Search results for: drug property prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5656

Search results for: drug property prediction

4366 The Prediction Mechanism of M. cajuputi Extract from Lampung-Indonesia, as an Anti-Inflammatory Agent for COVID-19 by NFκβ Pathway

Authors: Agustyas Tjiptaningrum, Intanri Kurniati, Fadilah Fadilah, Linda Erlina, Tiwuk Susantiningsih

Abstract:

Coronavirus disease-19 (COVID-19) is still one of the health problems. It can be a severe condition that is caused by a cytokine storm. In a cytokine storm, several proinflammatory cytokines are released massively. It destroys epithelial cells, and subsequently, it can cause death. The anti-inflammatory agent can be used to decrease the number of severe Covid-19 conditions. Melaleuca cajuputi is a plant that has antiviral, antibiotic, antioxidant, and anti-inflammatory activities. This study was carried out to analyze the prediction mechanism of the M. cajuputi extract from Lampung, Indonesia, as an anti-inflammatory agent for COVID-19. This study constructed a database of protein host target that was involved in the inflammation process of COVID-19 using data retrieval from GeneCards with the keyword “SARS-CoV2”, “inflammation,” “cytokine storm,” and “acute respiratory distress syndrome.” Subsequent protein-protein interaction was generated by using Cytoscape version 3.9.1. It can predict the significant target protein. Then the analysis of the Gene Ontology (GO) and KEGG pathways was conducted to generate the genes and components that play a role in COVID-19. The result of this study was 30 nodes representing significant proteins, namely NF-κβ, IL-6, IL-6R, IL-2RA, IL-2, IFN2, C3, TRAF6, IFNAR1, and DOX58. From the KEGG pathway, we obtained the result that NF-κβ has a role in the production of proinflammatory cytokines, which play a role in the COVID-19 cytokine storm. It is an important factor for macrophage transcription; therefore, it will induce inflammatory gene expression that encodes proinflammatory cytokines such as IL-6, TNF-α, and IL-1β. In conclusion, the blocking of NF-κβ is the prediction mechanism of the M. cajuputi extract as an anti-inflammation agent for COVID-19.

Keywords: antiinflammation, COVID-19, cytokine storm, NF-κβ, M. cajuputi

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4365 Synthesis of 5'-Azidonucleosides as Building Blocks for the Preparation of Biologically Active Bioconjugates

Authors: Brigitta Bodnár, Lajos Kovács, Zoltán Kupihár

Abstract:

The cancer cells require higher amount of nucleoside building blocks for their proliferation, therefore they have significantly higher uptake of nucleosides by the different nucleoside transporters. Therefore, the conjugation with nucleosides may significantly increase the efficiency and selectivity of potential active pharmaceutical ingredients. On the other hand, the advantage of using a nucleoside could be either the higher activity on targeted enzymes overrepresented in cancer cells or an enhanced cellular uptake of the bioconjugates in these cells compared to the healthy ones. This fact can be used to make the nucleosides, as targeting moieties covalently bound to anti-cancer drug molecules which can selectively accumulate in cancer cells. However, in order to form the nucleoside-drug conjugates, such nucleoside building blocks are needed, which can selectively be coupled to the drug molecules containing even a high number of diverse functional groups. One of the most selective conjugation techniques is the copper-catalyzed azide-alkyne click reaction that requires the presence of an alkyl group on one of the conjugated molecules and an azide group on the other. In case of nucleosides, the development of azide group is simpler for which the replacement of the 5'-hydroxy group is the most suitable. This transformation generally involves many side reactions and result in very low yields. In addition, during our experiments, the transformation of the 2'-deoxyguanosine to the corresponding 5'-deoxy-5’-azido-2’-deoxyguanosine could not be performed with any of the methods described in the literature. Therefore, we have tried to overcome these difficulties with not only using the traditional process based on the 2 step exchange of tosyl to azide, but also using the Mitsunobu reaction which requires only one step. However, this path proved to be unsuccessful in spite of the optimizing the reaction conditions. Finally, a method has been developed whereby the azide groups were incorporated into the 5’-position resulting in significantly better yields compared to all other previous methods, and we were able to produce all the four nucleoside derivatives.

Keywords: 5'-azidonucleosides, bioconjugate, click reaction, proliferation

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4364 Automation of Finite Element Simulations for the Design Space Exploration and Optimization of Type IV Pressure Vessel

Authors: Weili Jiang, Simon Cadavid Lopera, Klaus Drechsler

Abstract:

Fuel cell vehicle has become the most competitive solution for the transportation sector in the hydrogen economy. Type IV pressure vessel is currently the most popular and widely developed technology for the on-board storage, based on their high reliability and relatively low cost. Due to the stringent requirement on mechanical performance, the pressure vessel is subject to great amount of composite material, a major cost driver for the hydrogen tanks. Evidently, the optimization of composite layup design shows great potential in reducing the overall material usage, yet requires comprehensive understanding on underlying mechanisms as well as the influence of different design parameters on mechanical performance. Given the type of materials and manufacturing processes by which the type IV pressure vessels are manufactured, the design and optimization are a nuanced subject. The manifold of stacking sequence and fiber orientation variation possibilities have an out-standing effect on vessel strength due to the anisotropic property of carbon fiber composites, which make the design space high dimensional. Each variation of design parameters requires computational resources. Using finite element analysis to evaluate different designs is the most common method, however, the model-ing, setup and simulation process can be very time consuming and result in high computational cost. For this reason, it is necessary to build a reliable automation scheme to set up and analyze the di-verse composite layups. In this research, the simulation process of different tank designs regarding various parameters is conducted and automatized in a commercial finite element analysis framework Abaqus. Worth mentioning, the modeling of the composite overwrap is automatically generated using an Abaqus-Python scripting interface. The prediction of the winding angle of each layer and corresponding thickness variation on dome region is the most crucial step of the modeling, which is calculated and implemented using analytical methods. Subsequently, these different composites layups are simulated as axisymmetric models to facilitate the computational complexity and reduce the calculation time. Finally, the results are evaluated and compared regarding the ultimate tank strength. By automatically modeling, evaluating and comparing various composites layups, this system is applicable for the optimization of the tanks structures. As mentioned above, the mechanical property of the pressure vessel is highly dependent on composites layup, which requires big amount of simulations. Consequently, to automatize the simulation process gains a rapid way to compare the various designs and provide an indication of the optimum one. Moreover, this automation process can also be operated for creating a data bank of layups and corresponding mechanical properties with few preliminary configuration steps for the further case analysis. Subsequently, using e.g. machine learning to gather the optimum by the data pool directly without the simulation process.

