Search results for: neural cellular automata
Commenced in January 2007
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Edition: International
Paper Count: 2483

Search results for: neural cellular automata

323 Proteome-Wide Convergent Evolution on Vocal Learning Birds Reveals Insight into cAMP-Based Learning Pathway

Authors: Chul Lee, Seoae Cho, Erich D. Jarvis, Heebal Kim

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Vocal learning, the ability to imitate vocalizations based on auditory experience, is a homoplastic character state observed in different independent lineages of animals such as songbirds, parrots, hummingbirds and human. It has now become possible to perform genome-wide molecular analyses across vocal learners and vocal non-learners with the recent expansion of avian genome data. It was analyzed the whole genomes of human and 48 avian species including those belonging to the three avian vocal learning lineages, to determine if behavior and neural convergence are associated with molecular convergence in divergent species of vocal learners. Analyses of 8295 orthologous genes across bird species revealed 141 genes with amino acid substitutions specific to vocal learners. Out of these, 25 genes have vocal learner specific genetic homoplasies, and their functions were enriched for learning. Several sites in these genes are estimated under convergent evolution and positive selection. A potential role for a subset of these genes in vocal learning was supported by associations with gene expression profiles in vocal learning brain regions of songbirds and human disease that cause language dysfunctions. The key candidate gene with multiple independent lines of the evidences specific to vocal learners was DRD5. Our findings suggest cAMP-based learning pathway in avian vocal learners, indicating molecular homoplastic changes associated with a complex behavioral trait, vocal learning.

Keywords: amino acid substitutions, convergent evolution, positive selection, vocal learning

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322 MARISTEM: A COST Action Focused on Stem Cells of Aquatic Invertebrates

Authors: Arzu Karahan, Loriano Ballarin, Baruch Rinkevich

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Marine invertebrates, the highly diverse phyla of multicellular organisms, represent phenomena that are either not found or highly restricted in the vertebrates. These include phenomena like budding, fission, a fusion of ramets, and high regeneration power, such as the ability to create whole new organisms from either tiny parental fragment, many of which are controlled by totipotent, pluripotent, and multipotent stem cells. Thus, there is very much that can be learned from these organisms on the practical and evolutionary levels, further resembling Darwin's words, “It is not the strongest of the species that survives, nor the most intelligent, but the one most responsive to change”. The ‘stem cell’ notion highlights a cell that has the ability to continuously divide and differentiate into various progenitors and daughter cells. In vertebrates, adult stem cells are rare cells defined as lineage-restricted (multipotent at best) with tissue or organ-specific activities that are located in defined niches and further regulate the machinery of homeostasis, repair, and regeneration. They are usually categorized by their morphology, tissue of origin, plasticity, and potency. The above description not always holds when comparing the vertebrates with marine invertebrates’ stem cells that display wider ranges of plasticity and diversity at the taxonomic and the cellular levels. While marine/aquatic invertebrates stem cells (MISC) have recently raised more scientific interest, the know-how is still behind the attraction they deserve. MISC, not only are highly potent but, in many cases, are abundant (e.g., 1/3 of the entire animal cells), do not locate in permanent niches, participates in delayed-aging and whole-body regeneration phenomena, the knowledge of which can be clinically relevant. Moreover, they have massive hidden potential for the discovery of new bioactive molecules that can be used for human health (antitumor, antimicrobial) and biotechnology. The MARISTEM COST action (Stem Cells of Marine/Aquatic Invertebrates: From Basic Research to Innovative Applications) aims to connect the European fragmented MISC community. Under this scientific umbrella, the action conceptualizes the idea for adult stem cells that do not share many properties with the vertebrates’ stem cells, organizes meetings, summer schools, and workshops, stimulating young researchers, supplying technical and adviser support via short-term scientific studies, making new bridges between the MISC community and biomedical disciplines.

Keywords: aquatic/marine invertebrates, adult stem cell, regeneration, cell cultures, bioactive molecules

Procedia PDF Downloads 138
321 Effect of Long-Term Boron Exposure on Liver Structure of Adult Male Albino Rats and a Possible Role of Vitamin C

Authors: Ola Abdel-Tawab Hussein

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Background: Boron is a naturally occurring agent and an essential trace element of human, animals and higher plants. It is released in the form of boric acid (BA) that is water soluble and biolologically available. Its largest uses are in glass, detergents, agriculture, leather tanning industries, cosmetics, photographic materials, soaps and cleaners. Human consume daily few milligrams in the water, fruits and vegetables. High doses of boron had been recorded to be developmental and reproductive toxin in animals(Only few studies on human had investigated the health effects associated with exposure to boron. Vitamin C is a major water soluble non-enzymatic antioxidant, acts to overcome the oxidative stress. Aim of the work: However , the liver is exposed to toxic substances that are absorbed, degraded or conjugated there were little information exists about the effects of boron that it would specifically have in the liver tissue of experimental rats. So the present work aimed to study the effects of long-term boron ingestion on histological structural of the liver of adult male albino rats and to evaluate the protective role of vitamin C against induced changes. Material and Methods: 30 adult male albino rats were divided into 3 equal groups; Group I: control, Group II: recieved drinking water containing 55x10-6 gm boron/liter for 90 days and Group III: recieved vitamin C (200mg/Kg.B.W) orally concomitant with boron for the same period. liver specimens were processed for light and electron microscopic(TEM) study. Results: Examination of the liver sections of group II revealed foci of severe dilatation and congestion of central and portal veins with mononuclear cellular infiltration and hepatocellular vacuolation. Increased collagen deposition specially around the portal areas. Marked electrolucent areas in the cytoplasm, heterochromatic nuclei and destroyed organelles of the hepatocytes. Apoptotic cells were observed and decreased lipid content of ito cells. In Group III the co administration of vitamin C improved most of the structural changes of the hepatocytes, Ito cells, increased binucleated cells and decreased collagen fibers deposition. Conclusion: Thus, the long term exposure to boron, induced histological changes on the structure of liver. The co administration of vitamin C improved most of these structural changes.

Keywords: boron, liver, vitamin C, rats

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320 Anatomical and Histochemical Investigation of the Leaf of Vitex agnus-castus L.

