Search results for: protein stability prediction

Authors: Abdulrahman M. Alsuhaibani, Martin Maken

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FACTS devices have great influence on the grid stability and power markets price. Recently, there is intent to integrate a large scale of renewable energy sources to the power system which in turn push the power system to operate closer to the security limits. This paper discusses the power system stability and reliability improvement that could be achieved by using FACTS. There is a comparison between FACTS devices to evaluate their performance for different functions. A case study has also been made about its effect on reducing generation cost and minimizing transmission losses which have good impact on efficient and economic operation of electricity markets

Keywords: FACTS, grid stability, spot price, OPF

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Authors: Nisha Budhwar, Sunita Daniel

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In this paper, we analyse the stability of the SEIR model of malaria with infective immigrants which was recently formulated by the authors. The model consists of an SEIR model for the human population and SI Model for the mosquitoes. Susceptible humans become infected after they are bitten by infectious mosquitoes and move on to the Exposed, Infected and Recovered classes respectively. The susceptible mosquito becomes infected after biting an infected person and remains infected till death. We calculate the reproduction number R0 using the next generation method and then discuss about the stability of the equilibrium points. We use the Lyapunov function to show the global stability of the equilibrium points.

Keywords: equilibrium points, exposed, global stability, infective immigrants, Lyapunov function, recovered, reproduction number, susceptible

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Authors: Şevket Evci, Mehmet Akif Karsli

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The aim of this study is to determine nutrient contents, in situ ruminal degradation kinetics and protein fractions of screenings bean (B), chick pea (ChP), red lentil (RL) and green lentil (GL) that is used as residue in grain legume packing industry. For this purpose, four samples of each legumes species-a total of 16 samples, collected from different parts of our country were utilized. Feedstuffs used in the experiment were incubated for 0, 2 4, 8, 12, 24, and 48 hours in the rumen of 3 ruminally cannulated Akkaraman rams as duplicate. The nutrient contents, in situ ruminal dry matter (DM), organic matter (OM) and crude protein (CP) degradabilities and fractions, and escape protein contents were evaluated. The highest OM and CP contents were observed in RL (P<0.05). Chick pea had the highest ether extract (EE) content and EE values were 3.47, 6.72, 2.26, 8.66 % for RL, B, GL and ChP, respectively (P<0.05). Crude fiber (CF), ADF, and NDF contents were the highest in RL and the lowest in ChP. CF values were 24.03, 10.80, 4.09 and 3.57 % for RL, GL, B and ChP (P<0.05). Acid detergent insoluble nitrogen content of samples did not differ. Escape protein content was the highest in RL and the lowest in B (P<0.05). After 48 h incubation, the lowest OM and CP degradabilities were observed in RL. While the highest OM degradability was seen in ChP the highest CP degradability was observed in B (P<0.05). The lowest water soluble OM and CP contents were observed in RL whereas the highest potentially degradable OM and CP contents were seen in B and ChP (P<0.05). Both rate of OM and CP degradations (k-1) did not differ among samples (P>0.05). In conclusion, it was noted that feedstuffs (GL, ChP and B) used in the experiment except RL had a greater ruminal degradibilities of both OM and CP and moreover, had a higher escape protein contents, except B. It was thought that these feedstuffs can be substituted with some of common protein sources used in animal nutrition.

Keywords: in situ, nutrient contents, ruminant, subsieve

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Authors: Sabri Arik

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In this paper, we study the global asymptotic robust stability of delayed neural networks with norm-bounded uncertainties. By employing the Lyapunov stability theory and Homeomorphic mapping theorem, we derive some new types of sufficient conditions ensuring the existence, uniqueness and global asymptotic stability of the equilibrium point for the class of neural networks with discrete time delays under parameter uncertainties and with respect to continuous and slopebounded activation functions. An important aspect of our results is their low computational complexity as the reported results can be verified by checking some properties symmetric matrices associated with the uncertainty sets of network parameters. The obtained results are shown to be generalization of some of the previously published corresponding results. Some comparative numerical examples are also constructed to compare our results with some closely related existing literature results.

Keywords: neural networks, delayed systems, lyapunov functionals, stability analysis

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Authors: Pallavi Mane, Nikita Mankar, Shraddha Mazire, Rasika Pashankar

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Content sharing sites are very useful in sharing information and images. However, with the increasing demand of content sharing sites privacy and security concern have also increased. There is need to develop a tool for controlling user access to their shared content. Therefore, we are developing an Adaptive Privacy Policy Prediction (A3P) system which is helpful for users to create privacy settings for their images. We propose the two-level framework which assigns the best available privacy policy for the users images according to users available histories on the site.

