Search results for: VFA membrane extraction

Authors: Banaz Sdiq Abdulla

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Four local species (Allium sativum, Capsicum annum, Anethum graveolens, and Ocimum basilicum) were evaluated in the laboratory of Biolog Department, College of Education, for their ability to protect stored rice from the infection by weevil Sitophilus oryzae. Aqueous extracts of the plant species were applied as direct admixture of three concentrations levels of 1%, 2.5%, and 5% (W/V) to assess for mortality, adult emergence, and repellency and weight losses. The results showed that Al. sativum extracts was the most effective as it gave the highest mortality (90%)at 5% concentration followed by Capsicum annum (80%) on the 4th day post treatment, the result showed that the plant extract of different concentrations exhibited different level of reduction in adult emergence and different repellency of adults of Sitophilus oryzae. Allium sativum recorded the lowest mean number of adult emergence (8) followed by Capsicum annum (10) at 5% concentration, while Capsicum annum was found to be revealed complete repellent agent (100%) repellency on the 6th hours against Sitophilus oryzae followed by Allium sativum and Anethum graveolens (81.8%). There was a significant (P>0.05) reduction in the weight lossed by the weevils with less damaged recorded on grain treated with Allium sativum and Capsicum annum (1.6%) and (2.3%) respectively.

Keywords: plant extraction, rice, protectant, pest

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Authors: Suresh Kumar Verma, Jugal Kishore Das, Ealisha Jha, Mrutyunjay Suar, SKS Parashar

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In recent years nanoforms of inorganic metallic oxides has attracted a lot of interest due to their small size and significantly improved physical, chemical and biological properties compared to their molecular precursor. Some of the inorganic materials such as TiO2, ZnO, MgO, CaO, Al2O3 have been extensively used in biological applications. Zinc Oxide is a Wurtzite-type semiconductor and piezo-electric material exhibiting excellent electrical, optical and chemical properties with a band energy gap of 3.1-3.4 eV. Nanoforms of Zinc Oxide (ZnO) are increasingly recognised for their utility in biological application. The significant physical parameters such as surface area, particle size, surface charge and Zeta potential of Zinc Oxide (ZnO) nanoparticles makes it suitable for the uptake, persistance, biological, and chemical activities inside the living cells. The present study shows the effect of intrinsic defects of ZnO nanocrystals synthesized by high energy ball milling (HEBM) technique in their antibacterial activities. Bulk Zinc oxide purchased from market were ball milled for 7 h, 10 h, and 15 h respectively to produce nanosized Zinc Oxide. The structural and optical modification of such synthesized particles were determined by X-ray diffraction (XRD), Scanning Electron Microscopy and Electron Paramagnetic Resonance (EPR). The antibacterial property of synthesized Zinc Oxide nanoparticles was tested using well diffusion, minimum inhibitory Concentration, minimum bacteriocidal concentration, reactive oxygen species (ROS) estimation and membrane potential determination methods. In this study we observed that antibacterial activity of ZnO nanoparticles is because of the intrinsic defects that exist as a function of difference in size and milling time.

Keywords: high energy ball milling, ZnO nanoparticles, EPR, Antibacterial properties

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

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Authors: Abdunaser Abduelmula, Maria Luisa M. Bastos, José A. Gonçalves

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The modeling of the earth's surface and evaluation of urban environment, with 3D models, is an important research topic. New stereo capabilities of high-resolution optical satellites images, such as the tri-stereo mode of Pleiades, combined with new image matching algorithms, are now available and can be applied in urban area analysis. In addition, photogrammetry software packages gained new, more efficient matching algorithms, such as SGM, as well as improved filters to deal with shadow areas, can achieve denser and more precise results. This paper describes a comparison between 3D data extracted from tri-stereo and dual stereo satellite images, combined with pixel based matching and Wallis filter. The aim was to improve the accuracy of 3D models especially in urban areas, in order to assess if satellite images are appropriate for a rapid evaluation of urban environments. The results showed that 3D models achieved by Pleiades tri-stereo outperformed, both in terms of accuracy and detail, the result obtained from a Geo-eye pair. The assessment was made with reference digital surface models derived from high-resolution aerial photography. This could mean that tri-stereo images can be successfully used for the proposed urban change analyses.

Keywords: 3D models, environment, matching, pleiades

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Authors: Win Nee Phong, Tau Chuan Ling, Pau Loke Show

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From an industrial perspective, the exploitation of microalgae for protein source is of great economical and commercial interest due to numerous attractive characteristics. Nonetheless, the release of protein from microalgae is limited by the multiple layers of the rigid thick cell wall that generally contain a large proportion of cellulose. Thus an efficient cell disruption process is required to rupture the cell wall. The conventional downstream processing methods which typically involve several unit operational steps such as disruption, isolation, extraction, concentration and purification are energy-intensive and costly. To reduce the overall cost and establish a feasible technology for the success of the large-scale production, microalgal industry today demands a more cost-effective and eco-friendly technique in downstream processing. One of the main challenges to extract the proteins from microalgae is the presence of rigid cell wall. This study aims to provide some guidance on the selection of the efficient solvent to facilitate the proteins released during the cell disruption process. The effects of solvent types such as methanol, ethanol, 1-propanol and water in rupturing the microalgae cell wall were studied. It is interesting to know that water is the most effective solvent to recover proteins from microalgae and the cost is cheapest among all other solvents.