Authors: S. Mamoucha, J. Rahul, N. Christodoulakis

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Introduction: Nature has been the source of medicinal agents since the dawn of the human existence on Earth. Currently, millions of people, in the developing world, rely on medicinal plants for primary health care, income generation and lifespan improvement. In Greece, more than 5500 plant taxa are reported while about 250 of them are considered to be of great pharmaceutical importance. Among the plants used for medical purposes, Vitex agnus-castus L. (Verbenaceae) is known since ancient times. It is a small tree or shrub, widely distributed in the Mediterranean basin up to the Central Asia. It is also known as chaste tree or monks pepper. Theophrastus mentioned the shrub several times, as ‘agnos’ in his ‘Enquiry into Plants’. Dioscorides mentioned the use of V. agnus-castus for the stimulation of lactation in nursing mothers and the treatment of several female disorders. The plant has important medicinal properties and a long tradition in folk medicine as an antimicrobial, diuretic, digestive and insecticidal agent. Materials and methods: Leaves were cleaned, detached, fixed, sectioned and investigated with light and Scanning Electron Microscopy (SEM). Histochemical tests were executed as well. Specific histochemical reagents (osmium tetroxide, H2SO4, vanillin/HCl, antimony trichloride, Wagner’ s reagent, Dittmar’ s reagent, potassium bichromate, nitroso reaction, ferric chloride and di methoxy benzaldehyde) were used for the sub cellular localization of secondary metabolites. Results: Light microscopical investigations of the elongated leaves of V. agnus-castus revealed three layers of palisade parenchyma, just below the single layered adaxial epidermis. The spongy parenchyma is rather loose. Adaxial epidermal cells are larger in magnitude, compared to those of the abaxial epidermis. Four different types of capitate, secreting trichomes, were localized among the abaxial epidermal cells. Stomata were observed at the abaxial epidermis as well. SEM revealed the interesting arrangement of trichomes. Histochemical treatment on fresh and plastic embedded tissue sections revealed the nature and the sites of secondary metabolites accumulation (flavonoids, steroids, terpenes). Acknowledgment: This work was supported by IKY - State Scholarship Foundation, Athens, Greece.

Keywords: Vitex agnus-castus, leaf anatomy, histochemical reagents, secondary metabolites

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319 Data Augmentation for Early-Stage Lung Nodules Using Deep Image Prior and Pix2pix

Authors: Qasim Munye, Juned Islam, Haseeb Qureshi, Syed Jung

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Lung nodules are commonly identified in computed tomography (CT) scans by experienced radiologists at a relatively late stage. Early diagnosis can greatly increase survival. We propose using a pix2pix conditional generative adversarial network to generate realistic images simulating early-stage lung nodule growth. We have applied deep images prior to 2341 slices from 895 computed tomography (CT) scans from the Lung Image Database Consortium (LIDC) dataset to generate pseudo-healthy medical images. From these images, 819 were chosen to train a pix2pix network. We observed that for most of the images, the pix2pix network was able to generate images where the nodule increased in size and intensity across epochs. To evaluate the images, 400 generated images were chosen at random and shown to a medical student beside their corresponding original image. Of these 400 generated images, 384 were defined as satisfactory - meaning they resembled a nodule and were visually similar to the corresponding image. We believe that this generated dataset could be used as training data for neural networks to detect lung nodules at an early stage or to improve the accuracy of such networks. This is particularly significant as datasets containing the growth of early-stage nodules are scarce. This project shows that the combination of deep image prior and generative models could potentially open the door to creating larger datasets than currently possible and has the potential to increase the accuracy of medical classification tasks.

Keywords: medical technology, artificial intelligence, radiology, lung cancer

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318 Phenolic Content and Antioxidant Potential of Selected Nigerian Herbs and Spices: A Justification for Consumption and Use in the Food Industry

Authors: Amarachi Delight Onyemachi, Gregory Ikechukwu Onwuka

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The growing consumer trend for natural ingredients, functional foods with health benefits and the perceived risk of carcinogenesis associated with synthetic antioxidants have forced food manufacturers to look for alternatives for producing healthy and safe food. Herbs and spices are cheap, natural and harmless sources of antioxidants which can delay and prevent lipid oxidation of food products and also confer its unique organoleptic properties and health benefits to food products. The Nigerian climate has been proven to be conducive for the production of spices and herbs and is blessed bountifully with a wide range of them. Five selected Nigerian herbs and spices Piper guieense, Xylopia aethopica, Gongronema latifolium and Ocimum gratissimum were evaluated for their ability to act as radical scavengers. The spices were extracted with 80% ethanol and evaluated using total phenolic capacity (TPC), DPPH (1,1-diph diphenyl-2-picrylhydrazyl radical) ABTS (2,2’azinobis-(3-ethylbenzthiazoline-6-sulfonic acid)), total antioxidant capacity (TAC), reducing power (RP) assays. The TPC ranged from 5.33 µg GAE/mg (in Gongronema latifolium) to 15.55 µg GAE/mg (in Ocimum gratissimum). The DPPH and ABTS scavenging activity of the extracts ranged from 0.23-0.36 IC50 mg/ml and 2.32-7.25 Trolox equivalent % respectively. The TAC and RP of the extract ranged from 6.73-10.64 µg AAE/mg and 3.52-10.19 µg AAE/mg. The result of percentage yield of the extract ranged from as low as 9.94% in Gongronema latifolium and to as high as 23.85% in Xylopia aethopica. A very strong positive relationship existed between the total antioxidant capacity and total phenolic content of the tested herbs and spices (R2=0.96). All of the extracts exhibited different extent of strong antioxidant activity, high antioxidant activity was found in Ocimum gratissimum and Gongronema latifolium with the least. However, Gongronema latifolium possessed the highest total antioxidant capacity. These data confirm the appreciable antioxidant potentials and high phenolic content of Nigerian herbs and spices, thereby providing justification for their use in dishes and functional foods, prevention of cellular damage caused by free radicals and use as natural antioxidants in the food industry for prevention of lipid oxidation in food products. However, to utilize these natural antioxidants in food products, further analysis and studies of their behaviour in food systems at varying temperature, pH conditions and ionic concentrations should be carried out to displace the use of synthetic antioxidants like BHT and BHA.

Keywords: Antioxidant, free radicals, herbs, phenolic, spices

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317 Antioxidant Effects of C-Phycocyanin on Oxidized Astrocyte in Brain Injury Using 2D and 3D Neural Nanofiber Tissue Model

Authors: Seung Ju Yeon, Seul Ki Min, Jun Sang Park, Yeo Seon Kwon, Hoo Cheol Lee, Hyun Jung Shim, Il-Doo Kim, Ja Kyeong Lee, Hwa Sung Shin

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In brain injury, depleting oxidative stress is the most effective way to reduce the brain infarct size. C-phycocyanin (C-Pc) is a well-known antioxidant protein that has neuroprotective effects obtained from green microalgae. Astrocyte is glial cell that supports the nerve cell such as neuron, which account for a large portion of the brain. In brain injury, such as ischemia and reperfusion, astrocyte has an important rule that overcomes the oxidative stress and protect from brain reactive oxygen species (ROS) injury. However little is known about how C-Pc regulates the anti-oxidants effects of astrocyte. In this study, when the C-Pc was treated in oxidized astrocyte, we confirmed that inflammatory factors Interleukin-6 and Interleukin-3 were increased and antioxidants enzyme, Superoxide dismutase (SOD) and catalase was upregulated, and neurotrophic factors, brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) was alleviated. Also, it was confirmed to reduce infarct size of the brain in ischemia and reperfusion because C-Pc has anti-oxidant effects in middle cerebral artery occlusion (MCAO) animal model. These results show that C-Pc can help astrocytes lead neuroprotective activities in the oxidative stressed environment of the brain. In summary, the C-PC protects astrocytes from oxidative stress and has anti-oxidative, anti-inflammatory, neurotrophic effects under ischemic situations.

