Search results for: protein secondary structure prediction

Authors: Guido Trautmann-Sáez, Mario Pérez-Won, Vilbett Briones, María José Bugueño, Gipsy Tabilo-Munizaga, Luis Gonzáles-Cavieres

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Shrimp by-products are a valuable source of protein. However, traditional protein extraction methods have limitations in terms of their efficiency. Protein extraction from shrimp (Pleuroncodes monodon) industrial by-products assisted with ohmic heating (OH), microwave (MW) and pulsed electric field (PEF). It was performed by chemical method (using NaOH and HCl 2M) assisted with OH, MW and PEF in a continuous flow system (5 ml/s). Protein determination, differential scanning calorimetry (DSC) and Fourier-transform infrared (FTIR). Results indicate a 19.25% (PEF) 3.65% (OH) and 28.19% (MW) improvement in protein extraction efficiency. The most efficient method was selected for the electrospinning process and obtaining fiber.

Keywords: electrospinning process, emerging technology, protein extraction, shrimp by-products

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Authors: Gulcin Yildiz, Hao Feng

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In recent years there is growing interested in using soy protein because of several advantages compared to other protein sources, such as high nutritional value, steady supply, and low cost. Soy protein isolate (SPI) is the most refined soy protein product. It contains 90% protein in a moisture-free form and has some desirable functionalities. Creating a protein-polysaccharide conjugate to be the emulsifying agent rather than the protein alone can markedly enhance its stability. This study was undertaken to examine the effects of ultrasound treatments on the physicochemical properties of SPI-starch conjugates. The soy protein isolate (SPI, Pro-Fam® 955) samples were obtained from the Archer Daniels Midland Company. Protein concentrations were analyzed by the Bardford method using BSA as the standard. The volume-weighted mean diameters D [4,3] of protein–polysaccharide conjugates were measured by dynamic light scattering (DLS). Surface hydrophobicity of the conjugates was measured by using 1-anilino-8-naphthalenesulfonate (ANS) (Sigma-Aldrich, St. Louis, MO, USA). Increasing the pH from 2 to 12 resulted in increased protein solubility. The highest solubility was 69.2% for the sample treated with ultrasonication at pH 12, while the lowest (9.13%) was observed in the Control. For the other pH conditions, the protein solubility values ranged from 40.53 to 49.65%. The ultrasound treatment significantly decreased the particle sizes of the SPI-modified starch conjugates. While the D [4,3] for the Control was 731.6 nm, it was 293.7 nm for the samples treated by sonication at pH 12. The surface hydrophobicity (H0) of SPI-starch at all pH conditions were significantly higher than those in the Control. Ultrasonication was proven to be effective in improving the solubility and emulsifying properties of soy protein isolate-starch conjugates.

Keywords: particle size, solubility, soy protein isolate, ultrasonication

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Authors: Mark Bezner, Shani Deri, Tom Trigano, Kfir Ben-Harush

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Intermediate filament (IF) proteins-based fibers are among the toughest fibers in nature, as was shown by native hagfish slime threads and by synthetic fibers that are based on type V IF-proteins, the nuclear lamins. It is assumed that their mechanical performance stems from two major factors: (1) the transition from elastic -helices to stiff-sheets during tensile load; and (2) the specific organization of the coiled-coil proteins into a hierarchical network of nano-filaments. Here, we investigated the interrelationship between these two factors by using wet-spun fibers based on C. elegans (Ce) lamin. We found that Ce-lamin fibers, whether assembled in aqueous or alcoholic solutions, had the same nonlinear mechanical behavior, with the elastic region ending at ~5%. The pattern of the transition was, however, different: the ratio between -helices and -sheets/random coils was relatively constant until a 20% strain for fibers assembled in an aqueous solution, whereas for fibers assembled in 70% ethanol, the transition ended at a 6% strain. This structural phenomenon in alcoholic solution probably occurred through the transition between compacted and extended conformation of the random coil, and not between -helix and -sheets, as cycle analyses had suggested. The different transition pattern can also be explained by the different higher order organization of Ce-lamins in aqueous or alcoholic solutions, as demonstrated by introducing a point mutation in conserved residue in Ce-lamin gene that alter the structure of the Ce-lamins’ nano-fibrils. In addition, biomimicking the layered structure of silk and hair fibers by coating the Ce-lamin fiber with a hydrophobic layer enhanced fiber toughness and lead to a reversible transition between -helix and the extended conformation. This work suggests that different hierarchical structures, which are formed by specific assembly conditions, lead to diverse secondary structure transitions patterns, which in turn affect the fibers’ mechanical properties.