Keywords: online information services, prediction, security and protection, web based services

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

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Authors: Nagini Sabbineni, Rajini T. V. Kanth, B. V. Kiranmayee

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India’s economy primarily depends on agriculture yield growth and their allied agro industry products. The agriculture yield prediction is the toughest task for agricultural departments across the globe. The agriculture yield depends on various factors. Particularly countries like India, majority of agriculture growth depends on rain water, which is highly unpredictable. Agriculture growth depends on different parameters, namely Water, Nitrogen, Weather, Soil characteristics, Crop rotation, Soil moisture, Surface temperature and Rain water etc. In our paper, lot of Explorative Data Analysis is done and various predictive models were designed. Further various regression models like Linear, Multiple Linear, Non-linear models are tested for the effective prediction or the forecast of the agriculture yield for various crops in Andhra Pradesh and Telangana states.

Keywords: agriculture yield growth, agriculture yield prediction, explorative data analysis, predictive models, regression models

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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: Xiaolin Li, Terence Turney, John Forsythe, Bryce Feltis, Paul Wright, Vinh Truong, Will Gates

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Clay-hydrogel nanocomposites have attracted great attention recently, mainly because of their enhanced mechanical properties and ease of fabrication. Moreover, the unique platelet structure of clay nanoparticles enables the incorporation of bioactive molecules, such as proteins or drugs, through ion exchange, adsorption or intercalation. This study seeks to improve the mechanical and rheological properties of a novel hydrogel system, copolymerized from a tetrapodal polyethylene glycol (PEG) thiol and a linear, triblock PEG-PPG-PEG (PPG: polypropylene glycol) α,ω-bispropynoate polymer, with the simultaneous incorporation of various amounts of Na-saturated, montmorillonite clay (MMT) platelets (av. lateral dimension = 200 nm), to form a bioactive three-dimensional network. Although the parent hydrogel has controlled swelling ability and its PEG groups have good affinity for the clay platelets, it suffers from poor mechanical stability and is currently unsuitable for potential applications. Nanocomposite hydrogels containing 4wt% MMT showed a twelve-fold enhancement in compressive strength, reaching 0.75MPa, and also a three-fold acceleration in gelation time, when compared with the parent hydrogel. Interestingly, clay nanoplatelet incorporation into the hydrogel slowed down the rate of its dehydration in air. Preliminary results showed that protein binding by the MMT varied with the nature of the protein, as horseradish peroxidase (HRP) was more strongly bound than bovine serum albumin. The HRP was no longer active when bound, presumably as a result of extensive structural refolding. Further work is being undertaken to assess protein binding behaviour within the nanocomposite hydrogel for potential diabetic wound healing applications.

Keywords: hydrogel, nanocomposite, small molecule, wound healing

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Authors: Meenakshi Verma, Mandeep Singh Bakshi, Kultar Singh

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Magnetic nanoparticles have received incredible importance in view of their diverse applications, which arise primarily due to their response to the external magnetic field. The magnetic behaviour of magnetic nanoparticles (NPs) helps them in numerous different ways. The most important amongst them is the ease with which they can be purified and also can be separated from the media in which they are present merely by applying an external magnetic field. This exceptional ease of separation of the magnetic NPs from an aqueous media enables them to use for extracting/removing metal pollutants from complex aqueous medium. Functionalized magnetic NPs can be subjected for the metallic impurities extraction if are favourably adsorbed on the NPs surfaces. We have successfully used the magnetic NPs as vehicles for gold and silver NPs removal from the complex fluids. The NPs loaded with gold and silver NPs pollutant fractions has been easily removed from the aqueous media by using external magnetic field. Similarly, we have used the magnetic NPs for extraction of protein from complex media and then constantly washed with pure water to eliminate the unwanted surface adsorbed components for quantitative estimation. The purified and protein loaded magnetic NPs are best analyzed with SDS Page to not only for characterization but also for separating the protein fractions. A collective review of the results indicates that we have synthesized surfactant coated iron oxide NPs and then functionalized these with selected materials. These surface active magnetic NPs work very well for the extraction of metallic NPs from the aqueous bulk and make the whole process environmentally sustainable. Also, magnetic NPs-Au/Ag/Pd hybrids have excellent protein extracting properties. They are much easier to use in order to extract the magnetic impurities as well as protein fractions under the effect of external magnetic field without any complex conventional purification methods.

