Search results for: artificial cell

Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia

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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.

Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis

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Authors: Walid Tawfik, W. Askam Farooq, Sultan F. Alqhtani

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Quantum dots (QDots) are nanometer-sized crystals, less than 10 nm, comprise a semiconductor or metallic materials and contain from 100 - 100,000 atoms in each crystal. QDots play an important role in many applications; light emitting devices (LEDs), solar cells, drug delivery, and optical computers. In the current research, a fundamental wavelength of Nd:YAG laser was applied to analyse the impurities in homemade cadmium selenide (CdSe) QDots through laser-induced plasma (LIPS) technique. The CdSe QDots were fabricated by using hot-solution decomposition method where a mixture of Cd precursor and trioctylphosphine oxide (TOPO) is prepared at concentrations of TOPO under controlled temperatures 200-350ºC. By applying laser energy of 15 mJ, at frequency 10 Hz, and delay time 500 ns, LIPS spectra of CdSe QDots samples were observed. The qualitative LIPS analysis for CdSe QDs revealed that the sample contains Cd, Te, Se, H, P, Ar, O, Ni, C, Al and He impurities. These observed results gave precise details of the impurities present in the QDs sample. These impurities are important for future work at which controlling the impurity contents in the QDs samples may improve the physical, optical and electrical properties of the QDs used for solar cell application.

Keywords: cadmium selenide, TOPO, LIPS spectroscopy, quantum dots

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Authors: Safia Asif, Saadia Bano

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In a world with rapidly depleting resources, using artificial lighting during daytime is an act of human ignorance. Imitated light is the major source of energy consumption in public buildings. Despite, the fact that substantial working hours of these buildings usually persist in natural daylight time; there is a trend of isolated, un-fenestrated and a-contextual interiors majorly dependent on active energy sources. On the contrary, if direct and un-controlled sunlight is allowed inside the building, it will create visual and thermal discomfort. Controlled daylighting with appropriate design mechanisms is one of the important aspects of achieving thermal and visual comfort. The natural sunlight can be utilized intelligently with the help of architectural thermal controlling mechanisms to achieve a healthy and productive environment. This paper is an attempt to investigate and analyze the importance of daylighting with reference to energy efficiency and thermal comfort. For this purpose, three public buildings including two educational institutions and one general post office are selected, as case-studies in the context of Karachi, Pakistan. Various parameters of visual and thermal comfort are analyzed which includes orientation, ceiling heights, overall building profile along with daylight controlling mechanisms in terms of penetration, distribution, protection, and control. In the later part of the research, a questionnaire survey is also conducted to evaluate the user experience in terms of adequate daylighting and thermal comfort.

Keywords: daylight, public buildings, sustainable architecture, visual and thermal comfort

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Authors: Min-Ju Jo, Min-Young Um, Moonsung Choi, Sooim Shin

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Type 2 diabetes (T2D) is characterized by insulin resistance, the inability of β-cell and the dysfunction of mitochondria. To characterize effects of Cassia tora extract on mitochondrial dysfunction related T2D, the reduced glutathione level, amount of mitochondrial complexes and activities of mitochondrial complexes were measured. Three groups of mice were modeled; a control group was fed a normal diet, a diabetic group was fed a diabetic diet high in fat and carbohydrates, and a third group was fed a diabetic diet + 70% ethanol extracted Cassia tora seeds for 12 weeks. The amount of mitochondria was determined by Bradford assay after isolation of mitochondria in liver from each group. During isolation of mitochondria, cytosolic fractions of the tissue were collected to measure the reduced glutathione level. Interestingly, high level of the reduced glutathione was observed in Cassia tora treated group and decreased activities of mitochondrial complexes in Cassia tora treated group compared to the diabetic diet group. It indicates that Cassia tora has the potential to increase the reduced form of glutathione functioned as an important antioxidant in cells, and to reduce mitochondrial metabolic compensatory mechanism.