Keywords: protein-based fibers, intermediate filaments (IF) assembly, toughness, structure-property relationships

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Authors: Gagan Dhawan

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Mycobacterium tuberculosis was described as ‘captain of death’ with an inherent property of multiple drug resistance majorly caused by the competent mechanism of efflux pumps. In this study, various open source tools combining chemo-informatics with bioinformatics were used for efficient in-silico drug designing. The efflux pump, Rv1218c, belonging to the ABC transporter superfamily, which is predicted to be a tetronasin-transporter in M. tuberculosis was targeted. Recent studies have shown that Rv1218c forms a complex with two more efflux pumps (Rv1219c and Rv1217c) to provide multidrug resistance to the bacterium. The 3D structure of the protein was modeled (as the structure was unavailable in the previously collected databases on this gene). The TMHMM analysis of this protein in TubercuList has shown that this protein is present in the outer membrane of the bacterium. Virtual screening of compounds from various publically available chemical libraries was performed on the M. tuberculosis protein using various open source tools. These ligands were further assessed where various physicochemical properties were evaluated and analyzed. On comparison of different physicochemical properties, toxicity and docking, the ligand 2-(hydroxymethyl)-6-[4, 5, 6-trihydroxy-2-(hydroxymethyl) tetrahydropyran-3-yl] oxy-tetrahydropyran-3, 4, 5-triol was found to be best suited for further studies.

Keywords: drug resistance, efflux pump, molecular docking, virtual screening

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Authors: Cory A. Bennett

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Teaching and learning through the use of discourse support students’ conceptual understanding by attending to key concepts and relationships. One discourse structure used in primary classrooms is number talks wherein students mentally calculate, discuss, and reason about the appropriateness and efficiency of their strategies. In the secondary mathematics classroom, the mathematics understudy does not often lend itself to mental calculations yet learning to reason, and articulate reasoning, is central to learning mathematics. This qualitative case study discusses how one secondary school in the Middle East adapted the number talk protocol for secondary mathematics classrooms. Several challenges in implementing ‘reasoning talks’ became apparent including shifting current discourse protocols and practices to a more student-centric model, accurately recording and probing student thinking, and specifically attending to reasoning rather than computations.

Keywords: discourse, reasoning, secondary mathematics, teacher development

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Authors: Ravid Inbar

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CaMKII (calcium-calmodulin dependent protein kinase II) makes up 2% of the protein in our brain and has a critical role in memory formation and long-term potentiation of neurons. Despite this, research has yet to uncover the role of one of the domains on the activation of this kinase. The following proposes to express the protein without the hub domain in E. coli, leaving only the kinase and regulatory segment of the protein. Next, a series of kinase assays will be conducted to elucidate the role the hub domain plays on CaMKII sensitivity to calcium/calmodulin activation. The hub domain may be important for activation; however, it may also be a variety of domains working together to influence protein activation and not the hub alone. Characterization of a protein is critical to the future understanding of the protein's function, as well as for producing pharmacological targets in cases of patients with diseases.

Keywords: CaMKII, hub domain, kinase assays, kinase + reg seg

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Authors: Muhammet Baldan, Emel Timuçin

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Generally, absorption and bioavailability increase if solubility increases; therefore, it is crucial to predict them in drug discovery applications. Molecular descriptors and Molecular properties are traditionally used for the prediction of water solubility. There are various key descriptors that are used for this purpose, namely Drogan Descriptors, Morgan Descriptors, Maccs keys, etc., and each has different prediction capabilities with differentiating successes between different data sets. Another source for the prediction of solubility is structural features; they are commonly used for the prediction of solubility. However, there are little to no studies that combine three or more properties or descriptors for prediction to produce a more powerful prediction model. Unlike available models, we used a combination of those features in a random forest machine learning model for improved solubility prediction to better predict and, therefore, contribute to drug discovery systems.