Keywords: green, microalgae, protein, solvents

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Authors: Juan Carlos Quiñones

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Time has passed since the industrial design has put murder on a mass-production basis. The industrial design applies methods from different disciplines with a strategic approach, to place humans at the centers of the design process and to deliver solutions that are meaningful and desirable for users and for the market. This analysis summarizes some of the discussions that occurred in the 6th International Forum of Design as a Process, June 2016, Valencia. The aims of this conference were finding new linkages between systems and design interactions in order to define the social consequences. Through knowledge management we are able to transform the intangible aspect by using design as a transforming function capable of converting intangible knowledge into tangible solutions (i.e. products and services demanded by society). Industrial designers use knowledge consciously as a starting point for the ideation of the product. The handling of the intangible becomes more and more relevant over time as different methods emerge for knowledge extraction and subsequent organization. The different methodologies applied to the industrial design discipline and the evolution of the same discipline methods underpin the cultural and scientific background knowledge as a starting point of thought as a response to the needs; the whole thing coming through the instrument of creativity for the achievement of the proper and necessary balance between intuition and reason, design and science.

Keywords: creative process, creativity, industrial design, intangible

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Authors: Oustani Mabrouka, Halilat Md Tahar, Hannachi Slimane

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This study was conducted on representative and contrasting soils of arid regions. It focuses on the compared influence of two organic fertilizers: poultry manure (PM) and bovine manure (BM) on improving the microbial functioning of non-saline (SS) and saline (SSS) soils, in particularly, the process of mineralization of nitrogen and carbon. The microbiological activity was estimated by respirometric test (CO2–C emissions) and the extraction of two forms of mineral nitrogen (NH4+-N and NO3--N). Thus, after 56 days of incubation under controlled conditions (28 degrees and 80 per cent of the field capacity), the two types of manures showed that the mineralization activity varies according to type of soil and the organic substrate itself. However, the highest cumulative quantities of CO2–C, NH4+–N and NO3-–N obtained at the end of incubation were recorded in non-saline (SS) soil treated with poultry manure with 1173.4, 4.26 and 8.40 mg/100 g of dry soil, respectively. The reductions in rates of release of CO2–C and of nitrification under saline conditions were 21 and 36, 78 %, respectively. The influence of organic substratum on the microbial density shows a stimulating effect on all microbial groups studied. The whole results show the usefulness of two types of manures for the improvement of the microbiological functioning of arid soils.

Keywords: Salinity, Organic matter, Microorganisms, Mineralization, Nitrogen, Carbon, Arid regions

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Authors: Panadda Rojpibulstit, Suthathip Kittisenachai, Songchan Puthong, Sirikul Manochantr, Pornpen Gamnarai, Sasichai Kangsadalampai, Sittiruk Roytrakul

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Hepatocellular carcinoma (HCC) is the most primary hepatic cancer worldwide. Nowadays a targeted therapy via monoclonal antibodies (mAbs) specific to tumor-associated antigen is continually developed in HCC treatment. In this regard, after establishing and consequently exploring Hep88 mAb’s tumoricidal effect on hepatocellular carcinoma cell line (HepG2 cell line), the Hep88 mAb’s specific Ag from both membrane and cytoplasmic fractions of HepG2 cell line was identified by 2-D gel electrophoresis and western blot analysis. After in-gel digestion and subsequent analysis by liquid chromatography-mass spectrometry (LC-MS), mortalin (HSPA9) and alpha-enolase were identified. The recombinant proteins specific to Hep88 mAb were cloned and expressed in E.coli BL21 (DE3). Moreover, alteration of HepG2 and Chang liver cell line after being induced by Hep88 mAb for 1-3 days was investigated using a transmission electron microscope. The result demonstrated that Hep88 mAb can bind to the recombinant mortalin (HSPA9) andalpha-enolase. In addition, gradual appearance of mitochondria vacuolization and endoplasmic reticulum dilatation were observed. Taken together, paraptosis-like programmed cell death (PCD) of HepG2 is induced by binding of mortalin (HSPA9) and alpha-enolase to Hep88 mAb. Mortalin depletion by formation of Hep88 mAb-mortalin (HSPA9) complex might initiate transcription-independent of p53-mediated apoptosis. Additionally, Hep88 mAb-alpha-enolase complex might initiate HepG2 cells energy exhaustion by glycolysis pathway obstruction. These results imply that Hep88 mAb might be a promising tool for development of an effective treatment of HCC in the next decade.

