Search results for: protein stability prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7422

Search results for: protein stability prediction

7272 Study of Eatable Aquatic Invertebrates in the River Dhansiri, Dimapur, Nagaland, India

Authors: Dilip Nath

Abstract:

A study has been conducted on the available aquatic invertebrates in the river Dhansiri at Dimapur site. The study confirmed that the river body composed of aquatic macroinvertebrate community under two phyla viz., Arthropods and Molluscs. Total 10 species have been identified from there as the source of alternative protein food for the common people. Not only the protein source, they are also the component of aquatic food chain and indicators of aquatic ecosystem. Proper management and strategies to promote the edible invertebrates can be considered as the alternative protein and alternative income source for the common people for sustainable livelihood improvement.

Keywords: Dhansiri, Dimapur, invertebrates, livelihood improvement, protein

Procedia PDF Downloads 121
7271 Probabilistic Slope Stability Analysis of Excavation Induced Landslides Using Hermite Polynomial Chaos

Authors: Schadrack Mwizerwa

Abstract:

The characterization and prediction of landslides are crucial for assessing geological hazards and mitigating risks to infrastructure and communities. This research aims to develop a probabilistic framework for analyzing excavation-induced landslides, which is fundamental for assessing geological hazards and mitigating risks to infrastructure and communities. The study uses Hermite polynomial chaos, a non-stationary random process, to analyze the stability of a slope and characterize the failure probability of a real landslide induced by highway construction excavation. The correlation within the data is captured using the Karhunen-Loève (KL) expansion theory, and the finite element method is used to analyze the slope's stability. The research contributes to the field of landslide characterization by employing advanced random field approaches, providing valuable insights into the complex nature of landslide behavior and the effectiveness of advanced probabilistic models for risk assessment and management. The data collected from the Baiyuzui landslide, induced by highway construction, is used as an illustrative example. The findings highlight the importance of considering the probabilistic nature of landslides and provide valuable insights into the complex behavior of such hazards.

Keywords: Hermite polynomial chaos, Karhunen-Loeve, slope stability, probabilistic analysis

Procedia PDF Downloads 46
7270 The Effects of pH on p53 Phosphorylation by Ataxia Telangiectasia Mutated Kinase

Authors: Serap Pektas

Abstract:

Ataxia telangiectasia mutated (ATM) is a serine-threonine kinase, which is the major regulator of the DNA damage response. ATM is activated upon the formation of DNA double-strand breaks (DSBs) in the cells. ATM phosphorylates the proteins involved in apoptotic responses, cell cycle checkpoint control, DNA repair, etc. Tumor protein p53, known as p53 is one of these proteins that phosphorylated by ATM. Phosphorylation of p53 at Ser15 residue leads to p53 stabilization in the cells. Often enzymes activity is affected by hydrogen ion concentration (pH). In order to find the optimal pH range for ATM activity, steady-state kinetic assays were performed at acidic and basic pH ranges. Ser15 phosphorylation of p53 is determined by using ELISA. The results indicated that the phosphorylation rate was better at basic pH range compared with the acidic pH range. This could be due to enzyme stability, or enzyme-substrate interaction is pH dependent.

Keywords: ataxia telangiectasia mutated, DNA double strand breaks, DNA repair, tumor protein p53

Procedia PDF Downloads 107
7269 Modeling and Shape Prediction for Elastic Kinematic Chains

Authors: Jiun Jeon, Byung-Ju Yi

Abstract:

This paper investigates modeling and shape prediction of elastic kinematic chains such as colonoscopy. 2D and 3D models of elastic kinematic chains are suggested and their behaviors are demonstrated through simulation. To corroborate the effectiveness of those models, experimental work is performed using a magnetic sensor system.

Keywords: elastic kinematic chain, shape prediction, colonoscopy, modeling

Procedia PDF Downloads 571
7268 Rational Design of Potent Compounds for Inhibiting Ca2+ -Dependent Calmodulin Kinase IIa, a Target of Alzheimer’s Disease

Authors: Son Nguyen, Thanh Van, Ly Le

Abstract:

Ca2+ - dependent calmodulin kinase IIa (CaMKIIa) has recently been found to associate with protein tau missorting and polymerization in Alzheimer’s Disease (AD). However, there has yet inhibitors targeting CaMKIIa to investigate the correlation between CaMKIIa activity and protein tau polymer formation. Combining virtual screening and our statistics in binding contribution scoring function (BCSF), we rationally identified potential compounds that bind to specific CaMKIIa active site and specificity-affinity distribution of the ligand within the active site. Using molecular dynamics simulation, we identified structural stability of CaMKIIa and potent inhibitors, and site-directed bonding, separating non-specific and specific molecular interaction features. Despite of variation in confirmation of simulation time, interactions of the potent inhibitors were found to be strongly associated with the unique chemical features extracted from molecular binding poses. In addition, competitive inhibitors within CaMKIIa showed an important molecular recognition pattern toward specific ligand features. Our approach combining virtual screening with BCSF may provide an universally applicable method for precise identification in the discovery of compounds.