Keywords: c-phycocyanin, astrocyte, reactive oxygen species, ischemia and reperfusion, neuroprotective effect

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316 Study of Phase Separation Behavior in Flexible Polyurethane Foam

Authors: El Hatka Hicham, Hafidi Youssef, Saghiri Khalid, Ittobane Najim

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Flexible polyurethane foam (FPUF) is a low-density cellular material generally used as a cushioning material in many applications such as furniture, bedding, packaging, etc. It is commercially produced during a continuous process, where a reactive mixture of foam chemicals is poured onto a moving conveyor. FPUFs are produced by the catalytic balancing of two reactions involved, the blowing reaction (isocyanate-water) and the gelation reaction (isocyanate-polyol). The microstructure of FPUF is generally composed of soft phases (polyol phases) and rigid domains that separate into two domains of different sizes: the rigid polyurea microdomains and the macrodomains (larger aggregates). The morphological features of FPUF are strongly influenced by the phase separation morphology that plays a key role in determining the global FPUF properties. This phase-separated morphology results from a thermodynamic incompatibility between soft segments derived from aliphatic polyether and hard segments derived from the commonly used aromatic isocyanate. In order to improve the properties of FPUF against the different stresses faced by this material during its use, we report in this work a study of the phase separation phenomenon in FPUF that has been examined using SAXS WAXS and FTIR. Indeed, we have studied with these techniques the effect of water, isocyanates, and alkaline chlorides on the phase separation behavior. SAXS was used to study the morphology of the microphase separated, WAXS to examine the nature of the hard segment packing, and FTIR to investigate the hydrogen bonding characteristics of the materials studied. The prepared foams were shown to have different levels of urea phase connectivity; the increase in water content in the FPUF formulation leads to an increase in the amount of urea formed and consequently the increase of the size of urea aggregates formed. Alkali chlorides (NaCl, KCl, and LiCl) incorporated into FPUF formulations show that is the ability to prevent hydrogen bond formation and subsequently alter the rigid domains. FPUFs prepared by different isocyanate structures showed that urea aggregates are difficult to be formed in foams prepared by asymmetric diisocyanate, while are more easily formed in foams prepared by symmetric and aliphatic diisocyanate.

Keywords: flexible polyurethane foam, hard segments, phase separation, soft segments

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315 MicroRNA-1246 Expression Associated with Resistance to Oncogenic BRAF Inhibitors in Mutant BRAF Melanoma Cells

Authors: Jae-Hyeon Kim, Michael Lee

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Intrinsic and acquired resistance limits the therapeutic benefits of oncogenic BRAF inhibitors in melanoma. MicroRNAs (miRNA) regulate the expression of target mRNAs by repressing their translation. Thus, we investigated miRNA expression patterns in melanoma cell lines to identify candidate biomarkers for acquired resistance to BRAF inhibitor. Here, we used Affymetrix miRNA V3.0 microarray profiling platform to compare miRNA expression levels in three cell lines containing BRAF inhibitor-sensitive A375P BRAF V600E cells, their BRAF inhibitor-resistant counterparts (A375P/Mdr), and SK-MEL-2 BRAF-WT cells with intrinsic resistance to BRAF inhibitor. The miRNAs with at least a two-fold change in expression between BRAF inhibitor-sensitive and –resistant cell lines, were identified as differentially expressed. Averaged intensity measurements identified 138 and 217 miRNAs that were differentially expressed by 2 fold or more between: 1) A375P and A375P/Mdr; 2) A375P and SK-MEL-2, respectively. The hierarchical clustering revealed differences in miRNA expression profiles between BRAF inhibitor-sensitive and –resistant cell lines for miRNAs involved in intrinsic and acquired resistance to BRAF inhibitor. In particular, 43 miRNAs were identified whose expression was consistently altered in two BRAF inhibitor-resistant cell lines, regardless of intrinsic and acquired resistance. Twenty five miRNAs were consistently upregulated and 18 downregulated more than 2-fold. Although some discrepancies were detected when miRNA microarray data were compared with qPCR-measured expression levels, qRT-PCR for five miRNAs (miR-3617, miR-92a1, miR-1246, miR-1936-3p, and miR-17-3p) results showed excellent agreement with microarray experiments. To further investigate cellular functions of miRNAs, we examined effects on cell proliferation. Synthetic oligonucleotide miRNA mimics were transfected into three cell lines, and proliferation was quantified using a colorimetric assay. Of the 5 miRNAs tested, only miR-1246 altered cell proliferation of A375P/Mdr cells. The transfection of miR-1246 mimic strongly conferred PLX-4720 resistance to A375P/Mdr cells, implying that miR-1246 upregulation confers acquired resistance to BRAF inhibition. We also found that PLX-4720 caused much greater G2/M arrest in A375P/Mdr cells transfected with miR-1246mimic than that seen in scrambled RNA-transfected cells. Additionally, miR-1246 mimic partially caused a resistance to autophagy induction by PLX-4720. These results indicate that autophagy does play an essential death-promoting role inPLX-4720-induced cell death. Taken together, these results suggest that miRNA expression profiling in melanoma cells can provide valuable information for a network of BRAF inhibitor resistance-associated miRNAs.

