Search results for: toxicity prediction

Authors: Mohammad Y. Alfaifi

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Anything that poses a challenge or a threat to our well-being is a stress. Understanding the genetic material and cellular response of rats threatened with Repeated swimming stress provides insights that can influence human health. The aim of the present study was to assess the genetical damage and cytological changes caused by exposure of the test organism (Rattus rattus) to forced swimming stress. For this purpose, animals have been submerged in water path 15 minutes daily for 2 weeks. Following that, we performed a micronuclei (MN) test using MNNCE (Micronucleated normocromatic erythrocytes) and MNPCE (Micronucleated polychromatic erythrocytes), NDI (Nuclear division index) and cytological parameters using NDCI (nuclear division cytotoxicity index), necrotic and apoptotic cells in rat's bone marrow samples. Results showed that there was a slightly but not significant increase in the frequency of micronucleated as well as in cytological parameters in bone marrow cells.

Keywords: submergence stress, micronucleus, NDI, NDCI, toxicity, chromosomal aberrations

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Authors: Matar Celine, Gaucel Sebastien, Gontard Nathalie, Guilbert Stephane, Guillard Valerie

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To increase the very short shelf life of fresh fruits and vegetable, Modified Atmosphere Packaging (MAP) allows an optimal atmosphere composition to be maintained around the product and thus prevent its decay. This technology relies on the modification of internal packaging atmosphere due to equilibrium between production/consumption of gases by the respiring product and gas permeation through the packaging material. While, to the best of our knowledge, benefit of MAP for fresh fruits and vegetable has been widely demonstrated in the literature, its effect on shelf life increase has never been quantified and formalized in a clear and simple manner leading difficult to anticipate its economic and environmental benefit, notably through the decrease of food losses. Mathematical modelling of mass transfers in the food/packaging system is the basis for a better design and dimensioning of the food packaging system. But up to now, existing models did not permit to estimate food quality nor shelf life gain reached by using MAP. However, shelf life prediction is an indispensable prerequisite for quantifying the effect of MAP on food losses reduction. The objective of this work is to propose an innovative approach to predict shelf life of MAP food product and then to link it to a reduction of food losses and wastes. In this purpose, a ‘Virtual MAP modeling tool’ was developed by coupling a new predictive deterioration model (based on visual surface prediction of deterioration encompassing colour, texture and spoilage development) with models of the literature for respiration and permeation. A major input of this modelling tool is the maximal percentage of deterioration (MAD) which was assessed from dedicated consumers’ studies. Strawberries of the variety Charlotte were selected as the model food for its high perishability, high respiration rate; 50-100 ml CO₂/h/kg produced at 20°C, allowing it to be a good representative of challenging post-harvest storage. A value of 13% was determined as a limit of acceptability for the consumers, permitting to define products’ shelf life. The ‘Virtual MAP modeling tool’ was validated in isothermal conditions (5, 10 and 20°C) and in dynamic temperature conditions mimicking commercial post-harvest storage of strawberries. RMSE values were systematically lower than 3% for respectively, O₂, CO₂ and deterioration profiles as a function of time confirming the goodness of model fitting. For the investigated temperature profile, a shelf life gain of 0.33 days was obtained in MAP compared to the conventional storage situation (no MAP condition). Shelf life gain of more than 1 day could be obtained for optimized post-harvest conditions as numerically investigated. Such shelf life gain permitted to anticipate a significant reduction of food losses at the distribution and consumer steps. This food losses' reduction as a function of shelf life gain has been quantified using a dedicated mathematical equation that has been developed for this purpose.

Keywords: food losses and wastes, modified atmosphere packaging, mathematical modeling, shelf life prediction

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Authors: Weixiang Liu, Yukun Qin, Song Liu, Pengcheng Li

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Plant diseases can cause the death of crops with great economic losses. Particularly, those diseases are usually caused by pathogenic fungi. Metal fungicides are a type of pesticide that has advantages of a low-cost, broad antimicrobial spectrum and strong sterilization effect. However, the frequent and wide application of traditional metal fungicides has caused serious problems such as environmental pollution, the outbreak of mites and phytotoxicity. Therefore, it is critically necessary to discover new organic metal fungicides alternatives that have a low metal content, low toxicity, and little influence on mites. Chitosan, the second most abundant natural polysaccharide next to cellulose, was proved to have broad-spectrum antifungal activity against a variety of fungi. However, the use of chitosan was limited due to its poor solubility and weaker antifungal activity compared with commercial fungicide. Therefore, in order to improve the water solubility and antifungal activity, many researchers grafted the active groups onto chitosan. The present work was to combine free metal ions with chitosan, to prepare more potent antifungal chitosan derivatives, thus, based on condensation reaction, chitosan derivative bearing amino pyridine group was prepared and subsequently followed by coordination with cupric ions, zinc ions and nickel ions to synthesize chitosan metal complexes. The calculations by density functional theory (DFT) show that the copper ions and nickel ions underwent dsp2 hybridization, the zinc ions underwent sp3 hybridization, and all of them are coordinated by the carbon atom in the p-π conjugate group and the oxygen atoms in the acetate ion. The antifungal properties of chitosan metal complexes against Phytophthora capsici (P. capsici), Gibberella zeae (G. zeae), Fusarium oxysporum (F. oxysporum) and Botrytis cinerea (B. cinerea) were also assayed. In addition, a plant toxicity experiment was carried out. The experiments indicated that the derivatives have significantly enhanced antifungal activity after metal ions complexation compared with the original chitosan. It was shown that 0.20 mg/mL of O-CSPX-Cu can 100% inhibit the growth of P. capsici and 0.20 mg/mL of O-CSPX-Ni can 87.5% inhibit the growth of B. cinerea. In general, their activities are better than the positive control oligosaccharides. The combination of the pyridine formyl groups seems to favor biological activity. Additionally, the ligand fashion was precisely analyzed, and the results revealed that the copper ions and nickel ions underwent dsp2 hybridization, the zinc ions underwent sp3 hybridization, and the carbon atoms of the p-π conjugate group and the oxygen atoms of acetate ion are involved in the coordination of metal ions. The phytotoxicity assay of O-CSPX-M was also conducted, unlike the traditional metal fungicides, the metal complexes were not significantly toxic to the leaves of wheat. O-CSPX-Zn can even increase chlorophyll content in wheat leaves at 0.40 mg/mL. This is mainly because chitosan itself promotes plant growth and counteracts the phytotoxicity of metal ions. The chitosan derivative described here may lend themselves to future applicative studies in crop protection.

