Search results for: nucleic acid extraction

Authors: B. Benalioua, I. Benyamina, A. Bentouami, B. Boury

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The objective of this study is based on the synthesis of a new photocatalyst based on TiO2 and its application in the photo-degradation of an acid dye under the visible light. The material obtained was characterized by different techniques like diffuse reflectance UV–Vis spectroscopy (DRS), X-ray diffraction (XRD) and scanning electron microscopy (SEM). The photocatalytic efficiency of the Bi, N co-doped TiO2 treated at 600°C for 1 h was tested on the Indigo Carmine under the irradiation of visible light and compared with that of the commercial titanium oxide TiO2-P25 (Degussa). The XRD characterization of the material Bi -N- TiO2 (600°C) revealed the presence of the anatase phase and the absence of the rutile phase in comparison of the TiO2 P25 diffractogram. Characterization by UV- visible diffuse reflection (DRS) material showed that the Bi-N-TiO2 exhibits redshift (move visible) relative to commercial titanium oxide TiO2-P25, this property promises a photocatalytic activity of Bi-N-TiO2 under visible light. Indeed, the efficiency of photocatalytic Bi-N-TiO2 as a visible light is shown by a complete discoloration of indigo carmine solution of 16 mg/L after 40 minutes, whereas with the P25-TiO2 discoloration is achieved after 90 minutes.

Keywords: POA, heterogeneous photocatalysis, TiO2, co-doping

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Authors: Steffy Maria Joseph, Abdu Rahiman V, Abdul Hameed K. M.

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Online handwritten character recognition is a challenging field in Artificial Intelligence. The classification success rate of current techniques decreases when the dataset involves similarity and complexity in stroke styles, number of strokes and stroke characteristics variations. Malayalam is a complex south indian language spoken by about 35 million people especially in Kerala and Lakshadweep islands. In this paper, we consider the significant feature extraction for the similar stroke styles of Malayalam. This extracted feature set are suitable for the recognition of other handwritten south indian languages like Tamil, Telugu and Kannada. A classification scheme based on support vector machines (SVM) is proposed to improve the accuracy in classification and recognition of online malayalam handwritten characters. SVM Classifiers are the best for real world applications. The contribution of various features towards the accuracy in recognition is analysed. Performance for different kernels of SVM are also studied. A graphical user interface has developed for reading and displaying the character. Different writing styles are taken for each of the 44 alphabets. Various features are extracted and used for classification after the preprocessing of input data samples. Highest recognition accuracy of 97% is obtained experimentally at the best feature combination with polynomial kernel in SVM.

Keywords: SVM, matlab, malayalam, South Indian scripts, onlinehandwritten character recognition

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Authors: A. Ameur Ameur, F. Chougrani, M. Halbouche

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In order to characterize the sheep's milk, we analyzed and compared, in a first stage of our work, the physical and chemical characteristics in two Algerian sheep breeds: Hamra race and race Ouled Djellal breeding at the station the experimental ITELV Ain Hadjar (Saïda Province). Analyses are performed by Ekomilk Ultra-analyzer (EON TRADING LLC, USA), they focused on the pH, density, freezing, fat, total protein, solids-the total dry extract. The results obtained for these parameters showed no significant differences between the two breeds studied. The second stage of this work was the isolation and characterization of milk proteins. For this, we used the precipitation of caseins phi [pH 4.6]. For this, we used the precipitation of caseins Phi (pH 4.6). After extraction, purification and assay, both casein and serum protein fractions were then assayed by the Bradford method and controlled by polyacrylamide gel electrophoresis (PAGE) in the different conditions (native, in the presence of urea and in the presence of SDS). The electrophoretic pattern of milk samples showed the presence similarities of four major caseins variants (αs1-, αs2-β-and k-casein) and two whey proteins (β-lactoglobulin, α-lactalbumin) of two races Hamra and Ouled Djellal. But compared to bovine milk, they have helped to highlight some peculiarities as related to serum proteins (α La β Lg) as caseins, including αs1-Cn.