Keywords: magnetic nanoparticles, protein, functionalized, extraction

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Authors: Muhammad Ajmal

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- Thermal processing and subsequent storage of ultra-heat treated (UHT) milk leads to alteration in protein profile, Maillard reaction and lipid oxidation. Concentration of carbohydrates in normal and flavored version of UHT milk is considerably different. Transition in protein profile, Maillard reaction and lipid oxidation in UHT flavored milk was determined for 90 days at ambient conditions and analyzed at 0, 45 and 90 days of storage. Protein profile, hydroxymethyl furfural, furosine, Nε-carboxymethyl-l-lysine, fatty acid profile, free fatty acids, peroxide value and sensory characteristics were determined. After 90 days of storage, fat, protein, total solids contents and pH were significantly less than the initial values determined at 0 day. As compared to protein profile normal UHT milk, more pronounced changes were recorded in different fractions of protein in UHT milk at 45 and 90 days of storage. Tyrosine content of flavored UHT milk at 0, 45 and 90 days of storage were 3.5, 6.9 and 15.2 µg tyrosine/ml. After 45 days of storage, the decline in αs1-casein, αs2-casein, β-casein, κ-casein, β-lactoglobulin, α-lactalbumin, immunoglobulin and bovine serum albumin were 3.35%, 10.5%, 7.89%, 18.8%, 53.6%, 20.1%, 26.9 and 37.5%. After 90 days of storage, the decline in αs1-casein, αs2-casein, β-casein, κ-casein, β-lactoglobulin, α-lactalbumin, immunoglobulin and bovine serum albumin were 11.2%, 34.8%, 14.3%, 33.9%, 56.9%, 24.8%, 36.5% and 43.1%. Hydroxy methyl furfural content of UHT milk at 0, 45 and 90 days of storage were 1.56, 4.18 and 7.61 (µmol/L). Furosine content of flavored UHT milk at 0, 45 and 90 days of storage intervals were 278, 392 and 561 mg/100g protein. Nε-carboxymethyl-l-lysine content of UHT flavored milk at 0, 45 and 90 days of storage were 67, 135 and 343mg/kg protein. After 90 days of storage of flavored UHT milk, the loss of unsaturated fatty acids 45.7% from the initial values. At 0, 45 and 90 days of storage, free fatty acids of flavored UHT milk were 0.08%, 0.11% and 0.16% (p<0.05). Peroxide value of flavored UHT milk at 0, 45 and 90 days of storage was 0.22, 0.65 and 2.88 (MeqO²/kg). Sensory analysis of flavored UHT milk after 90 days indicated that appearance, flavor and mouth feel score significantly decreased from the initial values recorded at 0 day. Findings of this investigation evidenced that in flavored UHT milk more pronounced changes take place in protein profile, Maillard reaction products and lipid oxidation as compared to normal UHT milk.

Keywords: UHT flavored milk , hydroxymethyl furfural, lipid oxidation, sensory properties

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Authors: Hwang Ahreum, Kang Taejoon, Kim Bongsoo

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Nanosensors for high sensitive detection of diseases have been widely studied to improve the quality of life. Here, we suggest robust nano-plasmonic diagnostic sensor using cysteine tagged protein G (Cys3-protein G) and ultraflat, ultraclean and single-crystalline Au nanoplates. Protein G formed on an ultraflat Au surface provides ideal background for dense and uniform immobilization of antibodies. The Au is highly stable in diverse biochemical environment and can immobilize antibodies easily through Au-S bonding, having been widely used for various biosensing applications. Especially, atomically smooth single-crystalline Au nanomaterials synthesized using chemical vapor transport (CVT) method are very suitable to fabricate reproducible sensitive sensors. As the C-reactive protein (CRP) is a nonspecific biomarker of inflammation and infection, it can be used as a predictive or prognostic marker for various cardiovascular diseases. Cys3-protein G immobilized uniformly on the Au nanoplate enable CRP antibody (anti-CRP) to be ordered in a correct orientation, making their binding capacity be maximized for CRP detection. Immobilization condition for the Cys3-protein G and anti-CRP on the Au nanoplate is optimized visually by AFM analysis. Au nanoparticle - Au nanoplate (NPs-on-Au nanoplate) assembly fabricated from sandwich immunoassay for CRP can reduce zero-signal extremely caused by nonspecific bindings, providing a distinct surface-enhanced Raman scattering (SERS) enhancement still in 10-18 M of CRP concentration. Moreover, the NP-on-Au nanoplate sensor shows an excellent selectivity against non-target proteins with high concentration. In addition, comparing with control experiments employing a Au film fabricated by e-beam assisted deposition and linker molecule, we validate clearly contribution of the Au nanoplate for the attomolar sensitive detection of CRP. We expect that the devised platform employing the complex of single-crystalline Au nanoplates and Cys3-protein G can be applied for detection of many other cancer biomarkers.