Keywords: coordination, chitosan, metal complex, antifungal properties

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Authors: Sutapa Mondal Roy, Suban K. Sahoo

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The primary aim of this work is to synthesis silver nanoparticles (AgNPs) through environmentally benign routes to avoid any chemical toxicity related undesired side effects. The nanoparticles were stabilized with drug ciprofloxacin (Cp) and were studied for their effectiveness as drug delivery agent. Targeted drug delivery improves the therapeutic potential of drugs at the diseased site as well as lowers the overall dose and undesired side effects. The small size of nanoparticles greatly facilitates the transport of active agents (drugs) across biological membranes and allows them to pass through the smallest capillaries in the body that are 5-6 μm in diameter, and can minimize possible undesired side effects. AgNPs are non-toxic, inert, stable, and has a high binding capacity and thus can be considered as biomaterials. AgNPs were synthesized from the nutrient broth supernatant after the culture of environment-friendly bacteria Bacillus subtilis. The AgNPs were found to show the surface plasmon resonance (SPR) band at 425 nm. The Cp capped Ag nanoparticles formation was complete within 30 minutes, which was confirmed from absorbance spectroscopy. Physico-chemical nature of the AgNPs-Cp system was confirmed by Dynamic Light Scattering (DLS), Transmission Electron Microscopy (TEM) etc. The AgNPs-Cp system size was found to be in the range of 30-40 nm. To monitor the kinetics of drug release from the surface of nanoparticles, the release of Cp was carried out by careful dialysis keeping AgNPs-Cp system inside the dialysis bag at pH 7.4 over time. The drug release was almost complete after 30 hrs. During the drug delivery process, to understand the AgNPs-Cp system in a better way, the sincere theoretical investigation is been performed employing Density Functional Theory. Electronic charge transfer, electron density, binding energy as well as thermodynamic properties like enthalpy, entropy, Gibbs free energy etc. has been predicted. The electronic and thermodynamic properties, governed by the AgNPs-Cp interactions, indicate that the formation of AgNPs-Cp system is exothermic i.e. thermodynamically favorable process. The binding energy and charge transfer analysis implies the optimum stability of the AgNPs-Cp system. Thus, the synthesized Cp-Ag nanoparticles can be effectively used for biological purposes due to its environmentally benign routes of synthesis procedures, which is clean, biocompatible, non-toxic, safe, cost-effective, sustainable and eco-friendly. The Cp-AgNPs as biomaterials can be successfully used for drug delivery procedures due to slow release of drug from nanoparticles over a considerable period of time. The kinetics of the drug release show that this drug-nanoparticle assembly can be effectively used as potential tools for therapeutic applications. The ease of synthetic procedure, lack of possible chemical toxicity and their biological activity along with excellent application as drug delivery agent will open up vista of using nanoparticles as effective and successful drug delivery agent to be used in modern days.

Keywords: silver nanoparticles, ciprofloxacin, density functional theory, drug delivery

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Authors: Arindam Pramanik, Parimal Karmakar

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We have explored the synergistic anti-cancer activity of copper ion and acetylacetone complex containing 1,3 diketone group (like curcumin) in metallorganic compound “Copper acetylacetonate” (CuAA). The cytotoxicity mechanism of CuAA complex was evaluated on various cancer cell lines in vitro. Among these, reactive oxygen species (ROS), glutathione level (GSH) in the cell was found to increase. Further mitochondrial membrane damage was observed. The fate of cell death was found to be induced by apoptosis. For application purpose, we have developed a novel biodegradable, non-toxic polymer-based nanoparticle which has hydrophobically modified core for loading of the CuAA. Folic acid is conjugated on the surface of the polymer (chitosan) nanoparticle for targeting to cancer cells for minimizing toxicity to normal cells in-vivo. Thus, this novel drug CuAA has an efficient anticancer activity which has been targeted specifically to cancer cells through polymer nanoparticle.