Keywords: microRNA, BRAF inhibitor, drug resistance, autophagy

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314 An Event-Related Potentials Study on the Processing of English Subjunctive Mood by Chinese ESL Learners

Authors: Yan Huang

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Event-related potentials (ERPs) technique helps researchers to make continuous measures on the whole process of language comprehension, with an excellent temporal resolution at the level of milliseconds. The research on sentence processing has developed from the behavioral level to the neuropsychological level, which brings about a variety of sentence processing theories and models. However, the applicability of these models to L2 learners is still under debate. Therefore, the present study aims to investigate the neural mechanisms underlying English subjunctive mood processing by Chinese ESL learners. To this end, English subject clauses with subjunctive moods are used as the stimuli, all of which follow the same syntactic structure, “It is + adjective + that … + (should) do + …” Besides, in order to examine the role that language proficiency plays on L2 processing, this research deals with two groups of Chinese ESL learners (18 males and 22 females, mean age=21.68), namely, high proficiency group (Group H) and low proficiency group (Group L). Finally, the behavioral and neurophysiological data analysis reveals the following findings: 1) Syntax and semantics interact with each other on the SECOND phase (300-500ms) of sentence processing, which is partially in line with the Three-phase Sentence Model; 2) Language proficiency does affect L2 processing. Specifically, for Group H, it is the syntactic processing that plays the dominant role in sentence processing while for Group L, semantic processing also affects the syntactic parsing during the THIRD phase of sentence processing (500-700ms). Besides, Group H, compared to Group L, demonstrates a richer native-like ERPs pattern, which further demonstrates the role of language proficiency in L2 processing. Based on the research findings, this paper also provides some enlightenment for the L2 pedagogy as well as the L2 proficiency assessment.

Keywords: Chinese ESL learners, English subjunctive mood, ERPs, L2 processing

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313 Convolution Neural Network Based on Hypnogram of Sleep Stages to Predict Dosages and Types of Hypnotic Drugs for Insomnia

Authors: Chi Wu, Dean Wu, Wen-Te Liu, Cheng-Yu Tsai, Shin-Mei Hsu, Yin-Tzu Lin, Ru-Yin Yang

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Background: The results of previous studies compared the benefits and risks of receiving insomnia medication. However, the effects between hypnotic drugs used and enhancement of sleep quality were still unclear. Objective: The aim of this study is to establish a prediction model for hypnotic drugs' dosage used for insomnia subjects and associated the relationship between sleep stage ratio change and drug types. Methodologies: According to American Academy of Sleep Medicine (AASM) guideline, sleep stages were classified and transformed to hypnogram via the polysomnography (PSG) in a hospital in New Taipei City (Taiwan). The subjects with diagnosis for insomnia without receiving hypnotic drugs treatment were be set as the comparison group. Conversely, hypnotic drugs dosage within the past three months was obtained from the clinical registration for each subject. Furthermore, the collecting subjects were divided into two groups for training and testing. After training convolution neuron network (CNN) to predict types of hypnotics used and dosages are taken, the test group was used to evaluate the accuracy of classification. Results: We recruited 76 subjects in this study, who had been done PSG for transforming hypnogram from their sleep stages. The accuracy of dosages obtained from confusion matrix on the test group by CNN is 81.94%, and accuracy of hypnotic drug types used is 74.22%. Moreover, the subjects with high ratio of wake stage were correctly classified as requiring medical treatment. Conclusion: CNN with hypnogram was potentially used for adjusting the dosage of hypnotic drugs and providing subjects to pre-screening the types of hypnotic drugs taken.

Keywords: convolution neuron network, hypnotic drugs, insomnia, polysomnography

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312 Time Series Analysis the Case of China and USA Trade Examining during Covid-19 Trade Enormity of Abnormal Pricing with the Exchange rate

Authors: Md. Mahadi Hasan Sany, Mumenunnessa Keya, Sharun Khushbu, Sheikh Abujar

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Since the beginning of China's economic reform, trade between the U.S. and China has grown rapidly, and has increased since China's accession to the World Trade Organization in 2001. The US imports more than it exports from China, reducing the trade war between China and the U.S. for the 2019 trade deficit, but in 2020, the opposite happens. In international and U.S. trade, Washington launched a full-scale trade war against China in March 2016, which occurred a catastrophic epidemic. The main goal of our study is to measure and predict trade relations between China and the U.S., before and after the arrival of the COVID epidemic. The ML model uses different data as input but has no time dimension that is present in the time series models and is only able to predict the future from previously observed data. The LSTM (a well-known Recurrent Neural Network) model is applied as the best time series model for trading forecasting. We have been able to create a sustainable forecasting system in trade between China and the US by closely monitoring a dataset published by the State Website NZ Tatauranga Aotearoa from January 1, 2015, to April 30, 2021. Throughout the survey, we provided a 180-day forecast that outlined what would happen to trade between China and the US during COVID-19. In addition, we have illustrated that the LSTM model provides outstanding outcome in time series data analysis rather than RFR and SVR (e.g., both ML models). The study looks at how the current Covid outbreak affects China-US trade. As a comparative study, RMSE transmission rate is calculated for LSTM, RFR and SVR. From our time series analysis, it can be said that the LSTM model has given very favorable thoughts in terms of China-US trade on the future export situation.

Keywords: RFR, China-U.S. trade war, SVR, LSTM, deep learning, Covid-19, export value, forecasting, time series analysis

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311 Self-Organizing Maps for Credit Card Fraud Detection

Authors: ChunYi Peng, Wei Hsuan CHeng, Shyh Kuang Ueng

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This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

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310 Polypeptide Modified Carbon Nanotubes – Mediated GFP Gene Transfection for H1299 Cells and Toxicity Assessment

Authors: Pei-Ying Lo, Jing-Hao Ciou, Kai-Cheng Yang, Jia-Huei Zheng, Shih-Hsiang Huang, Kuen-Chan Lee, Er-Chieh Cho

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As-produced CNTs are insoluble in all organic solvents and aqueous solutions have imposed limitations to the use of CNTs. Therefore, how to debundle carbon nanotubes and to modify them for further uses is an important issue. There are several methods for the dispersion of CNTs in water using covalent attachment of hydrophilic groups to the surface of tubes. These methods, however, alter the electronic structure of the nanotubes by disrupting the network of sp2 hybridized carbons. In order to keep the nanotubes’ intrinsic mechanical and electrical properties intact, non-covalent interactions are increasingly being explored as an alternative route for dispersion. Apart from conventional surfactants such as sodium dodecylsulfate (SDS) or sodium dodecylbenzenesulfonate (SDBS) which are highly effective in dispersing CNTs, biopolymers have received much attention as dispersing agents due to the anticipated biocompatibility of the dispersed CNTs. Also, The pyrenyl group is known to interact strongly with the basal plane of graphene via π-stacking. In this study, a highly re-dispersible biopolymer is reported for the synthesis of pyrene-modified poly-L-lysine (PBPL) and poly(D-Glu, D-Lys) (PGLP). To provide the evidence of the safety of the PBPL/CNT & PGLP/CNT materials we use in this study, H1299 and HCT116 cells were incubated with PBPL/CNT & PGLP/CNT materials for toxicity analysis, MTS assays. The results from MTS assays indicated that no significant cellular toxicity was shown in H1299 and HCT116 cells. Furthermore, the fluorescence marker fluorescein isothiocyanate (FITC) was added to PBPL & PGLP dispersions. From the fluorescent measurements showed that the chemical functionalisation of the PBPL/CNT & PGLP/CNT conjugates with the fluorescence marker were successful. The fluorescent PBPL/CNT & PGLP/CNT conjugates could find application in medical imaging. In the next step, the GFP gene is immobilized onto PBPL/CNT conjugates by introducing electrostatic interaction. GFP-transfected cells that emitted fluorescence were imaged and counted under a fluorescence microscope. Due to the unique biocompatibility of PBPL modified CNTs, the GFP gene could be transported into H1299 cells without using antibodies. The applicability of such soluble and chemically functionalised polypeptide/CNT conjugates in biomedicine is currently investigated. We expect that this polypeptide/CNT system will be a safe and multi-functional nanomedical delivery platform and contribute to future medical therapy.