Keywords: solubility, molecular descriptors, machine learning, random forest

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Authors: Ahmad Saleem

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Ethereum is the second largest crypto currency in blockchain ecosystem. Along with standard transactions, it supports smart contracts and NFT’s. Current research trends are focused on analyzing the overall structure of the network its growth and behavior. Ethereum addresses are anonymous and can be created on fly. The nature of Ethereum network and addresses make it hard to predict their behavior. The activity period of an ethereum address is not much analyzed. Using machine learning we can make early prediction about the disposability of the address. In this paper we analyzed the lifetime of the addresses. We also identified and predicted the disposable addresses using machine learning models and compared the results.

Keywords: blockchain, Ethereum, cryptocurrency, prediction

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Authors: Yichao Liang, Biye Chen, Xiang Li, Steven R. Dimler

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This study investigated the effects of adding calcium and magnesium chloride on heat and storage stability of milk protein concentrate-soy protein isolate (8:2 respectively) mixtures containing 10% w/w total protein subjected to the in-container sterilization (115 °C x 15 min). The particle size does not change when emulsions are heated at pH between 6.7 and 7.3 irrespective of the mixed protein ratio. Increasing concentration of divalent cation salts resulted in an increase in protein particle size, dry sediment formation and sediment height and a decrease in pH, heat stability and hydration in milk protein concentrate-soy protein isolate mixtures solutions on sterilization at 115°C. Fortification of divalent cation salts in milk protein concentrate-soy protein isolate mixture solutions resulted in an accelerated protein sedimentation and two unique sediment regions during accelerated storage stability testing. Moreover, the heat stability decreased upon sterilization at 115°C, with addition of MgCl₂ causing a greater increase in sedimentation velocity and compressibility than CaCl₂. Increasing pH value of protein milk concentrate-soy protein isolate mixtures solutions from 6.7 to 7.2 resulted in an increase in viscosity following the heat treatment. The study demonstrated that the type and concentration of divalent cation salts used strongly impact heat and storage stability of milk protein concentrate-soy protein isolate mixture nutritional beverages.

Keywords: divalent cation salts, heat stability, milk protein concentrate, soy protein isolate, storage stability

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Authors: Marianna De Almeida

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Greek secondary education is a highly selective system with regard to the access of students to Greek universities. Since access from elementary to lower secondary education and afterward to upper secondary education is rather liberal and almost free of selective mechanisms, the basic selection process comes after graduating from upper secondary school into play when students go through a highly selective process for university entry. This structure is responsible for the experience of extreme stress on the part of the candidates during a period of at least two years before the entrance examination leading to a radical change in students' everyday life routines. Instead of the school being an important agent for academic and psychological support, it seems that other agents, such as the informal private preparatory school and the student's families, take on the supportive role.

Keywords: stress, entrance examinations, family support, secondary education

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Authors: S. Girish, N. Ajay

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Permeation properties have been widely used to quantify durability characteristics of concrete for assessing long term performance and sustainability. The processes of deterioration in concrete are mediated largely by water. There is a strong interest in finding a better way of assessing the material properties of concrete in terms of durability. Water sorptivity is a useful single material property which can be one of the measures of durability useful in service life planning and prediction, especially in severe environmental conditions. This paper presents the results of the comparative study of sorptivity of Self-Compacting Concrete (SCC) with conventionally vibrated concrete. SCC is a new, special type of concrete mixture, characterized by high resistance to segregation that can flow through intricate geometrical configuration in the presence of reinforcement, under its own mass, without vibration and compaction. SCC mixes were developed for the paste contents of 0.38, 0.41 and 0.43 with fly ash as the filler for different cement contents ranging from 300 to 450 kg/m3. The study shows better performance by SCC in terms of capillary absorption. The sorptivity value decreased as the volume of paste increased. The use of higher paste content in SCC can make the concrete robust with better densification of the micro-structure, improving the durability and making the concrete more sustainable with improved long term performance. The sorptivity based on secondary absorption can be effectively used as a durability index to predict the time duration required for the ingress of water to penetrate the concrete, which has practical significance.