Keywords: antioxidant, Cassia tora, diabetes, electron transport chain, glutathione, mitochondria, spectrophotometry

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Authors: Elham Mahdian, Reza Karazhian, Rahele Dehghan Tanha

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Pepper (Capsicum annum L.) which belong to the family Solananceae, are known for their versatility as a vegetable crop and are consumed both as fresh vegetables or dehydrated for spices. Pepper is considered an excellent source of bioactive nutrients. Ascorbic acid, carotenoids and phenolic compounds are its main antioxidant constituents. Ultrasound assisted extraction is an inexpensive, simple and efficient alternative to conventional extraction techniques. The mechanism of action for ultrasound-assisted extraction are attributed to cavitations, mechanical forces and thermal impact, which result in disruption of cells walls, reduce particle size, and enhance mass transfer across cell membranes. In this study, response surface methodology was used to optimize experimental conditions for ultrasonic assisted extraction of carotenoid compounds from Chili peppers. Variables were included extraction temperatures at 3 levels (30, 40 and 50 °C), extraction times at 3 levels (10, 25 and 40 minutes) and power at 3 levels (30, 60 and 90 %). It was observed that ultrasound waves applied at temperature of 49°C, time of 10 minutes and power 89 % resulted to the highest carotenoids contents (lycopene and β-carotene), while the lowest value was recorded in the control. Thus, results showed that ultrasound waves have strong impact on extraction of carotenoids from pepper.

Keywords: carotenoids, optimization, pepper, response surface methodology

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Authors: Yehjune Heo

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Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Keywords: anti-spoofing, CNN, fingerprint recognition, GAN

Procedia PDF Downloads 184

Authors: Yousry El-Sayed Elbolkiny, Mohamed Labib Salem

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Background: Rosemary (ROLE) and costus (SLRE) have been established to show antioxidant effects. Aim: This study aimed to evaluate the ameliorating effects of ROLE and SLRE on the side effects induced by cisplatin (CIS) in tumor-bearing mice. Materials and Methods: Extracts of ROLE and SLRE were examined for their phytochemical activities. To evaluate their anti-tumor effects, mice were inoculated intraperitoneally (i.p.) with 2.5x105 Ehrlich ascites carcinoma (EAC) and then treated i.p. with CIS at days 3-7 and with ROLE (dose) or SLRE (dose) at days 3-14. Mice were sacrificed on day 14 for CBC and T-cell analyses. Results: Phytochemical analysis revealed that both ROLE and SLRE showed similar antioxidant activities. Treatment of EAC-bearing mice with CIS-induced antitumor efficacy of about 90%. Treatment with CIS in combination with ROLE or SLRE did not further enhance the antitumor activity of CIS. However, co-administration of ROLE or SLRE with CIS significantly increased the antitumor efficacy of CIS. Flow cytometric analysis showed that the numbers of CD4+ and CD8+ T cells were decreased in EAC-bearing mice after treatment with CIS. Treatment with both ROLE and SLRE improved the number of these cells. Conclusion: Combinatorial treatment with rosemary and costus can enhance the antitumor activity of CIS

Keywords: CBC, cisplantin, costus, rosemary

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

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Authors: Payel Ghosh, Rama Chandra Pradhan, Sabyasachi Mishra

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Jamun (Syzygium cuminii L.) is one of the important indigenous minor fruit with high medicinal value. The jamun cultivation is unorganized and there is huge loss of this fruit every year. The perishable nature of the fruit makes its postharvest management further difficult. Due to the strong cell wall structure of pectin-protein bonds and hard seeds, extraction of juice becomes difficult. Enzymatic treatment has been commercially used for improvement of juice quality with high yield. The objective of the study was to optimize the best treatment method for juice extraction. Enzymes (Pectinase and Tannase) from different stains had been used and for each enzyme, best result obtained by using response surface methodology. Optimization had been done on the basis of physicochemical property, nutritional property, sensory quality and cost estimation. According to quality aspect, cost analysis and sensory evaluation, the optimizing enzymatic treatment was obtained by Pectinase from Aspergillus aculeatus strain. The optimum condition for the treatment was 44 ^oC with 80 minute with a concentration of 0.05% (w/w). At these conditions, 75% of yield with turbidity of 32.21NTU, clarity of 74.39%T, polyphenol content of 115.31 mg GAE/g, protein content of 102.43 mg/g have been obtained with a significant difference in overall acceptability.