Keywords: Au nanoplate, biomarker, diagnostic sensor, protein G, SERS

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Authors: Yazun Jarrar

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Smoking has effect on platelet aggregation and the activity of anti-platelet drugs. The chemical 20-hydroxyeicosatetraenoic acid (20-HETE) is a cardiotoxic arachidonic acid metabolite which increases platelet aggregation. In this study, we investigated the influence of cigarette smoking on 20-HETE levels and protein expression of 20-HETE producing enzyme CYP4A11 in isolated platelets from smoker and non-smoker volunteers. The protein expression and 20-HETE levels were analyzed using immunoblot and High-Performance Liquid Chromatography with Mass Spectrometry (HPL-MS) assays. The results showed that 20-HETE level was higher significantly among smokers than non-smokers (t-test, p-value<0.05). The protein expression of CYP4A11 was significantly higher (t-test, p-value<0.05) among the platelets of smokers. We concluded that cigarette smoking increased the level of platelet activator 20-HETE through increasing the protein expression of CYP4A11. These findings may increase the understanding of smoking-drug interaction during antiplatelets therapy.

Keywords: smoking, 20-HETE, CYP4A11, platelet

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Authors: Aghasadeghi MR., Bahramali G., Sadat SM., Sadeghi SA., Yousefi M., Khodaei K., Ghorbani M., Sadat Larijani M.

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Background:The emerging COVID-19 pandemic is a serious concernfor the public health worldwide. Despite the many mutations in the virus genome, it is important to find an effective vaccine against viral mutations. Therefore, in current study, we aimed at immunoinformatic evaluation of the virus proteins immunogenicity to design a preventive vaccine candidate, which could elicit humoral and cellular immune responses as well. Methods:Three antigenic regions are included;Spike, Membrane, and Nucleocapsid amino acid sequences were obtained, and possible fusion proteins were assessed andcompared by immunogenicity, structural features, and population coverage. The best fusion protein was also evaluated for MHC-I and MHC-II T-cell epitopes and the linear and conformational B-cell epitopes. Results: Among the four predicted models, the truncated Spike protein in fusion with M and N proteins is composed of 24 highly immunogenic human MHC class I and 29 MHC class II, along with 14 B-cell linear and 61 discontinues epitopes. Also, the selected protein has high antigenicity and acceptable population coverage of 82.95% in Iran and 92.51% in Europe. Conclusion: The data indicate that the truncated Spike-M-N SARS-CoV-2form which could be potential targets of neutralizing antibodies. The protein also has the ability to stimulate humoral and cellular immunity. The in silico study provided the fusion protein as a potential preventive vaccine candidate for further in vivo evaluation.

Keywords: SARS-CoV-2, immunoinformatic, protein, vaccine

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Authors: H. H. Goh, Q. S. Chua, S. W. Lee, B. C. Kok, K. C. Goh, K. T. K. Teo

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At present, the evaluation of voltage stability assessment experiences sizeable anxiety in the safe operation of power systems. This is due to the complications of a strain power system. With the snowballing of power demand by the consumers and also the restricted amount of power sources, therefore, the system has to perform at its maximum proficiency. Consequently, the noteworthy to discover the maximum ability boundary prior to voltage collapse should be undertaken. A preliminary warning can be perceived to evade the interruption of power system’s capacity. The effectiveness of line voltage stability indices (LVSI) is differentiated in this paper. The main purpose of the indices is used to predict the proximity of voltage instability of the electric power system. On the other hand, the indices are also able to decide the weakest load buses which are close to voltage collapse in the power system. The line stability indices are assessed using the IEEE 14 bus test system to validate its practicability. Results demonstrated that the implemented indices are practically relevant in predicting the manifestation of voltage collapse in the system. Therefore, essential actions can be taken to dodge the incident from arising.

Keywords: critical line, line outage, line voltage stability indices (LVSI), maximum loadability, voltage collapse, voltage instability, voltage stability analysis

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Authors: Kah Yan How, Peh Fern Ong, Keang Peng Song

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Porphyromonas gingivalis is a black-pigmented, anaerobic Gram-negative bacterium that is important in the progression of chronic and severe periodontitis. This organism has an essential requirement for iron, which is usually obtained from hemin, using specific membrane receptors, proteases, and lipoproteins. In this study, we report the characterization of a novel 24 kDa hemin-binding protein, HmuX, in P. gingivalis W50. The hmuX gene is 651 bp long which encodes for a 217 amino acid protein. HmuX was found to be identical at the C-terminus to the previously reported HmuY protein, differing by an additional 74 amino acids at the N-terminus. Recombinant HmuX demonstrated hemin-binding ability by LDS- PAGE and TMBZ staining. Sequence analysis of HmuX revealed a putative lipoprotein attachment site, suggesting its possible role as a lipoprotein. HmuX was also localized to the outer cell surface by transmission electron microscopy. Northern analysis showed hmuX to be transcribed as a single gene and that hmuX mRNA was tightly regulated by the availability of extra-cellular hemin. P. gingivalis isogenic mutant deficient in hmuX gene exhibited significant growth retardation under hemin-limited conditions. Taken together, these results suggest that HmuX is a hemin-binding lipoprotein, important in hemin utilization for the growth of P. gingivalis.