Keywords: self-compacting concrete, service life prediction, sorptivity, volume of paste

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Authors: Mehrnaz Aminifar

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The relation between textural parameters and casein network on release of aromatic compounds was investigated over 90-days of ripening. Low DE maltodextrin and WPI were used to modify the textural properties of low fat brined cheese. Hardness, brittleness and compaction of casein network were affected by addition of maltodextrin and WPI. Textural properties and aroma release from cheese texture were affected by interaction of WPI protein-cheese protein and maltodexterin-cheese protein.

Keywords: aroma release, brined cheese, maltodexterin, WPI

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Authors: Yew Mun Yip, Dawei Zhang

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Proteins are the biological machinery that executes specific vital functions in every cell of the human body by folding into their 3D structures. When a protein misfolds from its native structure, the machinery will malfunction and lead to misfolding diseases. Although in vitro experiments are able to conclude that the mutations of the amino acid sequence lead to incorrectly folded protein structures, these experiments are unable to decipher the folding process. Therefore, molecular dynamic (MD) simulations are employed to simulate the folding process so that our improved understanding of the folding process will enable us to contemplate better treatments for misfolding diseases. MD simulations make use of force fields to simulate the folding process of peptides. Secondary structures are formed via the hydrogen bonds formed between the backbone atoms (C, O, N, H). It is important that the hydrogen bond energy computed during the MD simulation is accurate in order to direct the folding process to the native structure. Since the atoms involved in a hydrogen bond possess very dissimilar electronegativities, the more electronegative atom will attract greater electron density from the less electronegative atom towards itself. This is known as the polarization effect. Since the polarization effect changes the electron density of the two atoms in close proximity, the atomic charges of the two atoms should also vary based on the strength of the polarization effect. However, the fixed atomic charge scheme in force fields does not account for the polarization effect. In this study, we introduce the polarized structure-specific backbone charge (PSBC) model. The PSBC model accounts for the polarization effect in MD simulation by updating the atomic charges of the backbone hydrogen bond atoms according to equations derived between the amount of charge transferred to the atom and the length of the hydrogen bond, which are calculated from quantum-mechanical calculations. Compared to other polarizable models, the PSBC model does not require quantum-mechanical calculations of the peptide simulated at every time-step of the simulation and maintains the dynamic update of atomic charges, thereby reducing the computational cost and time while accounting for the polarization effect dynamically at the same time. The PSBC model is applied to two different β-peptides, namely the Beta3s/GS peptide, a de novo designed three-stranded β-sheet whose structure is folded in vitro and studied by NMR, and the trpzip peptides, a double-stranded β-sheet where a correlation is found between the type of amino acids that constitute the β-turn and the β-propensity.

Keywords: hydrogen bond, polarization effect, protein folding, PSBC

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Authors: C. E. Chinma, S. O. Azeez, J. C. Anuonye, O. B. Ocheme, C. M. Yakubu, S. James, E. U. Ohuoba, I. A. Baba

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There is growing interest in the use of rice bran protein in food formulation due to its hypoallergenic protein, high nutritional value and health promoting potentials. For the first time, the amino acid profile, protein digestibility, antioxidant, and functional properties of protein concentrate from some local varieties of rice bran from Nigeria were studied for possible food applications. Protein concentrates were prepared from rice bran and analysed using standard methods. Results showed that protein content of Kwandala, Yardass, Jeep, and Jamila were 69.24%, 69.97%, 68.73%, and 71.62%, respectively while total essential amino acid were 52.71, 53.03, 51.86, and 55.75g/100g protein, respectively. In vitro protein digestibility of protein concentrate from Kwandala, Yardass, Jeep and Jamila were 90.70%, 91.39%, 90.57% and 91.63% respectively. DPPH radical inhibition of protein from Kwandala, Yardass, Jeep, and Jamila were 48.15%, 48.90%, 47.56%, and 53.29%, respectively while ferric reducing ability power were 0.52, 0.55, 0.47 and 0.67mmol TE per gram, respectively. Protein concentrate from Jamila had higher onset (92.57oC) and denaturation temperature (102.13oC), and enthalpy (0.72J/g) than Jeep (91.46oC, 101.76oC, and 0.68J/g, respectively), Kwandala (90.32oC, 100.54oC and 0.57J/g, respectively), and Yardass (88.94oC, 99.45oC, and 0.51J/g, respectively). In vitro digestibility of protein from Kwandala, Yardas, Jeep, and Jamila were 90.70%, 91.39%, 90.57% and 91.63% respectively. Oil absorption capacity of Kwandala, Yardass, Jeep, and Jamila were 3.61, 3.73, 3.40, and 4.23g oil/g sample respectively, while water absorption capacity were 4.19, 4.32, 3.55 and 4.48g water/g sample, respectively. Protein concentrates had low bulk density (0.37-0.43g/ml). Protein concentrate from Jamila rice bran had the highest foam capacity (37.25%), followed by Yardass (34.20%), Kwandala (30.14%) and Jeep (28.90%). Protein concentrates showed low emulsifying and gelling capacities. In conclusion, protein concentrate prepared from these local rice bran varieties could serve as functional ingredients in food formulations and for enriching low protein foods.