Keywords: carbon nanotube, nanotoxicology, GFP transfection, polypeptide/CNT hybrids

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309 Morphological Process of Villi Detachment Assessed by Computer-Assisted 3D Reconstruction of Intestinal Crypt from Serial Ultrathin Sections of Rat Duodenum Mucosa

Authors: Lise P. Labéjof, Ivna Mororó, Raquel G. Bastos, Maria Isabel G. Severo, Arno H. de Oliveira

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This work presents an alternative mode of intestine mucosa renewal that may allow to better understand the total loss of villi after irradiation. It was tested a morphological method of 3d reconstruction using micrographs of serial sections of rat duodenum. We used hundreds of sections of each specimen of duodenum placed on glass slides and examined under a light microscope. Those containing the detachment, approximately a dozen, were chosen for observation under a transmission electron microscope (TEM). Each of these sections was glued on a block of epon resin and recut into a hundred of 60 nm-thick sections. Ribbons of these ultrathin sections were distributed on a series of copper grids in the same order of appearance than during the process of microstomia. They were then stained by solutions of uranyl and lead salts and observed under a TEM. The sections were pictured and the electron micrographs showing signs of cells detachment were transferred into two softwares, ImageJ to align the cellular structures and Reconstruct to realize the 3d reconstruction. It has been detected epithelial cells that exhibited all signs of programmed cell death and localized at the villus-crypt junction. Their nucleus was irregular in shape with a condensed chromatin in clumps. Their cytoplasm was darker than that of neighboring cells, containing many swollen mitochondria. In some places of the sections, we could see intercellular spaces enlarged by the presence of shrunk cells which displayed a plasma membrane with an irregular shape in thermowell as if the cell interdigitations would distant from each other. The three-dimensional reconstruction of the crypts has allowed observe gradual loss of intercellular contacts of crypt cells in the longitudinal plan of the duodenal mucosa. In the transverse direction, there was a gradual increase of the intercellular space as if these cells moved away from one another. This observation allows assume that the gradual remoteness of the cells at the villus-crypt junction is the beginning of the mucosa detachment. Thus, the shrinking of cells due to apoptosis is the way that they detach from the mucosa and progressively the villi also. These results are in agreement with our initial hypothesis and thus have demonstrated that the villi become detached from the mucosa at the villus-crypt junction by the programmed cell death process. This type of loss of entire villus helps explain the rapid denudation of the intestinal mucosa in case of irradiation.

Keywords: 3dr, transmission electron microscopy, ionizing radiations, rat small intestine, apoptosis

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308 Copper Price Prediction Model for Various Economic Situations

Authors: Haidy S. Ghali, Engy Serag, A. Samer Ezeldin

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Copper is an essential raw material used in the construction industry. During the year 2021 and the first half of 2022, the global market suffered from a significant fluctuation in copper raw material prices due to the aftermath of both the COVID-19 pandemic and the Russia-Ukraine war, which exposed its consumers to an unexpected financial risk. Thereto, this paper aims to develop two ANN-LSTM price prediction models, using Python, that can forecast the average monthly copper prices traded in the London Metal Exchange; the first model is a multivariate model that forecasts the copper price of the next 1-month and the second is a univariate model that predicts the copper prices of the upcoming three months. Historical data of average monthly London Metal Exchange copper prices are collected from January 2009 till July 2022, and potential external factors are identified and employed in the multivariate model. These factors lie under three main categories: energy prices and economic indicators of the three major exporting countries of copper, depending on the data availability. Before developing the LSTM models, the collected external parameters are analyzed with respect to the copper prices using correlation and multicollinearity tests in R software; then, the parameters are further screened to select the parameters that influence the copper prices. Then, the two LSTM models are developed, and the dataset is divided into training, validation, and testing sets. The results show that the performance of the 3-Month prediction model is better than the 1-Month prediction model, but still, both models can act as predicting tools for diverse economic situations.

Keywords: copper prices, prediction model, neural network, time series forecasting

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307 Chaotic Electronic System with Lambda Diode

Authors: George Mahalu

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The Chua diode has been configured over time in various ways, using electronic structures like operational amplifiers (AOs) or devices with gas or semiconductors. When discussing the use of semiconductor devices, tunnel diodes (Esaki diodes) are most often considered, and more recently, transistorized configurations such as lambda diodes. The paperwork proposed here uses in the modeling a lambda diode type configuration consisting of two junction field effect transistors (JFET). The original scheme is created in the MULTISIM electronic simulation environment and is analyzed in order to identify the conditions for the appearance of evolutionary unpredictability specific to nonlinear dynamic systems with chaos-induced behavior. The chaotic deterministic oscillator is one autonomous type, a fact that places it in the class of Chua’s type oscillators, the only significant and most important difference being the presence of a nonlinear device like the one mentioned structure above. The chaotic behavior is identified both by means of strange attractor-type trajectories and visible during the simulation and by highlighting the hypersensitivity of the system to small variations of one of the input parameters. The results obtained through simulation and the conclusions drawn are useful in the further research of ways to implement such constructive electronic solutions in theoretical and practical applications related to modern small signal amplification structures, to systems for encoding and decoding messages through various modern ways of communication, as well as new structures that can be imagined both in modern neural networks and in those for the physical implementation of some requirements imposed by current research with the aim of obtaining practically usable solutions in quantum computing and quantum computers.

