Search results for: artificial cell

Authors: Yudhajit Datta

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Will is a phenomenon that has puzzled humanity for a long time. It is a belief that Will Power of an individual affects the success achieved by an individual in life. It is thought that a person endowed with great will power can overcome even the most crippling setbacks of life while a person with a weak will cannot make the most of life even the greatest assets. Behavioral aspects of the human experience such as will are rarely subjected to quantitative study owing to the numerous uncontrollable parameters involved. This work is an attempt to subject the phenomena of will to the test of an artificial neural network. The claim being tested is that will power of an individual largely determines success achieved in life. In the study, an attempt is made to incorporate the behavioral phenomenon of will into a computational model using data pertaining to the success of individuals obtained from an experiment. A neural network is to be trained using data based upon part of the model, and subsequently used to make predictions regarding will corresponding to data points of success. If the prediction is in agreement with the model values, the model is to be retained as a candidate. Ultimately, the best-fit model from among the many different candidates is to be selected, and used for studying the correlation between success and will.

Keywords: will power, will, success, apathy factor, random factor, characteristic function, life story

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Authors: Seyedeh Nasim Mirbahari, Taha Azad, Mehdi Totonchi

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Oncolytic viruses, which only replicate in tumor cells, are being extensively studied for their use in cancer therapy. A particular virus known as the vaccinia virus, a member of the poxvirus family, has demonstrated oncolytic abilities glioma. Treating Glioma with traditional methods such as chemotherapy and radiotherapy is quite challenging. Even though oncolytic viruses have shown immense potential in cancer treatment, their effectiveness in glioblastoma treatment is still low. Therefore, there is a need to improve and optimize immunotherapies for better results. In this study, we have designed oncoVV-TT, which can more effectively target tumor cells while minimizing replication in normal cells by replacing the thymidine kinase gene with a luc-p2a-GFP gene expression cassette. Human glioblastoma cell line U251 MG, rat glioblastoma cell line C6, and non-tumor cell line HFF were plated at 105 cells in a 12-well plates in 2 mL of DMEM-F2 medium with 10% FBS added to each well. Then incubated at 37°C. After 16 hours, the cells were treated with oncoVV-TT at an MOI of 0.01, 0.1 and left in the incubator for a further 24, 48, 72 and 96 hours. Viral replication assay, fluorescence imaging and viability tests, including trypan blue and crystal violet, were conducted to evaluate the cytotoxic effect of oncoVV-TT. The finding shows that oncoVV-TT had significantly higher cytotoxic activity and proliferation rates in tumor cells in a dose and time-dependent manner, with the strongest effect observed in U251 MG. To conclude, oncoVV-TT has the potential to be a promising oncolytic virus for cancer treatment, with a more cytotoxic effect in human glioblastoma cells versus rat glioma cells. To assess the effectiveness of vaccinia virus-mediated viral therapy, we have tested U251mg and C6 tumor cell lines taken from human and rat gliomas, respectively. The study evaluated oncoVV-TT's ability to replicate and lyse cells and analyzed the survival rates of the tested cell lines when treated with different doses of oncoVV-TT. Additionally, we compared the sensitivity of human and mouse glioma cell lines to the oncolytic vaccinia virus. All experiments regarding viruses were conducted under biosafety level 2. We engineered a Vaccinia-based oncolytic virus called oncoVV-TT to replicate specifically in tumor cells. To propagate the oncoVV-TT virus, HeLa cells (5 × 104/well) were plated in 24-well plates and incubated overnight to attach to the bottom of the wells. Subsequently, 10 MOI virus was added. After 48 h, cells were harvested by scraping, and viruses were collected by 3 sequential freezing and thawing cycles followed by removal of cell debris by centrifugation (1500 rpm, 5 min). The supernatant was stored at −80 ◦C for the following experiments. To measure the replication of the virus in Hela, cells (5 × 104/well) were plated in 24-well plates and incubated overnight to attach to the bottom of the wells. Subsequently, 5 MOI virus or equal dilution of PBS was added. At the treatment time of 0 h, 24 h, 48 h, 72 h and 96 h, the viral titers were determined under the fluorescence microscope (BZ-X700; Keyence, Osaka, Japan). Fluorescence intensity was quantified using the imagej software according to the manufacturer’s protocol. For the isolation of single-virus clones, HeLa cells seeded in six-well plates (5×105 cells/well). After 24 h (100% confluent), the cells were infected with a 10-fold dilution series of TianTan green fluorescent protein (GFP)virus and incubated for 4 h. To examine the cytotoxic effect of oncoVV-TT virus ofn U251mg and C6 cell, trypan blue and crystal violet assay was used.

Keywords: oncolytic virus, immune therapy, glioma, vaccinia virus

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Authors: Valeria Arcucci, Musarat Ishaq, Steven A. Stacker, Greg J. Goodall, Marc G. Achen