Keywords: enzymatic treatment, Jamun, optimization, physicochemical property, sensory analysis

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Authors: J. Barilla, M. Lokajíček, H. Pisaková, P. Simr

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The final biological effect of ionizing particles may be influenced strongly by some chemical substances present in cells mainly in the case of low-LET radiation. The influence of oxygen may be particularly important because oxygen is always present in living cells. The corresponding processes are then running mainly in the chemical stage of radio biological mechanism. The radical clusters formed by densely ionizing ends of primary or secondary charged particles are mainly responsible for final biological effect. The damage effect depends then on radical concentration at a time when the cluster meets a DNA molecule. It may be strongly influenced by oxygen present in a cell as oxygen may act in different directions: at small concentration of it the interaction with hydrogen radicals prevails while at higher concentrations additional efficient oxygen radicals may be formed. The basic radical concentration in individual clusters diminishes, which is influenced by two parallel processes: chemical reactions and diffusion of corresponding clusters. The given simultaneous evolution may be modeled and analyzed well with the help of Continuous Petri nets. The influence of other substances present in cells during irradiation may be studied, too. Some results concerning the impact of oxygen content will be presented.

Keywords: radiobiological mechanism, chemical phase, DSB formation, Petri nets

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Authors: H. Yousefnia, S. Zolghadri, A. Golabi Dezfuli

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Tris (1,10-phenanthroline) lanthanum(III)] trithiocyanate is a new compound that has shown to stop DNA synthesis in CCRF-CEM and Ehrlich ascites cells leading to a cell cycle arrest in G0/G1. One other important property of the phenanthroline nucleus is its ability to act as a triplet-state photosensitizer especially in complexes with lanthanides. In Nowadays, the radiation dose assessment resource (RADAR) method is known as the most common method for absorbed dose calculation. 177Lu was produced by irradiation of a natural Lu2O3 target at a thermal neutron flux of approximately 4 × 1013 n/cm2•s. 177Lu-PL3 was prepared in the optimized condition. The radiochemical yield was checked by ITLC method. The biodistribution of the complex was investigated by intravenously injection to wild-type rats via their tail veins. In this study, the absorbed dose of 177Lu-PL3 to human organs was estimated by RADAR method. 177Lu was prepared with a specific activity of 2.6-3 GBq.mg-1 and radionuclide purity of 99.98 %. The 177Lu-PL3 complex can prepare with high radiochemical yield (> 99 %) at optimized conditions. The results show that liver and spleen have received the highest absorbed dose of 1.051 and 0.441 mSv/MBq, respectivley. The absorbed dose values for these two dose-limiting tissues suggest more biological studies special in tumor-bearing animals.

Keywords: internal dosimetry, Lutetium-177, radar, animals

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Authors: Haifa El-Sadi, Maria Elektorowicz, Reed Rushing, Ammar Badawieh, Asif Chaudry

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Clay soils have particular properties that affect the assessment and remediation of contaminated sites. In clay soils, electro-kinetic transport of heavy metals has been carried out. The transport of these metals is predicated on maintaining a low pH throughout the cell, which, in turn, keeps the metals in the pore water phase where they are accessible to electro-kinetic transport. Supercritical fluid extraction and acid digestion were used for the analysis of heavy metals concentrations after the completion of electro-kinetic experimentation. Supercritical fluid (carbon dioxide) extraction is a new technique used to extract the heavy metal (lead, nickel, calcium and potassium) from clayey soil. The comparison between supercritical extraction and acid digestion of different metals was carried out. Supercritical fluid extraction, using ethylenediaminetetraacetic acid (EDTA) as a modifier, proved to be efficient and a safer technique than acid digestion technique in extracting metals from clayey soil. Mixing time of soil with EDTA before extracting heavy metals from clayey soil was investigated. The optimum and most practical shaking time for the extraction of lead, nickel, calcium and potassium was two hours.