Keywords: chua, diode, memristor, chaos

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306 Quercetin and INT3 Inhibits Endocrine Therapy Resistance and Epithelial to Mesenchymal Transition in MCF7 Breast Cancer Cells

Authors: S. Pradhan, D. Pradhan, G. Tripathy

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Anti-estrogen treatment resistant is a noteworthy reason for disease relapse and mortality in estrogen receptor alpha (ERα)- positive breast cancers. Tamoxifen or estrogen withdrawal increases the dependance of breast malignancy cells on INT3 signaling. Here, we researched the contribution of Quercetin and INT3 signaling in endocrine resistant breast cancer cells. Methods: We utilized two models of endocrine therapies resistant (ETR-) breast cancer: tamoxifen-resistant (TamR) and long term estrogen-deprived (LTED) MCF7 cells. We assessed the migratory and invasive limit of these cells by Transwell assay. Expression of epithelial to mesenchymal transition (EMT) controllers and in addition INT3 receptors and targets were assessed by real-time PCR and western blot analysis. Besides, we tried in vitro anti-Quercetin monoclonal antibodies (mAbs) and gamma secretase inhibitors (GSIs) as potential EMT reversal therapeutic agents. At last, we created stable Quercetin over expessing MCF7 cells and assessed their EMT features and response to tamoxifen. Results:We found that ETR cells acquired an epithelial to mesenchymal transition (EMT) phenotype and showed expanded levels of Quercetin and INT3 targets. Interestingly, we detected higher level of INT3 however lower levels of INT31 and INT32 proposing a switch to targeting through distinctive INT3 receptors after obtaining of resistance. Anti-Quercetin monoclonal antibodies and the GSI PF03084014 were effective in obstructing the Quercetin/INT3 axis and in part inhibiting the EMT process. As a consequence of this, cell migration and invasion were weakened and the stem cell like population was considerably decreased. Genetic hushing of Quercetin and INT3 prompted proportionate impacts. Finally, stable overexpression of Quercetin was adequate to make MCF7 lethargic to tamoxifen by INT3 activation. Conclusions: ETR cells express abnormal amounts of Quercetin and INT3, whose actuation eventually drives invasive conduct. Anti-Quercetin mAbs and GSI PF03084014 lessen expression of EMT molecules decreasing cellular invasiveness. Quercetin overexpression instigates tamoxifen resistance connected to obtaining of EMT phenotype. Our discovering propose that focusing on Quercetin and/or INT3 warrants further clinical assessment as substantial therapeutic methodologies in endocrine-resistant breast cancer.

Keywords: quercetin, INT3, mesenchymal transition, MCF7 breast cancer cells

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305 Self-Organizing Maps for Credit Card Fraud Detection and Visualization

Authors: Peng, Chun-Yi, Chen, Wei-Hsuan, Ueng, Shyh-Kuang

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This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

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304 TiO₂ Nanoparticles Induce DNA Damage and Expression of Biomarker of Oxidative Stress on Human Spermatozoa

Authors: Elena Maria Scalisi

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The increasing production and the use of TiO₂ nanoparticles (NPs) have inevitably led to their release into the environment, thereby posing a threat to organisms and also for human. Human exposure to TiO₂-NPs may occur during both manufacturing and use. TiO₂-NPs are common in consumer products for dermal application, toothpaste, food colorants, and nutritional supplements, then oral exposure may occur during use of such products. Into the body, TiO₂-NPs thanks to their small size (<100 nm), can, through testicular blood barrier inducing effect on testis and then on male reproductive health. The nanoscale size of TiO₂ increase the surface-to-volume ratio making them more reactive in a cell, then TiO₂ NPs increase their ability to produce reactive oxygen species (ROS). In male germ cells, ROS may have important implications in maintaining the normal functions of mature spermatozoa at physiological levels, moreover, in spermatozoa they are important signaling molecules for their hyperactivation and acrosome reaction. Nevertheless, an excess of ROS by external inputs such as NPs can increased the oxidative stress (OS), which results in damage DNA and apoptosis. The aim of our study has been investigate the impact of TiO₂ NPs on human spermatozoa, evaluating DNA damage and the expression of proteins involved in cell stress. According WHO guidelines 2021, we have exposed human spermatozoa in vitro to TiO₂ NP at concentrations 50 ppm, 100 ppm, 250 ppm, and 500 ppm for 1 hour (at 37°C and CO₂ at 5%). DNA damage was evaluated by Sperm Chromatin Dispersion Test (SCD) and TUNEL assay; moreover, we have evaluated the expression of biomarkers of oxidative stress like Heat Shock Protein 70 (HSP70) and Metallothioneins (MTs). Also, sperm parameters as motility viability have been evaluated. Our results not report a significant reduction in motility of spermatozoa at the end of the exposure. On the contrary, the progressive motility was increased at the highest concentration (500 ppm) and was statistically significant compared to control (p <0.05). Also, viability was not changed by exposure to TiO₂-NPs (p <0.05). However, increased DNA damage was observed at all concentrations, and the TUNEL assay highlighted the presence of single strand breaks in the DNA. The spermatozoa responded to the presence of TiO₂-NPs with the expression of Hsp70, which have a protective function because they allow the maintenance of cellular homeostasis in stressful/ lethal conditions. A positivity for MTs was observed mainly for the concentration of 4 mg/L. Although the biological and physiological function of the metallothionein (MTs) in the male genital organs is unclear, our results highlighted that the MTs expressed by spermatozoa maintain their biological role of detoxification from metals. Our results can give additional information to the data in the literature on the toxicity of TiO₂-NPs and reproduction.

Keywords: human spermatozoa, DNA damage, TiO₂-NPs, biomarkers

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303 Nanoceutical Intervention (Nanodrug) of Neonatal Hyperbilirubinemias Compared to Conventional Phototherapy

Authors: Samir Kumar Pal

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Background: Targeted rapid degradation of bilirubin has the potential to thwart incipient bilirubin encephalopathy. Uncontrolled hyperbilirubinemia is a potential problem in developing countries, including India, because of the lack of reliable healthcare institutes for conventional phototherapy. In India, most of the rural subjects duel in the exchange limit during transport, leading to a risk of kernicterus when they arrive at the treatment centre. Thus, an alternative pharmaceutical agent is needed for the hours. Objective: Exploration of a distinct therapeutic strategy for the control of neonatal hyperbilirubinemia compared to conventional phototherapy in a clinical setting. Method: We synthesized, characterized and investigated a spinel-structured Manganese citrate nanocomplex (C-Mn₃O₄ NC, the nanodrug) along with conventional phototherapy in neonatal subjects. We have also observed BIND scores in order to assess neurological dysfunctions. Results: Our observational study clearly reveals that the rate of declination of bilirubin in neonatal subjects with nanodrug oral administration and phototherapy is faster compared to that in the case of phototherapy only. The associated neural dysfunctions were also found to be significantly lower in the case of combined therapy. Conclusion: This study demonstrates that combined therapy works better than conventional phototherapy only for the control of hyperbilirubinemia. We have observed that a significant portion of neonatal subjects requiring blood exchange has been prevented with the combined therapeutic strategy. Further compilation of a drug-safety-dossier is warranted to translate this novel therapeutic chemo preventive approach to clinical settings.