Keywords: rice bran protein, amino acid profile, protein digestibility, antioxidant and functional properties

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Authors: Prajna Metta, Yanti Rusyanti, Nunung Rusminah, Bremmy Laksono

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The decrease of neutrophil chemotaxis function may cause increased susceptibility to aggressive periodontitis (AP). Neutrophil chemotaxis is affected by formyl peptide receptor 1 (FPR1), which when activated will respond to bacterial chemotactic peptide formyl methionyl leusyl phenylalanine (FMLP). FPR1 protein value is decreased in response to a wide number of inflammatory stimuli in AP patients. This study was aimed to assess the alteration of FPR1 protein value in AP patients and if FPR1 protein value could be used as an indicator of neutrophil chemotaxis dysfunction in AP. This is a case control study with 20 AP patients and 20 control subjects. Three milliliters of peripheral blood were drawn and analyzed for FPR1 protein value with ELISA. The data were statistically analyzed with Mann-Whitney test (p>0,05). Results showed that the mean value of FPR1 protein value in AP group is 0,353 pg/mL (0,11 to 1,18 pg/mL) and the mean value of FPR1 protein value in control group is 0,296 pg/mL (0,05 to 0,88 pg/mL). P value 0,787 > 0,05 suggested that there is no significant difference of FPR1 protein value in both groups. The present study suggests that FPR1 protein value has no significance alteration in AP patients and could not be used as an indicator of neutrophil chemotaxis dysfunction.

Keywords: aggressive periodontitis, chemotaxis dysfunction, FPR1 protein value, neutrophil

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Authors: Kefaya Qaddoum

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The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises a machine learning system called conformal prediction (CP), in order to assign consistent confidence measures to predictions, which are combined with GRNN. We apply the resulting algorithm to the problem of breast cancer diagnosis. The results show that the prediction constructed by this method is reasonable and could be useful in practice.

Keywords: neural network, conformal prediction, cancer classification, regression

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Authors: Phakamas Rachamontree, Theerawut Phusantisampan, Natthakorn Woravutthikul, Peerapong Pornwongthong, Malinee Sriariyanun

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A total of 115 yeast strains isolated from local cassava processing wastes were measured for crude protein content. Among these strains, the strain MSY-2 possessed the highest protein concentration (>3.5 mg protein/mL). By using molecular identification tools, it was identified to be a strain of Pichia kudriavzevii based on similarity of D1/D2 domain of 26S rDNA region. In this study, to optimize the protein production by MSY-2 strain, Response Surface Methodology (RSM) was applied. The tested parameters were the carbon content, nitrogen content, and incubation time. Here, the value of regression coefficient (R2) = 0.7194 could be explained by the model, which is high to support the significance of the model. Under the optimal condition, the protein content was produced up to 3.77 g per L of the culture and MSY-2 strain contain 66.8 g protein per 100 g of cell dry weight. These results revealed the plausibility of applying the novel strain of yeast in single-cell protein production.

Keywords: single cell protein, response surface methodology, yeast, cassava processing waste

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Authors: Tea Poklepović, Zdravka Aljinović, Branka Marasović

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Due to the importance of yield curve and its estimation it is inevitable to have valid methods for yield curve forecasting in cases when there are scarce issues of securities and/or week trade on a secondary market. Therefore in this paper, after the estimation of weekly yield curves on Croatian financial market from October 2011 to August 2012 using Nelson-Siegel and Svensson models, yield curves are forecasted using Vector auto-regressive model and Neural networks. In general, it can be concluded that both forecasting methods have good prediction abilities where forecasting of yield curves based on Nelson Siegel estimation model give better results in sense of lower Mean Squared Error than forecasting based on Svensson model Also, in this case Neural networks provide slightly better results. Finally, it can be concluded that most appropriate way of yield curve prediction is neural networks using Nelson-Siegel estimation of yield curves.