Keywords: type IV pressure vessels, carbon composites, finite element analy-sis, automation of simulation process

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4363 Design of Transmit Beamspace and DOA Estimation in MIMO Radar

Authors: S. Ilakkiya, A. Merline

Abstract:

A multiple-input multiple-output (MIMO) radar systems use modulated waveforms and directive antennas to transmit electromagnetic energy into a specific volume in space to search for targets. This paper deals with the design of transmit beamspace matrix and DOA estimation for multiple-input multiple-output (MIMO) radar with collocated antennas.The design of transmit beamspace matrix is based on minimizing the difference between a desired transmit beampattern and the actual one while enforcing the constraint of uniform power distribution across the transmit array elements. Rotational invariance property is established at the transmit array by imposing a specific structure on the beamspace matrix. Semidefinite programming and spatial-division based design (SDD) are also designed separately. In MIMO radar systems, DOA estimation is an essential process to determine the direction of incoming signals and thus to direct the beam of the antenna array towards the estimated direction. This estimation deals with non-adaptive spectral estimation and adaptive spectral estimation techniques. The design of the transmit beamspace matrix and spectral estimation techniques are studied through simulation.

Keywords: adaptive and non-adaptive spectral estimation, direction of arrival estimation, MIMO radar, rotational invariance property, transmit, receive beamforming

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4362 Use of Real Time Ultrasound for the Prediction of Carcass Composition in Serrana Goats

Authors: Antonio Monteiro, Jorge Azevedo, Severiano Silva, Alfredo Teixeira

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The objective of this study was to compare the carcass and in vivo real-time ultrasound measurements (RTU) and their capacity to predict the composition of Serrana goats up to 40% of maturity. Twenty one females (11.1 ± 3.97 kg) and Twenty one males (15.6 ± 5.38 kg) were utilized to made in vivo measurements with a 5 MHz probe (ALOKA 500V scanner) at the 9th-10th, 10th-11th thoracic vertebrae (uT910 and uT1011, respectively), at the 1st- 2nd, 3rd-4th, and 4th-5th lumbar vertebrae (uL12, ul34 and uL45, respectively) and also at the 3rd-4th sternebrae (EEST). It was recorded the images of RTU measurements of Longissimus thoracis et lumborum muscle (LTL) depth (EM), width (LM), perimeter (PM), area (AM) and subcutaneous fat thickness (SFD) above the LTL, as well as the depth of tissues of the sternum (EEST) between the 3rd-4th sternebrae. All RTU images were analyzed using the ImageJ software. After slaughter, the carcasses were stored at 4 ºC for 24 h. After this period the carcasses were divided and the left half was entirely dissected into muscle, dissected fat (subcutaneous fat plus intermuscular fat) and bone. Prior to the dissection measurements equivalent to those obtained in vivo with RTU were recorded. Using the Statistica 5, correlation and regression analyses were performed. The prediction of carcass composition was achieved by stepwise regression procedure, with live weight and RTU measurements with and without transformation of variables to the same dimension. The RTU and carcass measurements, except for SFD measurements, showed high correlation (r > 0.60, P < 0.001). The RTU measurements and the live weight, showed ability to predict carcass composition on muscle (R2 = 0.99, P < 0.001), subcutaneous fat (R2 = 0.41, P < 0.001), intermuscular fat (R2 = 0.84, P < 0.001), dissected fat (R2 = 0.71, P < 0.001) and bone (R2 = 0.94, P < 0.001). The transformation of variables allowed a slight increase of precision, but with the increase in the number of variables, with the exception of subcutaneous fat prediction. In vivo measurements by RTU can be applied to predict kid goat carcass composition, from 5 measurements of RTU and the live weight.

Keywords: carcass, goats, real time, ultrasound

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4361 Characterizing the Fracture Toughness Properties of Aluminum I-Rod Removed from National Research Universal Reactor

Authors: Michael Bach

Abstract:

Extensive weld repair was carried out in 2009 after a leak was detected in the aluminum 5052 vessel of the National Research Universal (NRU) reactor. This was the second vessel installed since 1974. In support of the NRU vessel leak repair and fitness for service assessments, an estimate of property changes due to irradiation exposure is required to extend the service of the reactor until 2018. In order to fully evaluate the property changes in the vessel wall, an Iodine-125 rod (I rod) made from the same material and irradiated in the NRU reactor from 1974 1991, was retrieved and sectioned for microstructure characterization and mechanical testing. The different sections of the I rod were exposed to various levels of thermal neutron fluences from 0 to a maximum of 11.9 x 1022 n/cm2. The end of life thermal neutron fluence of the NRU vessel is estimated to be 2.2 x 1022 n/cm2 at 35 years of service. Tensile test and fracture toughness test was performed on the I-rod material at various axial locations. The changes in tensile properties were attributed primarily to the creation of finely dispersed Mg-Si precipitates that harden the material and reduced the ductility. Despite having a reduction in fracture toughness, the NRU vessel is still operation at the current fluence levels.

Keywords: aluminum alloy, fitness-for-service assessment , fracutre toughness, nuclear reactor, precipitate strengthening, radiation damage, tensile strength

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4360 Study of Regulation and Registration Law of Veterinary Biological Drugs in Iran and Comparison between FDA, EMA and WHO

Authors: Hoda Dehghani, Zahra Dehghani

Abstract:

Considering the obvious growth and variety of veterinary biological product and increase consumption and also the price, it is necessary to establish the rules and serious monitoring of this products which are less expensive than the original products. The scope of this research is the study of comparing the registration criteria and procedures of veterinary biological drugs in the world's leading agencies such as EMA, FDA, and WHO. For this, purpose the rules and regulations for registration of these drugs in prestigious organizations such as the FDA, EMA and WHO were examined and compared with the existing legislation in Iran. Studies show that EMA is the forefront of the compilation and registration of drugs in the world. China is a one of the greatest country in the development of drugs and establishes very closely guidelines with creditable global guidelines, and Now, is the first country to implement the rules codified in the Far East and followed by china, India and, South Korea and Taiwan have taken incorporate the industry's top ranking in Asia. At now, Asia by creating appropriate indicators not only as a powerful center in the field of drug delivery but also as a competitor to the United States is a major source of drug discovery and creation of innovation. the activities such as clinical trials and pharmaceutical investment is the speed of technology on the continent.