Keywords: Hamra, Ouled Djellal, protein polymorphism, sheep breeds

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Authors: Priya Arora, Ashutosh Mishra

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Gene identification, towards the pursuit of mutated genes, leading to Parkinson’s disease, puts forward a challenge towards proactive cure of the disorder itself. Computational analysis is an effective technique for exploring genes in the form of protein sequences, as the theoretical and manual analysis is infeasible. The limitations and effectiveness of a particular computational method are entirely dependent on the previous data that is available for disease identification. The article presents a sequence-based classification method for the identification of genes responsible for Parkinson’s disease. During the initiation phase, the physicochemical properties of amino acids transform protein sequences into a feature vector. The second phase of the method employs Jaccard distances to select negative genes from the candidate population. The third phase involves artificial neural networks for making final predictions. The proposed approach is compared with the state of art methods on the basis of F-measure. The results confirm and estimate the efficiency of the method.

Keywords: disease gene identification, Parkinson’s disease, physicochemical properties of amino acid, protein sequences

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Authors: Peter O. Osifo, Hein W. J. P. Neomagus

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In this study, a predicted pH model was used to determine adsorption equilibrium properties of copper, lead, zinc and cadmium. Chitosan was prepared from the exoskeleton of Cape rock-lobsters, collected from the surroundings of Cape Town, South Africa. The beads were cross-linked with gluteraldehyde to restore its chemical stability in acid media. The chitosan beads were characterized; the beads water contents and pKa varied in the range of 90-96% and 4.3-6.0 respectively and the degree of crosslinking for the beads was 18%. A pH-model, which described the reversibility of the metal adsorbed onto the beads, was used to predict the equilibrium properties of copper, lead, zinc and cadmium adsorption onto the cross-linked beads. The model accounts for the effect of pH and the important model parameters; the equilibrium adsorption constant (Kads) and to a lesser extent the adsorbent adsorption capacity (qmax). The adsorption equilibrium constant for copper, lead, zinc and cadmium were found to be 2.58×10-3, 2.22×0-3, 9.55×0-3, and 4.79×0-3, respectively. The adsorbent maximum capacity was determined to be 4.2 mmol/g.

Keywords: chitosan beads, adsorption, heavy metals, waste water

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Authors: Trenten Theis, Trevor Daubert, Kennedy Kluthe, Austin Nuxoll

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Staphylococcus aureus is a gram-positive bacterium responsible for an estimated 23,000 deaths in the United States and 25,000 deaths in the European Union annually. Recurring S. aureus bacteremia is associated with biofilm-mediated infections and can occur in 5 - 20% of cases, even with the use of antibiotics. Despite these infections being caused by drug-susceptible pathogens, they are surprisingly difficult to eradicate. One potential explanation for this is the presence of persister cells—a dormant type of cell that shows a high tolerance to antibiotic treatment. Recent studies have shown a connection between low intracellular ATP and persister cell formation. Specifically, this decrease in ATP, and therefore increase in persister cell formation, is due to an interrupted tricarboxylic acid (TCA) cycle. However, S. aureus persister cells’ role in pathogenesis remains unclear. Initial studies have shown that a fumC (TCA cycle gene) knockout survives challenge from aspects of the innate immune system better than wild-type S. aureus. Specifically, challenges from two antimicrobial peptides--LL-37 and hBD-3—show a log increase in survival of the fumC::N∑ strain compared to wild type S. aureus after 18 hours. Furthermore, preliminary studies show that the fumC knockout has a log more survival within a macrophage. These data lead us to hypothesize that the fumC knockout is better suited to other aspects of the innate immune system compared to wild-type S. aureus. To further investigate the mechanism for increased survival of fumC::N∑ within a macrophage, we tested bacterial growth in the presence of reactive oxygen species (ROS), reactive nitrogen species (RNS), and a low pH. Preliminary results suggest that the fumC knockout has increased growth compared to wild-type S. aureus in the presence of all three antimicrobial factors; however, no difference was observed in any single factor alone. To investigate survival within a host, a nine-day biofilm-associated catheter infection was performed on 6–8-week-old male and female C57Bl/6 mice. Although both sexes struggled to clear the infection, female mice were trending toward more frequently clearing the HG003 wild-type infection compared to the fumC::N∑ infection. One possible reason for the inability to reduce the bacterial burden is that biofilms are largely composed of persister cells. To test this hypothesis further, flow cytometry in conjunction with a persister cell marker was used to measure persister cells within a biofilm. Cap5A (a known persister cell marker) expression was found to be increased in a maturing biofilm, with the lowest levels of expression seen in immature biofilms and the highest expression exhibited by the 48-hour biofilm. Additionally, bacterial cells in a biofilm state closely resemble persister cells and exhibit reduced membrane potential compared to cells in planktonic culture, further suggesting biofilms are largely made up of persister cells. These data may provide an explanation as to why infections caused by antibiotic-susceptible strains remain difficult to treat.