Keywords: Alzheimer’s disease, Ca 2+ -dependent calmodulin kinase IIa, protein tau, molecular docking

Procedia PDF Downloads 251
7267 CAP-Glycine Protein Governs Growth, Differentiation, and the Pathogenicity of Global Meningoencephalitis Fungi

Authors: Kyung-Tae Lee, Li Li Wang, Kwang-Woo Jung, Yong-Sun Bahn

Abstract:

Microtubules are involved in mechanical support, cytoplasmic organization as well as in a number of cellular processes by interacting with diverse microtubule-associated proteins (MAPs), such as plus-end tracking proteins, motor proteins, and tubulin-folding cofactors. A common feature of these proteins is the presence of a cytoskeleton-associated protein-glycine-rich (CAP-Gly) domain, which is evolutionarily conserved and generally considered to bind to α-tubulin to regulate functions of microtubules. However, there has been a dearth of research on CAP-Gly proteins in fungal pathogens, including Cryptococcus neoformans, which causes fatal meningoencephalitis globally. In this study, we identified five CAP-Gly proteins encoding genes in C. neoformans. Among these, Cgp1, encoded by CNAG_06352, has a unique domain structure that has not been reported before in other eukaryotes. Supporting the role of Cpg1 in microtubule-related functions, we demonstrate that deletion or overexpression of CGP1 alters cellular susceptibility to thiabendazole, a microtubule destabilizer, and Cgp1 is co-localized with cytoplasmic microtubules. Related to the cellular functions of microtubules, Cgp1 also governs maintenance of membrane stability and genotoxic stress responses. Furthermore, we demonstrate that Cgp1 uniquely regulates sexual differentiation of C. neoformans with distinct roles in the early and late stage of mating. Our domain analysis reveals that the CAP-Gly domain plays major roles in all the functions of Cgp1. Finally, the cgp1Δ mutant is attenuated in virulence. In conclusion, this novel CAP-Gly protein, Cgp1, has pleotropic roles in regulating growth, stress responses, differentiation and pathogenicity of C. neoformans.

Keywords: human fungal pathogen, CAP-Glycine protein, microtubule, meningoencephalitis

Procedia PDF Downloads 287
7266 Identification and Characterization of Nuclear Envelope Protein Interactions

Authors: Mohammed Hakim Jafferali, Balaje Vijayaraghavan, Ricardo A. Figueroa, Ellinor Crafoord, Veronica J. Larsson, Einar Hallberg, Santhosh Gudise

Abstract:

The nuclear envelope which surrounds the chromatin of eukaryotic cells contains more than a hundred transmembrane proteins. Mutations in some genes encoding nuclear envelope proteins give rise to human diseases including neurological disorders. The function of many nuclear envelope proteins is not well established. This is partly because nuclear envelope proteins and their interactions are difficult to study due to the inherent resistance to extraction of nuclear envelope proteins. We have developed a novel method called MCLIP, to identify interacting partners of nuclear envelope proteins in live cells. Using MCLIP, we found three new binding partners of the inner nuclear membrane protein Samp1: the intermediate filament protein Lamin B1, the LINC complex protein Sun1 and the G-protein Ran. Furthermore, using in vitro studies, we show that Samp1 binds both Emerin and Ran directly. We have also studied the interaction between Samp1 and Ran in detail. The results show that the Samp1 binds stronger to RanGTP than RanGDP. Samp1 is the first transmembrane protein known to bind Ran and it is tempting to speculate that Samp1 may provide local binding sites for RanGTP at membranes.

Keywords: MCLIP, nuclear envelope, ran, Samp1

Procedia PDF Downloads 323
7265 Prediction on Housing Price Based on Deep Learning

Authors: Li Yu, Chenlu Jiao, Hongrun Xin, Yan Wang, Kaiyang Wang

Abstract:

In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.