Keywords: Porphyromonas gingivalis, periodontal diseases, HmuX, protein characterization

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Authors: Iulianna Taritsa, Kuldeep Neote, Eric Fossel

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Lysosome-induced immunogenic cell death (LIICD) is a powerful mechanism of targeting cancer cells that kills circulating malignant cells and primes the host’s immune cells against future remission. Current immunotherapies for cancer are limited in preventing recurrence – a gap that can be bridged by training the immune system to recognize cancer neoantigens. Lysosomal leakage can be induced therapeutically to traffic antigens from dying cells to dendritic cells, which can later present those tumorigenic antigens to T cells. Previous research has shown that oxidative agents administered in the tumor microenvironment can initiate LIICD. We generated a fusion protein between an oxidative agent known as xanthine oxidase (XO) and a mini-antibody specific for EGFR/HER2-sensitive breast tumor cells. The anti-EGFR single domain antibody fragment is uniquely sourced from llama, which is functional without the presence of a light chain. These llama micro-antibodies have been shown to be better able to penetrate tissues and have improved physicochemical stability as compared to traditional monoclonal antibodies. We demonstrate that the fusion protein created is stable and can induce early markers of immunogenic cell death in an in vitro human breast cancer cell line (SkBr3). Specifically, we measured overall cell death, as well as surface-expressed calreticulin, extracellular ATP release, and HMGB1 production. These markers are consensus indicators of ICD. Flow cytometry, luminescence assays, and ELISA were used respectively to quantify biomarker levels between treated versus untreated cells. We also included a positive control group of SkBr3 cells dosed with doxorubicin (a known inducer of LIICD) and a negative control dosed with cisplatin (a known inducer of cell death, but not of the immunogenic variety). We looked at each marker at various time points after cancer cells were treated with the XO/antibody fusion protein, doxorubicin, and cisplatin. Upregulated biomarkers after treatment with the fusion protein indicate an immunogenic response. We thus show the potential for this fusion protein to induce an anticancer effect paired with an adaptive immune response against EGFR/HER2+ cells. Our research in human cell lines here provides evidence for the success of the same therapeutic method for patients and serves as the gateway to developing a new treatment approach against breast cancer.

Keywords: apoptosis, breast cancer, immunogenic cell death, lysosome

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Authors: Boualem Chetti

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The dynamic characteristics of a three-lobe journal bearing lubricated with micropolar fluids are determined by the linear stability theory. Lubricating oil containing additives and contaminants is modeled as micropolar fluid. The modified Reynolds equation is obtained using the micropolar lubrication theory and the finite difference technique has been used to solve it. The dynamic characteristics in terms of stiffness, damping coefficients, the critical mass and whirl ratio are determined for various values of size of material characteristic length and the coupling number. The computed results show compared with Newtonian fluids, that micropolar fluid exhibits better stability.

Keywords: three-lobe bearings, micropolar fluid, dynamic characteristics, stability analysis

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Authors: Shogo Kato, Daisuke Okamoto, Satoko Tsuru, Yoshinori Iizuka, Ryoko Shimono

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Healthcare safety has been perceived important. It is essential to prevent troubles in healthcare processes for healthcare safety. Trouble prevention is based on trouble prediction using accumulated knowledge on processes, troubles, and countermeasures. However, information on troubles has not been accumulated in hospitals in the appropriate structure, and it has not been utilized effectively to prevent troubles. In the previous study, though a detailed knowledge acquisition process for trouble prediction was proposed, the knowledgebase for countermeasures was not involved. In this paper, we aim to propose the structure of the knowledgebase for countermeasures in the knowledge acquisition process for trouble prediction in healthcare process. We first design the structure of countermeasures and propose the knowledge representation form on countermeasures. Then, we evaluate the validity of the proposal, by applying it into an actual hospital.

Keywords: trouble prevention, knowledge structure, structured knowledge, reusable knowledge

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Authors: Oscar Rubiano, Oscar Ortiz, Natalia Morales, Lida Alfonso, Johana Alvarado, Adriana Gutierrez, Daniel Botero