Keywords: anticancer, apoptosis, copper nanoparticle, targeted drug delivery

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Authors: Akintade O. Adeboyejo, Edwin O. Clarke, Oluwatoyin Aderinola

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The present study is on the sub-lethal toxicity of industrial effluents (IE) from the environment of Ologe Lagoon, Lagos, Nigeria on the African catfish fingerlings Clarias gariepinus. The fish were cultured in varying concentrations of industrial effluents: 0% (control), 5%, 15%, 25%, and 35%. Trials were carried out in triplicates for twelve (12) weeks. The culture system was a static renewable bioassay and was carried out in the fisheries laboratory of the Lagos State University, Ojo-Lagos. Weekly physico-chemical parameters: Temperature (0C), pH, Conductivity (ppm) and Dissolved Oxygen (DO in mg/l) were measured in each treatment tank. Length (cm) and weight (g) data were obtained weekly and used to calculate various growth parameters: mean weight gain (MWG), percentage weight gain (PWG), daily weight gain (DWG), specific growth rate (SGR) and survival. Haematological (Packed Cell Volume (PCV), Red blood cells (RBC), White Blood Cell (WBC), Neutrophil and Lymphocytes etc) and histological alterations were measured after 12 weeks. The physico-chemical parameters showed that the pH ranged from 7.82±0.25–8.07±0.02. DO range from 1.92±0.66-4.43±1.24 mg/l. The conductivity values increased with increase in concentration of I.E. While the temperature remained stable with mean value range between 26.08±2.14–26.38±2.28. The DO showed significant differences at P<0.05. There was progressive increase in length and weight of fish during the culture period. The fish placed in the control had highest increase in both weight and length while fish in 35% had the least. MWG ranged from 16.59–35.96, DWG is from 0.3–0.48, SGR varied from 1.0–1.86 and survival was 100%. Haematological results showed that C. gariepinus had PCV ranging from 13.0±1.7-27.7±0.6, RBC ranged from 4.7±0.6–9.1±0.1, and Neutrophil ranged from 26.7±4.6–61.0±1.0 amongst others. The highest values of these parameters were obtained in the control and lowest at 35%. While the reverse effects were observed for WBC and lymphocytes. This study has shown that effluents may affect the health status of the test organism and impair vital processes if exposure continues for a long period of time. The histological examination revealed several lesions as expressed by the gills and livers. The histopathology of the gills in the control tanks had normal tissues with no visible lesion, but at higher concentrations, there were: lifting of epithelium, swollen lamellae and gill arch infiltration, necrosis and gill arch destruction. While in the liver: control (0%) show normal liver cells, at higher toxic level, there were: vacoulation, destruction of the hepatic parenchyma, tissue becoming eosinophilic (i.e. tending towards Carcinogenicity) and severe disruption of the hepatic cord architecture. The study has shown that industrial effluents from the study area may affect fish health status and impair vital processes if exposure continues for a long period of time even at lower concentrations (Sublethal).

Keywords: sublethal toxicity, industrial effluents, clarias gariepinus, ologe lagoon

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Authors: Violina Angelova, Huu Q. Lee

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A field study was conducted to evaluate the efficacy of Vetiver (Chrysopogon zizanioides L.) for phytoremediation of contaminated soils. The experiment was performed on agricultural fields contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. The experimental plots were situated at different distances (0.5, 3.5, and 15 km) from the source of pollution. The concentrations of Pb, Zn, and Cd in vetiver (roots and leaves) were determined. Correlations between the content of the heavy metal mobile forms extracted with DTPA and their content in the roots and leaves of the Vetiver have been established. The Vetiver is tolerant to heavy metals and can be grown on soils contaminated with heavy metals. Plants are characterized by low ability to absorb and accumulate Pb, Cd, and Zn and have no signs of toxicity (chlorosis and necrosis) at 36.8 mg/kg Cd, 1158.8 mg/kg Pb and 1526.2 mg/kg Zn in the soil. Vetiver plants can be classified as Pb, Cd and Zn excluder, therefore, this plant has the suitable potential for the phytostabilization of heavy metal contaminated soils. Acknowledgements: The authors gratefully acknowledge the financial support by the Bulgarian National Science Fund (Project DFNI 04/9).

Keywords: contaminated soils, heavy metals, phytoremediation, vetiver

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Authors: Parvin Ghafarian, Mohammadreza Mohammadpur Panchah, Mehri Fallahi

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Synoptic patterns from surface up to tropopause are very important for forecasting the weather and atmospheric conditions. There are many tools to prepare and analyze these maps. Reanalysis data and the outputs of numerical weather prediction models, satellite images, meteorological radar, and weather station data are used in world forecasting centers to predict the weather. The forecasting extreme precipitating on the southern coast of the Caspian Sea (CS) is the main issue due to complex topography. Also, there are different types of climate in these areas. In this research, we used two reanalysis data such as ECMWF Reanalysis 5th Generation Description (ERA5) and National Centers for Environmental Prediction /National Center for Atmospheric Research (NCEP/NCAR) for verification of the numerical model. ERA5 is the latest version of ECMWF. The temporal resolution of ERA5 is hourly, and the NCEP/NCAR is every six hours. Some atmospheric parameters such as mean sea level pressure, geopotential height, relative humidity, wind speed and direction, sea surface temperature, etc. were selected and analyzed. Some different type of precipitation (rain and snow) was selected. The results showed that the NCEP/NCAR has more ability to demonstrate the intensity of the atmospheric system. The ERA5 is suitable for extract the value of parameters for specific point. Also, ERA5 is appropriate to analyze the snowfall events over CS (snow cover and snow depth). Sea surface temperature has the main role to generate instability over CS, especially when the cold air pass from the CS. Sea surface temperature of NCEP/NCAR product has low resolution near coast. However, both data were able to detect meteorological synoptic patterns that led to heavy rainfall over CS. However, due to the time lag, they are not suitable for forecast centers. The application of these two data is for research and verification of meteorological models. Finally, ERA5 has a better resolution, respect to NCEP/NCAR reanalysis data, but NCEP/NCAR data is available from 1948 and appropriate for long term research.

