollution

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Authors: Parcha Sreenivasa Rao, P. Lakshmi

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Diabetes Mellitus is metabolic disorder, characterized by high glucose levels in the blood due to one of the reason i.e., the death of β cells. The lack of β cells leads to the reduced insulin levels. The β cell death generally occurs due to apoptosis induced by the several cytokines. IL-1β, IFN- ϒ and TNF –α cytokines that are generally cause apoptosis to the β cell. The nutrient based apoptosis is generally seen with high glucose and free fatty acids. It is also noted that the β cell death triggered by Fas ligand and its receptor Fas at the surface of the activated CD8+ T- lymphocytes. Reports also reveal that the β cell apoptosis is under control of the transcription factors NF-kB and STAT- 1. The arresting or opposing of the β cell apoptosis can be overcome by the different growth factors like GLP-1, growth hormone, prolactin, VEGF, Dipeptidyl peptidase-4, Vildagliptin, suberoylanilidehydroxamic acid, trichistatin-A, XIAP, Bcl-2, FGF-21. Present investigation explains antiapoptotic property of the β cells derived from the mesenchymal stem cells of umbilical cord.

Keywords: stem cells, umblical cord, diabetes, apoptosis

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Authors: Ga-Young Lee, Hyun-Man Kim

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The modulation of the cell-cell junction is critical in epithelial-mesenchymal transition during tumorigenesis. As RhoA activity is known to be up-regulated to dissociate cell-cell junction by contracting acto-myosin complex in various cancer cells, the present study investigated if RhoA activity was also associated with the disruption of the cell-cell junction of oral cancer cells. We studied SCC-25 cells which are established from oral squamous cell carcinoma if their E-cadherin junction (ECJ) was under control of RhoA. Interestingly, development of ECJ of SCC-25 cells depended on the amount of fibronectin (FN) coated on the culture dishes. Seeded cells promptly aggregated to develop ECJ on the substrates coated with a low amount of FN, whereas they were retarded in the development of ECJ on the substrates coated with a high amount of FN. However, it was an unexpected finding that total RhoA activity was lower in the dissociated cells on the substrates of high FN than in the aggregated cells on the substrates of low FN. Treating the dissociated cells on the substrates of high FN with LPA, a RhoA activator, promoted the development to ECJ. In contrast, treating the aggregated cells on the substrates of low FN with Clostridium botulinum C3, a toxin decreasing RhoA activity, dissociated cells concomitant with the disruption of ECJ. Genetical knockdown of RhoA expression by transfecting RhoA siRNA also down-regulated the development of ECJ in SCC-25 cells. Furthermore, PMA, an activator of protein kinase C (PKC), down-regulated the development of ECJ junction of SCC-25 cells on the substrates coated with low FN. In contrast, GO6976, a PKC inhibitor, up-regulated the development of ECJ of SCC-25 cells with the activation of RhoA on the substrates coated with high FN. In conclusion, in the present study, we demonstrated unexpected results that the activation of RhoA promotes the development of ECJ, whereas the inhibition of RhoA retards the development of ECJ in SCC-25 cells.

Keywords: E-cadherin junction, oral squamous cell carcinoma, PKC, RhoA, SCC-25

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Authors: Catherine Felce, Lior Pachter

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Current methods for building phylogenetic trees from gene expression data consider mean expression levels. With single-cell technologies, we can leverage more information about cell dynamics by considering the entire distribution of gene expression across cells. Using biophysical modeling, we propose a method for constructing phylogenetic trees from scRNA-seq data, building on Felsenstein's method of continuous characters. This method can highlight genes whose level of expression may be unchanged between species, but whose rates of transcription/decay may have evolved over time.

Keywords: phylogenetics, single-cell, biophysical modeling, transcription

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Authors: Venkat Garigapati

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Cell-based therapies are limited due to underlying host immune system activity. Microencapsulation of living cells to overcome this issue has some serious drawbacks, such as limitations of nutrient and oxygen diffusion, which pose a threat to the function and longevity of cells. The conformal coating could overcome the issues which are generally involved in traditional microencapsulation. Some of the theoretical advantages of conformal coating include superior nutrient and oxygen supply to cells, prolonged lifespan, improved drug-secreting cell functionality and an opportunity to load high cell doses in small volumes. Despite several advantages to the conformal coating, there are no suitable methods available to apply to living cells. The ultra-thin conformal coating was achieved utilizing click-reactive methacryloyloxyethyl phosphorylcholine (MPC) polymers, which are capable of specifically reacting one polymer to another at neutral pH in the aqueous isotonic system at the desired temperature suitable for living cells without the need of deleterious initiators. ARPE-19 (Adult Retinal Pigment Epithelial cell line-19) cell-spheroids and rat pancreatic islets were used in the formulation studies. The in vitro studies of coated ARPE-19 cell-spheroids and rat islets indicate that the coat was intact; cells were viable and functioning. The in vitro study results revealed that the conformal coating technology seems promising and in vivo studies are being planned.