Keywords: deep learning, convolutional neural network, LSTM, housing prediction

Procedia PDF Downloads 279
7264 The Role of a Novel DEAD-Box Containing Protein in NLRP3 Inflammasome Activation

Authors: Yi-Hui Lai, Chih-Hsiang Yang, Li-Chung Hsu

Abstract:

The inflammasome is a protein complex that modulates caspase-1 activity, resulting in proteolytic cleavage of proinflammatory cytokines such as IL-1β and IL-18, into their bioactive forms. It has been shown that the inflammasomes play a crucial role in the clearance of pathogenic infection and tissue repair. However, dysregulated inflammasome activation contributes to a wide range of human diseases such as cancers and auto-inflammatory diseases. Yet, regulation of NLRP3 inflammasome activation remains largely unknown. We discovered a novel DEAD box protein, whose biological function has not been reported, not only negatively regulates NLRP3 inflammasome activation by interfering NLRP3 inflammasome assembly and cellular localization but also mitigate pyroptosis upon pathogen evasion. The DEAD-box protein is the first DEAD-box protein gets involved in modulation of the inflammasome activation. In our study, we found that caspase-1 activation and mature IL-1β production were largely enhanced upon LPS challenge in the DEAD box-containing protein- deleted THP-1 macrophages and bone marrow-derived macrophages (BMDMs). In addition, this DEAD box-containing protein migrates from the nucleus to the cytoplasm upon LPS stimulation, which is required for its inhibitory role in NLRP3 inflammasome activation. The DEAD box-containing protein specifically interacted with the LRR motif of NLRP3 via its DEAD domain. Furthermore, due to the crucial role of the NLRP3 LRR domain in the recruitment of NLRP3 to mitochondria and binding to its adaptor ASC, we found that the interaction of NLRP3 and ASC was downregulated in the presence of the DEAD box-containing protein. In addition to the mechanical study, we also found that this DEAD box protein protects host cells from inflammasome-triggered cell death in response to broad-ranging pathogens such as Candida albicans, Streptococcus pneumoniae, etc., involved in nosocomial infections and severe fever shock. Collectively, our results suggest that this novel DEAD box molecule might be a key therapeutic strategy for various infectious diseases.

Keywords: inflammasome, inflammation, innate immunity, pyroptosis

Procedia PDF Downloads 259
7263 RNA Antisense Coat Protein Showing Promising Effects against Cotton Leaf Curl Disease in Pakistani Cotton

Authors: Zunnu Raen Akhtar

Abstract:

Cotton Leaf Curl Disease (CLCuD) is from Gemini virus and is transmitted through whiteflies in cotton. Transgenic cotton containing Antisense Coat Protein (ACP) has been found to show better results against CLCuD in cotton. In current research, Antisense Coat Protein was inserted in cotton plants to observe resistance developed in the cotton plants against CLCuD. T1 generation of plants were observed for its expression in plants. Tests were carried out to observe the expression of Antisense Coat Protein using Polymerase Chain Reaction (PCR) technique and by southern blotting. Whiteflies showing positive Cotton Leaf Curl Virus (CLCV) were reared and released in bioassay on ACP expressing cotton plants under laboratory as well as confined semi-field conditions. Results confirmed the expression of AC protein in PCR and southern blotting. Further laboratory results showed that cotton plants expressing AC protein showed rare incidence of CLCuD infection as compared to control. In the confined semi-field, similar results were observed in AC protein expressing cotton as compared to control. These results explicitly show that ACP can help to tackle the CLCuD issue in the future and further studies on biochemical processes involved in these plants and effects of ACP induction on non-target organisms should also be studied for eco-system.

Keywords: cotton, white flies, antisense coat protein, CLCV

Procedia PDF Downloads 158
7262 Enhancing Protein Incorporation in Calcium Phosphate Coating on Titanium by Rapid Biomimetic Co-Precipitation Technique

Authors: J. Suwanprateeb, F. Thammarakcharoen

Abstract:

Calcium phosphate coating (CaP) has been employed for protein delivery, but the typical direct protein adsorption on the coating led to low incorporation content and fast release of the protein from the coating. By using bovine serum albumin (BSA) as a model protein, rapid biomimetic co-precipitation between calcium phosphate and BSA was employed to control the distribution of BSA within calcium phosphate coating during biomimetic formation on titanium surface for only 6 h at 50 oC in an accelerated calcium phosphate solution. As a result, the amount of BSA incorporation and release duration could be increased by using a rapid biomimetic co-precipitation technique. Up to 43 fold increases in the BSA incorporation content and the increase from 6 h to more than 360 h in release duration compared to typical direct adsorption technique were observed depending on the initial BSA concentration used during co-precipitation (1, 10, and 100 microgram/ml). From X-ray diffraction and Fourier transform infrared spectroscopy studies, the coating composition was not altered with the incorporation of BSA by this rapid biomimetic co-precipitation and mainly comprised octacalcium phosphate and hydroxyapatite. However, the microstructure of calcium phosphate crystals changed from straight, plate-like units to curved, plate-like units with increasing BSA content.