Keywords: Nelson-Siegel Model, neural networks, Svensson Model, vector autoregressive model, yield curve

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Authors: Seyed Mohammad Hosein Al Omrani Nejad, Ali Rezvani Aghdam

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This study was done in order to evaluation different irrigation intervals on amount of protein, and gel production in Aloe vera, a traditional medicinal plant. Plants was plnted in Greenhouse and irrigated according to Accumulative Pan Evaporation(APE). The treatments were included 20, 40, 60, 80, 100, 120, 140, 160, 180, and 200 mm APE which has been showed W1,W2, W3, W4, W5, W6, W7, W8,W9 and W10 respectively.The amount of protein and gel production was measured seperately. Results showed that highest protein and fresh weight of gel obtained plants which irrigated W6 and W7 respectively. According to these results can recomend which if plant irrigatedwhen APE reached 120 and 140 mm by Class A Evaporation Pan method gel production and protein would besuitable in north of khozestan province in limited irrigation conditions.

Keywords: irrigation, protein, gel, aloe vera, Iran

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Authors: Er-Yuan Chuang

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Bio-mimetic matters have biological functionalities. This might be valuable in the development of versatile biomaterials. At biological fields, protein-based materials might be components to form a 3D network of extracellular biomolecules, containing growth factors. Also, the protein-based biomaterial provides biochemical and structural assistance of adjacent cells. In this study, we try to prepare protein based biomaterial, which was harvested from living animal. We analyzed it’s chemical, physical and biological property in vitro. Besides, in vivo bio-interaction of the prepared biomimetic matrix was tested in an animal model. The protein-based biomaterial has degradability and biocompatibility. This development could be used for tissue regenerations and be served as platform technologies.

Keywords: protein based, in vitro study, in vivo study, biomaterials

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Authors: Danilo López, Edwin Rivas, Fernando Pedraza

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Currently, one of the major challenges in wireless networks is the optimal use of radio spectrum, which is managed inefficiently. One of the solutions to existing problem converges in the use of Cognitive Radio (CR), as an essential parameter so that the use of the available licensed spectrum is possible (by secondary users), well above the usage values that are currently detected; thus allowing the opportunistic use of the channel in the absence of primary users (PU). This article presents the results found when estimating or predicting the future use of a spectral transmission band (from the perspective of the PU) for a chaotic type channel arrival behavior. The time series prediction method (which the PU represents) used is ANFIS (Adaptive Neuro Fuzzy Inference System). The results obtained were compared to those delivered by the RNA (Artificial Neural Network) algorithm. The results show better performance in the characterization (modeling and prediction) with the ANFIS methodology.

Keywords: ANFIS, cognitive radio, prediction primary user, RNA

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Authors: Michelangelo Liban, Debbie Liquete

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A 70-year-old right-handed Filipina was seen by the Neurology service due to a new onset headache, bi-occipital in location, dull squeezing in character with a pain score of 8/10 with associated nausea and one episode of non-projectile, which provided no relief. Due to the alarming features of the headache despite the absence of risk factors and an essentially normal neurologic examination, a cranial CTA+CTV was done, which revealed a small left frontal and small right pontine hyper density with minimal perilesional edema. Findings also revealed filling defects in the straight and right transverse sinus and a consideration of hypoplastic left transverse sinus with no definite evidence of aneurysm nor A-V malformation. She had normal levels of D-Dimer, Protein C, ANA and Anti-DS DNA but had a low Protein S of 56% (N.V is 70-120%). Antithrombin, homocysteine and Factor V Leiden were not done due to unavailability of the tests. She was then treated as a case of Cerebral Venous Thrombosis with multiple hemorrhage from venous infraction and was given anticoagulants which provided relief of the headache. She did not manifest with any further cortical, bulbar or sensorimotor deficits hence was discharged improved after 15 hospital days. To our knowledge, there are no case reports of patients with CVT from Protein S deficiency and venous anomaly that presented with multiple hemorrhage from venous infarction, more so affecting the brainstem. In this paper, a rare location of CVT in a newly diagnosed Protein S deficient patient is presented together with an uneventful course and favorable outcome.