Keywords: Hepatocellular carcinoma, Monoclonal antibody, Paraptosis-like program cell death, Transmission electron microscopy, mortalin (HSPA9), alpha-enolase

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Authors: Mohamed Izzharif Abdul Halim, Niamh Nic Daeid

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Determining the source of pen inks used on a variety of documents is impartial for forensic document examiners. The examination of inks is often performed to differentiate between inks in order to evaluate the authenticity of a document. A ballpoint pen ink consists of synthetic dyes in (acidic and/or basic), pigments (organic and/or inorganic) and a range of additives. Inks of similar color may consist of different composition and are frequently the subjects of forensic examinations. This study emphasizes on blue ballpoint pen inks available in the market because it is reported that approximately 80% of questioned documents analysis involving ballpoint pen ink. Analytical techniques such as thin layer chromatography, high-performance liquid chromatography, UV-vis spectroscopy, luminescence spectroscopy and infrared spectroscopy have been used in the analysis of ink samples. In this study, application of Diamond Attenuated Total Reflectance (ATR) FTIR is straightforward but preferable in forensic science as it offers no sample preparation and minimal analysis time. The data obtained from these techniques were further analyzed using multivariate chemometric methods which enable extraction of more information based on the similarities and differences among samples in a dataset. It was indicated that some pens from the same manufactures can be similar in composition, however, discrete types can be significantly different.

Keywords: ATR FTIR, ballpoint, multivariate chemometric, PCA

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Authors: Seyede Sanaz Seyedebrahimi, Shima Rahimi, Shohreh Fakhari, Ali Jalili

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Background: CXCR4, as a chemokine receptor, plays well-known roles in various types of cancers. Several studies have been conducted to overcome CXCR4 axis acts in multiple myeloma (MM) pathogenesis and progression. Dexamethasone, a standard treatment for multiple myeloma, has been shown to increase CXCR4 levels in multiple myeloma cell lines. Herein, we focused on the effects of metformin and dexamethasone on CXCR4 at the cellular level and the migration rate of cell lines after exposure to a combination compared to single-agent models. Materials and Method: Multiple myeloma cell lines (U266 and RPMI8226) were cultured with different metformin and dexamethasone concentrations in single-agent and combination models. The simultaneous combination doses were calculated by CompuSyn software. Cell surface and mRNA expression of CXCR4 were determined using flow cytometry and the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay, respectively. The Transwell cell migration assay evaluated the migration ability. Results: In concurred with previous studies, our results showed a dexamethasone up-regulation effect on CXCR4 in a dose-dependent manner. Although, the metformin single-agent model could reduce CXCR4 expression of U266 and RPMI8226 in cell surface and mRNA expression level. Moreover, the administration of metformin and dexamethasone simultaneously exerted a higher suppression effect on CXCR4 expression than the metformin single-agent model. The migration rate through the combination model's matrigel membrane was remarkably lower than the metformin and dexamethasone single-agent model. Discussion: According to our findings, the combination of metformin and dexamethasone effectively inhibited dexamethasone-induced CXCR4 expression in multiple myeloma cell lines. As a result, metformin may be counted as an alternative medicine combined with other chemotherapies to combat multiple myeloma. However, more research is required.

Keywords: CXCR4, dexamethasone, metformin, migration, multiple myeloma

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Authors: Hao Li, Guy Y. Cornejo Maceda, Yiqing Li, Jianguo Tan, Marek Morzynski, Bernd R. Noack

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We propose an automated analysis of the flow control behaviour from an ensemble of control laws and associated time-resolved flow snapshots. The input may be the rich database of machine learning control (MLC) optimizing a feedback law for a cost function in the plant. The proposed methodology provides (1) insights into the control landscape, which maps control laws to performance, including extrema and ridge-lines, (2) a catalogue of representative flow states and their contribution to cost function for investigated control laws and (3) visualization of the dynamics. Key enablers are classification and feature extraction methods of machine learning. The analysis is successfully applied to the stabilization of a mixing layer with sensor-based feedback driving an upstream actuator. The fluctuation energy is reduced by 26%. The control replaces unforced Kelvin-Helmholtz vortices with subsequent vortex pairing by higher-frequency Kelvin-Helmholtz structures of lower energy. These efforts target a human interpretable, fully automated analysis of MLC identifying qualitatively different actuation regimes, distilling corresponding coherent structures, and developing a digital twin of the plant.

Keywords: machine learning control, mixing layer, feedback control, model-free control

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Authors: Nayira A. Abd Elbaky, Amal J. Fatani, Hazar Yaqub, Nouf M. Al-Rasheed, Naglaa El-Orabi, Mai Osman