Keywords: nanodrug, nanoparticle, Neonatal hyperbilirubinemia, alternative to phototherapy, redox modulation, redox medicine

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302 Security Issues in Long Term Evolution-Based Vehicle-To-Everything Communication Networks

Authors: Mujahid Muhammad, Paul Kearney, Adel Aneiba

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The ability for vehicles to communicate with other vehicles (V2V), the physical (V2I) and network (V2N) infrastructures, pedestrians (V2P), etc. – collectively known as V2X (Vehicle to Everything) – will enable a broad and growing set of applications and services within the intelligent transport domain for improving road safety, alleviate traffic congestion and support autonomous driving. The telecommunication research and industry communities and standardization bodies (notably 3GPP) has finally approved in Release 14, cellular communications connectivity to support V2X communication (known as LTE – V2X). LTE – V2X system will combine simultaneous connectivity across existing LTE network infrastructures via LTE-Uu interface and direct device-to-device (D2D) communications. In order for V2X services to function effectively, a robust security mechanism is needed to ensure legal and safe interaction among authenticated V2X entities in the LTE-based V2X architecture. The characteristics of vehicular networks, and the nature of most V2X applications, which involve human safety makes it significant to protect V2X messages from attacks that can result in catastrophically wrong decisions/actions include ones affecting road safety. Attack vectors include impersonation attacks, modification, masquerading, replay, MiM attacks, and Sybil attacks. In this paper, we focus our attention on LTE-based V2X security and access control mechanisms. The current LTE-A security framework provides its own access authentication scheme, the AKA protocol for mutual authentication and other essential cryptographic operations between UEs and the network. V2N systems can leverage this protocol to achieve mutual authentication between vehicles and the mobile core network. However, this protocol experiences technical challenges, such as high signaling overhead, lack of synchronization, handover delay and potential control plane signaling overloads, as well as privacy preservation issues, which cannot satisfy the adequate security requirements for majority of LTE-based V2X services. This paper examines these challenges and points to possible ways by which they can be addressed. One possible solution, is the implementation of the distributed peer-to-peer LTE security mechanism based on the Bitcoin/Namecoin framework, to allow for security operations with minimal overhead cost, which is desirable for V2X services. The proposed architecture can ensure fast, secure and robust V2X services under LTE network while meeting V2X security requirements.

Keywords: authentication, long term evolution, security, vehicle-to-everything

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301 Hematologic Inflammatory Markers and Inflammation-Related Hepatokines in Pediatric Obesity

Authors: Mustafa Metin Donma, Orkide Donma

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Obesity in children particularly draws attention because it may threaten the individual’s future life due to many chronic diseases it may lead to. Most of these diseases, including obesity itself altogether are related to inflammation. For this reason, inflammation-related parameters gain importance. Within this context, complete blood cell counts, ratios or indices derived from these counts have recently found some platform to be used as inflammatory markers. So far, mostly adipokines were investigated within the field of obesity. The liver is at the center of the metabolic pathways network. Metabolic inflammation is closely associated with cellular dysfunction. In this study, hematologic inflammatory markers and two major hepatokines, cytokines produced predominantly by the liver, fibroblast growth factor-21 (FGF-21) and fetuin A were investigated in pediatric obesity. Two groups were constituted from seventy-six obese children based on World Health Organization criteria. Group 1 was composed of children whose age- and sex-adjusted body mass index (BMI) percentiles were between 95 and 99. Group 2 consists of children who are above the 99ᵗʰ percentile. The first and the latter groups were defined as obese (OB) and morbid obese (MO). Anthropometric measurements of the children were performed. Informed consent forms and the approval of the institutional ethics committee were obtained. Blood cell counts and ratios were determined by an automated hematology analyzer. The related ratios and indexes were calculated. Statistical evaluation of the data was performed by the SPSS program. There was no statistically significant difference in terms of neutrophil-to lymphocyte ratio, monocyte-to-high density lipoprotein cholesterol ratio and the platelet-to-lymphocyte ratio between the groups. Mean platelet volume and platelet distribution width values were decreased (p<0.05), total platelet count, red cell distribution width (RDW) and systemic immune inflammation index values were increased (p<0.01) in MO group. Both hepatokines were increased in the same group; however, increases were not statistically significant. In this group, also a strong correlation was calculated between FGF-21 and RDW when controlled by age, hematocrit, iron and ferritin (r=0.425; p<0.01). In conclusion, the association between RDW, a hematologic inflammatory marker, and FGF-21, an inflammation-related hepatokine, found in MO group is an important finding discriminating between OB and MO children. This association is even more powerful when controlled by age and iron-related parameters.

Keywords: childhood obesity, fetuin A , fibroblast growth factor-21, hematologic markers, red cell distribution width

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300 Network Conditioning and Transfer Learning for Peripheral Nerve Segmentation in Ultrasound Images

Authors: Harold Mauricio Díaz-Vargas, Cristian Alfonso Jimenez-Castaño, David Augusto Cárdenas-Peña, Guillermo Alberto Ortiz-Gómez, Alvaro Angel Orozco-Gutierrez

Abstract:

Precise identification of the nerves is a crucial task performed by anesthesiologists for an effective Peripheral Nerve Blocking (PNB). Now, anesthesiologists use ultrasound imaging equipment to guide the PNB and detect nervous structures. However, visual identification of the nerves from ultrasound images is difficult, even for trained specialists, due to artifacts and low contrast. The recent advances in deep learning make neural networks a potential tool for accurate nerve segmentation systems, so addressing the above issues from raw data. The most widely spread U-Net network yields pixel-by-pixel segmentation by encoding the input image and decoding the attained feature vector into a semantic image. This work proposes a conditioning approach and encoder pre-training to enhance the nerve segmentation of traditional U-Nets. Conditioning is achieved by the one-hot encoding of the kind of target nerve a the network input, while the pre-training considers five well-known deep networks for image classification. The proposed approach is tested in a collection of 619 US images, where the best C-UNet architecture yields an 81% Dice coefficient, outperforming the 74% of the best traditional U-Net. Results prove that pre-trained models with the conditional approach outperform their equivalent baseline by supporting learning new features and enriching the discriminant capability of the tested networks.