Keywords: veterinary biological product, regulation of registration, biological products, regularity authorities

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4359 Identifying and Optimizing the Critical Excipients in Moisture Activated Dry Granulation Process for Two Anti TB Drugs of Different Aqueous Solubilities

Authors: K. Srujana, Vinay U. Rao, M. Sudhakar

Abstract:

Isoniazide (INH) a freely water soluble and pyrazinamide (Z) a practically water insoluble first line anti tubercular (TB) drugs were identified as candidates for optimizing the Moisture Activated Dry Granulation (MADG) process. The work focuses on identifying the effect of binder type and concentration as well as the effect of magnesium stearate level on critical quality attributes of Disintegration time (DT) and in vitro dissolution test when the tablets are processed by the MADG process. Also, the level of the drug concentration, binder concentration and fluid addition during the agglomeration stage of the MADG process was evaluated and optimized. For INH, it was identified that for tablets with HPMC as binder at both 2% w/w and 5% w/w level and Magnesium stearate upto 1%w/w as lubrication the DT is within 1 minute and the dissolution rate is the fastest (> 80% in 15 minutes) as compared to when PVP or pregelatinized starch is used as binder. Regarding the process, fast disintegrating and rapidly dissolving tablets are obtained when the level of drug, binder and fluid uptake in agglomeration stage is 25% w/w 0% w/w binder and 0.033%. w/w. At the other 2 levels of these three ingredients, the DT is significantly impacted and dissolution is also slower. For pyrazinamide,it was identified that for the tablets with 2% w/w level of each of PVP as binder and Cross Caramellose Sodium disintegrant the DT is within 2 minutes and the dissolution rate is the fastest(>80 in 15 minutes)as compared to when HPMC or pregelatinized starch is used as binder. This may be attributed to the fact that PVP may be acting as a solubilizer for the practically insoluble Pyrazinamide. Regarding the process,fast dispersing and rapidly disintegrating tablets are obtained when the level of drug, binder and fluid uptake in agglomeration stage is 10% w/w,25% w/w binder and 1% w/w.At the other 2 levels of these three ingredients, the DT is significantly impacted and dissolution is comparatively slower and less complete.

Keywords: agglomeration stage, isoniazide, MADG, moisture distribution stage, pyrazinamide

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4358 Oil Reservoir Asphalting Precipitation Estimating during CO2 Injection

Authors: I. Alhajri, G. Zahedi, R. Alazmi, A. Akbari

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In this paper, an Artificial Neural Network (ANN) was developed to predict Asphaltene Precipitation (AP) during the injection of carbon dioxide into crude oil reservoirs. In this study, the experimental data from six different oil fields were collected. Seventy percent of the data was used to develop the ANN model, and different ANN architectures were examined. A network with the Trainlm training algorithm was found to be the best network to estimate the AP. To check the validity of the proposed model, the model was used to predict the AP for the thirty percent of the data that was unevaluated. The Mean Square Error (MSE) of the prediction was 0.0018, which confirms the excellent prediction capability of the proposed model. In the second part of this study, the ANN model predictions were compared with modified Hirschberg model predictions. The ANN was found to provide more accurate estimates compared to the modified Hirschberg model. Finally, the proposed model was employed to examine the effect of different operating parameters during gas injection on the AP. It was found that the AP is mostly sensitive to the reservoir temperature. Furthermore, the carbon dioxide concentration in liquid phase increases the AP.

Keywords: artificial neural network, asphaltene, CO2 injection, Hirschberg model, oil reservoirs

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4357 Biosurfactant-Mediated Nanoparticle Synthesis by Bacillus subtilis

Authors: Satya Eswari Jujjavarapu, Swasti Dhagat, Lata Upadhyay, Reecha Sahu

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Silver nanoparticles have a broad range of antimicrobial and antifungal properties ranging from soaps, pastes to sterilization and drug delivery systems. These can be synthesized by physical, chemical and biological methods; biological methods being the most popular owing to their non-toxic nature and reduced energy requirements. Microbial surfactants, produced on the microbial cell surface or excreted extracellularly are an alternative to synthetic surfactants for the production of silver nanoparticles. Hence, they are also called as green molecules. Microbial lipopeptide surfactants (biosurfactant) exhibit anti-tumor and anti-microbial properties and can be used as drug delivery agents. In this study, biosurfactant was synthesized by using a strain of acillus subtilis. The biosurfactant thus produced was analysed by emulsification assay, oil spilling test, and haemolytic test. Biosurfactant-mediated silver nanoparticles were synthesised by microwave irradiation of the culture supernatant and further characterized by UV–vis spectroscopy for a range of 400-600 nm. The UV–vis spectra showed a surface plasmon resonance vibration band at 410 nm corresponding to the peak of silver nanoparticles.

Keywords: biosurfactant, Bacillus subtilis, silver nano particle, lipopeptide

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4356 Geotechnical Characterization of Residual Soil for Deterministic Landslide Assessment

Authors: Vera Karla S. Caingles, Glen A. Lorenzo

Abstract:

Soil, as the main material of landslides, plays a vital role in landslide assessment. An efficient and accurate method of doing an assessment is significantly important to prevent damage of properties and loss of lives. The study has two phases: to establish an empirical correlation of the residual soil thickness with the slope angle and to investigate the geotechnical characteristics of residual soil. Digital Elevation Model (DEM) in Geographic Information System (GIS) was used to establish the slope map and to program sampling points for field investigation. Physical and index property tests were undertaken on the 20 soil samples obtained from the area with Pliocene-Pleistocene geology and different slope angle in Kibawe, Bukidnon. The regression analysis result shows that the best fitting model that can describe the soil thickness-slope angle relationship is an exponential function. The physical property results revealed that soils contain a high percentage of clay and silts ranges from 41% - 99.52%. Based on the index properties test results, the soil exhibits a high degree of plasticity and expansion but not collapsible. It is deemed that this compendium will serve as primary data for slope stability analysis and deterministic landslide assessment.