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The present work is aimed to evaluate the protective effect of N-acetyl cystiene (NAC), coenzyme Q10 (CoQ10), and their combination against carbon tetrachloride (CCl4)-induced cardiotoxicity in rats. CCl4 treatment significantly elevated the levels of cardiac oxidative stress bio markers including nitric oxide (NO) and malondialdehyde (MDA). A concomitant decrease in the level of reduced glutathione and the activity of membrane bound enzyme, calcium-adenosine triphosphatase were observed in the hearts of rats exposed to CCl4 compared to respective values in normal group. Quantitative analysis of myocardial energy metabolism revealed a significant decrease in the glucose content coupled with depletion in the activities of myocardial glycolytic enzymes as hexokinase (HK), phosphofructokinase (PFK) and lactate dehydrogenase (LDH) after CCl4 treatment. In addition, a significant elevation in myocardial hydroxyproline level was observed in CCl4 intoxicated rats indicating interstitial collagen accumulation. Pretreatment with either NAC, CoQ10 or their combination successively alleviated the alterations in myocardial oxidative stress and antioxidant markers, as well as effectively up-regulated the decrease in cardiac energetic biomarkers in CCl4 intoxicated rats. Moreover, these antioxidants markedly reduced myocardial hydroxyproline level versus that of CCl4-treated animals. In conclusion, the present results illustrated that the prophylactic use of the current antioxidant resulted in a remarkable cardioprotective effect against CCl4 induced myocardial damage, which suggest that they may candidates as prophylactic agents against different cardio-toxins.

Keywords: carbon tetrachloride, lipid peroxidation, antioxidant, energy metabolism, hydroxyproline

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Authors: Ganfeng Yu, Yuefeng Ma, Shanliang Yang

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The word discovery is a key problem in text information retrieval technology. Methods in new word discovery tend to be closely related to words because they generally obtain new word results by analyzing words. With the popularity of social networks, individual netizens and online self-media have generated various network texts for the convenience of online life, including network words that are far from standard Chinese expression. How detect network words is one of the important goals in the field of text information retrieval today. In this paper, we integrate the word embedding model and clustering methods to propose a network word discovery framework based on sentence semantic similarity (S³-NWD) to detect network words effectively from the corpus. This framework constructs sentence semantic vectors through a distributed representation model, uses the similarity of sentence semantic vectors to determine the semantic relationship between sentences, and finally realizes network word discovery by the meaning of semantic replacement between sentences. The experiment verifies that the framework not only completes the rapid discovery of network words but also realizes the standard word meaning of the discovery of network words, which reflects the effectiveness of our work.

Keywords: text information retrieval, natural language processing, new word discovery, information extraction

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Authors: Nadine Wiesmann, Melanie Viel, Christoph Buhr, Rachel Tanner, Wolfgang Tremel, Juergen Brieger

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Recidivation of tumors and the development of resistances against the classical anti-tumor approaches represent a major challenge we face when treating cancer. In order to master this challenge, we are in desperate need of new treatment options beyond the beaten tracks. Zinc oxide nanoparticles (ZnO NPs) represent such an innovative approach. Zinc oxide is characterized by a high level of biocompatibility, concurrently ZnO NPs are able to exert anti-tumor effects. By concentration of the nanoparticles at the tumor site, tumor cells can specifically be exposed to the nanoparticles while low zinc concentrations at off-target sites are tolerated well and can be excreted easily. We evaluated the toxicity of ZnO NPs in vitro with the help of immortalized tumor cell lines and primary cells stemming from healthy tissue. Additionally, the Chorioallantoic Membrane Assay (CAM Assay) was employed to gain insights into the in vivo behavior of the nanoparticles. We could show that ZnO NPs interact with tumor cells as nanoparticulate matter. Furthermore, the extensive release of zinc ions from the nanoparticles nearby and within the tumor cells results in overload with zinc. Beyond that, ZnO NPs were found to further the generation of reactive oxygen species (ROS). We were able to show that tumor cells were more prone to the toxic effects of ZnO NPs at intermediate concentrations compared to fibroblasts. With the help of ZnO NPs covered by a silica shell in which FITC dye was incorporated, we were able to track ZnO NPs within tumor cells as well as within a whole organism in the CAM assay after injection into the bloodstream. Depending on the applied concentrations, selective tumor cell killing seems feasible. Furthermore, the combinational treatment of tumor cells with radiotherapy and ZnO NPs shows promising results. Still, further investigations are needed to gain a better understanding of the interaction between ZnO NPs and the human body to be able to pave the way for their application as an innovative anti-tumor agent in the clinics.

Keywords: metal oxide nanoparticles, nanomedicine, overcome resistances against classical treatment options, zinc oxide nanoparticles

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Authors: Mohammad Sheikhalishahi, Vahid Ebrahimipour, Amir Hossein Radman-Kian

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This paper proposes an Ontology framework for knowledge modeling and representation of the equipment integrity process in a typical oil and gas production plant. Our aim is to construct a knowledge modeling that facilitates translation, interpretation, and conversion of human-readable integrity interpretation into computer-readable representation. The framework provides a function structure related to fault propagation using ISO 14224 and ISO 15926 OWL-Lite/ Resource Description Framework (RDF) to obtain a generic system-level model of asset integrity that can be utilized in the integrity engineering process during the equipment life cycle. It employs standard terminology developed by ISO 15926 and ISO 14224 to map textual descriptions of equipment failure and then convert it to a causality-driven logic by semantic interpretation and computer-based representation using Lite/RDF. The framework applied for an offshore gas riser. The result shows that the approach can cross-link the failure-related integrity words and domain-specific logic to obtain a representation structure of equipment integrity with causality inference based on semantic extraction of inspection report context.