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Metastasis is the lethal aspect of cancer for most patients. Remodelling of lymphatic vessels associated with a tumour is a key initial step in metastasis because it facilitates the entry of cancer cells into the lymphatic vasculature and their spread to lymph nodes and distant organs. Although it is clear that vascular endothelial growth factors (VEGFs), such as VEGF-C and VEGF-D, are key drivers of lymphatic remodelling, the means by which many signaling pathways in endothelial cells are coordinately regulated to drive growth and remodelling of lymphatics in cancer is not understood. We seek to understand the broader molecular mechanisms that control cancer metastasis, and are focusing on microRNAs, which coordinately regulate signaling pathways involved in complex biological responses in health and disease. Here, using small RNA sequencing, we found that a specific microRNA, miR-132, is upregulated in expression in lymphatic endothelial cells (LECs) in response to the lymphangiogenic growth factors. Interestingly, ectopic expression of miR-132 in LECs in vitro stimulated proliferation and tube formation of these cells. Moreover, miR-132 is expressed in lymphatic vessels of a subset of human breast tumours which were previously found to express high levels of VEGF-D by immunohistochemical analysis on tumour tissue microarrays. In order to dissect the complexity of regulation by miR-132 in lymphatic biology, we performed Argonaute HITS-CLIP, which led us to identify the miR-132-mRNA interactome in LECs. We found that this microRNA in LECs is involved in the control of many different pathways mainly involved in cell proliferation and regulation of the extracellular matrix and cell-cell junctions. We are now exploring the functional significance of miR-132 targets in the biology of LECs using biochemical techniques, functional in vitro cell assays and in vivo lymphangiogenesis assays. This project will ultimately define the molecular regulation of lymphatic remodelling by miR-132, and thereby identify potential therapeutic targets for drugs designed to restrict the growth and remodelling of tumour lymphatics resulting in metastatic spread.

Keywords: argonaute HITS-CLIP, cancer, lymphatic remodelling, miR-132, VEGF

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Authors: Amit Verma, Simranjeet Kaur, Sandeep Kaur

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Test Case Prioritization (TCP) has gained wide spread acceptance as it often results in good quality software free from defects. Due to the increase in rate of faults in software traditional techniques for prioritization results in increased cost and time. Main challenge in TCP is difficulty in manually validate the priorities of different test cases due to large size of test suites and no more emphasis are made to make the TCP process automate. The objective of this paper is to detect the priorities of different test cases using an artificial neural network which helps to predict the correct priorities with the help of back propagation algorithm. In our proposed work one such method is implemented in which priorities are assigned to different test cases based on their frequency. After assigning the priorities ANN predicts whether correct priority is assigned to every test case or not otherwise it generates the interrupt when wrong priority is assigned. In order to classify the different priority test cases classifiers are used. Proposed algorithm is very effective as it reduces the complexity with robust efficiency and makes the process automated to prioritize the test cases.

Keywords: test case prioritization, classification, artificial neural networks, TF-IDF

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Authors: Hyuk Sang Yoo, Young Ju Son, Wei Mao, Myung Gu Kang, Sol Lee

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Biomedical applications of electrospun nanofibrous meshes have been received tremendous attentions because of their unique structures and versatilities as biomaterials. Incorporation of growth factors in fibrous meshes can be performed by surface-modification and encapsulation. Those growth factors stimulate differentiation and proliferation of specific types of cells and thus lead tissue regenerations of specific cell types. Topographical cues of electrospun nanofibrous meshes also increase differentiation of specific cell types according to alignments of fibrous structures. Wound healing treatments of diabetic ulcers were performed using nanofibrous meshes encapsulating multiple growth factors. Aligned nanofibrous meshes and those with random configuration were compared for differentiating mesenchymal stem cells into neuronal cells. Thus, nanofibrous meshes can be applied to drug delivery carriers and matrix for promoting cellular proliferation.

Keywords: nanofiber, tissue, mesh, drug

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Fitri Ayu, Nadia, Tanti, Putri, Fatkhan, Pasid Harlisa, Suparmi

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Acne is a skin abnormal conditions experienced by many teens, this is caused by various factors such as the climate is hot, humid and excessive sun exposure can aggravate acne because it will lead to excess oil production. Flavonoids form complex compounds against extracellular proteins that disrupt the integrity of bacterial cell membrane in a way denature bacterial cell proteins and bacterial cell membrane damage. This study aimed to test the antibacterial activity of corn silk extract with a concentration of 10 %, 20 %, 30 %, 40 %, 50 %, 60 %, 70 %, 80 %, 90 % and 100 % in vitro by measuring the inhibition of the growth of bacteria Propionibacterium acne, Staphylococcus aureus and Staphylococcus epidermis then compared with the standard antibiotic clindamycin. Extracts tested by Disk Diffusion Method, in which the blank disc soaked with their respective corn silk extract concentration for 15-30 minutes and then the medium of bacteria that have been planted with Propionibacterium acne, Staphylococcus aureus and Staphylococcus epidermis in the given disk that already contains extracts with various concentration. Incubated for 24 hours and then measured the growth inhibition zone Propionibacterium acne, Staphylococcus aureus and Staphylococcus epidermidis. Corn silk contains flavonoids, is shown by the test of flavonoids in corn silk extract by using a tube heating and without heating. Flavonoid in corn silk potentially as anti acne by inhibiting the growth of bacteria that cause acne. Corn silk extract concentration which has the highest antibacterial activity is then performed in a cream formulation and evaluation test of physical and chemical properties of the resulting cream preparation.

Keywords: antibacterial, flavonoid, corn silk, acne

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Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

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Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: neural network, motion detection, signature detection, convolutional neural network

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Authors: Yakubu Bala Mohammed, Nadire Chavus, Mohammed Bulama

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Generative Pre-trained Transformer (ChatGPT) represents an artificial intelligence (AI) tool capable of swiftly generating comprehensive responses to prompts and follow-up inquiries. This emerging AI tool was introduced in November 2022 by OpenAI firm, an American AI research laboratory, utilizing substantial language models. This present study aims to delve into the potential future consequences of ChatGPT usage in education using AI-based algorithms. The paper will bring forth the likely potential risks of ChatGBT utilization, such as academic integrity concerns, unfair learning assessments, excessive reliance on AI, and dissemination of inaccurate information using four machine learning algorithms: eXtreme-Gradient Boosting (XGBoost), Support vector machine (SVM), Emotional artificial neural network (EANN), and Random forest (RF) would be used to analyze the study collected data due to their robustness. Finally, the findings of the study will assist education stakeholders in understanding the future implications of ChatGPT usage in education and propose solutions and directions for upcoming studies.