Keywords: collapsibility, correlation, expansiveness, landslide, plasticity

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4355 Ionic Liquids-Polymer Nanoparticle Systems as Breakthrough Tools to Improve the Leprosy Treatment

Authors: A. Julio, R. Caparica, S. Costa Lima, S. Reis, J. G. Costa, P. Fonte, T. Santos De Almeida

Abstract:

The Mycobacterium leprae causes a chronic and infectious disease called leprosy, which the most common symptoms are peripheral neuropathy and deformation of several parts of the body. The pharmacological treatment of leprosy is a combined therapy with three different drugs, rifampicin, clofazimine, and dapsone. However, clofazimine and dapsone have poor solubility in water and also low bioavailability. Thus, it is crucial to develop strategies to overcome such drawbacks. The use of ionic liquids (ILs) may be a strategy to overcome the low solubility since they have been used as solubility promoters. ILs are salts, liquid below 100 ºC or even at room temperature, that may be placed in water, oils or hydroalcoholic solutions. Another approach may be the encapsulation of drugs into polymeric nanoparticles, which improves their bioavailability. In this study, two different classes of ILs were used, the imidazole- and the choline-based ionic liquids, as solubility enhancers of the poorly soluble antileprotic drugs. Thus, after the solubility studies, it was developed IL-PLGA nanoparticles hybrid systems to deliver such drugs. First of all, the solubility studies of clofazimine and dapsone were performed in water and in water: IL mixtures, at ILs concentrations where cell viability is maintained, at room temperature for 72 hours. For both drugs, it was observed an improvement on the drug solubility and [Cho][Phe] showed to be the best solubility enhancer, especially for clofazimine, where it was observed a 10-fold improvement. Later, it was produced nanoparticles, with a polymeric matrix of poly(lactic-co-glycolic acid) (PLGA) 75:25, by a modified solvent-evaporation W/O/W double emulsion technique in the presence of [Cho][Phe]. Thus, the inner phase was an aqueous solution of 0.2 % (v/v) of the above IL with each drug to its maximum solubility determined on the previous study. After the production, the nanosystem hybrid was physicochemically characterized. The produced nanoparticles had a diameter of around 580 nm and 640 nm, for clofazimine and dapsone, respectively. Regarding the polydispersity index, it was in agreement of the recommended value of this parameter for drug delivery systems (around 0.3). The association efficiency (AE) of the developed hybrid nanosystems demonstrated promising AE values for both drugs, given their low solubility (64.0 ± 4.0 % for clofazimine and 58.6 ± 10.0 % for dapsone), that prospects the capacity of these delivery systems to enhance the bioavailability and loading of clofazimine and dapsone. Overall, the study achievement may signify an upgrading of the patient’s quality of life, since it may mean a change in the therapeutic scheme, not requiring doses of drug so high to obtain a therapeutic effect. The authors would like to thank Fundação para a Ciência e a Tecnologia, Portugal (FCT/MCTES (PIDDAC), UID/DTP/04567/2016-CBIOS/PRUID/BI2/2018).

Keywords: ionic liquids, ionic liquids-PLGA nanoparticles hybrid systems, leprosy treatment, solubility

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4354 Strategies of Drug Discovery in Insects

Authors: Alaaeddeen M. Seufi

Abstract:

Many have been published on therapeutic derivatives from living organisms including insects. In addition to traditional maggot therapy, more than 900 therapeutic products were isolated from insects. Most people look at insects as enemies and others believe that insects are friends. Many beneficial insects rather than Honey Bees, Silk Worms and Shellac insect could insure human-insect friendship. In addition, insects could be MicroFactories, Biosensors or Bioreactors. InsectFarm is an amazing example of the applied research that transfers insects from laboratory to market by Prof Mircea Ciuhrii and co-workers. They worked for 18 years to derive therapeutics from insects. Their research resulted in production of more than 30 commercial medications derived from insects (e.g. Imunomax, Noblesse, etc.). Two general approaches were followed to discover drugs from living organisms. Some laboratories preferred biochemical approach to purify components of the innate immune system of insects and insect metabolites as well. Then the purified components could be tested for many therapeutic trials. Other researchers preferred molecular approach based on proteomic studies. Components of the innate immune system of insects were then tested for their medical activities. Our Laboratory team preferred to induce insect immune system (using oral, topical and injection routes of administration), then a transcriptomic study was done to discover the induced genes and to identify specific biomarkers that can help in drug discovery. Biomarkers play an important role in medicine and in drug discovery and development as well. Optimum biomarker development and application will require a team approach because of the multifaceted nature of biomarker selection, validation, and application. This team uses several techniques such as pharmacoepidemiology, pharmacogenomics, and functional proteomics; bioanalytical development and validation; modeling and simulation to improve and refine drug development. Our Achievements included the discovery of four components of the innate immune system of Spodoptera littoralis and Musca domestica. These components were designated as SpliDef (defesin), SpliLec (lectin), SpliCec (cecropin) and MdAtt (attacin). SpliDef, SpliLec and MdAtt were confirmed as antimicrobial peptides, while SpliCec was additionally confirmed as anticancer peptide. Our current research is going on to achieve something in antioxidants and anticoagulants from insects. Our perspective is to achieve something in the mass production of prototypes of our products and to reach it to the commercial level. These achievements are the integrated contributions of everybody in our team staff.