Keywords: protein S deficiency, cerebral venous thrombosis, pontine hemorrhage from venous infarction, elderly

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Authors: Verónica Díaz Quezada

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Despite the wide variety of educational resources on the market and the advances produced in the technological field, the practice of teaching continues to be supported mainly by textbooks. This article reports on descriptive research with qualitative methodology carried out on secondary school mathematics teachers in a region of Chile, in order to describe the use and the indicators of appreciation that teachers have on the textbooks distributed by the official body to public educational establishments. Data were collected through an open response opinion questionnaire. According to the results, among the texts available for the annual performance of their teaching work, the expository and technological books predominate, to the detriment of comprehensive books. The exhibition structure favors master expositions and repetitive exercises, while, with the technological structure, a productive exercise is attempted, proposing numerous applications with the intention of giving meaning to the different mathematical rules and procedures. In relation to the indicators of appreciation that teachers have regarding the use of mathematics textbooks, the suitability and quality of the teaching resources are verified as the most satisfying characteristic.

Keywords: mathematics, secondary school, teachers, textbooks

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Authors: Mohamed Abdullah Ahmed

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In a study of chickpea protein isolate (CPI) preparation, the wet alkaline extraction was carried out. The objectives were to determine the optimal extracting conditions of CPI and apply CPI into a sponge cake recipe to replace egg and make acceptable product. The design used in extraction was a central composite design. The response surface methodology was preferred to graphically express the relationship between extraction time and pH with the output variables of percent yield and protein content of CPI. It was noted that optimal extracting conditions were 60 min and pH 10.5 resulting in 90.07% protein content and 89.15% yield of CPI. The protein isolate (CPI) could be incorporated in cake to 20% without adversely affecting the cake physical properties such as cake hardness and sensory attributes. The higher protein content in cake was corresponding to the amount of CPI added. Therefore, adding CPI can significantly (p<0.05) increase protein content in cake. However, sensory evaluation showed that adding more than 20% of CPI decreased the overall acceptability. The results of this investigation could be used as a basic knowledge of CPI utilization in other food products.

Keywords: chick bean protein isolate, sponge cake, utilization, sponge

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Authors: Hui Zhang, Sherif Beskhyroun

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Structural Health monitoring systems (SHM) are commonly used to identify and assess structural damage. In terms of damage detection, SHM needs to periodically collect data from sensors placed in the structure as damage-sensitive features. This includes abnormal changes caused by the strain field and abnormal symptoms of the structure, such as damage and deterioration. Currently, deploying sensors on a large scale in a building structure is a challenge. In this study, a highly stretchable strain sensors are used in this study to collect data sets of strain generated on the surface of full-size reinforced concrete (RC) frames under extreme cyclic load application. This sensing sheet can be switched freely between the test bending strain and the axial strain to achieve two different configurations. On this basis, the deep neural network prediction model of the frame beam and frame column is established. The training results show that the method can accurately predict the strain value and has good generalization ability. The two deep neural network prediction models will also be deployed in the SHM system in the future as part of the intelligent strain sensor system.

Keywords: strain sensing sheets, deep neural networks, strain measurement, SHM system, RC frames

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Authors: Shayli Varasteh Moradi, Wayne A. Johnston, Dejan Gagoski, Kirill Alexandrov

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The demand for a rapid and more efficient technique to identify protein-protein interaction particularly in the areas of therapeutics and diagnostics development is growing. The method described here is a rapid in vitro protein-protein interaction analysis approach based on AlphaLISA technology combined with Leishmania tarentolae cell-free protein production (LTE) system. Cell-free protein synthesis allows the rapid production of recombinant proteins in a multiplexed format. Among available in vitro expression systems, LTE offers several advantages over other eukaryotic cell-free systems. It is based on a fast growing fermentable organism that is inexpensive in cultivation and lysate production. High integrity of proteins produced in this system and the ability to co-express multiple proteins makes it a desirable method for screening protein interactions. Following the translation of protein pairs in LTE system, the physical interaction between proteins of interests is analysed by AlphaLISA assay. The assay is performed using unpurified in vitro translation reaction and therefore can be readily multiplexed. This approach can be used in various research applications such as epitope mapping, antigen-antibody analysis and protein interaction network mapping. The intra-viral protein interaction network of Zika virus was studied using the developed technique. The viral proteins were co-expressed pair-wise in LTE and all possible interactions among viral proteins were tested using AlphaLISA. The assay resulted to the identification of 54 intra-viral protein-protein interactions from which 19 binary interactions were found to be novel. The presented technique provides a powerful tool for rapid analysis of protein-protein interaction with high sensitivity and throughput.