Keywords: clay soil, heavy metals, supercritical fluid extraction, acid digestion

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Authors: R. Ondarza-Rovira, T. J. M. Boyd

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Intense femtosecond laser light incident on over-critical density plasmas has shown to emit a prolific number of high-order harmonics of the driver frequency, with spectra characterized by power-law decays Pm ~ m-p, where m denotes the harmonic order and p the spectral decay index. When the laser pulse is p-polarized, plasma effects do modify the harmonic spectrum, weakening the so-called universal decay with p=8/3 to p=5/3, or below. In this work, appeal is made to a single particle radiation model in support of the predictions from particle-in-cell (PIC) simulations. Using this numerical technique we further show that the emission radiated by electrons -that are relativistically accelerated by the laser field inside the plasma, after being expelled into vacuum, the so-called Brunel electrons is characterized not only by the plasma line but also by ultraviolet harmonic orders described by the 5/3 decay index. Results obtained from these simulations suggest that for ultra-relativistic light intensities, the spectral decay index is further reduced, with p now in the range 2/3 ≤ p ≤ 4/3. This reduction is indicative of a transition from the regime where Brunel-induced plasma radiation influences the spectrum to one dominated by bremsstrahlung emission from the Brunel electrons.

Keywords: ultra-relativistic, laser-plasma interactions, high-order harmonic emission, radiation, spectrum

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Authors: Irnie Zakaria, W. A. N. W. Mohamed, W. H. Azmi

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Thermal enhancement of a single mini channel in Proton Exchange Membrane Fuel Cell (PEMFC) cooling plate is numerically investigated. In this study, low concentration of Al2O3 in Water - Ethylene Glycol mixtures is used as coolant in mini channel of carbon graphite plate to mimic the PEMFC cooling plate. A steady and incompressible flow with constant heat flux is assumed in the channel of 1mm x 5mm x 100mm. Nano particle of Al2O3 used ranges from 0.1, 0.3 and 0.5 vol % concentration and then dispersed in 60:40 (water: Ethylene Glycol) mixture. The effect of different flow rates to fluid flow and heat transfer enhancement in Re number range of 20 to 140 was observed. The result showed that heat transfer coefficient was improved by 18.11%, 9.86% and 5.37% for 0.5, 0.3 and 0.1 vol % Al2O3 in 60:40 (water: EG) as compared to base fluid of 60:40 (water: EG). It is also showed that the higher vol % concentration of Al2O3 performed better in term of thermal enhancement but at the expense of higher pumping power required due to increase in pressure drop experienced. Maximum additional pumping power of 0.0012W was required for 0.5 vol % Al2O3 in 60:40 (water: EG) at Re number 140.

Keywords: heat transfer, mini channel, nanofluid, PEMFC

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Authors: Ayoola, Simeon Oluwatoyin, Omogoriola Hannah Omoloye

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The effects of 17α-Methyltestosterone Hormone on blood composition of the Sex Reversed Sarotherodon melanotheron were investigated. S. melanotheron fry were reared in six (6) plastic tanks for three (3) months, of which three (3) tanks served as treatment tanks while the other three (3) served as the control. The fry were fed with 17α-methyl testosterone enzyme, which functions as a sex reversal hormone. The fry were administered this hormone for 30 days, to ensure complete sex reversal. All the S. melanotheron fry were reared to table size for duration of three (3) months, after which, blood samples were taken from both the control and treatment fishes. The blood parameters showed no significant differences with the same values of White Blood Cell count (WBC) and Total plasma protein for the control and experimental fishes. A total protein value for sex reversed specimens was 3.99g/dL, while urea and creatinine values were 0.2g/dL. Alkaline Phosphatase, Aspartate transaminase and Alanine transaminase for the treatment specimen were 183nm/mg protein/min, 98nm/mg protein/min and 105nm/mg protein/min respectively. A total protein value for control specimens was 2.81g/dL, while urea and creatinine values were 0.2g/dL. Alkaline Phosphatase, Aspartate transaminase and Alanine transaminase for the control species were 174nm/mg protein/min, 93nm/mg protein/min and 106nm/mg protein/min respectively. The safety of MT on S. melanotheron is therefore proved since there is no adverse effect on the fish.