Keywords: asset integrity modeling, interoperability, OWL, RDF/XML

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Authors: Muzaffar Iqbal, Essam Ezzeldin, Khalid A. Al-Rashood

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Pomalidomide is a second generation oral immunomodulatory agent, being used for the treatment of multiple myeloma in patients with disease refractory to lenalidomide and bortezomib. In this study, a sensitive UPLC-MS/MS assay was developed and validated for high-throughput determination of pomalidomide in rat plasma using celecoxib as an internal standard (IS). Liquid liquid extraction using dichloromethane as extracting agent was employed to extract pomalidomide and IS from 200 µL of plasma. Chromatographic separation was carried on Acquity BEHTM C18 column (50 × 2.1 mm, 1.7 µm) using an isocratic mobile phase of acetonitrile:10 mM ammonium acetate (80:20, v/v), at a flow rate of 0.250 mL/min. Both pomalidomide and IS were eluted at 0.66 ± 0.03 and 0.80 ± 0.03 min, respectively with a total run time of 1.5 min only. Detection was performed on a triple quadrupole tandem mass spectrometer using electrospray ionization in negative mode. The precursor to product ion transitions of m/z 272.01 → 160.89 for pomalidomide and m/z 380.08 → 316.01 for IS were used to quantify them respectively, using multiple reaction monitoring mode. The developed method was validated according to regulatory guideline for bioanalytical method validation. The linearity in plasma sample was achieved in the concentration range of 0.47–400 ng/mL (r2 ≥ 0.997). The intra and inter-day precision values were ≤ 11.1% (RSD, %) whereas accuracy values ranged from - 6.8 – 8.5% (RE, %). In addition, other validation results were within the acceptance criteria and the method was successfully applied in a pharmacokinetic study of pomalidomide in rats.

Keywords: pomalidomide, pharmacokinetics, LC-MS/MS, celecoxib

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Authors: Hagen Stosnach

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The analytical demands on modern instruments for element analysis in food samples include the analysis of major, trace and ultra-trace essential elements as well as potentially toxic trace elements. In this study total reflection, X-ray fluorescence analysis (TXRF) is presented as an analytical technique, which meets the requirements, defined by the Association of Official Agricultural Chemists (AOAC) regarding the limit of quantification, repeatability, reproducibility and recovery for most of the target elements. The advantages of TXRF are the small sample mass required, the broad linear range from µg/kg up to wt.-% values, no consumption of gases or cooling water, and the flexible and easy sample preparation. Liquid samples like alcoholic or non-alcoholic beverages can be analyzed without any preparation. For solid food samples, the most common sample pre-treatment methods are mineralization, direct deposition of the sample onto the reflector without/with minimal treatment, mainly as solid suspensions or after extraction. The main disadvantages are due to the possible peaks overlapping, which may lower the accuracy of quantitative analysis and the limit in the element identification. This analytical technique will be presented by several application examples, covering a broad range of liquid and solid food types.

Keywords: essential elements, toxic metals, XRF, spectroscopy

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Authors: Hasan Türe, Kader Terzioglu, Evren Tunca

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Contamination of aqueous environment by heavy metal ions is a serious and complex problem, owing to their hazards to human being and ecological systems. The treatment methods utilized for removing metal ions from aqueous solution include membrane separation, ion exchange and chemical precipitation. However, these methods are limited by high operational cost. Recently, biobased beads are considered as promising biosorbent to remove heavy metal ions from water. The aim of present study was to characterize the alginate/perlite composite beads and to investigate the adsorption performance of obtained beads for removing Pb (II) from aqueous solution. Alginate beads were synthesized by ionic gelation methods and different amount of perlite (aljinate:perlite=1, 2, 3, 4, 5 wt./wt.) was incorporated into alginate beads. Samples were characterized by means of X-ray diffraction (XRD), thermogravimetric analysis (TGA), scanning electron microscopy (SEM). The effects of perlite level, the initial concentration of Pb (II), initial pH value of Pb(II) solution and effect of contact time on the adsorption capacity of beads were investigated by using batch method. XRD analysis indicated that perlite includes silicon or silicon and aluminum bearing crystalline phase. The diffraction pattern of perlite containing beads is similar to that of that perlite powder with reduced intensity. SEM analysis revealed that perlite was embedded into alginate polymer and SEM-EDX (Energy-Dispersive X-ray) showed that composite beads (aljinate:perlite=1) composed of C (41.93 wt.%,), O (43.64 wt.%), Na (10.20 wt.%), Al (0.74 wt.%), Si (2.72 wt.%) ve K (0.77 wt.%). According to TGA analysis, incorporation of perlite into beads significantly improved the thermal stability of the samples. Batch experiment indicated that optimum pH value for Pb (II) adsorption was found at pH=7 with 1 hour contact time. It was also found that the adsorption capacity of beads decreased with increases in perlite concentration. The results implied that alginate/perlite composite beads could be used as promising adsorbents for the removal of Pb (II) from wastewater. Acknowledgement: This study was supported by TUBITAK (Project No: 214Z146).