Keywords: cells, hydrogel, conformal coating, microencapsulation, insulin

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Authors: Leila Ayat, Afak Meftah

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Amorphous-silicon alloys have great promise as low cost solar cell materials. They have excellent photo-conductivity and high optical absorption to sunlight. Now PIN a-Si:H based solar cells are widely used in power generation modules. However, to improve the performance of these cells further, a better fundamental under-standing of the factors limiting cell performance in the homo junction PIN structure is necessary. In this paper we discuss the sensitivity of light J-V characteristics to various device and material parameters in PIN homo junction solar cells. This work is a numerical simulation of the output parameters of a PIN a-Si:H solar cell under AM1.5 spectrum. These parameters are the short circuit current (Jsc), the open circuit voltage (Voc), the fill factor (FF), the conversion efficiency. The simulation was performed with SCAPS-1D software version 3.3 developed at ELIS in Belgium by Marc Burgelman et al. The obtained results are in agreement with experiment. In addition, the effect of the thickness, doping density, capture cross sections of the gap states and the band microscopic mobilities on the output parameters of the cell are also presented.

Keywords: amorphous silicon p-i-n junctions, thin film, solar cells, sensitivity

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Authors: Kiyoumars Roushangar, Saeid Sadaghian

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Although accurate sediment load prediction is very important in planning, designing, operating and maintenance of water resources structures, the transport mechanism is complex, and the deterministic transport models are based on simplifying assumptions often lead to large prediction errors. In this research, firstly, two intelligent ANN methods, Radial Basis and General Regression Neural Networks, are adopted to model of total sediment load transport into Madani Dam reservoir (north of Iran) using the measured data and then applicability of the sediment transport methods developed by Engelund and Hansen, Ackers and White, Yang, and Toffaleti for predicting of sediment load discharge are evaluated. Based on comparison of the results, it is found that the GRNN model gives better estimates than the sediment rating curve and mentioned classic methods.

Keywords: sediment transport, dam reservoir, RBF, GRNN, prediction

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Authors: Rajapaksha Gedara Prasad Tharanga Jayasooriya, Matharage Gayani Dilshara, Yung Hyun Choi, Gi-Young Kim

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Camptothecin (CPT) is a quinolone alkaloid which inhibits DNA topoisomerase I that induces cytotoxicity in a variety of cancer cell lines. We previously showed that CPT effectively inhibited invasion of prostate cancer cells and also combined treatment with subtoxic doses of CPT and TNF-related apoptosis-inducing ligand (TRAIL) potentially enhanced apoptosis in a caspase-dependent manner in hepatoma cancer cells. Here, we found that treatment with CPT caused an irreversible cell cycle arrest in the G2/M phase. CPT-induced cell cycle arrest was associated with a decrease in protein levels of cell division cycle 25C (Cdc25C) and increased the level of cyclin B and p21. The CPT-induced decrease in Cdc25C was blocked in the presence of proteasome inhibitor MG132, thus reversed the cell cycle arrest. In addition to that treatment of CPT-increased phosphorylation of Cdc25C was the resulted of activation of checkpoint kinase 2 (Chk2), which was associated with phosphorylation of ataxia telangiectasia-mutated. Interestingly CPT induced G2/M phase of the cell cycle arrest is reactive oxygen species (ROS) dependent where ROS inhibitors NAC and GSH reversed the CPT-induced cell cycle arrest. These results further confirm by using transient knockdown of nuclear factor-erythroid 2-related factor 2 (Nrf2) since it regulates the production of ROS. Our data reveal that treatment of siNrf2 increased the ROS level as well as further increased the CPT induce G2/M phase cell cycle arrest. Our data also indicate CPT-enhanced cell cycle arrest through the extracellular signal-regulated kinase (ERK) and the c-Jun N-terminal kinase (JNK) pathway. Inhibitors of ERK and JNK more decreased the Cdc25C expression and protein expression of p21 and cyclin B. These findings indicate that Chk2-mediated phosphorylation of Cdc25C plays a major role in G2/M arrest by CPT.