Keywords: biomimetic, Calcium Phosphate Coating, protein, titanium

Procedia PDF Downloads 359
7261 Surface Characterization and Femtosecond-Nanosecond Transient Absorption Dynamics of Bioconjugated Gold Nanoparticles: Insight into the Warfarin Drug-Binding Site of Human Serum Albumin

Authors: Osama K. Abou-Zied, Saba A. Sulaiman

Abstract:

We studied the spectroscopy of 25-nm diameter gold nanoparticles (AuNPs), coated with human serum albumin (HSA) as a model drug carrier. The morphology and coating of the AuNPs were examined using transmission electron microscopy and dynamic light scattering. Resonance energy transfer from the sole tryptophan of HSA (Trp214) to the AuNPs was observed in which the fluorescence quenching of Trp214 is dominated by a static mechanism. Using fluorescein (FL) to probe the warfarin drug-binding site in HSA revealed the unchanged nature of the binding cavity on the surface of the AuNPs, indicating the stability of the protein structure on the metal surface. The transient absorption results of the surface plasmonic resonance (SPR) band of the AuNPs show three ultrafast dynamics that are involved in the relaxation process after excitation at 460 nm. The three decay components were assigned to the electron-electron (~ 400 fs), electron-phonon (~ 2.0 ps) and phonon-phonon (200–250 ps) interactions. These dynamics were not changed upon coating the AuNPs with HSA which indicates the chemical and physical stability of the AuNPs upon bioconjugation. Binding of FL in HSA did not have any measurable effect on the bleach recovery dynamics of the SPR band, although both FL and AuNPs were excited at 460 nm. The current study is important for a better understanding of the physical and dynamical properties of protein-coated metal nanoparticles which are expected to help in optimizing their properties for critical applications in nanomedicine.

Keywords: gold nanoparticles, human serum albumin, fluorescein, femtosecond transient absorption

Procedia PDF Downloads 306
7260 Slope Stability Considering the Top Building Load

Authors: Micke Didit, Xiwen Zhang, Weidong Zhu

Abstract:

Slope stability is one of the most important subjects of geotechnics. The slope top-loading plays a key role in the stability of slopes in hill slope areas. Therefore, it is of great importance to study the relationship between the load and the stability of the slope. This study aims to analyze the influence of the building load applied on the top of the slope and deduces its effect on the slope stability. For this purpose, a three-dimensional slope model under different building loads with different distances to the slope shoulder was established using the finite-difference analysis software Flac3D. The results show that the loads applied at different distances on the top of the slope have different effects on the slope stability. The slope factor of safety (fos) increases with the increase of the distance between the top-loading and the slope shoulder, resulting in the decrease of the coincidence area between the load-deformation and the potential sliding surface. The slope is no longer affected by the potential risk of sliding at approximately 20 m away from the slope shoulder.

Keywords: building load, finite-difference analysis, FLAC3D software, slope factor of safety, slope stability

Procedia PDF Downloads 151
7259 Protein Extraction by Enzyme-Assisted Extraction followed by Alkaline Extraction from Red Seaweed Eucheuma denticulatum (Spinosum) Used in Carrageenan Production

Authors: Alireza Naseri, Susan L. Holdt, Charlotte Jacobsen

Abstract:

In 2014, the global amount of carrageenan production was 60,000 ton with a value of US$ 626 million. From this number, it can be estimated that the total dried seaweed consumption for this production was at least 300,000 ton/year. The protein content of these types of seaweed is 5 – 25%. If just half of this total amount of protein could be extracted, 18,000 ton/year of a high-value protein product would be obtained. The overall aim of this study was to develop a technology that will ensure further utilization of the seaweed that is used only as raw materials for carrageenan production as single extraction at present. More specifically, proteins should be extracted from the seaweed either before or after extraction of carrageenan with focus on maintaining the quality of carrageenan as a main product. Different mechanical, chemical and enzymatic technologies were evaluated. The optimized process was implemented in lab scale and based on its results; the new experiments were done a pilot and larger scale. In order to calculate the efficiency of the new upstream multi-extraction process, protein content was tested before and after extraction. After this step, the extraction of carrageenan was done and carrageenan content and the effect of extraction on yield were evaluated. The functionality and quality of carrageenan were measured based on rheological parameters. The results showed that by using the new multi-extraction process (submitted patent); it is possible to extract almost 50% of total protein without any negative impact on the carrageenan quality. Moreover, compared to the routine carrageenan extraction process, the new multi-extraction process could increase the yield of carrageenan and the rheological properties such as gel strength in the final carrageenan had a promising improvement. The extracted protein has initially been screened as a plant protein source in typical food applications. Further work will be carried out in order to improve properties such as color, solubility, and taste.