Keywords: machine learning, ChatGPT, education, learning, implications

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Authors: Hani Belhadj, Daoud Harzallah, Seddik Khennouf, Saliha Dahamna, Mouloud Ghadbane

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In this study, Lactobacillus strains isolated from pollen were identified by means of phenotypic and genotypic methods, At pH 2, most strains proved to be acid resistants, with losses in cell viability ranging from 0.77 to 4.04 Log orders. In addition, at pH 3 all strains could grew and resist the acidic conditions, with losses in cell viability ranging from 0.40 to 3.61 Log orders. It seems that, 0.3% and 0.5% of bile salts does not affect greatly the survival of most strains, excluding Lactobacillus sp. BH1398. Survival ranged from 81.0±3.5 to 93.5±3.9%. In contrast, in the presence of 1.0% bile salts, survival of five strains was decreased by more than 50%. Lactobacillus fermentum BH1509 was considered the most tolerant strain (77.5% for 1% bile) followed by Lactobacillus plantarum BH1541 (59.9% for 1% bile). Furthermore, all strains were resistant to colistine, clindamycine, chloramphenicol, and ciprofloxacine, but most of the strains were susceptible to Peniciline, Oxacillin, Oxytetracyclin, and Amoxicillin. Functionally interesting Lactobacillus isolates may be used in the future as probiotic cultures for manufacturing fermented foods and as bioactive delivery systems.

Keywords: probiotics, lactobacillus, pollen, bile, acid tolerance

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Authors: Strahinja Kovačević, Jelena Vladić, Senka Vidović, Zoran Zeković, Lidija Jevrić, Sanja Podunavac Kuzmanović

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Supercritical extracts of highly valuated medicinal plant Satureja montana were prepared by application of supercritical carbon dioxide extraction in the carbon dioxide pressure range from 125 to 350 bar and temperature range from 40 to 60°C. Using GC/MS method of analysis chemical profiles (aromatic constituents) of S. montana extracts were obtained. Self-training artificial neural networks were applied to predict the retention time of the analyzed terpenes in GC/MS system. The best ANN model obtained was multilayer perceptron (MLP 11-11-1). Hidden activation was tanh and output activation was identity with Broyden–Fletcher–Goldfarb–Shanno training algorithm. Correlation measures of the obtained network were the following: R(training) = 0.9975, R(test) = 0.9971 and R(validation) = 0.9999. The comparison of the experimental and predicted retention times of the analyzed compounds showed very high correlation (R = 0.9913) and significant predictive power of the established neural network.

Keywords: ANN regression, GC/MS, Satureja montana, terpenes

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Authors: Sujatha Edla

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Introduction: New compounds and possible uses for the bioactive substances produced by freshwater cyanobacteria are constantly being discovered through research. Certain molecules are hazardous to the environment and human health, but others have potential applications in industry, biotechnology, and pharmaceuticals. These discoveries advance our knowledge of the varied functions these microbes perform in different ecosystems. Cyanobacterial silver nanoparticles (AgNPs) have special qualities and possible therapeutic advantages, which make them very promising for a range of medicinal uses. Aim: In our study; the attention was focused on the analysis and characterization of bioactive compounds extracted from freshwater cyanobacteria Planktothricoides raciorskii and its comparative study on Cyanobacteria-mediated silver nanoparticles synthesized by cell-free extract of Planktothricoides raciorskii. Material and Methods: A variety of bioactive secondary metabolites have been extracted, purified, and identified from cyanobacterial species using column chromatography, FTIR, and GC-MS/MS chromatography techniques and evaluated for antibacterial and cytotoxic studies, where the Cyanobacterial silver nanoparticles (CSNPs) were characterized by UV-Vis spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), and Fourier transform infrared (FTIR) analysis and were further tested for antibacterial and cytotoxic efficiency. Results: The synthesis of CSNPs was confirmed through visible color change and shift of peaks at 430–445 nm by UV-Vis spectroscopy. The size of CSNPs was between 22 and 34 nm and oval-shaped which were confirmed by SEM and TEM analyses. The FTIR spectra showed a new peak at the range of 3,400–3,460 cm−1 compared to the control, confirming the reduction of silver nitrate. The antibacterial activity of both crude bioactive compound extract and CSNPs showed remarkable activity with Zone of inhibition against E. coli with 9.5mm and 10.2mm, 13mm and 14.5mm against S. paratyphi, 9.2mm and 9.8mm zone of inhibition against K. pneumonia by both crude extract and CSNPs, respectively. The cytotoxicity as evaluated by extracts of Planktothricoides raciorskii against MCF7-Human Breast Adenocarcinoma cell line and HepG2- Human Hepatocellular Carcinoma cell line employing MTT assay gave IC50 value of 47.18ug/ml, 110.81ug/ml against MCF7cell line and HepG2 cell line, respectively. The cytotoxic evaluation of Planktothricoides raciorskii CSNPs against the MCF7cell line was 43.37 ug/ml and 20.88 ug/ml against the HepG2 cell line. Our ongoing research in this field aims to uncover the full therapeutic potential of cyanobacterial silver nanoparticles and address any associated challenges.