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Athletes who usually use protein supplements, are those who practice strength and power sports, whose goal is to achieve a large muscle mass. However, it has also been explored in sports or endurance activities such as cycling, and where despite requiring high power, prominent muscle development can impede good competitive performance due to the determinant of body mass for good performance of the athlete body. This research shows, the effect with protein supplements establishes a protein - muscle mass ratio, although in a lesser proportion the relationship between protein types and muscle power. Thus, we intend to explore as a first approximation, the behavior of muscle power in lower limbs after the intake of two protein supplements from different sources. The aim of the study was to describe the behavior of muscle power in lower limbs after the consumption of animal protein (AP) and vegetable protein (VP) in four route cyclists from 18 to 20 years of the Bogota cycling league. The methodological design of this study is quantitative, with a non-probabilistic sampling, based on a pre-experimental model. The jumping power was evaluated before and after the intervention by means of the squat jump test (SJ), Counter movement jump (CMJ) and Abalacov (AB). Cyclists consumed a drink with whey protein and a soy isolate after training four times a week for three months. The amount of protein in each cyclist, was calculated according to body weight (0.5 g / kg of muscle mass). The results show that subjects who consumed PV improved muscle strength and landing strength. In contrast, the power and landing force decreased for subjects who consumed PA. For the group that consumed PV, the increase was positive at 164.26 watts, 135.70 watts and 33.96 watts for the AB, SJ and CMJ jumps respectively. While for PA, the differences of the medians were negative at -32.29 watts, -82.79 watts and -143.86 watts for the AB, SJ and CMJ jumps respectively. The differences of the medians in the AB jump were positive for both the PV (121.61 Newton) and PA (454.34 Newton) cases, however, the difference was greater for PA. For the SJ jump, the difference for the PA cases was 371.52 Newton, while for the PV cases the difference was negative -448.56 Newton, so the difference was greater in the SJ jump for PA. In jump CMJ, the differences of the medians were negative for the cases of PA and PV, being -7.05 for PA and - 958.2 for PV. So the difference was greater for PA. The conclusion of this study shows that serum protein supplementation showed no improvement in muscle power in the lower limbs of the cyclists studied, which could suggest that whey protein does not have a beneficial effect on performance in terms of power, either, showed an impact on body composition. In contrast, supplementation with soy isolate showed positive effects on muscle power, body.

Keywords: animal protein (AP), muscle power, supplements, vegetable protein (VP)

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Authors: Oluwaponmile David Alao

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Due to an increase in the death rate as a result of heart attack. There is need to develop a system that can be useful in the diagnosis of the disease at the medical centre. This system will help in preventing misdiagnosis that may occur from the medical practitioner or the physicians. In this research work, heart disease dataset obtained from UCI repository has been used to develop an intelligent prediction diagnosis system. The system is modeled on a feedforwad neural network and trained with back propagation neural network. A recognition rate of 86% is obtained from the testing of the network.

Keywords: heart disease, artificial neural network, diagnosis, prediction system

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Authors: J. Gabrielczyk, J. Kluitmann, T. Dammeyer, H. J. Jördening

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High-level expression of proteins in bacteria often causes production of insoluble protein aggregates, called inclusion bodies (IB). They contain mainly one type of protein and offer an easy and efficient way to get purified protein. On the other hand, proteins in IB are normally devoid of function and therefore need a special treatment to become active. Most refolding techniques aim at diluting the solubilizing chaotropic agents. Unfortunately, optimal refolding conditions have to be found empirically for every protein. For large-scale applications, a simple refolding process with high yields and high final enzyme concentrations is still missing. The constructed plasmid pASK-IBA63b containing the sequence of fructosyltransferase (FTF, EC 2.4.1.162) from Bacillus subtilis NCIMB 11871 was transformed into E. coli BL21 (DE3) Rosetta. The bacterium was cultivated in a fed-batch bioreactor. The produced FTF was obtained mainly as IB. For refolding experiments, five different amounts of IBs were solubilized in urea buffer with protein concentration of 0.2-8.5 g/L. Solubilizates were refolded with batch or continuous dialysis. The refolding yield was determined by measuring the protein concentration of the clear supernatant before and after the dialysis. Particle size was measured by dynamic light scattering. We tested the solubilization properties of fructosyltransferase IBs. The particle size measurements revealed that the solubilization of the aggregates is achieved at urea concentration of 5M or higher and confirmed by absorption spectroscopy. All results confirm previous investigations that refolding yields are dependent upon initial protein concentration. In batch dialysis, the yields dropped from 67% to 12% and 72% to 19% for continuous dialysis, in relation to initial concentrations from 0.2 to 8.5 g/L. Often used additives such as sucrose and glycerol had no effect on refolding yields. Buffer screening indicated a significant increase in activity but also temperature stability of FTF with citrate/phosphate buffer. By adding citrate to the dialysis buffer, we were able to increase the refolding yields to 82-47% in batch and 90-74% in the continuous process. Further experiments showed that in general, higher ionic strength of buffers had major impact on refolding yields; doubling the buffer concentration increased the yields up to threefold. Finally, we achieved corresponding high refolding yields by reducing the chamber volume by 75% and the amount of buffer needed. The refolded enzyme had an optimal activity of 12.5±0.3 x104 units/g. However, detailed experiments with native FTF revealed a reaggregation of the molecules and loss in specific activity depending on the enzyme concentration and particle size. For that reason, we actually focus on developing a process of simultaneous enzyme refolding and immobilization. The results of this study show a new approach in finding optimal refolding conditions for inclusion bodies at high concentrations. Straightforward buffer screening and increase of the ionic strength can optimize the refolding yield of the target protein by 400%. Gentle removal of chaotrope with continuous dialysis increases the yields by an additional 65%, independent of the refolding buffer applied. In general time is the crucial parameter for successful refolding of solubilized proteins.