Keywords: antibiotic tolerance, Staphylococcus aureus, host-pathogen interactions, microbial pathogenesis

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Authors: Hussin K. Ragb, Vijayan K. Asari

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In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor

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Authors: Ming-Yeh Lu, Shiao-Shing Chen, Saikat Sinha Ray, Hung-Te Hsu

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The submerged anaerobic osmotic membrane bioreactor (AnOMBR) integrated with periodic microfiltration (MF) extraction for simultaneous phosphorus and clean water recovery from wastewater was evaluated. A laboratory-scale AnOMBR used cellulose triacetate (CTA) membranes with effective membrane area of 130 cm² was fully submerged into a 5 L bioreactor at 30-35 ℃. Active layer was orientated to feed stream for minimizing membrane fouling and scaling. Additionally, a peristaltic pump was used to circulate magnesium sulphate (MgSO₄) solution applied as draw solution (DS). Microfiltration membrane periodically extracted about 1 L solution when the TDS reaches to 5 g/L to recover phosphorus and simultaneously control the salt accumulation in the bioreactor. During experiment progress, the average water flux was around 1.6 LMH. The AnOMBR process showed greater than 95% removal of soluble chemical oxygen demand (sCOD), nearly 100% of total phosphorous whereas only partial of ammonia was removed. On the other hand, the average methane production of 0.22 L/g sCOD was obtained. Subsequently, the overall performance demonstrates that a novel submerged AnOMBR system is potential for simultaneous wastewater treatment and resource recovery from wastewater. Therefore, the new concept of this system can be used to replace for the conventional AnMBR in the future.

Keywords: anaerobic treatment, forward osmosis, phosphorus recovery, membrane bioreactor

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Authors: Maria da Conceição Proença

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This case study implements the evaluation of burned areas that suffered successive wildfires in Portugal mainland during the summer of 2017, killing more than 60 people. It’s intended to show that this evaluation can be done with remote sensing data free of charges in a simple laptop, with open-source software, describing the not-so-simple methodology step by step, to make it available for county workers in city halls of the areas attained, where the availability of information is essential for the immediate planning of mitigation measures, such as restoring road access, allocate funds for the recovery of human dwellings and assess further restoration of the ecological system. Wildfires also devastate forest ecosystems having a direct impact on vegetation cover and killing or driving away from the animal population. The economic interest is also attained, as the pinewood burned becomes useless for the noblest applications, so its value decreases, and resin extraction ends for several years. The tools described in this paper enable the location of the areas where took place the annihilation of natural habitats and establish a baseline for major changes in forest ecosystems recovery. Moreover, the result allows the follow up of the surface fuel loading, enabling the targeting and evaluation of restoration measures in a time basis planning.

Keywords: image processing, remote sensing, wildfires, burned areas evaluation, sentinel-2

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Authors: Abdullah Bal, Sevdenur Bal

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This paper purposes a new type of hardware application for training of cellular neural networks (CNN) using optical joint transform correlation (JTC) architecture for image feature extraction. CNNs require much more computation during the training stage compare to test process. Since optoelectronic hardware applications offer possibility of parallel high speed processing capability for 2D data processing applications, CNN training algorithm can be realized using Fourier optics technique. JTC employs lens and CCD cameras with laser beam that realize 2D matrix multiplication and summation in the light speed. Therefore, in the each iteration of training, JTC carries more computation burden inherently and the rest of mathematical computation realized digitally. The bipolar data is encoded by phase and summation of correlation operations is realized using multi-object input joint images. Overlapping properties of JTC are then utilized for summation of two cross-correlations which provide less computation possibility for training stage. Phase-only JTC does not require data rearrangement, electronic pre-calculation and strict system alignment. The proposed system can be incorporated simultaneously with various optical image processing or optical pattern recognition techniques just in the same optical system.

Keywords: CNN training, image processing, joint transform correlation, optoelectronic hardware

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Authors: Alexander Hudson, Shaogang Gong

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Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.