Keywords: cyanobacteria, silvernanoparticles, pharmaceuticals, bioactive compounds, cytotoxic

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Authors: Yu-Lin Shen, Ming-Kuen Chang

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In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electro Magnetic Acoustic Transducer Testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length.. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, NDT, artificial defect, ultrasonic testing

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Authors: Akhila Potluru

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Worldwide, more than 250 bodies of water are transboundary, meaning they cross the political boundaries of multiple countries. This creates a system of hydrological, economic, and social interdependence between communities reliant on these water sources. Transboundary water conflicts can occur as a result of this intense interdependence. Many factors contribute to the sparking of transboundary water conflicts, ranging from natural hydrological factors to hydro-political interactions. Previous attempts to predict transboundary water conflicts by analysing changes or trends in the contributing factors have typically failed because patterns in the data are hard to identify. However, there is potential for artificial intelligence and machine learning to fill this gap and identify future ‘hotspots’ up to a year in advance by identifying patterns in data where humans can’t. This research determines the extent to which AI can be used to predict and prevent transboundary water conflicts. This is done via a critical literature review of previous case studies and datasets where AI was deployed to predict water conflict. This research not only delivered a more nuanced understanding of previously undervalued factors that contribute toward transboundary water conflicts (in particular, culture and disinformation) but also by detecting conflict early, governance bodies can engage in processes to de-escalate conflict by providing pre-emptive solutions. Looking forward, this gives rise to significant policy implications and water-sharing agreements, which may be able to prevent water conflicts from developing into wide-scale disasters. Additionally, AI can be used to gain a fuller picture of water-based conflicts in areas where security concerns mean it is not possible to have staff on the ground. Therefore, AI enhances not only the depth of our knowledge about transboundary water conflicts but also the breadth of our knowledge. With demand for water constantly growing, competition between countries over shared water will increasingly lead to water conflict. There has never been a more significant time for us to be able to accurately predict and take precautions to prevent global water conflicts.

Keywords: artificial intelligence, machine learning, transboundary water conflict, water management

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Authors: Cagla Gul Guldiken, Levent Akyalcin, Hasan Ferdi Gercel

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Fuel cells are electrochemical devices which convert the chemical energy of hydrogen into the electricity. Among the types of fuel cells, polymer electrolyte membrane fuel cells (PEMFCs) are attracting considerable attention as non-polluting power generators with high energy conversion efficiencies in mobile applications. Polymer electrolyte membrane (PEM) is one of the essential components of PEMFCs. Perfluorosulfonic acid based membranes known as Nafion® is widely used as PEMs. Nafion® membranes water dependent proton conductivity which limits the operating temperature below 100ᵒC. At higher temperatures, proton conductivity and mechanical stability of these membranes decrease because of dehydration. Polybenzimidazole (PBI), which has good anhydrous proton conductivity after doped with acids, as well as excellent thermal stability, shows great potential in the application of high temperature PEMFCs. In the present study, PBI polymers were synthesized by solution polycondensation at 190 and 210ᵒC. The synthesized polymers were characterized by FTIR, 1H NMR, and TGA. Phosphoric acid doped PBI membranes were prepared and tested in a PEMFC. The influences of reaction temperature on structural properties of synthesized polymers were investigated. Mechanical properties, acid-doping level, proton conductivity, and fuel cell performances of prepared phosphoric acid doped PBI membranes were evaluated. The maximum power density was found as 32.5 mW/cm² at 120ᵒC.

Keywords: fuel cell, high temperature polymer electrolyte membrane, polybenzimidazole, proton exchange membrane fuel cell

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Authors: Razvan Mercut, Mihaela Ionescu, Vlad Parvanescu, Razvan Ghita, Tudor-Gabriel Caragea, Cristina Simionescu, Marius-Eugen Ciurea

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Introduction: Over the past years, the incidence of non-melanoma skin cancer (NMSC) has continuously increased, being one of the most commonly diagnosed carcinomasofthe cephalic extremity. NMSC regroups basal cell carcinoma (BCC), squamous cell carcinoma (SCC), Merkel cell carcinoma, cutaneous lymphoma, and sarcoma. The most common forms are BCC and SCC, both still implying a significant level of morbidity due to local invasion (especially BCC), even if the overall death rates are declining. The objective of our study was the evaluation of clinical and histological aspects of NMSC for a group of patients with BCC and SCC, from Craiova, a south-western major city in Romania. Materialand method: Our study lot comprised 65 patients, with an almost equal distribution of sexes, and ages between 23-91 years old (mean value±standard deviation62.61±16.67), all treated within the Clinic of Plastic Surgery and Reconstructive Microsurgery, Clinical Emergency County Hospital Craiova, Romania, between 2019-2020. In order to determine the main morphological characteristics of both studied cancers, we used paraffin embedding techniques, with various staining methods:hematoxylin-eosin, Masson's trichrome stain with aniline blue, and Periodic acid-schiffAlcian Blue. The statistical study was completed using Microsoft Excel (Microsoft Corp., Redmond, WA, USA), with XLSTAT (Addinsoft SARL, Paris, France). Results: The overall results of our study indicate that BCC accounts for 67.69% of all NMSC forms; SCC covers 27.69%, while 4.62% are representedby other forms. The most frequent site is the nose for BCC (27.69%, 18 patients), being followed by preauricular regions, forehead, and periorbital areas. For patients with SCC, tumors were mainly located at lips level (66.67%, 12 patients). The analysis of NMSC histological forms indicated that nodular BCC is predominant (45.45%, 20 patients), as well as ulcero-vegetant SCC (38.89%, 7 patients). We have not identified any topographic characteristics or NMSC forms significantly related to age or sex. Conclusions: The most frequent NMSC form identified for our study lot was BCC. The preferred location was the nose for BCC. For SCC, the oral cavity is the most frequent anatomical site, especially the lips level. Nodular BCC and ulcero-vegetant SCC were the most commonly identified histological types. Our findings emphasize the need for periodic screening, in order to improve prevention and early treatment for these malignancies.