Keywords: AlphaLISA technology, cell-free protein expression, epitope mapping, Leishmania tarentolae, protein-protein interaction

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Authors: Feng Guolin, Gong Zhiqiang

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In order to study the spatial structure and dynamical mechanism of extreme precipitation in East Asia, a corresponding climate network is constructed by employing the method of event synchronization. It is found that the area of East Asian summer extreme precipitation can be separated into two regions: one with high area weighted connectivity receiving heavy precipitation mostly during the active phase of the East Asian Summer Monsoon (EASM), and another one with low area weighted connectivity receiving heavy precipitation during both the active and the retreat phase of the EASM. Besides，a way for the prediction of extreme precipitation is also developed by constructing a directed climate networks. The simulation accuracy in East Asia is 58% with a 0-day lead, and the prediction accuracy is 21% and average 12% with a 1-day and an n-day (2≤n≤10) lead, respectively. Compare to the normal EASM year, the prediction accuracy is lower in a weak year and higher in a strong year, which is relevant to the differences in correlations and extreme precipitation rates in different EASM situations. Recognizing and identifying these effects is good for understanding and predicting extreme precipitation in East Asia.

Keywords: synchronization, climate network, prediction, rainfall

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Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

Abstract:

This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: neural network, self-organizing map, rule extraction, rule insertion

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Authors: Angga S. Fajar, A. Aminullah, J. Kiyono, R. A. Safitri

Abstract:

This paper discusses about the application of ANN for optimizing of bridge structure design. ANN has been applied in various field of science concerning prediction and optimization. The structural optimization has several benefit including accelerate structural design process, saving the structural material, and minimize self-weight and mass of structure. In this paper, there are three types of bridge structure that being optimized including PSC I-girder superstructure, composite steel-concrete girder superstructure, and RC bridge pier. The different optimization strategy on each bridge structure implement back propagation method of ANN is conducted in this research. The optimal weight and easier design process of bridge structure with satisfied error are achieved.

Keywords: bridge structures, ANN, optimization, back propagation

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Authors: Zoe M. G. Skalkos, Sam N. Dowland, James U. Van Dyke, Camilla. M. Whittington

Abstract:

Syngnathid fishes (seahorses, pipefishes, and seadragons) are unique because embryos develop on or in the male in a specialised brooding structure. Many seahorse species are endangered or vulnerable, while others are popular in the ornamental fish trade. Seahorses are capable of nutrient provisioning (patrotrophy) of lipids during pregnancy via their fully enclosed brood pouch. Protein is vital for gene regulation and tissue growth during embryogenesis. We tested the hypothesis that protein is paternally transported to developing embryos during pregnancy in the Australian Pot-bellied seahorse, Hippocampus abdominalis. We compared the dry masses and nitrogen content in recently fertilised H. abdominalis embryos and newborns. We calculated an updated patrotrophy index, 1.34, but without a significant difference in dry mass between the two developmental stages. There was, however, a significant increase in total protein content from recently fertilised embryos to neonates. This suggests paternal protein transport is essential for H. abdominalis embryogenesis because protein yolk reserves are depleted by embryonic metabolism, and supplementation is required. This study is the first to provide evidence for paternal protein transport during pregnancy in seahorses. It furthers our understanding of the paternal influence on embryonic development in male pregnancy and how a protein-deficient diet during pregnancy may limit the allocation of resources to embryos, reducing offspring fitness. This research contributes to a deeper understanding of the fundamental reproductive biology of seahorses, which can help improve conservation and farming production outcomes.

Keywords: brood pouch, embryonic provisioning, nitrogen, parentotrophy, paternal investment, reproduction

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