Keywords: transfer learning, protein distance maps, protein structure classification, neural networks

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Authors: Lav Kesharwani, Nalini Shankar, A. K. Gupta

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A serial number is a unique code assigned for identification of a single unit. Serial number are present on many objects. In an attempt to hide the identity of the numbered item, the numbers are often obliterated or removed by mechanical methods. The present work was carried out with an objective to develop less toxic, less time consuming, more result oriented chemical etching reagent for restoration of serial number on the copper metal plate. Around nine different reagents were prepared using different combination of reagent along with standard reagent and it was applied over 50 erased samples of copper metal and compared it with the standard reagent for restoration of erased marks. After experiment, it was found that the prepared Etching reagent no. 3 (10 g FeCl3 + 20 ml glacial acetic acid + 100 ml distilled H2O) showed the best result for restoration of erased serial number on the copper metal plate .The reagent was also less toxic and less time consuming as compared to standard reagent (19 g FeCl3 + 6 ml cans. HCl + 100 ml distilled H2O).

Keywords: serial number restoration, copper plate, obliteration, chemical method

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Authors: Ayad Dalloo, Sulaf Dalloo

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Electrocardiogram (ECG) recording is prone to complications, on analysis by physicians, due to noise and artifacts, thus creating ambiguity leading to possible error of diagnosis. Such drawbacks may be overcome with the advent of high resolution Methods, such as Discrete Wavelet Analysis and Digital Signal Processing (DSP) techniques. This ECG signal analysis is implemented in three stages: ECG preprocessing, features extraction and classification with the aim of realizing high resolution ECG diagnosis and improved detection of abnormal conditions in the heart. The preprocessing stage involves removing spurious artifacts (noise), due to such factors as muscle contraction, motion, respiration, etc. ECG features are extracted by applying DSP and suggested sloping method techniques. These measured features represent peak amplitude values and intervals of P, Q, R, S, R’, and T waves on ECG, and other features such as ST elevation, QRS width, heart rate, electrical axis, QR and QT intervals. The classification is preformed using these extracted features and the criteria for cardiovascular diseases. The ECG diagnostic system is successfully applied to 12-lead ECG recordings for 12 cases. The system is provided with information to enable it diagnoses 15 different diseases. Physician’s and computer’s diagnoses are compared with 90% agreement, with respect to physician diagnosis, and the time taken for diagnosis is 2 seconds. All of these operations are programmed in Matlab environment.

Keywords: ECG diagnostic system, QRS detection, ECG baseline removal, cardiovascular diseases

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Authors: T. Wresdiyati, S. Sa’diah, A. Winarto

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Diabetes mellitus (DM) is a metabolic disease that can be indicated by the high level of blood glucose. The objective of this study was to observe the antidiabetic properties of ethanolic extract of Indonesian Swietenia mahagoni Jacq. seed on the profile of pancreatic superoxide dismutase and β-cells in the alloxan- experimental diabetic rats. The Swietenia mahagoni seed was obtained from Leuwiliang-Bogor, Indonesia. Extraction of Swietenia mahagoni was done by using ethanol with maceration methods. A total of 25 male Sprague dawley rats were divided into five groups; (a) negative control group, (b) positive control group (DM), (c) DM group that was treated with Swietenia mahagoni seed extract, (d) DM group that was treated with acarbose, and (e) non-DM group that was treated with Swietenia mahagoni seed extract. The DM groups were induced by alloxan (110 mg/kgBW). The extract was orally administrated to diabetic rats 500 mg/kg/BW/day for 28 days. The extract showed hypoglycemic effect, increased body weight, increased the content of superoxide dismutase in the pancreatic tissue, and delayed the rate of β-cells damage of experimental diabetic rats. These results suggested that the ethanolic extract of Indonesian Swietenia mahagoni Jacq. seed could be proposed as a potential anti-diabetic agent.