Keywords: alginate, adsorption, beads, perlite

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Authors: Merouani Nawel, Belhattab Rachid

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Aristolochia longa L. (Aristolochiacea) is a native plant of Algeria used in traditional medicine. This study was devoted to the determination of polyphenols, flavonoids, and condensed tannins contents of Aristolochia longa L. after their extraction by using various solvents with different polarities (methanol, acetone and distilled water). These extracts were prepared from stem, leaves, fruits and rhizome. The antioxidant activity was determined using three in vitro assays methods: scavenging effect on DPPH, the reducing power assay and ẞ-carotene bleaching inhibition (CBI). The results obtained indicate that the acetone extracts from the aerial parts presented the highest contents of polyphenols. The results of The antioxidant activity showed that all extracts of Aristolochia longa L., prepared using different solvent, have diverse antioxidant capacities. However, the aerial parts methanol extract exhibited the highest antioxidant capacity of DPPH and reducing power (Respectively 55,04ug/ml±1,29 and 0,2 mg/ml±0,019 ). Nevertheless, the aerial parts acetone extract showed the highest antioxidant capacity in the test of ẞ-carotene bleaching inhibition with 57%. These preliminary results could be used to justify the traditional use of this plant and their bioactive substances could be exploited for therapeutic purposes such as antioxidant and antimicrobial.

Keywords: aristolochia longa l., polyphenols, flavonoids, condensed tannins, antioxidant activity

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Authors: Rita Magdalena, N. K. Caecar Pratiwi, Yunendah Nur Fuadah, Sofia Saidah, Bima Sakti

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Vessel segmentation of retinal fundus is important for biomedical sciences in diagnosing ailments related to the eye. Segmentation can simplify medical experts in diagnosing retinal fundus image state. Therefore, in this study, we designed a software using MATLAB which enables the segmentation of the retinal blood vessels on retinal fundus images. There are two main steps in the process of segmentation. The first step is image preprocessing that aims to improve the quality of the image to be optimum segmented. The second step is the image segmentation in order to perform the extraction process to retrieve the retina’s blood vessel from the eye fundus image. The image segmentation methods that will be analyzed in this study are Morphology Operation, Discrete Wavelet Transform and combination of both. The amount of data that used in this project is 40 for the retinal image and 40 for manually segmentation image. After doing some testing scenarios, the average accuracy for Morphology Operation method is 88.46 % while for Discrete Wavelet Transform is 89.28 %. By combining the two methods mentioned in later, the average accuracy was increased to 89.53 %. The result of this study is an image processing system that can segment the blood vessels in retinal fundus with high accuracy and low computation time.

Keywords: discrete wavelet transform, fundus retina, morphology operation, segmentation, vessel

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Authors: Shengbiao Wu, Weihua Cao, Min Wu, Can Liu

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This paper presents an intelligent tuning method of microwave filter based on complex neural network and improved space mapping. The tuning process consists of two stages: the initial tuning and the fine tuning. At the beginning of the tuning, the return loss of the filter is transferred to the passband via the error of phase. During the fine tuning, the phase shift caused by the transmission line and the higher order mode is removed by the curve fitting. Then, an Cauchy method based on the admittance parameter (Y-parameter) is used to extract the coupling matrix. The influence of the resonant cavity loss is eliminated during the parameter extraction process. By using processed data pairs (the amount of screw variation and the variation of the coupling matrix), a tuning model is established by the complex neural network. In view of the improved space mapping algorithm, the mapping relationship between the actual model and the ideal model is established, and the amplitude and direction of the tuning is constantly updated. Finally, the tuning experiment of the eight order coaxial cavity filter shows that the proposed method has a good effect in tuning time and tuning precision.

Keywords: microwave filter, scattering parameter, coupling matrix, intelligent tuning

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Authors: Mulata Haile Nega, Derebew Fikadu Berhe, Vera Ribeiro Marques

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There is no epidemiologic data on this gene polymorphism in several countries. Therefore, this study aimed to assess the genotype and allele frequencies of the gene variant in three countries. This study involved healthy individuals from Colombia, Mozambique, and Portugal. Genomic DNA was isolated from blood samples using the Qiamp DNA Extraction Kit (Qiagen). The isolated DNA was genotyped using Polymerase Chain Reaction (PCR) - Restriction Fragment Length Polymorphism. Microstat and GraphPad quick cal software were used for the Chi-square test and evaluation of Hardy-Weinberg equilibrium, respectively. A total of 181 individuals’ blood sample was analyzed. Overall, TT (74.0%) genotype was the highest, and CC (7.8%) was the lowest. Country wise genotypic frequencies were Colombia 47(70.2%) TT, 12(17.9%) TC and 8(11.9%) CC; Mozambique 47(88.7%) TT, 5(9.4%) TC, and 1(1.9%) CC; and Portugal 40(65.6%) TT, 16(26.2%) TC, and 5(8.2%) CC. The reference (T) allele was highest among Mozambicans (93.4%) compared to Colombians (79.1%) and Portuguese (78.7%). Mozambicans showed statistically significant genotypic and allelic frequency differences compared to Colombians (p<0.01) and Portuguese (p <0.01). Overall and country-wise, the CC genotype was less frequent and relatively high for Colombians and Portuguese populations. This finding may imply statins risk-benefit variability associated with CC genotype among these populations that needs further understanding.