Keywords: AMPs, insect, innate immunitty, therappeutics

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4353 The Restrictions of the Householder’s ‘Double Two-Thirds Principles’ in Decision-Making for Elevators Addition to Existing Condominium

Authors: Haifeng Shi, Kun Song, Yili Zhao

Abstract:

In China, with the extensive promotion of the ‘aging in place’ pension policy as the background, most of the elders will choose to remain in their current homes and communities, finding out of preference or necessity that they will need to remodel their homes to fit their changing needs. This generation elder born in the 1960s to 1970s almost live in the same form of housing-condominium built from 1982 to 2012. Based on the survey of existing multi-family housing, especially in Tianjin, it is found that the current ‘double two-thirds principles’ is becoming the threshold for modification to existing house, particularly in the project of elevators addition to existing condominium (built from 1982 to 2016 without elevators below 6 floors according to the previous building code). Firstly, this article concludes the local policies of elevator addition nationwide, most of which has determined the importance and necessity of the community-based self-organization principle in the operation of the elevator addition. Secondly, by comparing the three existing community management systems (owners' congress, property management system and community committee) in instances, find that the community-based ‘two-thirds’ principle is not conducive to implement for multi-owned property renovation in the community or common accessibility modification in the building. However, analysis the property and other community management related laws, pointing out the shortcomings of the existing community-based ‘two-thirds’ decision-making norms. The analyzation showed that the unit-based and ‘100% principle’ method is more capable of common accessibility in the condominium in China. Differing from existing laws, the unit-based principle will be effective for the process of decision-making and ‘100% principle’ will protect closely profit-related householders for condominium modification in the multi-owned area. These three aspects of the analysis suggest that the establishment of the unit-based self-organization mechanism is a preferred and inevitable method to solve the problem of elevators addition to the existing condominium in China.

Keywords: aging in place, condominium, modification, multi own

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4352 Numerical Prediction of Effects of Location of Across-the-Width Laminations on Tensile Properties of Rectangular Wires

Authors: Kazeem K. Adewole

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This paper presents the finite element analysis numerical investigation of the effects of the location of across-the-width lamination on the tensile properties of rectangular wires for civil engineering applications. FE analysis revealed that the presence of the mid-thickness across-the-width lamination changes the cup and cone fracture shape exhibited by the lamination-free wire to a V-shaped fracture shape with an opening at the bottom/pointed end of the V-shape at the location of the mid-thickness across-the-width lamination. FE analysis also revealed that the presence of the mid-width across-the-thickness lamination changes the cup and cone fracture shape of the lamination-free wire without an opening to a cup and cone fracture shape with an opening at the location of the mid-width across-the-thickness lamination. The FE fracture behaviour prediction approach presented in this work serves as a tool for failure analysis of wires with lamination at different orientations which cannot be conducted experimentally.

Keywords: across-the-width lamination, tensile properties, lamination location, wire

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4351 Additive Weibull Model Using Warranty Claim and Finite Element Analysis Fatigue Analysis

Authors: Kanchan Mondal, Dasharath Koulage, Dattatray Manerikar, Asmita Ghate

Abstract:

This paper presents an additive reliability model using warranty data and Finite Element Analysis (FEA) data. Warranty data for any product gives insight to its underlying issues. This is often used by Reliability Engineers to build prediction model to forecast failure rate of parts. But there is one major limitation in using warranty data for prediction. Warranty periods constitute only a small fraction of total lifetime of a product, most of the time it covers only the infant mortality and useful life zone of a bathtub curve. Predicting with warranty data alone in these cases is not generally provide results with desired accuracy. Failure rate of a mechanical part is driven by random issues initially and wear-out or usage related issues at later stages of the lifetime. For better predictability of failure rate, one need to explore the failure rate behavior at wear out zone of a bathtub curve. Due to cost and time constraints, it is not always possible to test samples till failure, but FEA-Fatigue analysis can provide the failure rate behavior of a part much beyond warranty period in a quicker time and at lesser cost. In this work, the authors proposed an Additive Weibull Model, which make use of both warranty and FEA fatigue analysis data for predicting failure rates. It involves modeling of two data sets of a part, one with existing warranty claims and other with fatigue life data. Hazard rate base Weibull estimation has been used for the modeling the warranty data whereas S-N curved based Weibull parameter estimation is used for FEA data. Two separate Weibull models’ parameters are estimated and combined to form the proposed Additive Weibull Model for prediction.

Keywords: bathtub curve, fatigue, FEA, reliability, warranty, Weibull

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4350 Evaluation of the CRISP-DM Business Understanding Step: An Approach for Assessing the Predictive Power of Regression versus Classification for the Quality Prediction of Hydraulic Test Results

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Digitalisation in production technology is a driver for the application of machine learning methods. Through the application of predictive quality, the great potential for saving necessary quality control can be exploited through the data-based prediction of product quality and states. However, the serial use of machine learning applications is often prevented by various problems. Fluctuations occur in real production data sets, which are reflected in trends and systematic shifts over time. To counteract these problems, data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets to extract stable features. Successful process control of the target variables aims to centre the measured values around a mean and minimise variance. Competitive leaders claim to have mastered their processes. As a result, much of the real data has a relatively low variance. For the training of prediction models, the highest possible generalisability is required, which is at least made more difficult by this data availability. The implementation of a machine learning application can be interpreted as a production process. The CRoss Industry Standard Process for Data Mining (CRISP-DM) is a process model with six phases that describes the life cycle of data science. As in any process, the costs to eliminate errors increase significantly with each advancing process phase. For the quality prediction of hydraulic test steps of directional control valves, the question arises in the initial phase whether a regression or a classification is more suitable. In the context of this work, the initial phase of the CRISP-DM, the business understanding, is critically compared for the use case at Bosch Rexroth with regard to regression and classification. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. Suitable methods for leakage volume flow regression and classification for inspection decision are applied. Impressively, classification is clearly superior to regression and achieves promising accuracies.

Keywords: classification, CRISP-DM, machine learning, predictive quality, regression

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4349 Development of Intellectual Property Information Services in Zimbabwe’s University Libraries: Assessing the Current Status and Mapping the Future Direction

Authors: Jonathan Munyoro, Takawira Machimbidza, Stephen Mutula

Abstract:

The study investigates the current status of Intellectual Property (IP) information services in Zimbabwe's university libraries. Specifically, the study assesses the current IP information services offered in Zimbabwe’s university libraries, identifies challenges to the development of comprehensive IP information services in Zimbabwe’s university libraries, and suggests solutions for the development of IP information services in Zimbabwe’s university libraries. The study is born out of a realisation that research on IP information services in university libraries has received little attention, especially in developing country contexts, despite the fact that there are calls for heightened participation of university libraries in IP information services. In Zimbabwe, the launch of the National Intellectual Property Policy and Implementation Strategy 2018-2022 and the introduction of the Education 5.0 concept are set to significantly change the IP landscape in the country. Education 5.0 places more emphasis on innovation and industrialisation (in addition to teaching, community service, and research), and has the potential to shift the focus and level of IP output produced in higher and tertiary education institutions beyond copyrights and more towards commercially exploited patents, utility models, and industrial designs. The growing importance of IP commercialisation in universities creates a need for appropriate IP information services to assist students, academics, researchers, administrators, start-ups, entrepreneurs, and inventors. The critical challenge for university libraries is to reposition themselves and remain relevant in the new trajectory. Designing specialised information services to support increased IP generation and commercialisation appears to be an opportunity for university libraries to stay relevant in the knowledge economy. However, IP information services in Zimbabwe’s universities appear to be incomplete and focused mostly on assisting with research publications and copyright-related activities. Research on the existing status of IP services in university libraries in Zimbabwe is therefore necessary to help identify gaps and provide solutions in order to stimulate the growth of new forms of such services. The study employed a quantitative approach. An online questionnaire was administered to 57 academic librarians from 15 university libraries. Findings show that the current focus of the surveyed institutions is on providing scientific research support services (15); disseminating/sharing university research output (14); and copyright activities (12). More specialised IP information services such as IP education and training, patent information services, IP consulting services, IP online service platforms, and web-based IP information services are largely unavailable in Zimbabwean university libraries. Results reveal that the underlying challenge in the development of IP information services in Zimbabwe's university libraries is insufficient IP knowledge among academic librarians, which is exacerbated by inadequate IP management frameworks in university institutions. The study proposes a framework for the entrenchment of IP information services in Zimbabwe's university libraries.

Keywords: academic libraries, information services, intellectual property, IP knowledge, university libraries, Zimbabwe

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4348 Title: Real World Evidence a Tool to Overcome the Lack of a Comparative Arm in Drug Evaluation in the Context of Rare Diseases

Authors: Mohamed Wahba

Abstract:

Objective: To build a comparative arm for product (X) in specific gene mutated advanced gastrointestinal cancer using real world evidence to fulfill HTA requirements in drug evaluation. Methods: Data for product (X) were collected from phase II clinical trial while real world data for (Y) and (Z) were collected from US database. Real-world (RW) cohorts were matched to clinical trial base line characteristics using weighting by odds method. Outcomes included progression-free survival (PFS) and overall survival (OS) rates. Study location and participants: Internationally (product X, n=80) and from USA (Product Y and Z, n=73) Results: Two comparisons were made: trial cohort 1 (X) versus real-world cohort 1 (Z), trial cohort 2 (X) versus real-world cohort 2 (Y). For first line, the median OS was 9.7 months (95% CI 8.6- 11.5) and the median PFS was 5.2 months (95% CI 4.7- not reached) for real-world cohort 1. For second line, the median OS was 10.6 months (95% CI 4.7- 27.3) for real-world cohort 2 and the median PFS was 5.0 months (95% CI 2.1- 29.3). For OS analysis, results were statistically significant but not for PFS analysis. Conclusion: This study provided the clinical comparative outcomes needed for HTA evaluation.

Keywords: real world evidence, pharmacoeconomics, HTA agencies, oncology

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4347 COVID-19 Analysis with Deep Learning Model Using Chest X-Rays Images

Authors: Uma Maheshwari V., Rajanikanth Aluvalu, Kumar Gautam

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The COVID-19 disease is a highly contagious viral infection with major worldwide health implications. The global economy suffers as a result of COVID. The spread of this pandemic disease can be slowed if positive patients are found early. COVID-19 disease prediction is beneficial for identifying patients' health problems that are at risk for COVID. Deep learning and machine learning algorithms for COVID prediction using X-rays have the potential to be extremely useful in solving the scarcity of doctors and clinicians in remote places. In this paper, a convolutional neural network (CNN) with deep layers is presented for recognizing COVID-19 patients using real-world datasets. We gathered around 6000 X-ray scan images from various sources and split them into two categories: normal and COVID-impacted. Our model examines chest X-ray images to recognize such patients. Because X-rays are commonly available and affordable, our findings show that X-ray analysis is effective in COVID diagnosis. The predictions performed well, with an average accuracy of 99% on training photographs and 88% on X-ray test images.

Keywords: deep CNN, COVID–19 analysis, feature extraction, feature map, accuracy

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4346 Application of Liquid Chromatographic Method for the in vitro Determination of Gastric and Intestinal Stability of Pure Andrographolide in the Extract of Andrographis paniculata

Authors: Vijay R. Patil, Sathiyanarayanan Lohidasan, K. R. Mahadik

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Gastrointestinal stability of andrographolide was evaluated in vitro in simulated gastric (SGF) and intestinal (SIF) fluids using a validated HPLC-PDA method. The method was validated using a 5μm ThermoHypersil GOLD C18column (250 mm × 4.0 mm) and mobile phase consisting of water: acetonitrile; 70: 30 (v/v) delivered isocratically at a flow rate of 1 mL/min with UV detection at 228 nm. Andrographolide in pure form and extract Andrographis paniculata was incubated at 37°C in an incubator shaker in USP simulated gastric and intestinal fluids with and without enzymes. Systematic protocol as per FDA Guidance System was followed for stability study and samples were assayed at 0, 15, 30 and 60 min intervals for gastric and at 0, 15, 30, 60 min, 1, 2 and 3 h for intestinal stability study. Also, the stability study was performed up to 24 h to see the degradation pattern in SGF and SIF (with enzyme and without enzyme). The developed method was found to be accurate, precise and robust. Andrographolide was found to be stable in SGF (pH ∼ 1.2) for 1h and SIF (pH 6.8) up to 3 h. The relative difference (RD) of amount of drug added and found at all time points was found to be < 3%. The present study suggests that drug loss in the gastrointestinal tract takes place may be by membrane permeation rather than a degradation process.