Keywords: synoptic patterns, heavy precipitation, reanalysis data, snow

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Authors: Joy Cao, Min Zhou

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Purpose: Acute Type A aortic dissection is a well-known cause of extremely high mortality rate. A highly accurate and cost-effective non-invasive predictor is critically needed so that the patient can be treated at earlier stage. Although various CFD approaches have been tried to establish some prediction frameworks, they are sensitive to uncertainty in both image segmentation and boundary conditions. Tedious pre-processing and demanding calibration procedures requirement further compound the issue, thus hampering their clinical applicability. Using the latest physics informed deep learning methods to establish an accurate and cost-effective predictor framework are amongst the main goals for a better Type A aortic dissection treatment. Methods: Via training a novel physics-informed deep residual network, with non-invasive 4D MRI displacement vectors as inputs, the trained model can cost-effectively calculate all these biomarkers: aortic blood pressure, WSS, and OSI, which are used to predict potential type A aortic dissection to avoid the high mortality events down the road. Results: The proposed deep learning method has been successfully trained and tested with both synthetic 3D aneurysm dataset and a clinical dataset in the aortic dissection context using Google colab environment. In both cases, the model has generated aortic blood pressure, WSS, and OSI results matching the expected patient’s health status. Conclusion: The proposed novel physics-informed deep residual network shows great potential to create a cost-effective, non-invasive predictor framework. Additional physics-based de-noising algorithm will be added to make the model more robust to clinical data noises. Further studies will be conducted in collaboration with big institutions such as Cleveland Clinic with more clinical samples to further improve the model’s clinical applicability.

Keywords: type-a aortic dissection, deep residual networks, blood flow modeling, data-driven modeling, non-invasive diagnostics, deep learning, artificial intelligence.

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Authors: Abbas Hadj Abbas, Hacini Massaoud, Aiad Lahcen

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In Hassi-Messoud’s oil industry, the systems which are water based (WBM) are generally used for drilling in the first phase. For the rest of the well, the oil mud systems are employed (OBM). In the field of oil exploration, panoply of chemical products is employed in the drilling fluids formulation. These components of different natures and whose toxicity and biodegradability are of ill-defined parameters are; however, thrown into nature. In addition to the hydrocarbon (HC, such as diesel) which is a major constituent of oil based mud, we also can notice spills as well as a variety of other products and additives on the drilling sites. These wastes are usually stored in places called (crud wastes). These may cause major problems to the ecosystem. To treat these wastes, we have considered two methods which are: solidification/ stabilization (chemical) and thermal. So that we can evaluate the techniques of treatment, a series of analyses are performed on dozens of specimens of wastes before treatment. After that, and on the basis of our analyses of wastes, we opted for diagnostic treatments of pollution before and after solidification and stabilization. Finally, we have done some analyses before and after the thermal treatment to check the efficiency of the methods followed in the study.

Keywords: wastes treatment, the oil pollution, the norms, wastes drilling

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Authors: Sadaoui Djaouida

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In this paper, the predictive control method is proposed to control the synchronization of two perturbed satellites attitude motion. Based on delayed feedback control of continuous-time systems combines with the prediction-based method of discrete-time systems, this approach only needs a single controller to realize synchronization, which has considerable significance in reducing the cost and complexity for controller implementation.

Keywords: predictive control, synchronization, satellite attitude, control engineering

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Authors: Xianglu Tang, Zhenxue Jiang, Zhuo Li

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Characterization of shale multi scale heterogeneity is an important part to evaluate size and space distribution of shale gas reservoirs in sedimentary basins. The origin of shale heterogeneity has always been a hot research topic for it determines shale micro characteristics description and macro quality reservoir prediction. Shale multi scale heterogeneity was discussed based on thin section observation, FIB-SEM, QEMSCAN, TOC, XRD, mercury intrusion porosimetry (MIP), and nitrogen adsorption analysis from 30 core samples in Silurian Longmaxi formation. Results show that shale heterogeneity can be characterized by pore structure and mineral composition. The heterogeneity of shale pore is showed by different size pores at nm-μm scale. Macropores (pore diameter > 50 nm) have a large percentage of pore volume than mesopores (pore diameter between 2~ 50 nm) and micropores (pore diameter < 2nm). However, they have a low specific surface area than mesopores and micropores. Fractal dimensions of the pores from nitrogen adsorption data are higher than 2.7, what are higher than 2.8 from MIP data, showing extremely complex pore structure. This complexity in pore structure is mainly due to the organic matter and clay minerals with complex pore network structures, and diagenesis makes it more complicated. The heterogeneity of shale minerals is showed by mineral grains, lamina, and different lithology at nm-km scale under the continuous changing horizon. Through analyzing the change of mineral composition at each scale, random arrangement of mineral equal proportion, seasonal climate changes, large changes of sedimentary environment, and provenance supply are considered to be the main reasons that cause shale minerals heterogeneity from microcosmic to macroscopic. Due to scale effect, the change of shale multi scale heterogeneity is a discontinuous process, and there is a transformation boundary between homogeneous and in homogeneous. Therefore, a shale multi scale heterogeneity changing model is established by defining four types of homogeneous unit at different scales, which can be used to guide the prediction of shale gas distribution from micro scale to macro scale.