Keywords: carrageenan, extraction, protein, seaweed

Procedia PDF Downloads 250
7258 Landfill Design for Reclamation of Şırnak Coal Mine Dumps: Shalefill Stability and Risk Assessment

Authors: Yıldırım I. Tosun, Halim Cevizci, Hakan Ceylan

Abstract:

By GEO5 FEM program with four rockfill slope modeling and stability analysis was performed for S1, S2, S3 and S4 slopes where landslides of the shalefills were limited. Effective angle of internal friction (φ'°) 17°-22.5°, the effective cohesion (c') from 0.5 to 1.8 kPa, saturated unit weight 1.78-2.43 g/cm3, natural unit weight 1.9-2.35 g/cm3, dry unit weight 1.97-2.40 g/cm3, the permeability coefficient of 1x10-4 - 6.5x10-4 cm/s. In cross-sections of the slope, GEO 5 FEM program possible critical surface tension was examined. Rockfill dump design was made to prevent sliding slopes. Bulk material designated geotechnical properties using also GEO5 programs FEM and stability program via a safety factor determined and calculated according to the values S3 and S4 No. slopes are stable S1 and S2 No. slopes were close to stable state that has been found to be risk. GEO5 programs with limestone rock fill dump through FEM program was found to exhibit stability.

Keywords: slope stability, stability analysis, rockfills, sock stability

Procedia PDF Downloads 459
7257 Urban Growth Prediction Using Artificial Neural Networks in Athens, Greece

Authors: Dimitrios Triantakonstantis, Demetris Stathakis

Abstract:

Urban areas have been expanded throughout the globe. Monitoring and modeling urban growth have become a necessity for a sustainable urban planning and decision making. Urban prediction models are important tools for analyzing the causes and consequences of urban land use dynamics. The objective of this research paper is to analyze and model the urban change, which has been occurred from 1990 to 2000 using CORINE land cover maps. The model was developed using drivers of urban changes (such as road distance, slope, etc.) under an Artificial Neural Network modeling approach. Validation was achieved using a prediction map for 2006 which was compared with a real map of Urban Atlas of 2006. The accuracy produced a Kappa index of agreement of 0,639 and a value of Cramer's V of 0,648. These encouraging results indicate the importance of the developed urban growth prediction model which using a set of available common biophysical drivers could serve as a management tool for the assessment of urban change.

Keywords: artificial neural networks, CORINE, urban atlas, urban growth prediction

Procedia PDF Downloads 501
7256 Relation between Initial Stability of the Dental Implant and Bone-Implant Contact Level

Authors: Jui-Ting Hsu, Heng-Li Huang, Ming-Tzu Tsai, Kuo-Chih Su, Lih-Jyh Fuh

Abstract:

The objectives of this study were to measure the initial stability of the dental implant (ISQ and PTV) in the artificial foam bone block with three different quality levels. In addition, the 3D bone to implant contact percentage (BIC%) was measured based on the micro-computed tomography images. Furthermore, the relation between the initial stability of dental implant (ISQ and PTV) and BIC% were calculated. The experimental results indicated that enhanced the material property of the artificial foam bone increased the initial stability of the dental implant. The Pearson’s correlation coefficient between the BIC% and the two approaches (ISQ and PTV) were 0.652 and 0.745.

Keywords: dental implant, implant stability quotient, peak insertion torque, bone-implant contact, micro-computed tomography

Procedia PDF Downloads 555
7255 Characterization of the Catalytic and Structural Roles of the Human Hexokinase 2 in Cancer Progression

Authors: Mir Hussain Nawaz, Lyudmila Nedyalkova, Haizhong Zhu, Wael M. Rabeh

Abstract:

In this study, we aim to biochemically and structurally characterize the interactions of human HK2 with the mitochondria in addition to the role of its N-terminal domain in catalysis and stability of the full-length enzyme. Here, we solved the crystal structure of human HK2 in complex with glucose and glucose-6-phosphate (PDB code: 2NZT), where it is a homodimer with catalytically active N- and C-terminal domains linked by a seven-turn α-helix. Different from the inactive N-terminal domains of isozymes 1 and 3, the N- domain of HK2 not only capable to catalyze a reaction but it is responsible for the thermodynamic stabilizes of the full-length enzyme. Deletion of first α-helix of the N-domain that binds to the mitochondria altered the stability and catalytic activity of the full-length HK2. In addition, we found the linker helix between the N- and C-terminal domains to play an important role in controlling the catalytic activity of the N-terminal domain. HK2 is a major step in the regulation of glucose metabolism in cancer making it an ideal target for the development of new anticancer therapeutics. Characterizing the structural and molecular mechanisms of human HK2 and its role in cancer metabolism will accelerate the design and development of new cancer therapeutics that are safe and cancer specific.