Keywords: 17α-Methyltestosterone, haematology, sex reversal, sarotherodon melanotheron

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Authors: Arash Esfandiari, Ebrahim Parsaei

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The purpose of this research was to survey the effect of tribulus terresteris on histomorphometrical changes of testis induced by ethanol administration in male wistar rats. Fifteen male wistar rats divided into three groups: 1- control group (n=5). 2- Experimental group I (IP received 1 mg/gr Alcohole 20% for 30 days) (n=5). 3- Experimental group II (IP received 1 mg/gr Alcohole 20% for 30 days and IP received 100 mg/kg tribulus terresteris 15 days before received Alcohole for 45 days) (n=5). All procedures and care of the animals were conducted following protocols approved by the ethical committee (Iranian Society for the Prevention of cruelty to animal, and Iranian Veterinary Organization). Results showed that the thickness of the wall of seminiferous tubule, the weight of testis, the number of spermatogenic cells were decreased in experimental group I. In addition, all of these parameters were increased in experimental group II compared with experimental group I. These decrement of all of parameters in experimental group I with significant difference in comparison control group (p≤ 0.05). But all of parameters had increment in experimental group II with no significant difference compared with control group (p≥ 0.05) and significant difference with experimental group I (p≤ 0.05).It is concluded that tribulus terresteris may prevent from reducing the number of spermatogenic cell that has been created by the consumption of alcohole.

Keywords: ethanol, histomorphometric, testis, teribulus terresteris

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Authors: Sang Guen Kim, Sib Sankar Giri, Jin Woo Jun, Saekil Yun, Hyoun Joong Kim, Sang Wha Kim, Jung Woo Kang, Se Jin Han, Se Chang Park

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Emerging of the super bacteria, bacteriophages are considered to be as an alternative to antibiotics. As the demand of phage increased, economical and large production of phage is becoming one of the critical points. For the therapeutic use, what is important is to eradicate the pathogenic bacteria as fast as possible, so higher concentration of phages is generally needed for effective therapeutic function. On the contrary, for the maximum production, bacteria work as a phage producing factory. As a microbial cell factory, bacteria is needed to last longer producing the phages without eradication. Consequently, killing the bacteria fast has a negative effect on large production. In this study, Multiplicity of Infection (MOI) was manipulated based on initial bacterial inoculation and used phage pAh-6C which has therapeutic effect against Aeromonas hydrophila. 1, 5 and 10 percent of overnight bacterial culture was inoculated and each bacterial culture was co-cultured with the phage of which MOI of 0.01, 0.0001, and 0.000001 respectively. Simply changing the initial MOI as well as bacterial inoculation concentration has regulated the production quantity of the phage without any other changes to culture conditions. It is anticipated that this result can be used as a foundational data for mass production of lytic bacteriophages which can be used as the therapeutic bio-control agent.

Keywords: bacteriophage, multiplicity of infection, optimization, Aeromonas hydrophila

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Authors: Shuofeng Yuan, Bojian Zheng

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Assembly of the heterotrimeric polymerase complex of influenza virus from the individual subunits PB1, PA, and PB2 is a prerequisite for viral replication, in which the interaction between the N-terminal of PB1 (PB1N) and the C terminal of PA (PAC) may be a desired target for antiviral development. In this study, we first compared the feasibility of high throughput screening by enzyme-linked immunosorbent assay (ELISA) and fluorescence polarization (FP) assay. Among the two, ELISA was demonstrated to own broader dynamic range so that it was used for screening inhibitors, which blocked PA and PB1 interaction. Several binding inhibitors of PAC-PB1N were identified and subsequently tested for the antiviral efficacy. Apparently, 3-(2-chlorophenyl)-6-ethyl-7-methyl[1,2,4]triazolo[4,3-a]pyrimidin-5-ol, designated ANA-1, was found to be a strong inhibitor of PAC-PB1N interaction and act as a potent antiviral agent against the infections of multiple subtypes of influenza A virus, including H1N1, H3N2, H5N1, H7N7, H7N9 and H9N2 subtypes, in cell cultures. Intranasal administration of ANA-1 protected mice from lethal challenge and reduced lung viral loads in H1N1 virus infected BALB/c mice. Docking analyses predicted that ANA-1 bound to an allosteric site of PAC, which would cause conformational changes thereby disrupting the PAC-PB1N interaction. Overall, our study has identified a novel compound with potential to be developed as an anti-influenza drug.