Keywords: dialysis, inclusion body, refolding, solubilization

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Authors: Hamid Hossein Khezri, Afsaneh Javdani-Mallak

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Fast inhibitory neurotransmission in the mammalian nervous system is largely mediated by GABAA receptors, chloride-selective members of the superfamily of pentameric Cys-loop receptors. Cannabidiol (CBD) is one of the members of cannabinoid compounds found in cannabis. CBD and Cannabinol (CBN), as the other extract of plant Cannabis were able to reduce myofascial pain in rats with immunosuppressive and anti-inflammatory activities. In this study, we accomplished protein-protein BLAST, and the sequence was found to be for Gamma-aminobutyric acid receptor subunit alpha-1 (GBRA1) chain A and its 3D structure was subsequently downloaded from Protein Data Bank. The structures of the ligands, cannabinol, and cannabidiol, were obtained from PubChem. After the necessary process of the obtained files, AutoDock Vina was used to perform molecular docking. Docking between the ligands and GBRA1 chain A revealed that cannabinol has a higher affinity to GBRA1 (binding energy = -7.5 kcal/mol) compared to cannabidiol (binding energy = -6.5 kcal/mol). Furthermore, cannabinol seems to be able to interact with 10 residues of the protein, out of which 3 are in the neurotransmitter-gated ion-channel transmembrane domain of GBRA1, whereas cannabidiol interacts with two other residues. Although the results of this project do not indicate the activating /or inhibitory capability of the studied compounds, it suggests that cannabinol can act as a relatively strong ligand for GBRA1.

Keywords: protein-ligand docking, cannabinol, cannabidiol, GBRA1

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Authors: Zahra Akbari, Farzin Zokaee, Talat Ghomashchi

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Whey is a by-product of the dairy industry whose major components are lactose (44–52 g/L), proteins (6–8 g/L) and mineral salts (4–9 g/L). Approximately 50% of 121 million tons of whey produced in the world in 1993 were disposed into rivers, lakes or other water bodies, treated in wastewater treatment plants or loaded onto land. This represents a significant loss of resources and causes serious pollution problems since whey is a heavy organic pollutant with high COD and BOD values, 40–60 g/L and 50–80 g/L, respectively. The removal of cheese whey proteins and minerals represent an important task both in environmental and in food sciences. The most important treatments which are considered in this study, have been done by using lime, Al2O3, FeCl3 and AlCl3 along with heating and also acidic-alkaline method. Results show that the best way for removal of protein is accomplished with adding HCl to decrease pH from 6 to 4, boiling for 20 min, and filtering protein aggregates. Also partial demineralization in whey solution for reducing ash is accomplished by adding NaOH to increase pH to 7.2 and heating solution for 20 min.

Keywords: whey treatment, dairy industry, precipitation, protein, mineral

Procedia PDF Downloads 415

Authors: Lin Lu, Qiang Li, Tao Cai, Pengjun Zhang

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In this study, a detailed analysis of trajectory stability and flow characteristics of a high-speed projectile during the water-entry and water-exit process has been investigated numerically. The Zwart-Gerber-Belamri (Z-G-B) cavitation model and the SST k-ω turbulence model based on the Reynolds Averaged Navier-Stokes (RANS) method are employed. The numerical methodology is validated by comparing the experimental photograph of cavitation shape and the experimental underwater velocity with the numerical simulation results. Based on the numerical methodology, the influences of rotational speed, water-entry and water-exit angle of the projectile on the trajectory stability and flow characteristics have been carried out in detail. The variation features of projectile trajectory and total resistance have been conducted, respectively. In addition, the cavitation characteristics of water-entry and water-exit have been presented and analyzed. Results show that it may not be applicable for the water-entry and water-exit to achieve the projectile stability through the rotation of projectile. Furthermore, there ought to be a critical water-entry angle for the water-entry stability of practical projectile. The impact of water-exit angle on the trajectory stability and cavity phenomenon is not as remarkable as that of the water-entry angle.

Keywords: cavitation characteristics, high-speed projectile, numerical predictions, trajectory stability, water-entry, water-exit

Procedia PDF Downloads 136

Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

Procedia PDF Downloads 137

Authors: JingWei Yu, Hong Yang Yu

Abstract:

At present, the increasingly serious air pollution in various cities of China has made people pay more attention to the air quality index(hereinafter referred to as AQI) of their living areas. To face this situation, it is of great significance to predict air pollution in heavily polluted areas. In this paper, based on the time series model of LSTM, a spatiotemporal prediction model of PM2.5 concentration in Mianyang, Sichuan Province, is established. The model fully considers the temporal variability and spatial distribution characteristics of PM2.5 concentration. The spatial correlation of air quality at different locations is based on the Air quality status of other nearby monitoring stations, including AQI and meteorological data to predict the air quality of a monitoring station. The experimental results show that the method has good prediction accuracy that the fitting degree with the actual measured data reaches more than 0.7, which can be applied to the modeling and prediction of the spatial and temporal distribution of regional PM2.5 concentration.