Keywords: cancer metabolism, enzymology, drug discovery, protein stability

Procedia PDF Downloads 237
7254 Virtual Reality Based 3D Video Games and Speech-Lip Synchronization Superseding Algebraic Code Excited Linear Prediction

Authors: P. S. Jagadeesh Kumar, S. Meenakshi Sundaram, Wenli Hu, Yang Yung

Abstract:

In 3D video games, the dominance of production is unceasingly growing with a protruding level of affordability in terms of budget. Afterward, the automation of speech-lip synchronization technique is customarily onerous and has advanced a critical research subject in virtual reality based 3D video games. This paper presents one of these automatic tools, precisely riveted on the synchronization of the speech and the lip movement of the game characters. A robust and precise speech recognition segment that systematized with Algebraic Code Excited Linear Prediction method is developed which unconventionally delivers lip sync results. The Algebraic Code Excited Linear Prediction algorithm is constructed on that used in code-excited linear prediction, but Algebraic Code Excited Linear Prediction codebooks have an explicit algebraic structure levied upon them. This affords a quicker substitute to the software enactments of lip sync algorithms and thus advances the superiority of service factors abridged production cost.

Keywords: algebraic code excited linear prediction, speech-lip synchronization, video games, virtual reality

Procedia PDF Downloads 445
7253 Inhibitory Effects of Ambrosia trifida L. on the Development of Root Hairs and Protein Patterns of Radicles

Authors: Ji-Hyon Kil, Kew-Cheol Shim, Kyoung-Ae Park, Kyoungho Kim

Abstract:

Ambrosia trifida L. is designated as invasive alien species by the Act on the Conservation and Use of Biodiversity by the Ministry of Environment, Korea. The purpose of present paper was to investigate the inhibitory effects of aqueous extracts of A.trifida on the development of root hairs of Triticum aestivum L., and Allium tuberosum Rottler ex Spreng and the electrophoretic protein patterns of their radicles. The development of root hairs was inhibited by increasing of aqueous extract concentrations. Through SDS-PAGE, the electrophoretic protein bands of extracted proteins from their radicles were appeared in controls, but protein bands of specific molecular weight disappeared or weakened in treatments. In conclusion, inhibitory effects of A. trifida made two receptor species changed morphologically, and at the molecular level in early growth stage.

Keywords: Ambrosia trifida L., invasive alien species, inhibitory effect, root hair, electrophoretic protein, radicle

Procedia PDF Downloads 326
7252 The Effect of Using Levels of Red Tiger Shrimp Meal in Starter Broiler Diet upon Growth Performance

Authors: Mohammed I.A. Al-Neemi, Mohammed S.B., Al-Hlawee, Ilham N. Ezaddin, Soz A. Faris, Omer E. Fakhry, Heemen S. Mageed

Abstract:

This objective of this study was to measure the effect of replacing different levels of animal protein concentrate with Red Tiger shrimp meal (RTSM: 60 % crude protein, 2400 M.E kcal/kg and the source of RTSM was imported from china) in the broiler starter diets. A total 300 broiler chicks (Ross-308) were randomly assigned in treatments dietary contained three different levels of RTSM (0.00, 4.16 and 8.32 %) in experimental diet with a completely randomized design (CRD). Each treatment included four replicates (floor pens) and 25 broilers in each replication (Pen). Therefore, floor space for each boilers was 900 cm2. Initially, the broilers where exposed to a continues lighting of 23:30 hours and dark period of 30 minutes in each 24 hours. Feed and water were supplied ad libitum to the broilers throughout the experimental period (1-21 days). The results of this study indicated that body weight (B.W.), body weight gain (B.W.G), conversion ratio of feed, protein and energy (F.CR, P.C.R and E.C.R) were significantly (p ≤ 0.05) decreased by complete substituting (RTSM) for animal protein concentration (third treatment). Mortality percentage significantly (p ≤ 0.05) increased for third dietary treatment. No significant differences were found for feed, protein and energy intake among treatments during the experimental period (three weeks). In conclusion, (RTSM) could be included to 4.16% in the broiler starter diet or substitute the protein Red Tiger shrimp as alternative of protein animal protein concentrate as much as 50%.

