Search results for: microbial detection

Authors: Fatih Tarlak

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Predictive microbiology can be considered as an important field in food microbiology in which it uses predictive models to describe the microbial growth in different food products. Predictive models estimate the growth of microorganisms quickly, efficiently, and in a cost-effective way as compared to traditional methods of enumeration, which are long-lasting, expensive, and time-consuming. The mathematical models used in predictive microbiology are mainly categorised as primary and secondary models. The primary models are the mathematical equations that define the growth data as a function of time under a constant environmental condition. The secondary models describe the effects of environmental factors, such as temperature, pH, and water activity (aw) on the parameters of the primary models, including the maximum specific growth rate and lag phase duration, which are the most critical growth kinetic parameters. The combination of primary and secondary models provides valuable information to set limits for the quantitative detection of the microbial spoilage and assess product shelf-life.

Keywords: shelf-life, growth model, predictive microbiology, simulation

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Authors: Abu Yousuf, Maksudur Rahman Khan, Ahasanul Karim, Amirul Islam, Minhaj Uddin Monir, Sharmin Sultana, Domenico Pirozzi

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Traditional biodiesel feedstock like edible oils or plant oils, animal fats and cooking waste oil have been replaced by microbial oil in recent research of biodiesel synthesis. The well-known community of microbial oil producers includes microalgae, oleaginous yeast and seaweeds. Conventional transesterification of microbial oil to produce biodiesel is lethargic, energy consuming, cost-ineffective and environmentally unhealthy. This process follows several steps such as microbial biomass drying, cell disruption, oil extraction, solvent recovery, oil separation and transesterification. Therefore, direct transesterification of biodiesel synthesis has been studying for last few years. It combines all the steps in a single reactor and it eliminates the steps of biomass drying, oil extraction and separation from solvent. Apparently, it seems to be cost-effective and faster process but number of difficulties need to be solved to make it large scale applicable. The main challenges are microbial cell disruption in bulk volume and make faster the esterification reaction, because water contents of the medium sluggish the reaction rate. Several methods have been proposed but none of them is up to the level to implement in large scale. It is still a great challenge to extract maximum lipid from microbial cells (yeast, fungi, algae) investing minimum energy. Electroporation technique results a significant increase in cell conductivity and permeability caused due to the application of an external electric field. Electroporation is required to alter the size and structure of the cells to increase their porosity as well as to disrupt the microbial cell walls within few seconds to leak out the intracellular lipid to the solution. Therefore, incorporation of electroporation techniques contributed in direct transesterification of microbial lipids by increasing the efficiency of biodiesel production rate.

Keywords: biodiesel, electroporation, microbial lipids, transesterification

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Authors: Yousef Farhaoui

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An IDS is a tool which is used to improve the level of security. We present in this paper different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection) for securing web servers and applications by the Intrusion Detection System (IDS).

Keywords: intrusion detection, architectures, characteristic, tools, security, web server

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Authors: Priyanka Dargode, Suhas Gore, Manju Sharma, Arvind Lali

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Anaerobic digestion has been widely used for production of methane from different biowastes. However, the complexity of microbial communities involved in the process is poorly understood. The performance of biogas production process concerning the process productivity is closely coupled to its microbial community structure and syntrophic interactions amongst the community members. The present study aims at understanding taxonomic variations occurring in any starter inoculum when acclimatised to different lignocellulosic biomass (LBM) feedstocks relating to time of digestion. The work underlines use of high throughput Next Generation Sequencing (NGS) for validating the changes in taxonomic patterns of microbial communities. Biomethane Potential (BMP) batches were set up with different pretreated and non-pretreated LBM residues using the same microbial consortium and samples were withdrawn for studying the changes in microbial community in terms of its structure and predominance with respect to changes in metabolic profile of the process. DNA of samples withdrawn at different time intervals with reference to performance changes of the digestion process, was extracted followed by its 16S rRNA amplicon sequencing analysis using Illumina Platform. Biomethane potential and substrate consumption was monitored using Gas Chromatography(GC) and reduction in COD (Chemical Oxygen Demand) respectively. Taxonomic analysis by QIIME server data revealed that microbial community structure changes with different substrates as well as at different time intervals. It was observed that biomethane potential of each substrate was relatively similar but, the time required for substrate utilization and its conversion to biomethane was different for different substrates. This could be attributed to the nature of substrate and consequently the discrepancy between the dominance of microbial communities with regards to different substrate and at different phases of anaerobic digestion process. Knowledge of microbial communities involved would allow a rational substrate specific consortium design which will help to reduce consortium adaptation period and enhance the substrate utilisation resulting in improved efficacy of biogas process.