Keywords: nerve segmentation, U-Net, deep learning, ultrasound imaging, peripheral nerve blocking

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299 Consumption and Diffusion Based Model of Tissue Organoid Development

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

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

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

Procedia PDF Downloads 293
298 Artificial Intelligence in Bioscience: The Next Frontier

Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

Procedia PDF Downloads 337
297 Design of Robust and Intelligent Controller for Active Removal of Space Debris

Authors: Shabadini Sampath, Jinglang Feng

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With huge kinetic energy, space debris poses a major threat to astronauts’ space activities and spacecraft in orbit if a collision happens. The active removal of space debris is required in order to avoid frequent collisions that would occur. In addition, the amount of space debris will increase uncontrollably, posing a threat to the safety of the entire space system. But the safe and reliable removal of large-scale space debris has been a huge challenge to date. While capturing and deorbiting space debris, the space manipulator has to achieve high control precision. However, due to uncertainties and unknown disturbances, there is difficulty in coordinating the control of the space manipulator. To address this challenge, this paper focuses on developing a robust and intelligent control algorithm that controls joint movement and restricts it on the sliding manifold by reducing uncertainties. A neural network adaptive sliding mode controller (NNASMC) is applied with the objective of finding the control law such that the joint motions of the space manipulator follow the given trajectory. A computed torque control (CTC) is an effective motion control strategy that is used in this paper for computing space manipulator arm torque to generate the required motion. Based on the Lyapunov stability theorem, the proposed intelligent controller NNASMC and CTC guarantees the robustness and global asymptotic stability of the closed-loop control system. Finally, the controllers used in the paper are modeled and simulated using MATLAB Simulink. The results are presented to prove the effectiveness of the proposed controller approach.

Keywords: GNC, active removal of space debris, AI controllers, MatLabSimulink

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296 The Importance of Visual Communication in Artificial Intelligence

Authors: Manjitsingh Rajput

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Visual communication plays an important role in artificial intelligence (AI) because it enables machines to understand and interpret visual information, similar to how humans do. This abstract explores the importance of visual communication in AI and emphasizes the importance of various applications such as computer vision, object emphasis recognition, image classification and autonomous systems. In going deeper, with deep learning techniques and neural networks that modify visual understanding, In addition to AI programming, the abstract discusses challenges facing visual interfaces for AI, such as data scarcity, domain optimization, and interpretability. Visual communication and other approaches, such as natural language processing and speech recognition, have also been explored. Overall, this abstract highlights the critical role that visual communication plays in advancing AI capabilities and enabling machines to perceive and understand the world around them. The abstract also explores the integration of visual communication with other modalities like natural language processing and speech recognition, emphasizing the critical role of visual communication in AI capabilities. This methodology explores the importance of visual communication in AI development and implementation, highlighting its potential to enhance the effectiveness and accessibility of AI systems. It provides a comprehensive approach to integrating visual elements into AI systems, making them more user-friendly and efficient. In conclusion, Visual communication is crucial in AI systems for object recognition, facial analysis, and augmented reality, but challenges like data quality, interpretability, and ethics must be addressed. Visual communication enhances user experience, decision-making, accessibility, and collaboration. Developers can integrate visual elements for efficient and accessible AI systems.

Keywords: visual communication AI, computer vision, visual aid in communication, essence of visual communication.

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295 Impact of Climate Change on Sea Level Rise along the Coastline of Mumbai City, India

Authors: Chakraborty Sudipta, A. R. Kambekar, Sarma Arnab

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Sea-level rise being one of the most important impacts of anthropogenic induced climate change resulting from global warming and melting of icebergs at Arctic and Antarctic, the investigations done by various researchers both on Indian Coast and elsewhere during the last decade has been reviewed in this paper. The paper aims to ascertain the propensity of consistency of different suggested methods to predict the near-accurate future sea level rise along the coast of Mumbai. Case studies at East Coast, Southern Tip and West and South West coast of India have been reviewed. Coastal Vulnerability Index of several important international places has been compared, which matched with Intergovernmental Panel on Climate Change forecasts. The application of Geographic Information System mapping, use of remote sensing technology, both Multi Spectral Scanner and Thematic Mapping data from Landsat classified through Iterative Self-Organizing Data Analysis Technique for arriving at high, moderate and low Coastal Vulnerability Index at various important coastal cities have been observed. Instead of data driven, hindcast based forecast for Significant Wave Height, additional impact of sea level rise has been suggested. Efficacy and limitations of numerical methods vis-à-vis Artificial Neural Network has been assessed, importance of Root Mean Square error on numerical results is mentioned. Comparing between various computerized methods on forecast results obtained from MIKE 21 has been opined to be more reliable than Delft 3D model.

Keywords: climate change, Coastal Vulnerability Index, global warming, sea level rise

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294 Connecting MRI Physics to Glioma Microenvironment: Comparing Simulated T2-Weighted MRI Models of Fixed and Expanding Extracellular Space

Authors: Pamela R. Jackson, Andrea Hawkins-Daarud, Cassandra R. Rickertsen, Kamala Clark-Swanson, Scott A. Whitmire, Kristin R. Swanson

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Glioblastoma Multiforme (GBM), the most common primary brain tumor, often presents with hyperintensity on T2-weighted or T2-weighted fluid attenuated inversion recovery (T2/FLAIR) magnetic resonance imaging (MRI). This hyperintensity corresponds with vasogenic edema, however there are likely many infiltrating tumor cells within the hyperintensity as well. While MRIs do not directly indicate tumor cells, MRIs do reflect the microenvironmental water abnormalities caused by the presence of tumor cells and edema. The inherent heterogeneity and resulting MRI features of GBMs complicate assessing disease response. To understand how hyperintensity on T2/FLAIR MRI may correlate with edema in the extracellular space (ECS), a multi-compartmental MRI signal equation which takes into account tissue compartments and their associated volumes with input coming from a mathematical model of glioma growth that incorporates edema formation was explored. The reasonableness of two possible extracellular space schema was evaluated by varying the T2 of the edema compartment and calculating the possible resulting T2s in tumor and peripheral edema. In the mathematical model, gliomas were comprised of vasculature and three tumor cellular phenotypes: normoxic, hypoxic, and necrotic. Edema was characterized as fluid leaking from abnormal tumor vessels. Spatial maps of tumor cell density and edema for virtual tumors were simulated with different rates of proliferation and invasion and various ECS expansion schemes. These spatial maps were then passed into a multi-compartmental MRI signal model for generating simulated T2/FLAIR MR images. Individual compartments’ T2 values in the signal equation were either from literature or estimated and the T2 for edema specifically was varied over a wide range (200 ms – 9200 ms). T2 maps were calculated from simulated images. T2 values based on simulated images were evaluated for regions of interest (ROIs) in normal appearing white matter, tumor, and peripheral edema. The ROI T2 values were compared to T2 values reported in literature. The expanding scheme of extracellular space is had T2 values similar to the literature calculated values. The static scheme of extracellular space had a much lower T2 values and no matter what T2 was associated with edema, the intensities did not come close to literature values. Expanding the extracellular space is necessary to achieve simulated edema intensities commiserate with acquired MRIs.

Keywords: extracellular space, glioblastoma multiforme, magnetic resonance imaging, mathematical modeling

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