Keywords: c.521T>C, polymorphism, SLCO1B1, SNP, statins

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Authors: Bing Li, Zhi Li, Yilong Yang

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Web classification can promote the quality of service discovery and management in the service repository. It is widely used to locate developers desired services. Although traditional classification methods based on supervised learning models can achieve classification tasks, developers need to manually mark web services, and the quality of these tags may not be enough to establish an accurate classifier for service classification. With the doubling of the number of web services, the manual tagging method has become unrealistic. In recent years, the attention mechanism has made remarkable progress in the field of deep learning, and its huge potential has been fully demonstrated in various fields. This paper designs a multi-head attention graph convolutional network (MHAGCN) service classification method, which can assign different weights to the neighborhood nodes without complicated matrix operations or relying on understanding the entire graph structure. The framework combines the advantages of the attention mechanism and graph convolutional neural network. It can classify web services through automatic feature extraction. The comprehensive experimental results on a real dataset not only show the superior performance of the proposed model over the existing models but also demonstrate its potentially good interpretability for graph analysis.

Keywords: attention mechanism, graph convolutional network, interpretability, service classification, service discovery

Procedia PDF Downloads 135

Authors: Shokoufeh Roudashti, Shahin Bahari, Fakhri Haghi, Habib Zeighami, Ghazal Naderi, Paniz Shirmast

Abstract:

Background: Mycobacterium tuberculosis complex (MTBC) causes tuberculosis (TB) in humans and animals. Mycobacterium MTBC is one of the most important species of zoonotic pathogens that can be transmitted from cattle to humans. The disease can transmit to human by direct contact with the infected animals, drinking unpasteurized milk and consumption of uncooked meat. The presence of these opportunistic, pathogenic bacteria in bovine milk has emerged as a public-health concern, especially among individuals who consume raw milk. Tuberculosis MTBC is the predominant infectious cause of morbidity and morality worldwide, It is estimated that one third of the world population (approx. 1.8 billion persons) is infected with M. tuberculosis and each year there are 8 million new cases worldwide. The aim of this study, to detect Mycobacterium MTBC in raw milk samples using polymerase chain reaction (PCR). Materials and Methods: In the present study, 60 raw milk samples were collected from rural areas in Zanjan, Iran. After extraction of DNAs and using special primers for Is6110 gene as a marker, PCR was applied to detect the presence or non-presence of the related gene. Results: According to the findings of this study, 8 (13.5 %) out of 60 milk samples were positive for Mycobacterium spp (P < 0.1). Conclusions: The Outbreak of genus Mycobacteria spp in milk samples were determined to be relatively high in Zanjan, Iran.

Keywords: Mycobacteria spp, raw milk, PCR, Zanjan

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Authors: Alev Atak

Abstract:

In this paper, we aim to create a financial sentiment index by investigating the company’s voluntary information disclosures. We retrieve structured content from BIST 100 companies’ financial reports for the period 1998-2018 and extract relevant financial information for sentiment analysis through Natural Language Processing. We measure strategy-related disclosures and their cross-sectional variation and classify report content into generic sections using synonym lists divided into four main categories according to their liquidity risk profile, risk positions, intra-annual information, and exposure to risk. We use Word Error Rate and Cosin Similarity for comparing and measuring text similarity and derivation in sets of texts. In addition to performing text extraction, we will provide a range of text analysis options, such as the readability metrics, word counts using pre-determined lists (e.g., forward-looking, uncertainty, tone, etc.), and comparison with reference corpus (word, parts of speech and semantic level). Therefore, we create an adequate analytical tool and a financial dictionary to depict the importance of granular financial disclosure for investors to identify correctly the risk-taking behavior and hence make the aggregated effects traceable.

Keywords: financial sentiment, machine learning, information disclosure, risk

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Authors: S. Saju, G. Thirugnanam

Abstract:

In this paper, a medical image watermarking algorithm based on contourlet is proposed. Medical image watermarking is a special subcategory of image watermarking in the sense that images have special requirements. Watermarked medical images should not differ perceptually from their original counterparts because clinical reading of images must not be affected. Watermarking techniques based on wavelet transform are reported in many literatures but robustness and security using contourlet are better when compared to wavelet transform. The main challenge in exploring geometry in images comes from the discrete nature of the data. In this paper, original image is decomposed to two level using contourlet and the watermark is embedded in the resultant sub-bands. Sub-band selection is based on the value of Peak Signal to Noise Ratio (PSNR) that is calculated between watermarked and original image. To extract the watermark, Kernel ICA is used and it has a novel characteristic is that it does not require the transformation process to extract the watermark. Simulation results show that proposed scheme is robust against attacks such as Salt and Pepper noise, Median filtering and rotation. The performance measures like PSNR and Similarity measure are evaluated and compared with Discrete Wavelet Transform (DWT) to prove the robustness of the scheme. Simulations are carried out using Matlab Software.