Keywords: beta cells, diabetes, hypoglycemic, rat, Swietenia mahagoni

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Authors: Olufunke O. Ezekiel, Adenike O. Ogunshe, Omotola F. Olagunju, Arinola O. Falola

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Studies were conducted on fermentation of tamarind seed for production of food condiment. Fermentation followed the conventional traditional method of fermented locust bean (iru) production and was carried out over a period of three days (72 hours). Samples were withdrawn and analysed for proximate composition, pH, titratable acidity, tannin content, phytic acid content and trypsin inhibitor activity using standard methods. Effects of fermentation on proximate composition, anti-nutritional factors and sensory properties of the seed were evaluated. All data were analysed using ANOVA and means separated using Duncan multiple range test. Microbiological analysis to identify and characterize the microflora responsible for the fermentation of the seed was also carried out. Fermentation had significant effect on the proximate composition on the fermented seeds. As fermentation progressed, there was significant reduction in the anti-nutrient contents. Organisms isolated from the fermenting tamarind seeds were identified as non-pathogenic and common with fermented legumes.

Keywords: condiment, fermentation, legume, tamarind seed

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Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

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High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

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Authors: Ewa Brychcy, Natalia Ulbin-Figlewicz, Dominika Kulig, Żaneta Król, Andrzej Jarmoluk

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Acidic electrolyzed water (AEW) is an alternative with environmentally friendly broad spectrum microbial decontamination. It is produced by membrane electrolysis of a dilute NaCl solution in water ionizers. The aim of the study was to evaluate the effectiveness of low-concentrated AEW in reducing selected foodborne pathogens and to examine its bactericidal effect on cellular structures of Escherichia coli. E. coli and S. aureus cells were undetectable after 10 minutes of contact with electrolyzed salt solutions. Non-electrolyzed solutions did not inhibit the growth of bacteria. AE water was found to destroy the cellular structures of the E. coli. The use of more concentrated salt solutions and prolonged electrolysis time from 5 to 10 minutes resulted in a greater changes of rods shape as compared to the control and non-electrolyzed NaCl solutions. This research showed that low-concentrated acid electrolyzed water is an effective method to significantly reduce pathogenic microorganisms and indicated its potential application for decontamination of meat.

Keywords: acidic electrolyzed water, foodborne pathogens, meat decontamination, membrane electrolysis

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Authors: Yavuz Unal, Kemal Polat, H. Erdinc Kocer

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In this study, a decision support system comprising three stages has been proposed to detect the disc abnormalities of the lumbar region. In the first stage named the feature extraction, T2-weighted sagittal and axial Magnetic Resonance Images (MRI) were taken from 55 people and then 27 appearance and shape features were acquired from both sagittal and transverse images. In the second stage named the feature weighting process, k-means clustering based feature weighting (KMCBFW) proposed by Gunes et al. Finally, in the third stage named the classification process, the classifier algorithms including multi-layer perceptron (MLP- neural network), support vector machine (SVM), Naïve Bayes, and decision tree have been used to classify whether the subject has lumbar disc or not. In order to test the performance of the proposed method, the classification accuracy (%), sensitivity, specificity, precision, recall, f-measure, kappa value, and computation times have been used. The best hybrid model is the combination of k-means clustering based feature weighting and decision tree in the detecting of lumbar disc disease based on both sagittal and axial MR images.

Keywords: lumbar disc abnormality, lumbar MRI, lumbar spine, hybrid models, hybrid features, k-means clustering based feature weighting

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Authors: N. Marzban, J. K. Heydarzadeh M. Pourmohammadbagher, M. H. Hatami, A. Samia

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A nano-alumina-zirconia composite catalyst was synthesized by a simple aqueous sol-gel method using AlCl₃.6H₂O and ZrCl₄ as precursors. Thermal decomposition of the precursor and subsequent formation of γ-Al₂O₃ and t-Zr were investigated by thermal analysis. XRD analysis showed that γ-Al₂O₃ and t-ZrO₂ phases were formed at 700 °C. FT-IR analysis also indicated that the phase transition to γ-Al₂O₃ occurred in corroboration with X-ray studies. TEM analysis of the calcined powder revealed that spherical particles were in the range of 8-12 nm. The nano-alumina-zirconia composite particles were mesoporous and uniformly distributed in their crystalline phase. In order to measure the catalytic activity, esterification reaction was carried out. Biodiesel, as a renewable fuel, was formed in a continuous packed column reactor. Free fatty acid (FFA) was esterified with ethanol in a heterogeneous catalytic reactor. It was found that the synthesized γ-Al₂O₃/ZrO₂ composite had the potential to be used as a heterogeneous base catalyst for biodiesel production processes.