Keywords: non-melanoma skin cancer, basal cell carcinoma, squamous cell carcinoma, histological

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Authors: Rohaya Abdul Wahab, Raja Mohd Fuad Tengku Aziz, Nazaliza Othman, Sharifah Saleh, Nabihah Razali, Rozaimah Baharim, Md Hanif Md Nasir

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This paper will discuss flip chip methodology, in which I/O pads, standard cells, macros and bump cells array are placed in the floorplan, then routed using Astro place and route tool. Final DRC and LVS checking is done using Calibre verification tool. The design vehicle to run this methodology is an OpenRISC design targeted to Silterra 0.18 micrometer technology with 6 metal layers for routing. Astro has extensive support for flip chip placement and routing. Astro tool commands for flip chip are straightforward approach like the conventional standard wire bond packaging. However since we do not have flip chip commands in our Astro tool, no LEF file for bump cell and no LEF file for flip chip I/O pad, we create our own methodology to prepare for future flip chip tapeout. 

Keywords: methodology, flip chip, bump cell, LEF, astro, calibre, SCHEME, TCL

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Authors: Neha Singh, Anuj Ranjan, Tanu Jindal

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Over the last decade, the exponential growth of mobile communication has been accompanied by a parallel increase in density of electromagnetic fields (EMF). The continued expansion of mobile phone usage raises important questions as EMF, especially radio frequency (RF), have long been suspected of having biological effects. In the present experiments, we studied the effects of RF-EMF on cell death (apoptosis) and DNA damage of a well- tested biological model, Drosophila melanogaster exposed to 2400 MHz frequency for different time duration i.e. 2 hrs, 4 hrs, 6 hrs,8 hrs, 10 hrs, and 12 hrs each day for five continuous days in ambient temperature and humidity conditions inside an exposure chamber. The flies were grouped into control, sham-exposed, and exposed with 100 flies in each group. In this study, well-known techniques like Comet Assay and TUNEL (Terminal deoxynucleotide transferase dUTP Nick End Labeling) Assay were used to detect DNA damage and for apoptosis studies, respectively. Experiments results showed DNA damage in the brain cells of Drosophila which increases as the duration of exposure increases when observed under the observed when we compared results of control, sham-exposed, and exposed group which indicates that EMF radiation-induced stress in the organism that leads to DNA damage and cell death. The process of apoptosis and mutation follows similar pathway for all eukaryotic cells; therefore, studying apoptosis and genotoxicity in Drosophila makes similar relevance for human beings as well.

Keywords: cell death, apoptosis, Comet Assay, DNA damage, Drosophila, electromagnetic fields, EMF, radio frequency, RF, TUNEL assay

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Authors: Teh Kean Kheng, Low Soon Yee, Burra Venkata Durga Kumar

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In 2022, as the future world becomes increasingly computer-related, more individuals are attempting to study coding for themselves or in school. This is because they have discovered the value of learning code and the benefits it will provide them. But learning coding is difficult for most people. Even senior programmers that have experience for a decade year still need help from the online source while coding. The reason causing this is that coding is not like talking to other people; it has the specific syntax to make the computer understand what we want it to do, so coding will be hard for normal people if they don’t have contact in this field before. Coding is hard. If a user wants to learn bash code with bash prompt, it will be harder because if we look at the bash prompt, we will find that it is just an empty box and waiting for a user to tell the computer what we want to do, if we don’t refer to the internet, we will not know what we can do with the prompt. From here, we can conclude that the bash prompt is not user-friendly for new users who are learning bash code. Our goal in writing this paper is to give an idea to implement a user-friendly Bash prompt in Ubuntu OS using Artificial Intelligent (AI) to lower the threshold of learning in Bash code, to make the user use their own words and concept to write and learn Bash code.

Keywords: user-friendly, bash code, artificial intelligence, threshold, semantic similarity, lexical similarity

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Authors: Kouzi Katia

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This paper proposes a Direct Torque Control (DTC) algorithm of dual Stator Induction Motor (DSIM) drive using two approach intelligent techniques: Artificial Neural Network (ANN) approach replaces the switching table selector block of conventional DTC and Mamdani Fuzzy Logic controller (FLC) is used for stator resistance estimation. The fuzzy estimation method is based on an online stator resistance correction through the variations of stator current estimation error and its variation. The fuzzy logic controller gives the future stator resistance increment at the output. The main advantage of suggested algorithm control is to reduce the hardware complexity of conventional selectors, to avoid the drive instability that may occur in certain situation and ensure the tracking of the actual of the stator resistance. The effectiveness of the technique and the improvement of the whole system performance are proved by results.