Keywords: LSTM, PM2.5, neural networks, spatio-temporal prediction

Procedia PDF Downloads 134

Authors: Sadaf Sahar, Usman Qamar, Sadaf Ayaz

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In the software development lifecycle, the quality prediction techniques hold a prime importance in order to minimize future design errors and expensive maintenance. There are many techniques proposed by various researchers, but with the increasing complexity of the software lifecycle model, it is crucial to develop a flexible system which can cater for the factors which in result have an impact on the quality of the end product. These factors include properties of the software development process and the product along with its operation conditions. In this paper, a neural network (perceptron) based software quality prediction technique is proposed. Using this technique, the stakeholders can predict the quality of the resulting software during the early phases of the lifecycle saving time and resources on future elimination of design errors and costly maintenance. This technique can be brought into practical use using successful training.

Keywords: software quality, fuzzy logic, perception, prediction

Procedia PDF Downloads 317

Authors: Farid Shekari

Abstract:

Salicylic Acid (SA) is a plant hormone that improves some physiological responses of plants under stress conditions. Seeds of two desi type chickpea cultivars, viz., Kaka and Pirooz, primed with 250, 500, 750, and 1000 μM of SA and a group of seeds without any treating (as control) were evaluated under rain fed conditions. Seed priming in both cultivars led to higher efficiency compare to non-primed treatments. In general, seed priming with 500 and 750 μM of SA had appropriate effects; however the cultivars responses were different in this regard. Kaka showed better performance both in primed and non-primed seed than Pirooz. Results of this study revealed that not only yield quantity but also yield quality, as seed protein amounts, could positively affect by SA treatments. It seems that SA by enhancing of soluble sugars and proline amounts enhanced total water potential (ψ) and RWC. The increment in RWC led to rose of chlorophyll content of plants chlorophyll stability. In general, SA increased water use efficiency, both in biologic and seed yield base, and drought tolerance of chickpea plants. HI was a little decreased in SA treatments and it shows that SA more effective in biomass production than seed yield.

Keywords: chlorophyll, harvest index, proline, seed protein, soluble sugar, water use efficiency, yield component

Procedia PDF Downloads 423

Authors: Berhan Fikru

Abstract:

The objective of this study was to develop new complementary food from maize, soybean and moringa for young children. The complementary foods were formulated with linear programming (LP Nutri-survey software) and Faffa (corn soya blend) use as control. Analysis were made for formulated blends and compared with the control and recommended daily intake (RDI). Three complementary foods composed of maize, soya bean, moringa and sugar with ratio of 65:20:15:0, 55:25:15:5 and 65:20:10:5 for blend 1, 2 and 3, respectively. The blends were formulated based on the protein, energy, mineral (iron, zinc an calcium) and vitamin (vitamin A and C) content of foods. The overall results indicated that nutrient content of faffa (control) was 16.32 % protein, 422.31 kcal energy, 64.47 mg calcium, 3.8 mg iron, 1.87mg zinc, 0.19 mg vitamin A and 1.19 vitamin C; blend 1 had 17.16 % protein, 429.84 kcal energy, 330.40 mg calcium, 6.19 mg iron, 1.62 mg zinc, 6.33 mg vitamin A and 4.05 mg vitamin C; blend 2 had 20.26 % protein, 418.79 kcal energy, 417.44 mg calcium, 9.26 mg iron, 2.16 mg zinc, 8.43 mg vitamin A and 4.19 mg vitamin C whereas blend 3 exhibited 16.44 % protein, 417.42 kcal energy, 242.4 mg calcium, 7.09 mg iron, 2.22 mg zinc, 3.69 mg vitamin A and 4.72 mg vitamin C, respectively. The difference was found between all means statically significance (P < 0.05). Sensory evaluation showed that the faffa control and blend 3 were preferred by semi-trained panelists. Blend 3 had better in terms of its mineral and vitamin content than FAFFA corn soya blend and comparable with WFP proprietary products CSB+, CSB++ and fulfills the WHO recommendation for protein, energy and calcium. The suggested formulation with Moringa powder can therefore be used as a complementary food to improve the nutritional status and also help solve problems associated with protein energy and micronutrient malnutrition for young children in developing countries, particularly in Ethiopia.

Keywords: corn soya blend, proximate composition, micronutrient, mineral chelating agents, complementary foods

Procedia PDF Downloads 295