Keywords: heterogeneity, homogeneous unit, multiscale, shale

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Authors: Ruth Goldschmidt, Vyacheslav Kalchenko, Lilah Agemy, Rachel Elmoalem, Avigdor Scherz

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Vascular Targeted Photodynamic therapy (VTP) is a new modality for selective cancer treatment that leads to the complete tumor ablation. A photosensitizer, a bacteriochlorophyll derivative in our case, is first administered to the patient and followed by the illumination of the tumor area, by a near-IR laser for its photoactivation. The photoactivated drug releases reactive oxygen species (ROS) in the circulation, which reacts with blood cells and the endothelium leading to the occlusion of the blood vasculature. If the blood vessels are only partially closed, the tumor may recover, and cancer cells could survive. On the other hand, excessive treatment may lead to toxicity of healthy tissues nearby. Simultaneous VTP monitoring and image processing independent of the photoexcitation laser has not yet been reported, to our knowledge. Here we present a method for blood flow monitoring, using a real-time laser speckle imaging (RTLSI) in the tumor during VTP. We have synthesized over the years a library of bacteriochlorophyll derivatives, among them WST11 and STL-6014. Both are water soluble derivatives that are retained in the blood vasculature through their partial binding to HSA. WST11 has been approved in Mexico for VTP treatment of prostate cancer at a certain drug dose, and time/intensity of illumination. Application to other bacteriochlorophyll derivatives or other cancers may require different treatment parameters (such as light/drug administration). VTP parameters for STL-6014 are still under study. This new derivative mainly differs from WST11 by its lack of the central Palladium, and its conjugation to an Arg-Gly-Asp (RGD) sequence. RGD is a tumor-specific ligand that is used for targeting the necrotic tumor domains through its affinity to αVβ3 integrin receptors. This enables the study of cell-targeted VTP. We developed a special RTLSI module, based on Labview software environment for data processing. The new module enables to acquire raw laser speckle images and calculate the values of the laser temporal statistics of time-integrated speckles in real time, without additional off-line processing. Using RTLSI, we could monitor the tumor’s blood flow following VTP in a CT26 colon carcinoma ear model. VTP with WST11 induced an immediate slow down of the blood flow within the tumor and a complete final flow arrest, after some sporadic reperfusions. If the irradiation continued further, the blood flow stopped also in the blood vessels of the surrounding healthy tissue. This emphasizes the significance of light dose control. Using our RTLSI system, we could prevent any additional healthy tissue damage by controlling the illumination time and restrict blood flow arrest within the tumor only. In addition, we found that VTP with STL-6014 was the most effective when the photoactivation was conducted 4h post-injection, in terms of tumor ablation success in-vivo and blood vessel flow arrest. In conclusion, RTSLI application should allow to optimize VTP efficacy vs. toxicity in both the preclinical and clinical arenas.

Keywords: blood vessel occlusion, cancer treatment, photodynamic therapy, real time imaging

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Authors: Md Fazle Alam, Amaj Ahmed Laskar, Hina Younus

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Melamine toxicity which causes renal failure and death of humans and animals have recently attracted worldwide attention. Developing an easy, fast and sensitive method for the routine melamine detection is the need of the hour. Herein, we have developed a rapid, sensitive, one step and selective colorimetric method for the detection of melamine in milk samples based upon in-situ formation of silver nanoparticles (AgNPs) via tannic acid at room temperature. These AgNPs thus formed were characterized by UV-VIS spectrophotometer, transmission electron microscope (TEM), zetasizer and dynamic light scattering (DLS). Under optimal conditions, melamine could be selectively detected within the concentration range of 0.05-1.4 µM with a limit of detection (LOD) of 10.1 nM, which is lower than the strictest melamine safety requirement of 1 ppm. This assay does not utilize organic cosolvents, enzymatic reactions, light sensitive dye molecules and sophisticated instrumentation, thereby overcoming some of the limitations of conventional methods.

Keywords: milk adulteration, melamine, silver nanoparticles, tannic acid

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Authors: Amna B. Medani, M. A. Elbadwi Samia, Hassan A. Khalid

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In our study, nine Nubian goat kids were obtained, allotted into three groups, and healthily adapted in pens within the premises of the Veterinary Teaching Hospital, University of Khartoum to be given the oral doses of the dried herb shoots at daily doses of 1 and 5 gm/kg/day with drinking water, while the kids of the control group were left undosed. All goats were slaughtered,if not died, after 35 days. S. argel at the given doses caused signs of arched posture, ruffled hair, shivering and paralysis of limbs. On post mortem, lesions were seen to be hepatic fatty changes, renal necrosis, congested lungs and inflamed intestines. Serum chemistry investigations revealed significant increase (P< 0.05-0.01) in the activities of ALP(alkaline phosphates) and AST( aspartate-aminotransferase) in goats dosed with 5 gm /kg/ day. Also observed were significant increases in inorganic phosphorus and urea concentrations (P < 0.05-0.01) in both dosed goat groups. .Other investigations including the activity of GGT( gamma glutamyltransferase), creatinine, calcium, total protein and albumin illustrated no significant difference from that of the undosed controls. On haematological evaluation , the goat kids dosed with 5 gm/kg/dayshowed a decrease in haemoglobin concentration and red blood cells count of (P < 0.05-0.01).Both groups of dosed goats showed a higher packed cell volume values of (P < 0.05) when compared to the control goats .Mean corpuscular haemoglobin values were not different from those of the control kids. S. argel at the given doses caused signs of arched posture, ruffled hair, shivering and paralysis of limbs. On post mortem, lesions were seen to be hepatic fatty changes, renal necrosis, congested lungs and inflamed intestines. Serum chemistry investigations revealed significant increase (P < 0.05-0.01) in the activities of ALP(alkaline phosphates) and AST( aspartate-aminotransferase) in goats dosed with 5 gm /kg/ day. Also observed were significant increases in inorganic phosphorus and urea concentrations (P < 0.05-0.01) in both dosed goat groups. .Other investigations including the activity of GGT( gamma-glutamyltransferase), creatinine, calcium, total protein and albumin illustrated no significant difference from that of the undosed controls. calcium, total protein and albumin illustrated no significant difference from that of the undosed controls. On haematological evaluation , the goat kids dosed with 5 gm/kg/dayshowed a decrease in haemoglobin concentration and red blood cells count of (P < 0.05-0.01).Both groups of dosed goats showed a higher packed cell volume values of (P < 0.05) when compared to the control goats .Mean corpuscular haemoglobin values were not different from those of the control kids. Data obtained were then discussed to find S. argel irritable to intestines , toxic to the kidney and liver and a haematological mild toxin.Suggestions for future were forwarded.