Keywords: andrographolide, Andrographis paniculata, in vitro, stability, gastric, Intestinal HPLC-PDA

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4345 Pattern Recognition Using Feature Based Die-Map Clustering in the Semiconductor Manufacturing Process

Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

Abstract:

Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: die-map clustering, feature extraction, pattern recognition, semiconductor manufacturing process

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4344 Application of Artificial Neural Network for Prediction of Load-Haul-Dump Machine Performance Characteristics

Authors: J. Balaraju, M. Govinda Raj, C. S. N. Murthy

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Every industry is constantly looking for enhancement of its day to day production and productivity. This can be possible only by maintaining the men and machinery at its adequate level. Prediction of performance characteristics plays an important role in performance evaluation of the equipment. Analytical and statistical approaches will take a bit more time to solve complex problems such as performance estimations as compared with software-based approaches. Keeping this in view the present study deals with an Artificial Neural Network (ANN) modelling of a Load-Haul-Dump (LHD) machine to predict the performance characteristics such as reliability, availability and preventive maintenance (PM). A feed-forward-back-propagation ANN technique has been used to model the Levenberg-Marquardt (LM) training algorithm. The performance characteristics were computed using Isograph Reliability Workbench 13.0 software. These computed values were validated using predicted output responses of ANN models. Further, recommendations are given to the industry based on the performed analysis for improvement of equipment performance.

Keywords: load-haul-dump, LHD, artificial neural network, ANN, performance, reliability, availability, preventive maintenance

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4343 Assessment of Knowledge, Attitude, and Practice of Health Care Professionals and Factors Associated with Adverse Drug Reaction Reporting in Public and Private Hospitals of Islamabad

Authors: Zaka Nisa, Farooq Sher

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Adverse drug reactions (ADRs) underreporting is a great challenge to Pharmacovigilance. Health care professionals have to consider ADR reporting as their professional obligation, an effective system of ADR reporting is important to improve patient health care and safety. The present study is designed to assess the knowledge, attitude, practice and factors associated with ADR reporting by health care professionals (physicians and pharmacists) in public and private hospitals of Pakistan. A pretested questionnaire was administered to 384 physicians and pharmacists in public and private hospitals. Respondents were evaluated for their knowledge, attitude, and practice related to ADR reporting. The data was analyzed using the SPSS statistical software, the factors which encourage and discourage respondents in reporting ADRs were determined. Most of the respondents have shown a positive attitude towards ADR reporting. The response rate was 95.32%. Of the 367 questionnaires, including 333 (86.5%) physicians and 34 (8.8%) pharmacists with the mean age 28.34 (SD= 6.69), most of the respondents showed poor ADR reporting knowledge (83.1%). The majority of respondents (78.2%) showed positive attitude towards ADR reporting and only (12.3%) hospitals have good ADR reporting practice. Knowledge of respondents in public hospitals (8.6%) was less as compare to those in the private hospitals (29.7%) (P < 0.001). Attitude of respondents in private hospitals was more positive (92.4%) than those in public hospitals (68.8%) (P < 0.001). No significant difference was observed in practicing of ADR reporting in public (11.8%) and private hospitals (13.1%) (P value 0.89). Seriousness of ADR, unusualness of reaction, new drug involvement and confidence in diagnosis of ADR were the factors which encourage respondents to report ADR, however, lack of knowledge regarding where and how to report ADR, lack of access to ADR reporting form, managing patients was more important than reporting ADR, legal liability issues were the factors which discourage respondents to report ADR. The study reveals poor knowledge and practice regarding ADR reporting. However positive attitude was seen regarding ADR reporting. There is a need of educational training for health care professionals as well as genuine and continuous efforts are required by Government and health authorities to ensure the proper implementation of ADR reporting system in all of the hospitals.

Keywords: adverse drugs reactions (ADR), pharmacovigilance, spontaneous ADR reporting, knowledge of ADR, attitude of health care profesionals, practice of ADR reporting

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4342 Clinical Prediction Rules for Using Open Kinetic Chain Exercise in Treatment of Knee Osteoarthritis

Authors: Mohamed Aly, Aliaa Rehan Youssef, Emad Sawerees, Mounir Guirgis

Abstract:

Relevance: Osteoarthritis (OA) is the most common degenerative disease seen in all populations. It causes disability and substantial socioeconomic burden. Evidence supports that exercise are the most effective conservative treatment for patients with OA. Therapists experience and clinical judgment play major role in exercise prescription and scientific evidence for this regard is lacking. The development of clinical prediction rules to identify patients who are most likely benefit from exercise may help solving this dilemma. Purpose: This study investigated whether body mass index and functional ability at baseline can predict patients’ response to a selected exercise program. Approach: Fifty-six patients, aged 35 to 65 years, completed an exercise program consisting of open kinetic chain strengthening and passive stretching exercises. The program was given for 3 sessions per week, 45 minutes per session, for 6 weeks Evaluation: At baseline and post treatment, pain severity was assessed using the numerical pain rating scale, whereas functional ability was being assessed by step test (ST), time up and go test (TUG) and 50 feet time walk test (50 FTW). After completing the program, global rate of change (GROC) score of greater than 4 was used to categorize patients as successful and non-successful. Thirty-eight patients (68%) had successful response to the intervention. Logistic regression showed that BMI and 50 FTW test were the only significant predictors. Based on the results, patients with BMI less than 34.71 kg/m2 and 50 FTW test less than 25.64 sec are 68% to 89% more likely to benefit from the exercise program. Conclusions: Clinicians should consider the described strengthening and flexibility exercise program for patents with BMI less than 34.7 Kg/m2 and 50 FTW faster than 25.6 seconds. The validity of these predictors should be investigated for other exercise.

Keywords: clinical prediction rule, knee osteoarthritis, physical therapy exercises, validity

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4341 The Application of Artificial Neural Networks for the Performance Prediction of Evacuated Tube Solar Air Collector with Phase Change Material

Authors: Sukhbir Singh

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This paper describes the modeling of novel solar air collector (NSAC) system by using artificial neural network (ANN) model. The objective of the study is to demonstrate the application of the ANN model to predict the performance of the NSAC with acetamide as a phase change material (PCM) storage. Input data set consist of time, solar intensity and ambient temperature wherever as outlet air temperature of NSAC was considered as output. Experiments were conducted between 9.00 and 24.00 h in June and July 2014 underneath the prevailing atmospheric condition of Kurukshetra (city of the India). After that, experimental results were utilized to train the back propagation neural network (BPNN) to predict the outlet air temperature of NSAC. The results of proposed algorithm show that the BPNN is effective tool for the prediction of responses. The BPNN predicted results are 99% in agreement with the experimental results.