Keywords: nano alumina-zirconia, composite catalyst, thin film, biodiesel

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Authors: Afiqah Shafify Amran, Siti Aisyah Shamsudin, Nurul Yuziana Mohd Yusof

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Cadmium Sulphide (CdS) from group II-IV quantum dots with good optical properties was successfully synthesized by using the simple colloidal method. Capping them with ligand Polyethylinamine (PEI) alters the surface defect of CdS while, thioglycolic acid (TGA) was added to the reaction as a stabilizer. Due to their cytotoxicity, we decided to conjugate them with the protein cage nanoparticles. In this research, we used capsid of Cowpea Chlorotic Mottle Virus (CCMV) to package the CdS because they have the potential to serve in drug delivery, cell targeting and imaging. Adding Sodium Hydroxide (NaOH) changes the pH of the systems hence the isoelectric charge is adjusted. We have characterized and studied the morphology and the optical properties of CdS and CdS-CCMV by transmitted electron microscopic (TEM), UV-Vis spectroscopy, photoluminescence spectroscopy, UV lamp and Fourier transform infrared spectroscopy (FTIR), respectively. The results obtained suggest that the protein cage nanoparticles do not affect the optical properties of CdS.

Keywords: cadmium sulphide, cowpea chlorotic mottle virus, protein cage nanoparticles, quantum dots

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Authors: Pareshkumar Umedbhai Patel

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Variety of microbes were isolated from surface of fruit and vegetables to get idea about normal flora of their surface. The process of isolation of microbes involved use of sterilized cotton swabs to wipe the surface of the samples. For isolation of Bacteria, yeast and fungi microbiological media used were nutrient agar medium, GYE agar medium and MRBA agar medium respectively. The microscopical and macroscopical characteristics of all the isolates were studied. Different plants with known antimicrobial activity were selected for obtaining samples for extraction e.g. Ficus (Ficus religosa) stem, Amla (Phyllanthus emblica) fruit, Tulsi (Ocimum tenuiflorum) leaves and Lemon grass (Cymbopogon citratus) oil. Antimicrobial activity of these samples was tested initially against known bacteria followed by study against microbes isolated from surface of vegetables and fruits. During the studies carried out throughout the work, lemongrass oil and Amla extract were found superior. Lemongrass oil and Amla extract respectively inhibited growth of 65% and 42% microbes isolated from fruit and vegetable surfaces. Rest two studied plant extracts showed only 11% of inhibition against the studied isolates. The results of isolate inhibition show the antibacterial effect of lemongrass oil better than the rest of the studied plant extracts.

Keywords: herbal extracts, vegetables, fruits, antimicrobial activity

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Authors: Abdelsabour G. A. Khaled, Ahmed W. A. Abdalla And Sabry Y. M. Mahmoud

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Banana plants showing typical mosaic and yellow stripes on leaves as symptoms were collected from Assiut Governorate in Egypt. The causal agent was identified as Cucumber mosaic virus (CMV) on the basis of symptoms, transmission, serology, transmission electron microscopy and reverse transcription polymerase chain reaction (RT-PCR). Coat protein (CP) gene was amplified using gene specific primers for coat protein (CP), followed by cloning into desired cloning vector for sequencing. In this study the CMV was transmitted into propagation host either by aphid or mechanically. The transmission was confirmed through Direct Antigen Coating Enzyme Linked Immuno Sorbent Assay (DAC-ELISA). Analysis of the 120 deduced amino acid sequence of the coat protein gene revealed that the EG-A strain of CMV shared from 97.50 to 98.33% with those strains belonging to subgroup IA. The cluster analysis grouped the Egyptian isolate with strains Fny and Ri8 belonging sub-group IA. It appears that there occurs a high incidence of CMV infecting banana belonging to IA subgroup in most parts of Egypt.