Keywords: influenza, antiviral, viral polymerase, compounds

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Authors: Rakesh Hajiyani, Chetan Chauhan, Harshkant Jethva, Mihir Joshi

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Metal bis-thiourea type organo-metallic crystals are popular as non-linear optical materials. Bis-thiourea nickel barium chloride was synthesized and crystals were grown by slow aqueous solvent evaporation technique. The transparent and colorless crystals having maximum dimensions of 13 mm x 8 mm x 2.2 mm were obtained. The EDAX was carried out to estimate the content of nickel and barium in the grown crystals. The powder XRD analysis suggested orthorhombic crystal structure with unit cell parameters as: a= 9.70 Å, b= 10.68 Å and c= 17.95 Å. The FTIR spectroscopy study confirmed the presence of various functional groups. The UV-vis spectroscopy study indicated that the crystals were transparent in the visible region with 90% transmittance level further optical parameters were studied. From the TGA it was found that the crystals remained stable up to 170 0C and then decomposed through two decomposition stages. The dielectric study was carried out in the frequency range of applied field from 500 Hz to 1 MHz. The variations of dielectric constant, dielectric loss were studied with frequency. It was found that the dielectric constant and the dielectric loss decreased as the frequency of applied field increased. The results are discussed.

Keywords: crystal growth, dielectric study, optical parameters, organo-metallic crystals, powder xrd, slow evaporation technique, TGA

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Authors: Abul B. M. M. K. Islam, Nuria Lopez-Bigas, Elizaveta V. Benevolenskaya

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RBP2 has shown to be important for cell differentiation control through epigenetic mechanism. The main aim of the present study is genome-wide location analysis of human RBP2 isoforms that differ in a histone-binding domain by ChIPseq. It is conceivable that the larger isoform (LI) of RBP2, which contains a specific H3K4me3 interacting domain, differs from the smaller isoform (SI) in genomic location, may account for the observed diversity in RBP2 function. To distinguish the two RBP2 isoforms, we used the fact that the SI lacks the C-terminal PHD domain and hence used the antibodies detecting both RBP2 isoforms (AI) through a common central domain, and the antibodies detecting only LI but not SI, through a C-terminal PHD domain. Overall our analysis suggests that RBP2 occupies about 77 nucleotides and binds GC rich motifs of active genes, does not bind to centromere, telomere, or enhancer regions, and binding sites are conserved compare to random. A striking difference between the only-SI and only-LI is that a large number of only-SI peaks are located in CpG islands and close to TSS compared to only-LI peaks. Enrichment analysis of the related genes indicates that several oncogenic pathways and metabolic pathways/processes are significantly enriched among only-SI/AI targets, but not LI/only-LI peak’s targets.

Keywords: bioinformatics, cancer, ChIP-seq, KDM5A

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Authors: Christodoulou Christos, Politis Anastasios

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The utilization of Wireless Body Area Network (WBAN) is experiencing a notable surge in popularity as a result of its widespread implementation in the field of smart health. WBANs utilize small sensors implanted within the human body to monitor and record physiological indicators. These sensors transmit the collected data to hospitals and healthcare facilities through designated access points. Bio-sensors exhibit a diverse array of shapes and sizes, and their deployment can be tailored to the condition of the individual. Multiple sensors may be strategically placed within, on, or around the human body to effectively observe, record, and transmit essential physiological indicators. These measurements serve as a basis for subsequent analysis, evaluation, and therapeutic interventions. In conjunction with physical health concerns, numerous smartwatches are engineered to employ artificial intelligence techniques for the purpose of detecting mental health conditions such as depression and anxiety. The utilization of smartwatches serves as a secure and cost-effective solution for monitoring mental health. Physiological signals are widely regarded as a highly dependable method for the recognition of emotions due to the inherent inability of individuals to deliberately influence them over extended periods of time. The techniques that WBANs employ to recognize emotions are thoroughly examined in this article.