Keywords: Evacuated tube solar air collector, Artificial neural network, Phase change material, solar air collector

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4340 Formulation Design and Optimization of Orodispersible Tablets of Diphenhydramine Hydrochloride Having Adequate Mechanical Strength

Authors: Jiwan P. Lavande, A. V. Chandewar

Abstract:

In the present study, orodispersible tablets of diphenhydramine hydrochloride were prepared using croscarmellose sodium, crospovidone and camphor, menthol (as subliming agents) in different ratios and ODTs prepared with superdisintegrants were compared with ODTs prepared with camphor and menthol (subliming agents) for the following evaluation of in vitro disintegration time, dispersion time, wetting time, hardness and water absorption ratio. Results revealed that the tablets of all formulations have acceptable physical parameters. The drug and excipients compatibility study was evaluated using FTIR technique and has not detected any incompatibility. The in vitro release of drug from DC6 formulation was quick when compared to other formulations. Stability study was carried out as per ICH guidelines for three months and results revealed that upon storage disintegration time of tablets had not shown any significant difference. Microscopic study of different formulations of sublimed tablets showed formation of pores for the tablets prepared by sublimation method. Thus, conclusion can be made that the stable orodispersible tablets of diphenhydramine hydrochloride can be developed for the rapid release of diphenhydramine hydrochloride.

Keywords: orodispersible tablet, subliming agent, super disintegrants, diphenhydramine hydrochloride

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4339 New Strategy for Breeding of Artemisia annua L. for a Sustainable Production of the Antimalarial Drug Artemisinin

Authors: Nadali Babaeian Jelodar, Chan Lai Keng, Arvind Bhatt, Laleh Bordbar, Leow E Shuen, Kamaruzaman Mohamed

Abstract:

Recently artemisinin (the endoperoxide sesquiterpene lactone) has received considerable attention because of its antimalarial activity. It is isolated from the aerial part of the Artemisia annua L. Artemisinin is very difficult to synthesise also its production by mean of cell, tissue or organ cultures is very low. Presently, only its extraction from A. annua L. plants remains the only source of the drug. The reported yield of artemisinin from leaves of A. annua L. is very low and unstable, with yields typically less than 1% of leaf dry weight. To increase the percentage of artemisinin, researchers have been engaged in developing new varieties. A review concerning the breeding of A. annua L. is presented. The aim of this review is to bring together most of the available scientific research papers about the breeding conducted on the genus A. annua L., which is currently scattered across various publications. Through this review the authors hope to attract the attention of breeders throughout the world to focus on the unexplored potential of A. annua L. species. Also the future scope of this plant has been emphasized with a view of the importance of breeding of A. annua L. for increasing of artemisinin content. By releasing of new cultivar of A. annua L. and cultivation of this plant offers the opportunity to optimize yield and achieve a uniform, high quality product.

Keywords: Artemisia annua L., breeding, artemisinin, cultivation, medicinal plant

Procedia PDF Downloads 263
4338 The Theory behind Logistic Regression

Authors: Jan Henrik Wosnitza

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The logistic regression has developed into a standard approach for estimating conditional probabilities in a wide range of applications including credit risk prediction. The article at hand contributes to the current literature on logistic regression fourfold: First, it is demonstrated that the binary logistic regression automatically meets its model assumptions under very general conditions. This result explains, at least in part, the logistic regression's popularity. Second, the requirement of homoscedasticity in the context of binary logistic regression is theoretically substantiated. The variances among the groups of defaulted and non-defaulted obligors have to be the same across the level of the aggregated default indicators in order to achieve linear logits. Third, this article sheds some light on the question why nonlinear logits might be superior to linear logits in case of a small amount of data. Fourth, an innovative methodology for estimating correlations between obligor-specific log-odds is proposed. In order to crystallize the key ideas, this paper focuses on the example of credit risk prediction. However, the results presented in this paper can easily be transferred to any other field of application.

Keywords: correlation, credit risk estimation, default correlation, homoscedasticity, logistic regression, nonlinear logistic regression

Procedia PDF Downloads 426
4337 Intellectual Property Law as a Tool to Enhance and Sustain Museums in Digital Era

Authors: Nayira Ahmed Galal Elden Hassan, Amr Mostafa Awad Kassem

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The management of Intellectual Property (IP) in museums presents a multifaceted challenge, requiring a balance between granting access to cultural assets and maintaining control over them. In the digital age, IP has emerged as a critical aspect of museum operations, encompassing valuable assets within collections and museum-generated content. Effective IP management enables museums to generate revenue, protect rights, and promote cultural heritage while leveraging digital technologies. Opportunities such as e-commerce and licensing can drive economic growth, but they also introduce complexities related to IP protection and regulation. This study explores the dual nature of IP assets—collection-based and museum-generated—highlighting their implications for sustainability and cultural preservation. The analysis includes examples such as the German State Museum’s management of replicas from the Nefertiti bust, showcasing the challenges museums face when navigating IP frameworks. The research underscores the importance of a comprehensive understanding of IP laws to prevent legal disputes, reputational risks, and revenue loss. By adopting an analytical and comparative methodology, this paper examines museums that have effectively implemented IP rules to enhance their operations and sustain their resources. It investigates how IP management can help museums fulfill their mission of community engagement, education, and outreach while ensuring long-term sustainability. The findings demonstrate that balanced IP strategies are essential for securing financial stability, safeguarding cultural heritage, and adapting to the demands of the digital era. This research seeks to explore how museums can effectively fulfill their mission of community engagement, education, and outreach while ensuring long-term sustainability. It examines the extent to which intellectual property (IP) management can contribute to achieving these objectives, focusing on the benefits and challenges associated with adopting IP management strategies. Additionally, the study addresses the question of ownership by investigating who holds the rights to cultural assets and how these rights can be managed effectively to align with both institutional goals and the preservation of cultural heritage.The findings underscore the pivotal role of effective IP management in empowering museums to navigate the digital landscape, maximize revenue streams, and safeguard cultural heritage. The study emphasizes the necessity of adopting a balanced approach to IP management, which aligns institutional goals with the ethical and legal considerations of cultural heritage preservation.

Keywords: intellectual property, museums, IP management, digital technologies, sustainability, cultural heritage

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