Keywords: artificial neural network, direct torque control, dual stator induction motor, fuzzy logic estimator, switching table

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Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

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The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: artificial neural network, low series manufacturing, polymer cutting, setup period estimation

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Authors: Julius Denafas, Irina Kliopova, Gintaras Denafas

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Three opportunities for implementation of industrial ecology principles in the real industrial production of c-Si solar cells and modules are presented in this study. It includes: material flow dematerialisation, product modification and industrial symbiosis. Firstly, it is shown how the collaboration between R&D institutes and industry helps to achieve significant reduction of material consumption by a) refuse from phosphor silicate glass cleaning process and b) shortening of SiNx coating production step. This work was performed in the frame of Eco-Solar project, where Soli Tek R&D is collaborating together with the partners from ISC-Konstanz institute. Secondly, it was shown how the modification of solar module design can reduce the CO2 footprint for this product and enhance waste prevention. It was achieved by implementing a frameless glass/glass solar module design instead of glass/backsheet with aluminium frame. Such a design change is possible without purchasing new equipment and without loss of main product properties like efficiency, rigidity and longevity. Thirdly, industrial symbiosis in the solar cell production is possible in such case when manufacturing waste (silicon wafer and solar cell breakage) are collected, sorted and supplied as raw-materials to other companies involved in the production chain of c-Si solar cells. The obtained results showed that solar cells produced from recycled silicon can have a comparable electrical parameters like produced from standard, commercial silicon wafers. The above mentioned work was performed at solar cell producer Soli Tek R&D in the frame of H2020 projects CABRISS and Eco-Solar.

Keywords: solar cells and solar modules, manufacturing, waste prevention, recycling

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Authors: George Cudjoe Agbemabiese, John Paul Kosiba, Michael Boadi Nyamekye, Vanessa Narkie Tetteh, Caleb Nunoo, Mohammed Muniru Husseini

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The smartphone industry continues to experience massive growth, evidenced by expanding markets and an increasing number of brands, models and manufacturers. As technology advances rapidly, manufacturers of smartphones are consistently introducing new innovations to keep up with the latest evolving industry trends and customer demand for more modern devices. This study aimed to assess the influence of artificial intelligence (AI) voice assistant (VA) on improving customer experience, resulting in the continuous use of mobile brands. Specifically, this article assesses the role of hedonic, utilitarian, and social benefits provided by AIVA on customer experience and the continuance intention to use mobile phone brands. Using a primary data collection instrument, the quantitative approach was adopted to examine the study's variables. Data from 348 valid responses were used for the analysis based on structural equation modeling (SEM) with AMOS version 23. Three main factors were identified to influence customer experience, which results in continuous usage of mobile phone brands. These factors are social benefits, hedonic benefits, and utilitarian benefits. In conclusion, a significant and positive relationship exists between the factors influencing customer experience for continuous usage of mobile phone brands. The study concludes that mobile brands that invest in delivering positive user experiences are in a better position to improve usage and increase preference for their brands. The study recommends that mobile brands consider and research their prospects' and customers' social, hedonic, and utilitarian needs to provide them with desired products and experiences.

Keywords: artificial intelligence, continuance usage, customer experience, smartphone industry

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Authors: I. Bochev, A. Shterev, S. Kyurkchiev

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One of the factors associated with poor success rates in human in vitro fertilization (IVF) is the suboptimal culture conditions in which fertilization and early embryonic growth occur. Co-culture systems with helper cell lines appear to enhance the in vitro conditions and allow embryos to demonstrate improved in vitro development. The co-culture of human embryos with monolayers of autologous endometrial stromal cell (EnSCs) results in increased blastocyst development with a larger number of blastomeres, lower incidence of fragmentation and higher pregnancy rates in patients with recurrent implantation failure (RIF). The aim of the study was to examine the influence of autologous endometrial stromal cell (EnSC) co-culture on day 3 embryo quality by comparing the morphological status of the embryos from the same patients undergoing consecutive IVF/Intracytoplasmic sperm injection (ICSI) cycles without and with EnSC co-culture. This retrospective randomized study (2015-2017) includes 20 couples and a total of 46 IVF/ICSI cycles. Each patient couple included had at least two IVF/ICSI procedures – one with and one without autologous EnSC co-culture. Embryo quality was assessed at 68±1 hours in culture, according to Istanbul consensus criteria (2010). Day 3 embryos were classified into three groups: good – grade 1; fair – grade 2; poor – grade 3. Embryos from all cycles were divided into two groups (A – co-cultivated; B – not co-cultivated) and analyzed. Second, for each patient couple, embryos from matched IVF/ICSI cycles (with and without co-culture) were analyzed separately. When an analysis of co-cultivated day 3 embryos from all cycles was performed (n=137; group A), 43.1% of the embryos were graded as “good”, which was not significantly different from the respective embryo quality rate of 42.2% (p = NS) in group B (n=147) with non-co-cultivated embryos. The proportions of fair and poor quality embryos in group A and group B were similar as well – 11.7% vs 10.2% and 45.2% vs 47.6% (p=NS), respectively. Nevertheless, the separate embryo analysis by matched cycles for each couple revealed that in 65% of the cases the proportion of morphologically better embryos was increased in cycles with co-culture in comparison with those without co-culture. A decrease in this proportion after endometrial stromal cell co-cultivation was found in 30% of the cases, whereas no difference was observed in only one couple. The results demonstrated that there is no marked difference in the overall morphological quality between co-cultured and non-co-cultured embryos on day 3. However, in significantly greater percentage of couples the process of autologous EnSC co-culture could increase the proportion of morphologically improved day 3 embryos. By mimicking the in vivo relationship between embryo and maternal environment, co-culture in autologous EnSC system represents a perspective approach to improve the quality of embryos in cases with elevated risk for development of embryos with impaired morphology.