Keywords: red tiger shrimp, broiler, starter diet, growth performance, animal protein concentrate

Procedia PDF Downloads 543
7251 Cross Project Software Fault Prediction at Design Phase

Authors: Pradeep Singh, Shrish Verma

Abstract:

Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. The earlier we predict the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven data sets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.

Keywords: software metrics, fault prediction, cross project, within project.

Procedia PDF Downloads 312
7250 Effect of Change in Angle of Slope and Height of an Embankment on Safety Factor during Rapid Drawdown

Authors: Seyed Abolhassan Naeini, Azam Kouhpeyma

Abstract:

Reduction of water level at which a slope is submerged with it is called drawdown. Draw down can took place rapidly or slowly and in both situations, it can affect slope stability. Using coupled analysis (seepage and stability analysis) causes more accurate results. In this study, the stability of homogeneous embankment is investigated numerically. Slope safety factor changes due to changes in three factors of height, slope and drawdown rate have been investigated and compared. It was found that with increasing height and slope, the safety factor decreases, and with increasing the discharge rate, the safety factor increases.

Keywords: drawdown, slope stability, coupled seepage and stability analysis

Procedia PDF Downloads 92
7249 Nutritional Characteristics, Mineral contents, Amino acid Composition and Phytochemical Analysis of Eryngium alpinium Leaf Protein Concentrates

Authors: Owonikoko A. D., Odoje O. F.

Abstract:

Fresh sample of Eryngium alpinum was purchased and processed for leaf protein concentrates with a view to evaluating its nutritional potential, mineral composition, amino acid characteristics and phytochemical constituents. Using standard analytical methods. The proximate composition of the leaf protein concentrates revealed moisture content;(5.35±0.21)g/100g, ash;(11.37±0.43)g/100g, crude protein;(48.17±0.46)g/100g, crude fat;(15.38±0.07)g/100g, crude fibre (3.05±0.46)g/100g, and Nitrogen free extractive; (16.68±0.30) g/100g. The mineral content was: Na;(51.88±0.23) mg/100g, K;(65.40±0.32)mg/100g, Ca; (86.89±0.46)mg/100g, Mg;(49.27±0.42) mg/100g, Zn;(0.62±0.03)mg/100g, Fe (6.65±0.43)mg/100g, Mn;(0.96±0.54)mg/100g, Cd;(0.28±0.04)mg/100g, P; (8.55±0.97)mg/100g, while selenium, lead and mercury were not detected in the sample indicating that the sample is free of causing risk of metal poisoning. The results of phytochemical constituents showed phytate; (18.34±0.36)mg/100g, flavonoid (0.25±0.41)mg/100g. The sample contain both essential and non-essential amino acid, with the highest value of Glutamic acid (12.26) and the lowest value of Tryptophan 1.05. the content of the leaf protein content shows that the sample is fit for dietary consumption and could as well be processed to be used as food additives.

Keywords: mineral composition, phytochemical analysis, leaf protein concentrates, eryngium alpinum

Procedia PDF Downloads 79
7248 A Deep Learning-Based Pedestrian Trajectory Prediction Algorithm

Authors: Haozhe Xiang

Abstract:

With the rise of the Internet of Things era, intelligent products are gradually integrating into people's lives. Pedestrian trajectory prediction has become a key issue, which is crucial for the motion path planning of intelligent agents such as autonomous vehicles, robots, and drones. In the current technological context, deep learning technology is becoming increasingly sophisticated and gradually replacing traditional models. The pedestrian trajectory prediction algorithm combining neural networks and attention mechanisms has significantly improved prediction accuracy. Based on in-depth research on deep learning and pedestrian trajectory prediction algorithms, this article focuses on physical environment modeling and learning of historical trajectory time dependence. At the same time, social interaction between pedestrians and scene interaction between pedestrians and the environment were handled. An improved pedestrian trajectory prediction algorithm is proposed by analyzing the existing model architecture. With the help of these improvements, acceptable predicted trajectories were successfully obtained. Experiments on public datasets have demonstrated the algorithm's effectiveness and achieved acceptable results.