Keywords: emotion recognition, wireless body area network, WBAN, ERC, wearable devices, psychological signals, emotion, smart-watch, prediction

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Authors: Amthal Al-Gailani, Olujide Sanni, Thibaut Charpentier, Anne Neville

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Formation of inorganic scale on heat transfer surfaces is a serious problem encountered in industrial, commercial, and domestic heat exchangers and systems. Several industries use potable/groundwater sources such as rivers, lakes, and oceans to use water as a working fluid in heat exchangers and steamers. As potable/surface water contains diverse salt ionic species, the scaling kinetics and deposit morphology are expected to be different from those found in artificially hardened solutions. In this work, scale formation on the heat transfer surfaces from potable water has been studied using a once-through open flow cell under atmospheric pressure. The surface scaling mechanism and deposit morphology are investigated at high surface temperature. Thus the water evaporation process has to be considered. The effect of surface temperature, flow rate, and inhibitor deployment on the thermal resistance and morphology of the scale have been investigated. The study findings show how an increase in surface temperature enhances the crystallization reaction kinetics on the surface. There is an increase in the amount of scale and the resistance to heat transfer. The fluid flow rate also increases the fouling resistance and the thickness of the scale layer.

Keywords: fouling, heat exchanger, thermal resistance, crystallization, potable water

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Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: artificial intelligence, COVID-19, depression detection, psychiatric disorder

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Authors: Nathaniel Carpenter

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Web-enabled systems for supporting youth mental health management in Australia are pioneering in their field; however, with their success, these systems are experiencing exponential growth in demand which is straining an already stretched service. Supporting youth mental is critical as the lack of support is associated with significant and lasting negative consequences. To meet this growing demand, and provide critical support, investigations are needed on evaluating and improving existing online support services. Improvements should focus on developing frameworks capable of augmenting and scaling service provisions. There are few investigations informing best-practice frameworks when implementing e-mental health support systems for youth mental health; there are fewer which implement machine learning or artificially intelligent systems to facilitate the delivering of services. This investigation will use a case study methodology to highlight the design features which are important for systems to enable young people to self-manage their mental health. The investigation will also highlight the current information system challenges, to include challenges associated with service quality, provisioning, and scaling. This work will propose methods of meeting these challenges through improved design, service augmentation and automation, service quality, and through artificially intelligent inspired solutions. The results of this study will inform a framework for supporting youth mental health with intelligent and scalable web-enabled technologies to support an ever-growing user base.

Keywords: artificial intelligence, information systems, machine learning, youth mental health

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Authors: Madhuresh Dwivedi, Navneet Singh Deora, H. N. Mishra

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In the context of bakery products, the gluten component of wheat has a crucial role in stabilizing the gas-cell and crumb structures, appearance, mouth feel and maintaining the rheological properties, thus the acceptability of these products. However, because of coeliac disease, some individuals cannot tolerate the protein gliadin present in the gluten fraction of wheat flour. Also termed as gluten-sensitive enteropathy, it is a common chronicle disorder in populations throughout the world with average prevalence of 0.37%. The safest way for celiac sufferers is to stay away from gluten-containing foods such as wheat, rye, barley as well as durum wheat, spelt wheat, and triticale. Thus, in view of the current increasing incidence of gluten intolerant sufferers (due to improved diagnostic procedures), the development of gluten-free cereal-based bakery products suitable for celiac patients represents a challenging and serious task, but also very demanding call for food technologists as well as for the bakers. The use of alternative cereal starches (like rice, soy, maize, potato and so on), gums, hydrocolloids, dietary fibres, alternative protein sources, prebiotics and combinations of them represent the most widespread approach used as replacement to mimic gluten in the manufacture of industrial processable gluten-free bakery products due to their structure-building and water binding properties.