Keywords: camptothecin, cell cycle, checkpoint kinase 2, nuclear factor-erythroid 2-related factor 2, reactive oxygen species

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Authors: Sharon Yunger, Liat Altman, Yuval Garini, Yaron Shav-Tal

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Understanding the dynamics of transcription in living cells has improved since the development of quantitative fluorescence-based imaging techniques. We established a method for following transcription from a single copy gene in living cells. A gene tagged with MS2 repeats, used for mRNA tagging, in its 3' UTR was integrated into a single genomic locus. The actively transcribing gene was detected and analyzed by fluorescence in situ hybridization (FISH) and live-cell imaging. Several cell clones were created that differed in the promoter regulating the gene. Thus, comparative analysis could be obtained without the risk of different position effects at each integration site. Cells in S/G2 phases could be detected exhibiting two adjacent transcription sites on sister chromatids. A sharp reduction in the transcription levels was observed as cells progressed along the cell cycle. We hypothesized that a change in chromatin structure acts as a general mechanism during the cell cycle leading to down-regulation in the activity of some genes. We addressed this question by treating the cells with chromatin decondensing agents. Quantifying and imaging the treated cells suggests that chromatin structure plays a role both in regulating transcriptional levels along the cell cycle, as well as in limiting an active gene from reaching its maximum transcription potential at any given time. These results contribute to understanding the role of chromatin as a regulator of gene expression.

Keywords: cell cycle, living cells, nucleus, transcription

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Authors: Alexandre Barbosa de Almeida, Telma Woerle de Lima Soares

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Protein structure prediction is a challenging task in the bioinformatics field. The biological function of all proteins majorly relies on the shape of their three-dimensional conformational structure, but less than 1% of all known proteins in the world have their structure solved. This work proposes a deep learning model to address this problem, attempting to predict some aspects of the protein conformations. Throughout a process of multiobjective dominance, a recurrent neural network was trained to abstract the particular bias of each individual multiobjective algorithm, generating a heuristic that could be useful to predict some of the relevant aspects of the three-dimensional conformation process formation, known as protein folding.

Keywords: Ab initio heuristic modeling, multiobjective optimization, protein structure prediction, recurrent neural network

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Authors: Christelle E. Chua, Alicia L. Ho

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The development of a panel of differential gene expression signatures has been of interest in the field of biomarker discovery for radiation exposure. In the absence of the availability of exposed human subjects, lymphocyte cell lines have often been used as a surrogate to human whole blood, when performing ex vivo irradiation studies. The extent of variation between different lymphocyte cell lines is currently unclear, especially with regard to the expression of extracellular miRNA. This study compares the expression profile of extracellular miRNA isolated from different lymphocyte cell lines. It also compares the profile of miRNA obtained when different exosome isolation kits are used. Lymphocyte cell lines were created using lymphocytes isolated from healthy adult males of similar racial descent (Chinese American and Chinese Singaporean) and immortalised with Epstein-Barr virus. The cell lines were cultured in exosome-free cell culture media for 72h and the cell culture supernatant was removed for exosome isolation. Two exosome isolation kits were used. Total exosome isolation reagent (TEIR, ThermoFisher) is a polyethylene glycol (PEG)-based exosome precipitation kit, while ExoSpin (ES, Cell Guidance Systems) is a PEG-based exosome precipitation kit that includes an additional size exclusion chromatography step. miRNA from the isolated exosomes were isolated using miRNEASY minikit (Qiagen) and analysed using nCounter miRNA assay (Nanostring). Principal component analysis (PCA) results suggested that the overall extracellular miRNA expression profile differed between the lymphocyte cell line originating from the Chinese American donor and the cell line originating from the Chinese Singaporean donor. As the gender, age and racial origins of both donors are similar, this may suggest that there are other genetic or epigenetic differences that account for the variation in extracellular miRNA gene expression in lymphocyte cell lines. However, statistical analysis showed that only 3 miRNA genes had a fold difference > 2 at p < 0.05, suggesting that the differences may not be of that great a significance as to impact overall conclusions drawn from different cell lines. Subsequent analysis using cell lines from other donors will give further insight into the reproducibility of results when difference cell lines are used. PCA results also suggested that the method of exosome isolation impacted the expression profile. 107 miRNA had a fold difference > 2 at p < 0.05. This suggests that the inclusion of an additional size exclusion chromatography step altered the subset of the extracellular vesicles that were isolated. In conclusion, these results suggest that extracellular miRNA can be isolated and analysed from exosomes derived from lymphocyte cell lines. However, care must be taken in the choice of cell line and method of exosome isolation used.