Keywords: banana, CMV, transmission, CP gene, RT-PCR

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Authors: Xudong Guan, Ainong Li, Gaohuan Liu, Chong Huang, Wei Zhao

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Due to the low spatial resolution of MODIS data, the accuracy of small-area plaque extraction with a high degree of landscape fragmentation is greatly limited. To this end, the study combines Landsat data with higher spatial resolution and MODIS data with higher temporal resolution for decision-level fusion. Considering the importance of the land heterogeneity factor in the fusion process, it is superimposed with the weighting factor, which is to linearly weight the Landsat classification result and the MOIDS classification result. Three levels were used to complete the process of data fusion, that is the pixel of MODIS data, the pixel of Landsat data, and objects level that connect between these two levels. The multilevel decision fusion scheme was tested in two sites of the lower Mekong basin. We put forth a comparison test, and it was proved that the classification accuracy was improved compared with the single data source classification results in terms of the overall accuracy. The method was also compared with the two-level combination results and a weighted sum decision rule-based approach. The decision fusion scheme is extensible to other multi-resolution data decision fusion applications.

Keywords: image classification, decision fusion, multi-temporal, remote sensing

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Authors: Nawel Boucherba, Azzedine Bettache, Abdelaziz Messis, Francis Duchiron, Said Benallaoua

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The impetus for research in the field of bioseparation has been sparked by the difficulty and complexity in the downstream processing of biological products. Indeed, 50% to 90% of the production cost for a typical biological product resides in the purification strategy. There is a need for efficient and economical large scale bioseparation techniques which will achieve high purity and high recovery while maintaining the biological activity of the molecule. One such purification technique which meets these criteria involves the partitioning of biomolecules between two immiscible phases in an aqueous system (ATPS). The Production of xylanases is carried out in 500ml of a liquid medium based on birchwood xylan. In each ATPS, PEG 1000 is added to a mixture consisting of dipotassium phosphate, sodium chloride and the culture medium inoculated with the strain Jonesia denitrificans, the mixture was adjusted to different pH. The concentration of PEG 1000 was varied: 8 to 16 % and the NaCl percentages are also varied from 2 to 4% while maintaining the other parameters constant. The results showed that the best ATPS for purification of xylanases is composed of PEG 1000 at 8.33%, 13.14 % of K2HPO4, 1.62% NaCl at pH 7. We obtained a yield of 96.62 %, a partition coefficient of 86.66 and a purification factor of 2.9. The zymogram showed that the activity is mainly detected in the top phase.

Keywords: Jonesia denitrificans BN13, xylanase, aqueous two phases system, zymogram

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Authors: Luguang Qi, Chuang Xie

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In recent years, there has been an increase in the number of reports on cocrystal polymorphism and stoichiomorphism. However, the research on the factors that influence these phenomena is limited. Herein, picolinamide (PAM), nicotinamide (NAM), and isonicotinamide (INA) were selected as co-formers to form multicomponent solids with 4-chloro-3-sulfamoylbenzoic acid (CSBA). Six new cocrystal forms of CSBA were discovered, and their crystal structures were determined. It was found that PAM and NAM can only form one cocrystal with CSBA, while INA can form up to four cocrystals, including both cocrystal polymorphism and stoichiomorphism. Molecular electrostatic potential analysis and crystal structure analysis showed that the functional group position of PAM limited the diversity of cocrystal synthons, while the lattice energy limited the diversity of cocrystal synthons when NAM acted as a co-former. Only INA was not subject to these restrictions when forming cocrystals. Finally, the influence of solvents on cocrystals was illustrated by determining the ternary phase diagrams. The mechanism of two similar solvents, ethyl acetate, and acetone, controlling the crystallization of cocrystal polymorphism was analyzed by molecular simulations.

Keywords: cocrystal polymorphism, cocrystal stoichiomorphism, phase diagram, molecular simulation

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Authors: Elham Rezaee, Sayyed Abbas Tabatabai

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Dual inhibition of COX-2 and sEH enzymes represents one of the distinct pharmaceutical approaches for the treatment of inflammation, pain, cancers, and other diseases. The discovery of these inhibitors for treatment is a great deal of attention because of some advantages such as increased efficacy, a promising safety profile, ease of formulation, and better target engagement. In this research, based on the structure-activity relationship of COX-2 and sEH inhibitors, some amide derivatives with oxadiazole and dihydropyrimidinone rings against sEH and COX-2 enzymes were developed. The designed compounds showed high affinity to the active site of both enzymes in docking studies and were synthesized in good yield and characterized by IR, Mass, 1HNMR, and 13CNMR. All of the novel compounds exhibited considerable in-vitro sEH and COX-2 inhibitory activities in comparison with 12-(3-Adamantan-1-yl-ureido)- dodecanoic acid and celecoxib (a potent urea-based sEH inhibitor and selective nonsteroidal anti-inflammatory drug, respectively). Ethyl 6-methyl-4-(4-(4-(methylsulfonyl)benzamido)phenyl)-2-oxo-1,2,3,4-tetrahydropyrimidine-5-carboxylate was found to be the most selective COX-2 inhibitor (COX-2/COX-1 ratio: 683) with IC50 value of 2.1 nM targeting sEH enzyme.