Keywords: digital watermarking, independent component analysis, wavelet transform, contourlet

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Authors: Iyasu Eibedingil

Abstract:

The construction industry is one of the major factors responsible for causing a negative impact on the environment. It has the largest share in the use of natural resources including land use, material extraction, and greenhouse gases emissions. For this reason, it is imperative to reduce its environmental impact through the construction of sustainable buildings with less impact. These days, it is possible to measure the environmental impact by using different tools such as the life cycle assessment (LCA) approach. Given this premise, this study explored the environmental impact of two types of roofing systems through comparative life cycle assessment approach. The tiles were analyzed to select the most environmentally friendly roofing system for the villa at Khalifa City A, Abu Dhabi, United Arab Emirates. These products are available in various forms; however, in this study concrete roof tiles and clay roof tiles were considered. The results showed that concrete roof tiles have lower environmental impact. In all scenarios considered, manufacturing the roof tiles locally, using recovered fuels for firing clay tiles, and using renewable energy (electricity from PV plant) showed that the concrete roof tiles were found to be excellent in terms of its embodied carbon, embodied the energy and various other environmental performance indicators.

Keywords: clay roof tile, concrete roof tile, life cycle assessment, sensitivity analysis

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Authors: Sharareh Sharifi, Pargol Ghavam Mostafavi, Ali Mashinchian Moradi, Mohammad Hadi Givianrad, Hassan Niknejad

Abstract:

Marine organisms such as soft coral, sponge, ascidians, and tunicate containing rich source of natural compound have been studied in last decades because of their special chemical compounds with anticancer properties. The aim of this study was to investigate anti-cancer property of ethyl acetate extracted from marine sea pen Virgularia gustaviana found from Persian Gulf coastal (Bandar Abbas). The extraction processes were carried out with ethyl acetate for five days. Thin layer chromatography (TLC) and high-performance liquid chromatography (HPLC) were used for qualitative identification of crude extract. The viability of HeLa and MDA-Mb-231 cancer cells was investigated using MTT assay at the concentration of 25, 50, and a 100 µl/ml of ethyl acetate is extracted. The crude extract of Virgularia gustaviana demonstrated ten fractions with different Retention factor (Rf) by TLC and Retention time (Rt) evaluated by HPLC. The crude extract dose-dependently decreased cancer cell viability compared to control group. According to the results, the ethyl acetate extracted from Virgularia gustaviana inhibits the growth of cancer cells, an effect which needs to be further investigated in the future studies.

Keywords: anti-cancer, Hela cancer cell, MDA-Md-231 cancer cell, Virgularia gustavina

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Authors: Shinoy Vengaramkode Bhaskaran, Kaushik Sathupadi, Sandesh Achar

Abstract:

Human locomotion recognition is important in a variety of sectors, such as robotics, security, healthcare, fitness tracking and cloud computing. With the increasing pervasiveness of peripheral devices, particularly Inertial Measurement Units (IMUs) sensors, researchers have attempted to exploit these advancements in order to precisely and efficiently identify and categorize human activities. This research paper introduces a state-of-the-art methodology for the recognition of human locomotion patterns in a cloud environment. The methodology is based on a publicly available benchmark dataset. The investigation implements a denoising and windowing strategy to deal with the unprocessed data. Next, feature extraction is adopted to abstract the main cues from the data. The SelectKBest strategy is used to abstract optimal features from the data. Furthermore, state-of-the-art ML classifiers are used to evaluate the performance of the system, including logistic regression, random forest, gradient boosting and SVM have been investigated to accomplish precise locomotion classification. Finally, a detailed comparative analysis of results is presented to reveal the performance of recognition models.

Keywords: artificial intelligence, cloud computing, IoT, human locomotion, gradient boosting, random forest, neural networks, body-worn sensors

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Authors: Xiang Yu, Chuntao Feng, Lu Yang, Meiyang Song, Wenhao Zhou

Abstract:

The existing two-dimensional micro-Doppler features extraction ignores the correlation information between the spatial and temporal dimension features. For the range-Doppler map, the time dimension is introduced, and a frequency modulation continuous wave (FMCW) radar human fall detection algorithm based on time-varying range-Doppler features is proposed. Firstly, the range-Doppler sequence maps are generated from the echo signals of the continuous motion of the human body collected by the radar. Then the three-dimensional data cube composed of multiple frames of range-Doppler maps is input into the three-dimensional Convolutional Neural Network (3D CNN). The spatial and temporal features of time-varying range-Doppler are extracted by the convolution layer and pool layer at the same time. Finally, the extracted spatial and temporal features are input into the fully connected layer for classification. The experimental results show that the proposed fall detection algorithm has a detection accuracy of 95.66%.

Keywords: FMCW radar, fall detection, 3D CNN, time-varying range-doppler features

Procedia PDF Downloads 122