Keywords: autologous endometrial stromal cells, co-culture, day 3 embryo, morphological quality

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Authors: M. Cardenas-Garcia, P. P. Gonzalez-Perez

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Intercellular communication is a necessary condition for cellular functions and it allows a group of cells to survive as a population. Throughout this interaction, the cells work in a coordinated and collaborative way which facilitates their survival. In the case of cancerous cells, these take advantage of intercellular communication to preserve their malignancy, since through these physical unions they can send signs of malignancy. The Wnt/β-catenin signaling pathway plays an important role in the formation of intercellular communications, being also involved in a large number of cellular processes such as proliferation, differentiation, adhesion, cell survival, and cell death. The modeling and simulation of cellular signaling systems have found valuable support in a wide range of modeling approaches, which cover a wide spectrum ranging from mathematical models; e.g., ordinary differential equations, statistical methods, and numerical methods– to computational models; e.g., process algebra for modeling behavior and variation in molecular systems. Based on these models, different simulation tools have been developed from mathematical ones to computational ones. Regarding cellular and molecular processes in cancer, its study has also found a valuable support in different simulation tools that, covering a spectrum as mentioned above, have allowed the in silico experimentation of this phenomenon at the cellular and molecular level. In this work, we simulate and explore the complex interaction patterns of intercellular communication in cancer cells using the Cellulat bioinformatics tool, a computational simulation tool developed by us and motivated by two key elements: 1) a biochemically inspired model of self-organizing coordination in tuple spaces, and 2) the Gillespie’s algorithm, a stochastic simulation algorithm typically used to mimic systems of chemical/biochemical reactions in an efficient and accurate way. The main idea behind the Cellulat simulation tool is to provide an in silico experimentation environment that complements and guides in vitro experimentation in intra and intercellular signaling networks. Unlike most of the cell signaling simulation tools, such as E-Cell, BetaWB and Cell Illustrator which provides abstractions to model only intracellular behavior, Cellulat is appropriate for modeling both intracellular signaling and intercellular communication, providing the abstractions required to model –and as a result, simulate– the interaction mechanisms that involve two or more cells, that is essential in the scenario discussed in this work. During the development of this work we made evident the application of our computational simulation tool (Cellulat) for the modeling and simulation of intercellular communication between normal and cancerous cells, and in this way, propose key molecules that may prevent the arrival of malignant signals to the cells that surround the tumor cells. In this manner, we could identify the significant role that has the Wnt/β-catenin signaling pathway in cellular communication, and therefore, in the dissemination of cancer cells. We verified, using in silico experiments, how the inhibition of this signaling pathway prevents that the cells that surround a cancerous cell are transformed.

Keywords: cancer cells, in silico approach, intercellular communication, key molecules, modeling and simulation

Procedia PDF Downloads 239

Authors: Mehrnaz Mostafavi, Mahtab Shabani, Alireza Azani, Fatemeh Ghafari

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Artificial intelligence (AI) can transform breast cancer diagnosis and therapy by providing sophisticated solutions for screening, imaging interpretation, histopathological analysis, and treatment planning. This literature review digs into the many uses of AI in breast cancer treatment, highlighting the need for collaboration between AI scientists and healthcare practitioners. It emphasizes advances in AI-driven breast imaging interpretation, such as computer-aided detection and diagnosis (CADe/CADx) systems and deep learning algorithms. These have shown significant potential for improving diagnostic accuracy and lowering radiologists' workloads. Furthermore, AI approaches such as deep learning have been used in histopathological research to accurately predict hormone receptor status and categorize tumor-associated stroma from regular H&E stains. These AI-powered approaches simplify diagnostic procedures while providing insights into tumor biology and prognosis. As AI becomes more embedded in breast cancer care, it is crucial to ensure its ethical, efficient, and patient-focused implementation to improve outcomes for breast cancer patients ultimately.

Keywords: breast cancer, artificial intelligence, cancer diagnosis, clinical practice

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Authors: Aroonsri Priprem, Sucharat Limsitthichaikoon, Suttasinee Thappasarapong

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Anthocyanins are natural pigments with effective UV protection but their topical use could be limited due to their physicochemical characteristics. An attempt to overcome such limitations by complexation of 2 major anthocyanin-rich sources, C. ternatea, and Z. mays, for investigation on potential use as topical anti-inflammatory. Cell studies indicate no cytotoxicity of the anthocyanin complex (AC) up to 1 mg/ml tested in HaCaT and human forehead fibroblasts by MTT. Croton oil-induced ear edema in Wistar rats suggests an effective dose of 5 mg/cm2 of AC as a topical anti-inflammatory in comparison to 0.5 mg/cm2 of fluocinolone acetonide. Niosomal encapsulation of the AC significantly prolonged the anti-inflammatory activity particularly at 8 h after topical application (p = 0.0001). The AC was not cytotoxic and its anti-inflammatory and activity was dose-dependent and prolonged by niosomal encapsulation. It has also shown to promote collagen type 1 production in cell culture. Thus, AC could be a potential candidate for topical anti-inflammatory agent from natural resources.

Keywords: anthocyanin complex, ear edema, inflammation, niosomes, skin

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Authors: Hilal T. Sasmazel, Seda Surucu