Keywords: hargal, nubian goats, solenstemma argel, toxicity

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Authors: Rishi Saxena

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Cyanobacteria is a photosynthetic prokaryote, and these obtain their energy through photosynthesis. In this paper, we studied the effect of iron on metabolic changes in the diazotrophic cyanobacterium Anabaena PCC 7120. Nowadays, metal contamination due to natural and anthropogenic sources is a global environment concern. Iron induced changes in growth, N2-fixation, CO2 fixation and photosynthetic activity were studied in a diazotrophic cyanobacterium Anabaena PCC 7120. Iron at 50 uM concentration supported the maximum growth, heterocyst frequency, CO2 fixation, photosystem I (PS I), photosystem II (PS II) and nitrogenase activities in the organism. Higher concentration of iron inhibited these processes. Chl a and PS II activities were more sensitive to iron than the protein and PS I activity. Here, it is also mentioned that heavy metal induced altered macromolecules metabolism and changes in the central dogma of life (DNA→ mRNA → Protein). And also recent advances have been made in understanding heavy metal-cyanobacteria interaction and their application for metal detoxification.

Keywords: cyanobacterium anabaena 7120, nitrogen fixation, photosystem I (PS I), photosystem II (PS II)

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Authors: Defne Uz

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Horizontal Tail of helicopter is exposed to repeated oscillatory loading generated by aerodynamic and inertial loads, and bending moments depending on operating conditions and maneuvers of the helicopter. In order to ensure that maximum stress levels do not exceed certain fatigue limit of the material and to prevent damage, a numerical analysis approach can be utilized through the Finite Element Method. Therefore, in this paper, fatigue analysis of the Horizontal Tail model is studied numerically to predict high-cycle and low-cycle fatigue life related to defined loading. The analysis estimates the stress field at stress concentration regions such as around fastener holes where the maximum principal stresses are considered for each load case. Critical element identification of the main load carrying structural components of the model with rivet holes is performed as a post-process since critical regions with high-stress values are used as an input for fatigue life calculation. Once the maximum stress is obtained at the critical element and the related mean and alternating components, it is compared with the endurance limit by applying Soderberg approach. The constant life straight line provides the limit for several combinations of mean and alternating stresses. The life calculation based on S-N (Stress-Number of Cycles) curve is also applied with fully reversed loading to determine the number of cycles corresponds to the oscillatory stress with zero means. The results determine the appropriateness of the design of the model for its fatigue strength and the number of cycles that the model can withstand for the calculated stress. The effect of correctly determining the critical rivet holes is investigated by analyzing stresses at different structural parts in the model. In the case of low life prediction, alternative design solutions are developed, and flight hours can be estimated for the fatigue safe operation of the model.

Keywords: fatigue analysis, finite element method, helicopter horizontal tail, life prediction, stress concentration

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Authors: A.M. Kaja, Q. Yu, H.J.H Brouwers

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An increased functionality of concrete towards higher eco-efficiency is nowadays of great importance due to the decreasing air quality in urban areas. Surface modifications of concrete walls and roads, as a coating or an intermixing of the surface layer with TiO₂, provide an opportunity to improve the air quality by reducing NOx via photocatalytic phenomena. Nevertheless, there are still concerns regarding the cost-efficiency as well as the toxicity of intermediate products which can be produced during the photocatalysis, limiting a widespread adoption of these materials. This study addresses the problem of the selectivity of cement mortars towards nitrate in terms of microstructural characteristics and hydration products. The ability of cement mortars matrix intermixed with commercial TiO₂ and TiO₂-SiO₂ composite to abate NO₂ is investigated. The influence of hydration products formed under the carbonation facilitating conditions is discussed and solutions how to optimize the mix design are proposed. The incorporation of the TiO₂-SiO₂ composite into cement mortar is found to increase the nitrate selectivity index.