Keywords: COX-2, dual inhibitors, sEH, synthesis

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Authors: Patricia O. Carvalho, Marcia C. F. Messias, Laura Credidio, Carlos A. R. Martinez

Abstract:

Lipidomic strategy can provide important information regarding cancer pathogenesis mechanisms and could reveal new biomarkers to enable early diagnosis of rectal adenocarcinoma (RAC). This study set out to evaluate lipoperoxidation biomarkers, and lipidomic signature by gas chromatography (GC) and electrospray ionization-qToF-mass spectrometry (ESI-qToF-MS) combined with multivariate data analysis in plasma from 23 RAC patients (early- or advanced-stages cancer) and 18 healthy controls. The most abundant ions identified in the RAC patients were those of phosphatidylcholine (PC) and phosphatidylethanolamine (PE) while those of lisophosphatidylcholine (LPC), identified as LPC (16:1), LPC (18:1) and LPC (18:2), were down-regulated. LPC plasmalogen containing palmitoleic acid (LPC (P-16:1)), with highest VIP score, showed a low tendency in the cancer patients. Malondialdehyde plasma levels were higher in patients with advanced cancer (III/IV stages) than in the early stages groups and the healthy group (p<0.05). No differences in F2-isoprostane levels were observed between these groups. This study shows that the reduction in plasma levels of LPC plasmalogens associated to an increase in MDA levels may indicate increased oxidative stress in these patients and identify the metabolite LPC (P-16:1) as new biomarkers for RAC.

Keywords: biomarkers, lipidomic, plasmalogen, rectal adenocarcinoma

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Authors: Saha Saradindu, Das Payel, Somdeb BoseDasgupta

Abstract:

Tuberculosis caused by Mycobacteria tuberculosis is a dreadful disease and more so with the advent of extreme and total drug-resistant species. Mycobacterial pathogenesis is an ever-changing paradigm from phagosome maturation block to phagosomal escape into macrophage cytosol and finally acid tolerance and survival inside the lysosome. Mycobacteria are adept at subverting the host immune response by highjacking host cell signaling and secreting virulence factors. One such virulence factor is a ser/thr kinase; Protein kinase G (PknG), which is known to prevent phagosome maturation. The host substrates of PknG, allowing successful pathogenesis still remain an enigma. Hence we carried out a comparative phosphoproteomic screen and identified a number of substrates phosphorylated by PknG. We characterized some of these substrates in vivo and in vitro and observed that PknG mediated phosphorylation of these substrates leads to reduced TNFa production as well as decreased response to TNFa induced macrophage necroptosis, thus enabling mycobacterial survival and proliferation.

Keywords: mycobacteria, Protein kinase G, phosphoproteomics, necroptosis

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Authors: Yuling Xu, Haibo Wang, Dong Xie

Abstract:

A photopolymerizable dimethacrylamide was synthesized and copolymerized with the selected (meth)acrylates. The polymerization rate, degree of conversion, gel time, and compressive strength of the formed neat resins were investigated. The results show that in situ photo-polymerization of the synthesized dimethacrylamide with comonomers having an electron-withdrawing and/or acrylate group dramatically increased the polymerization rate, degree of conversion, and compressive strength. On the other hand, an electron-donating group on either carbon-carbon double bond or the ester linkage slowed down the polymerization. In contrast, the triethylene glycol dimethacrylate-based system did not show a clear pattern. Both strong hydrogen-bonding between (meth)acrylamide and organic acid groups may be responsible for higher compressive strengths. Within the limitation of this study, the photo-polymerization of dimethacrylamide can be greatly accelerated by copolymerization with monomers having electron-withdrawing and/or acrylate groups. The monomers with methacrylate group can significantly reduce the polymerization rate and degree of conversion.

Keywords: photopolymerization, dimethacrylamide, the degree of conversion, compressive strength

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

Abstract:

Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

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