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Skin tissue engineering is a promising field for the treatment of skin defects using scaffolds. This approach involves the use of living cells and biomaterials to restore, maintain, or regenerate tissues and organs in the body by providing; (i) larger surface area for cell attachment, (ii) proper porosity for cell colonization and cell to cell interaction, and (iii) 3-dimensionality at macroscopic scale. Recent studies on this area mainly focus on fabrication of scaffolds that can closely mimic the natural extracellular matrix (ECM) for creation of tissue specific niche-like environment at the subcellular scale. Scaffolds designed as ECM-like architectures incorporating into the host with minimal scarring/pain and facilitate angiogenesis. This study is related to combining of synthetic PCL and natural chitosan polymers to form 3D PCL/Chitosan core-shell structures for skin tissue engineering applications. Amongst the polymers used in tissue engineering, natural polymer chitosan and synthetic polymer poly(ε-caprolactone) (PCL) are widely preferred in the literature. Chitosan has been among researchers for a very long time because of its superior biocompatibility and structural resemblance to the glycosaminoglycan of bone tissue. However, the low mechanical flexibility and limited biodegradability properties reveals the necessity of using this polymer in a composite structure. On the other hand, PCL is a versatile polymer due to its low melting point (60°C), ease of processability, degradability with non-enzymatic processes (hydrolysis) and good mechanical properties. Nevertheless, there are also several disadvantages of PCL such as its hydrophobic structure, limited bio-interaction and susceptibility to bacterial biodegradation. Therefore, it became crucial to use both of these polymers together as a hybrid material in order to overcome the disadvantages of both polymers and combine advantages of those. The scaffolds here were fabricated by using electrospinning technique and the characterizations of the samples were done by contact angle (CA) measurements, scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-Ray Photoelectron spectroscopy (XPS). Additionally, gas permeability test, mechanical test, thickness measurement and PBS absorption and shrinkage tests were performed for all type of scaffolds (PCL, chitosan and PCL/chitosan core-shell). By using ImageJ launcher software program (USA) from SEM photographs the average inter-fiber diameter values were calculated as 0.717±0.198 µm for PCL, 0.660±0.070 µm for chitosan and 0.412±0.339 µm for PCL/chitosan core-shell structures. Additionally, the average inter-fiber pore size values exhibited decrease of 66.91% and 61.90% for the PCL and chitosan structures respectively, compare to PCL/chitosan core-shell structures. TEM images proved that homogenous and continuous bead free core-shell fibers were obtained. XPS analysis of the PCL/chitosan core-shell structures exhibited the characteristic peaks of PCL and chitosan polymers. Measured average gas permeability value of produced PCL/chitosan core-shell structure was determined 2315±3.4 g.m-2.day-1. In the future, cell-material interactions of those developed PCL/chitosan core-shell structures will be carried out with L929 ATCC CCL-1 mouse fibroblast cell line. Standard MTT assay and microscopic imaging methods will be used for the investigation of the cell attachment, proliferation and growth capacities of the developed materials.

Keywords: chitosan, coaxial electrospinning, core-shell, PCL, tissue scaffold

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Authors: Cristina Busuioc, Georgeta Voicu, Sorin-Ion Jinga

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The human bone presents in its dry form piezoelectric properties, which means that a mechanical stress results in electric polarization and an applied electric field causes strain. The immediate consequence was the revealing of piezoelectricity role in bone remodelling, as well as the integration of ceramic materials with piezoelectric behaviour in the composition of unitary or composite biomaterials. Thus, we prepared hydroxyapatite - collagen hybrid materials with barium titanate addition in order to achieve a better osseointegration. Barium titanate powder synthesized by a combined sol-gel-hydrothermal method, commercial hydroxyapatite and laboratory extracted collagen gel were employed as starting materials. Before the composites, fabrication, the powder with piezoelectric features was characterized in detail from the compositional, structural, morphological and electrical point of view. The next step was to elucidate the influence of barium titanate presence especially on the biological properties of the final materials. The biocompatibility of the hybrid supports without or with piezoelectric addition was investigated on mouse osteoblast cells through LDH cytotoxicity assay, LIVE/DEAD cell viability assay, and MTT cell proliferation assay. All results indicated that the analysed materials do not exert cytotoxic effects and present the ability to sustain cell survival and to promote their proliferation. In conclusion, barium titanate nanoparticles exhibit a good biocompatibility and osteoinductive properties, while the derived composite materials based on hydroxyapatite as oxide phase and collagen as polymeric phase can be successfully used for tissue engineering applications.

Keywords: barium titanate, hybrid composites, piezoelectricity, tissue engineering

Procedia PDF Downloads 300

Authors: V. Marzal, J. C. Torres, B. Garcia-Camara, Manuel Cano-Garcia, Xabier Quintana, I. Perez Garcilopez, J. M. Sanchez-Pena

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At the present time, the use of nanostructures in complex media, like liquid crystals, is widely extended to manipulate their properties, either electrical or optical. In addition, these media can also be used to control the optical properties of the nanoparticles, for instance when they are resonant. In this work, the change on electrical properties of a liquid crystal cell by adding TiO₂ nanoparticles on one of the alignment layers has been analyzed. These nanoparticles, with a diameter of 100 nm and spherical shape, were deposited in one of the substrates (ITO + polyimide) by spin-coating in order to produce a homogeneous layer. These substrates were checked using an optical microscope (objective x100) to avoid potential agglomerates. The liquid crystal cell is then fabricated, using one of these substrates and another without nanoparticles, and filled with E7. The study of the electrical response was done through impedance measurements in a long range of frequencies (3 Hz- 6 MHz) and at ambient temperature. Different nanoparticle concentrations were considered, as well as pure E7 and an empty cell for comparison purposes. Results about the effective dielectric permittivity and conductivity are presented along with models of equivalent electric circuits and its physical interpretation. As a summary, it has been observed the clear influence of the presence of the nanoparticles, strongly modifying the electric response of the device. In particular, a variation of both the effective permittivity and the conductivity of the device have been observed. This result requires a deep analysis of the effect of these nanoparticles on the trapping of free ions in the device, allowing a controlled manipulation and frequency tuning of the electrical response of these devices.

Keywords: alignment layer, electrical behavior, liquid crystal, TiO₂ nanoparticles

Procedia PDF Downloads 192