Keywords: biomarker, extracellular miRNA, isolation methods, lymphocyte cell line

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Authors: Danladi Ali, Abdullahi Mukaila

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In this work, GSM signal strength (power) was monitored in an indoor environment. Samples of the GSM signal strength was measured on mobile equipment (ME). One-dimensional multilevel wavelet is used to predict the fading phenomenon of the GSM signal measured and neural network clustering to determine the average power received in the study area. The wavelet prediction revealed that the GSM signal is attenuated due to the fast fading phenomenon which fades about 7 times faster than the radio wavelength while the neural network clustering determined that -75dBm appeared more frequently followed by -85dBm. The work revealed that significant part of the signal measured is dominated by weak signal and the signal followed more of Rayleigh than Gaussian distribution. This confirmed the wavelet prediction.

Keywords: decomposition, clustering, propagation, model, wavelet, signal strength and spectral efficiency

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Authors: Ciro Cursio, Giulia Cursio, Pio Luigi Cursio, Luigi Cursio

Abstract:

Communication between practitioner and patient is of the utmost importance in aesthetic medicine: as of today, images of previous treatments are the most common tool used by doctors to describe and anticipate future results for their patients. However, using photos of other people often reduces the engagement of the prospective patient and is further limited by the number and quality of pictures available to the practitioner. Pre-existing work solves this issue in two ways: 3D scanning of the area with manual editing of the 3D model by the doctor or automatic prediction of the treatment by warping the image with hand-written parameters. The first approach requires the manual intervention of the doctor, while the second approach always generates results that aren’t always realistic. Thus, in one case, there is significant manual work required by the doctor, and in the other case, the prediction looks artificial. We propose an AI-based algorithm that autonomously generates a realistic prediction of treatment results. For the purpose of this study, we focus on hyaluronic acid treatments in the facial area. Our approach takes into account the individual characteristics of each face, and furthermore, the prediction system allows the patient to decide which area of the face she wants to modify. We show that the predictions generated by our system are realistic: first, the quality of the generated images is on par with real images; second, the prediction matches the actual results obtained after the treatment is completed. In conclusion, the proposed approach provides a valid tool for doctors to show patients what they will look like before deciding on the treatment.

Keywords: prediction, hyaluronic acid, treatment, artificial intelligence

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Authors: Etienne Alain Feukeu, L. W. Snyman

Abstract:

Water scarcity is becoming a real issue nowadays. Most countries in the world are facing it in their own way based on their own geographical coordinate and condition. Many countries are facing a challenge of a growing water demand as a result of not only an increased population, economic growth, but also as a pressure of the population dynamic and urbanization. In view to mitigate some of this related problem, an accurate method of water estimation and future prediction, forecast is essential to guarantee not only the sufficient quantity, but also a good water distribution and management system. Beside the fact that several works have been undertaken to address this concern, there is still a considerable disparity between different methods and standard used for water prediction and estimation. Hence this work contrast and compare two well-defined and established methods from two countries (USA and South Africa) to demonstrate the inconsistency when different method and standards are used interchangeably.

Keywords: water scarcity, water estimation, water prediction, water forecast.

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Authors: Yessica Nataliani, Miin-Shen Yang

Abstract:

Cell formation (CF) is an important step in group technology. It is used in designing cellular manufacturing systems using similarities between parts in relation to machines so that it can identify part families and machine groups. There are many CF methods in the literature, but there is less spectral clustering used in CF. In this paper, we propose a spectral clustering algorithm for machine-part CF. Some experimental examples are used to illustrate its efficiency. Overall, the spectral clustering algorithm can be used in CF with a wide variety of machine/part matrices.

Keywords: group technology, cell formation, spectral clustering, grouping efficiency

Procedia PDF Downloads 405

Authors: Hend Mesbah, Yehia Youssef, Ibrahim Hassan, Shaaban Nosier, Ahmed El-Shazly, Ahmed Helal

Abstract:

The problem of drinking water shortage is becoming more crucial nowadays as a result of the increased demand due to the population growth and the rise in the standard living. In recent years, desalination using electrodialysis powered by solar energy (PV-ED) is being widely used to help provide treated water and reduce the scarcity in water supply. In the present study, a water desalination laboratory scale ED cell with a fixed bed circulation system was designed, developed, and tested. The effect of three parameters (namely, cell voltage , flowrate, and salt concentration) on the removal percentage of salt ions was studied. The cell voltage was adjusted at 3 , 4 and 6 V. A flow rate of 5, 10, and 20 ml/s and an initial salt concentration of 2000, 5000, and 7000 ppm were investigated. The maximum salt percentage removal obtained was 52.5% at the lowest initial concentration (2000 ppm) and at the highest cell voltage (6 V). There was no significant effect of the flow rate on the removal percentage. A model of PV module has also been developed to calculate the dimensions of a solar cell based on the amount of energy consumed and it was calculated from the Overall ED cell voltage.

Keywords: desalination, electrodialysis, solar desalination, photovoltaic electrodialysis

Procedia PDF Downloads 146