Keywords: cement matrix, NO₂ abatement, photocatalysis, TiO₂-SiO₂ composite

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

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Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Abdulmalek Ahmed

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Formation pressure is the main function that affects drilling operation economically and efficiently. Knowing the pore pressure and the parameters that affect it will help to reduce the cost of drilling process. Many empirical models reported in the literature were used to calculate the formation pressure based on different parameters. Some of these models used only drilling parameters to estimate pore pressure. Other models predicted the formation pressure based on log data. All of these models required different trends such as normal or abnormal to predict the pore pressure. Few researchers applied artificial intelligence (AI) techniques to predict the formation pressure by only one method or a maximum of two methods of AI. The objective of this research is to predict the pore pressure based on both drilling parameters and log data namely; weight on bit, rotary speed, rate of penetration, mud weight, bulk density, porosity and delta sonic time. A real field data is used to predict the formation pressure using five different artificial intelligence (AI) methods such as; artificial neural networks (ANN), radial basis function (RBF), fuzzy logic (FL), support vector machine (SVM) and functional networks (FN). All AI tools were compared with different empirical models. AI methods estimated the formation pressure by a high accuracy (high correlation coefficient and low average absolute percentage error) and outperformed all previous. The advantage of the new technique is its simplicity, which represented from its estimation of pore pressure without the need of different trends as compared to other models which require a two different trend (normal or abnormal pressure). Moreover, by comparing the AI tools with each other, the results indicate that SVM has the advantage of pore pressure prediction by its fast processing speed and high performance (a high correlation coefficient of 0.997 and a low average absolute percentage error of 0.14%). In the end, a new empirical correlation for formation pressure was developed using ANN method that can estimate pore pressure with a high precision (correlation coefficient of 0.998 and average absolute percentage error of 0.17%).

Keywords: Artificial Intelligence (AI), Formation pressure, Artificial Neural Networks (ANN), Fuzzy Logic (FL), Support Vector Machine (SVM), Functional Networks (FN), Radial Basis Function (RBF)

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Authors: Kimberley Phoena Fan, Yu Zhang

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ECOSURF™ EH-3 Surfactant (EH3) is a nonionic surfactant and has superior wetting and excellent oil removal properties. It is biodegradable with low toxicity and meets or exceeds US EPA Design for the Environment Criteria, and is widely used as a home cleaner, commercial and industrial degreaser. We have recently found that EH3 also possesses a special function which is characterized as an enhancer to Taq DNA polymerase and ameliorator to reduce the effects of PCR inhibitors, i.e., blood, urea, Guanidinium thiocyanate, Humic acids, polyphenol, and Polysaccharides. This is a new kind of PCR enhancer that does not work on relieving secondary structures of GC-rich templates. We have compared EH3’s effects on Taq DNA Polymerase along with other well-known enhancers, such as DMSO, betaine, and BSA, using GC rich or deficient template and found that, unlike DMSO and Betaine, the EH3 boosting effect on PCR reaction is not through reducing Tm. The results show the same increase of PCR products regardless of the GC contents or secondary structures. The mechanism of EH3 enhancing PCR is through its direct interaction with or stimulation of the DNA polymerase and making the enzymes more resistant to inhibitors in the presence of EH3. This phenomenon has first been observed for EH3, a new type of PCR enzyme enhancer. Subsequent research also shows that a series of similar surfactants boost Taq DNA polymerase as well.

Keywords: EH3, DNA, polymerase, enhancer, raw biological samples

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Authors: Mostafa Ghasemi, Andrew Urquhart

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In this study, fluorescent carbon dots (CDs) were synthesized in a green way using a one-step hydrothermal method. Carbon dots are carbon-based nanomaterials with a size of less than 10 nm, unique structure, and excellent properties such as low toxicity, good biocompatibility, tunable fluorescence, excellent photostability, and easy functionalization. These properties make them a good candidate to use in different fields such as biological sensing, photocatalysis, photodynamic, and drug delivery. Fourier transformed infrared (FTIR) spectra approved OH/NH groups on the surface of the as-synthesized CDs, and UV-vis spectra showed excellent fluorescence quenching effect of Fe (III) ion on the as-synthesized CDs with high selectivity detection compared with other metal ions. The probe showed a linear response concentration range (0–2.0 mM) to Fe (III) ion, and the limit of detection was calculated to be about 0.50 μM. In addition, CDs also showed good sensitivity to the pH value in the range from 2 to 14, indicating great potential as a pH sensor.

Keywords: carbon dots, fluorescence, pH sensing, metal ions sensor

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Authors: Prachi Singh

Abstract:

This paper presents a low-cost, eco-friendly and reproducible microbe mediated biosynthesis of TiO₂ nanoparticles. TiO₂ nanoparticles synthesized using the bacterium, Bacillus subtilis, from titanium as a precursor, were confirmed by TEM analysis. The morphological characteristics state spherical shape, with the size of individual or aggregate nanoparticles, around 30-40 nm. Microbial resistance represents a challenge for the scientific community to develop new bioactive compounds. Here, the antibacterial effect of TiO₂ nanoparticles on Escherichia coli was investigated, which was confirmed by CFU (Colony-forming unit). Further, growth curve study of E. coli Hb101 in the presence and absence of TiO₂ nanoparticles was done. Optical density decrease was observed with the increase in the concentration of TiO₂. It could be attributed to the inactivation of cellular enzymes and DNA by binding to electron-donating groups such as carboxylates, amides, indoles, hydroxyls, thiols, etc. which cause little pores in bacterial cell walls, leading to increased permeability and cell death. This justifies that TiO₂ nanoparticles have efficient antibacterial effect and have potential to be used as an antibacterial agent for different purposes.