Keywords: deep learning, graph convolutional network, attention mechanism, LSTM

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7247 Formulation of Extended-Release Ranolazine Tablet and Investigation Its Stability in the Accelerated Stability Condition at 40⁰C and 75% Humidity

Authors: Farzad Khajavi, Farzaneh Jalilfar, Faranak Jafari, Leila Shokrani

Abstract:

Formulation of Ranolazine in the form of extended-release tablet in 500 mg dosage form was performed using Eudragit L100-55 as a retarding agent. Drug-release profiles were investigated in comparison with the reference Ranexa extended-release 500 mg tablet. F₂ and f₁ were calculated as 64.16 and 8.53, respectively. According to Peppas equation, the release of drug is controlled by diffusion (n=0.5). The tablets were put into accelerated stability conditions (40 °C, 75% humidity) for 3 and 6 months. The dissolution release profiles and other physical and chemical characteristics of the tablets confirmed the robustness and stability of formulation in this condition.

Keywords: drug release, extended-release tablet, ranolazine, stability

Procedia PDF Downloads 127
7246 Development of Prediction Models of Day-Ahead Hourly Building Electricity Consumption and Peak Power Demand Using the Machine Learning Method

Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

Abstract:

To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

Procedia PDF Downloads 291
7245 Comparative Rumen Degradable and Rumen Undegradable Fractions in Untreated, Formaldehyde and Heat Treated Vegetable Protein Sources of Pakistan

Authors: Illahi Bakhsh Marghazani, Nasrullah, Masood Ul Haq Kakar, Abdul Hameed Baloch, Ahmad Nawaz Khoso, Behram Chacher

Abstract:

Protein sources are the major part of ration fed to dairy buffaloes in Pakistan however, the limited availability and lack of judicious use of protein resources are further aggravating the conditions to enhance milk and meat production. In order to gain maximum production from limited protein source availability, it is necessary to balance feed for rumen degradable and rumen undegradable protein fractions. This study planned to know the rumen degradable and rumen undegradable fractions in all vegetable protein sources with (formaldehyde and heat treatment) and without treatments. Samples of soybean meal, corn gluten meal 60%, maize gluten feed, guar meal, sunflower meal, rapeseed meal, rapeseed cake, canola meal, cottonseed cake, cottonseed meal, coconut cake, coconut meal, palm kernel cake, almond cake and sesame cake were collected from ten different geographical locations of Pakistan. These samples were also subjected to formaldehyde (1% /100g CP of test feed) and heat treatments (1 hr at 15 lb psi/100 g CP of test feed). In situ technique was used to know the ruminal degradability characteristics. Data obtained were fitted to Orskove equation. Results showed that both treatments significantly (P < 0.05) decreased ruminal degradability in all vegetable protein sources than untreated vegetable protein sources, however, of both treatments, heat treatment was more effective than formaldehyde treatment in decreasing ruminal degradability in most of the studied vegetable protein sources.

Keywords: formaldehyde and heat treatments, in situ technique, rumen degradable and rumen undegradable fractions, vegetable protein sources

Procedia PDF Downloads 304
7244 Stability and Boundedness Theorems of Solutions of Certain Systems of Differential Equations

Authors: Adetunji A. Adeyanju., Mathew O. Omeike, Johnson O. Adeniran, Biodun S. Badmus

Abstract:

In this paper, we discuss certain conditions for uniform asymptotic stability and uniform ultimate boundedness of solutions to some systems of Aizermann-type of differential equations by means of second method of Lyapunov. In achieving our goal, some Lyapunov functions are constructed to serve as basic tools. The stability results in this paper, extend some stability results for some Aizermann-type of differential equations found in literature. Also, we prove some results on uniform boundedness and uniform ultimate boundedness of solutions of systems of equations study.

Keywords: Aizermann, boundedness, first order, Lyapunov function, stability

Procedia PDF Downloads 61
7243 Prediction of CO2 Concentration in the Korea Train Express (KTX) Cabins

Authors: Yong-Il Lee, Do-Yeon Hwang, Won-Seog Jeong, Duckshin Park

Abstract:

Recently, because of the high-speed trains forced ventilation, it is important to control the ventilation. The ventilation is for controlling various contaminants, temperature, and humidity. The high-speed train route is straight to a destination having a high speed. And there are many mountainous areas in Korea. So, tunnel rate is higher then other country. KTX HVAC block off the outdoor air, when entering tunnel. So the high tunnel rate is an effect of ventilation in the KTX cabin. It is important to reduction rate in CO2 concentration prediction. To meet the air quality of the public transport vehicles recommend standards, the KTX cabin of CO2 concentration should be managed. In this study, the concentration change was predicted by CO2 prediction simulation in route to be opened.

Keywords: CO2 prediction, KTX, ventilation, infrastructure and transportation engineering

Procedia PDF Downloads 514