Keywords: gluten-free, coeliac disease, alternative flour, hydrocolloid, crumb structure

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Authors: Abdulkader Helwan

Abstract:

Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

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Authors: Daudi S. Simbeye, Mbazingwa E. Mkiramweni

Abstract:

Plant diseases have the potential to drastically diminish the quantity and quality of agricultural products. Guava (Psidium guajava), sometimes known as the apple of the tropics, is one of the most widely cultivated fruits in tropical regions. Monitoring plant health and diagnosing illnesses is an essential matter for sustainable agriculture, requiring the inspection of visually evident patterns on plant leaves and fruits. Due to minor variations in the symptoms of various guava illnesses, a professional opinion is required for disease diagnosis. Due to improper pesticide application by farmers, erroneous diagnoses may result in economic losses. This study proposes a method that uses artificial intelligence (AI) to detect and classify the most widespread guava plant by comparing images of its leaves and fruits to datasets. ESP32 CAM is responsible for data collection, which includes images of guava leaves and fruits. By comparing the datasets, these image formats are used as datasets to help in the diagnosis of plant diseases through the leaves and fruits, which is vital for the development of an effective automated agricultural system. The system test yielded the most accurate identification findings (99 percent accuracy in differentiating four guava fruit diseases (Canker, Mummification, Dot, and Rust) from healthy fruit). The proposed model has been interfaced with a mobile application to be used by smartphones to make a quick and responsible judgment, which can help the farmers instantly detect and prevent future production losses by enabling them to take precautions beforehand.

Keywords: early identification, guava plants, fruit diseases, deep learning

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Authors: Juhi Faridi, Mohd. Ajmal Kafeel

Abstract:

The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems

Procedia PDF Downloads 176

Authors: Naser Shagerdi Esmaeli, Mohsen Hamidpour, Parisa Hasankhani Tehrani

Abstract:

Background: The TP53 mutation is frequently detected in acute myeloid leukemia (AML) patients with complex karyotype (CK), but the stability of this mutation during the clinical course remains unclear. Material and Methods: In this study, TP53 mutations were identified in 7% of 500 patients with de novo AML and 58.8% of patients with CK in Tabriz, Iran. TP53 mutations were closely associated with older age, lower white blood cell (WBC) and platelet counts, FAB M6 subtype, unfavorable-risk cytogenetics, and CK, but negatively associated with NPM1 mutation, FLT3/ITD and DNMT3A mutation. Result: Multivariate analysis demonstrated that TP53 mutation was an independent poor prognostic factor for overall survival and disease-free survival among the total cohort and the subgroup of patients with CK. A scoring system incorporating TP53 mutation and nine other prognostic factors, including age, WBC counts, cytogenetics, and gene mutations, into survival analysis proved to be very useful to stratify AML patients. Sequential study of 420 samples showed that TP53 mutations were stable during AML evolution, whereas the mutation was acquired only in 1 of the 126 TP53 wild-type patients when therapy-related AML originated from different clone emerged. Conclusion: In conclusion, TP53 mutations are associated with distinct clinic-biological features and poor prognosis in de novo AML patients and are rather stable during disease progression.

Keywords: acute myloblastic leukemia, TP53, FLT3/ITD, Iran

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Authors: John Gibbs, Benjamin Flanders, Dylan Pozorski, Weixuan Liu

Abstract:

Weight Painting–adjusting the influence a skeletal joint has on a given vertex in a character mesh–is an arduous and time con- suming part of the 3D animation pipeline. This process generally requires a trained technical animator and many hours of work to complete. Our skiNNer plug-in, which works within Autodesk’s Maya 3D animation software, uses Machine Learning and data pro- cessing techniques to create a deep neural network model that can accomplish the weight painting task in seconds rather than hours for bipedal quasi-humanoid character meshes. In order to create a properly trained network, a number of challenges were overcome, including curating an appropriately large data library, managing an arbitrary 3D mesh size, handling arbitrary skeletal architectures, accounting for extreme numeric values (most data points are near 0 or 1 for weight maps), and constructing an appropriate neural network model that can properly capture the high frequency alter- ation between high weight values (near 1.0) and low weight values (near 0.0). The arrived at neural network model is a cross between a traditional CNN, deep residual network, and fully dense network. The resultant network captures the unusually hard-edged features of a weight map matrix, and produces excellent results on many bipedal models.

Keywords: 3d animation, animation, character, rigging, skinning, weight painting, machine learning, artificial intelligence, neural network, deep neural network

Procedia PDF Downloads 274