Keywords: antibacterial effect, CFU, Escherichia coli Hb101, growth curve, TEM, TiO2 nanoparticle, Toxicity, UV-Vis

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Authors: Alaa A. Ghanem, S. E. M. Desouky

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Natural gas (NG) is considered one of the most essential global energy sources. NG fields are often far away from the market, and a long-distance transporting pipeline usually is required. Production of NG with high content of CO₂ leads to severe problems such as equipment corrosion along with the production line until refinery.in addition to a high level of toxicity and decreasing in calorific value of the NG. So it is recommended to remove or decrease the CO₂ percent to meet transport specifications. This can be reached using different removal techniques such as physical and chemical absorption, pressure swing adsorption, membrane separation, or low-temperature separation. Many solvents and chemicals are being used to capture carbon dioxide on a large scale; among them, Ionic liquids have great potential due to their tunable properties; low vapour pressure, low melting point, and sensible thermal stability. In this research, three modifiedimidazolium ionic liquids will be synthesized and characterized using different tools of analysis such as FT-IR, 1H NMR. Thermal stability and surface activity will be studied. The synthesized compounds will be evaluated as selective solvents for CO₂ removal from natural gas using PVT cell.

Keywords: natural gas, CO₂ capture, imidazolium ionic liquid, PVT cell

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Authors: Iyd Eqqab Maree, Moouyad Ibrahim Abbood

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The purpose behind this study is to predict damping effect for steel cantilever beam by using two methods of passive viscoelastic constrained layer damping. First method is Matlab Program, this method depend on the Ross, Kerwin and Unger (RKU) model for passive viscoelastic damping. Second method is experimental lab (frequency domain method), in this method used the half-power bandwidth method and can be used to determine the system loss factors for damped steel cantilever beam. The RKU method has been applied to a cantilever beam because beam is a major part of a structure and this prediction may further leads to utilize for different kinds of structural application according to design requirements in many industries. In this method of damping a simple cantilever beam is treated by making sandwich structure to make the beam damp, and this is usually done by using viscoelastic material as a core to ensure the damping effect. The use of viscoelastic layers constrained between elastic layers is known to be effective for damping of flexural vibrations of structures over a wide range of frequencies. The energy dissipated in these arrangements is due to shear deformation in the viscoelastic layers, which occurs due to flexural vibration of the structures. The theory of dynamic stability of elastic systems deals with the study of vibrations induced by pulsating loads that are parametric with respect to certain forms of deformation. There is a very good agreement of the experimental results with the theoretical findings. The main ideas of this thesis are to find the transition region for damped steel cantilever beam (4mm and 8mm thickness) from experimental lab and theoretical prediction (Matlab R2011a). Experimentally and theoretically proved that the transition region for two specimens occurs at modal frequency between mode 1 and mode 2, which give the best damping, maximum loss factor and maximum damping ratio, thus this type of viscoelastic material core (3M468) is very appropriate to use in automotive industry and in any mechanical application has modal frequency eventuate between mode 1 and mode 2.

Keywords: 3M-468 material core, loss factor and frequency, domain method, bioinformatics, biomedicine, MATLAB

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Authors: Krunal Thakar

Abstract:

Wire ropes combine high tensile strength and flexibility as compared to other general steel products. They are used in various application areas such as cranes, mining, elevators, bridges, cable cars, etc. The earliest reported use of wire ropes was for mining hoist application in 1830s. Over the period, there have been substantial advancement in the design of wire ropes for various application areas. Under operational conditions, wire ropes are subjected to varying tensile loads and bending loads resulting in material wear and eventual structural failure due to fretting fatigue. The conventional inspection methods to determine wire failure is only limited to outer wires of rope. However, till date, there is no effective mathematical model to examine the inter wire contact forces and wear characteristics. The scope of this paper is to present a computational simulation technique to evaluate inter wire contact forces and wear, which are in many cases responsible for rope failure. Two different type of ropes, IWRC-6xFi(29) and U3xSeS(48) were taken for structural strength evaluation and wear prediction. Both ropes have a double helix twisted wire profile as per JIS standards and are mainly used in cranes. CAD models of both ropes were developed in general purpose design software using in house developed formulation to generate double helix profile. Numerical simulation was done under two different load cases (a) Axial Tension and (b) Bending over Sheave. Different parameters such as stresses, contact forces, wear depth, load-elongation, etc., were investigated and compared between both ropes. Numerical simulation method facilitates the detailed investigation of inter wire contact and wear characteristics. In addition, various selection parameters like sheave diameter, rope diameter, helix angle, swaging, maximum load carrying capacity, etc., can be quickly analyzed.

Keywords: steel wire ropes, numerical simulation, material wear, structural strength, axial tension, bending over sheave

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Authors: M. Azarbarmas, J. M. Cabrera, J. Calvo, M. Aghaie-Khafri

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The modeling of hot deformation behavior for unseen conditions is important in metal-forming. In this study, the hot deformation of IN718 has been characterized in the temperature range 950-1100 and strain rate range 0.001-0.1 s-1 using hot compression tests. All stress-strain curves showed the occurrence of dynamic recrystallization. These curves were implemented quantitatively in mathematics, and then constitutive equation indicating the relationship between the flow stress and hot deformation parameters was obtained successfully.

Keywords: compression test, constitutive equation, dynamic recrystallization, hot working

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Authors: Reza Hedayati, Meysam Jahanbakhshi

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In this work, Fracture Mechanics is used to predict crack propagation in the adhesive jointing aluminum and composite plates. Three types of loadings and two types of glass-epoxy composite sequences: [0/90]2s and [0/45/-45/90]s are considered for the composite plate. Therefore 2*3=6 cases are considered and their results are compared. The debonding initiation load, complete debonding load, crack face profile and load-displacement diagram have been compared for the six cases.

Keywords: fracture, adhesive joint, debonding, APDL, LEFM

Procedia PDF Downloads 400