Keywords: amplicon sequencing, biomethane potential, community predominance, taxonomic analysis

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Authors: A. Elain, M. Le Fellic, A. Le Pemp, N. Hachet

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Iodinated Compounds (IC) are widely detected contaminants in most aquatic environments including sewage treatment plant, surface water, ground water and even drinking water, up to the µg.L-1 range. As IC contribute in the adsorbable organic halides (AOX) level, their removal or dehalogenation is expected. We report here on the biodegradability of a mixture of IC from an industrial effluent using a microbial consortium adapted to grow on IC as well as the native microorganisms. Both aerobic and anaerobic treatments were studied during batch experiments in 500-mL flasks. The degree of mineralization and recovery of iodide were monitored by HPLC-UV, TOC analysis and potentiometric titration. Providing ethanol as an electron acceptor was found to stimulate anaerobic reductive deiodination of IC while sodium chloride even at high concentration (22 g.l-1) had no influence on the degradation rates nor on the microbial viability. Phylogenetic analysis of 16S RNA gene sequence (MicroSeq®) was applied to provide a better understanding of the degradative microbial community.

Keywords: iodinated compounds, biodegradability, deiodination, electron-accepting conditions, microbial consortium

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Authors: Ji-Hoon Hong, Dong-Hee Kim, Nam-Uk Kim, Tai-Myoung Chung

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Smartphone users are increasing rapidly. Accordingly, many companies are running BYOD (Bring Your Own Device: Policies to bring private-smartphones to the company) policy to increase work efficiency. However, smartphones are always under the threat of malware, thus the company network that is connected smartphone is exposed to serious risks. Most smartphone malware detection techniques are to perform an independent detection (perform the detection of a single target application). In this paper, we analyzed a variety of intrusion detection techniques. Based on the results of analysis propose an agent using the network IDS.

Keywords: android malware detection, software-defined network, interaction environment, android malware detection, software-defined network, interaction environment

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Authors: Medjram Sofiane, Babahenini Mohamed Chaouki, Mohamed Benali Yamina

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Skin detection is an important task for computer vision systems. A good method for skin detection means a good and successful result of the system. The colour is a good descriptor that allows us to detect skin colour in the images, but because of lightings effects and objects that have a similar colour skin, skin detection becomes difficult. In this paper, we proposed a method using the YCbCr colour space for skin detection and lighting effects elimination, then we use the information of texture to eliminate the false regions detected by the YCbCr colour skin model.

Keywords: skin detection, YCbCr, GLCM, texture, human skin

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Authors: Sajida Rasheed, Imran Hashmi, Luiza Campos, Qizhi Zhou, Kim Keu

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A quadratic model (p ˂ 0.0001) was developed by using central composite design of 50 experimental runs (42 non-center + 8 center points) to assess efficiency of background chlorine residuals in combating accidental microbial episode in a prototype distribution network (DN) (rig). A known amount of background chlorine residuals were maintained in DN and a required number of bacteria, Escherichia coli K-12 strain were introduced by an injection port in the pipe loop system. Samples were taken at various time intervals at different pipe lengths. Spread plate count was performed to count bacterial number. The model developed was significant. With microbial concentration and time (p ˂ 0.0001), pipe length (p ˂ 0.022), background chlorine residuals (p ˂ 0.07) and time^2 (p ˂ 0.09) as significant factors. The ramp function of variables shows that at the microbial count of 10^6, at 0.76 L/min, and pipe length of 133 meters, a background residual chlorine 0.16 mg/L was enough for complete inactivation of microbial episode in approximately 18 minutes.

Keywords: central composite design (CCD), distribution network, Escherichia coli, residual chlorine

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Authors: Wisdom Robert Duruji

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Local farmers and fruit processors in developing countries of West Africa use different ripening agents to accelerate the ripening process of plantain and banana. This study reports on the influence of different ripening agents on the shelf-life and microbial load of organic and inorganic plantain (Musa paradisiaca) and banana (Musa sapientum) during ripening process and the health implication for food security in Nigeria. The experiment consisted of four treatments, namely: Calcium carbide, Irvingia gabonensis fruits, Newbouldia laevis leaves and a control, where no ripening agent was applied to the fingers of plantain and banana. The unripe and ripened plantain and banana were subjected to microbial analysis by isolating their micro flora (Bacteria, Yeast and Mould) using pour plate method. Microbes present in the samples were enumerated, characterized and classified to genera and species. The result indicated that the microbial load of inorganic plantain from (Urban day) open market in Ile-Ife increased from 8.00 for unripe to 12.11 cfu/g for ripened; and the microbial load of organic plantain from Obafemi Awolowo University Teaching and Research Farm (OAUTRF) increased from 6.00 for unripe to 11.60 cfu/g for ripened. Also, the microbial load of inorganic banana from (Urban day) open market in Ile-Ife increased from 8.00 for unripe to 11.50 cfu/g for ripened; while the microbial load of organic banana from OAUTRF increased from 6.50 for unripe to 9.40 cfu/g for ripened. The microbial effects of the ripening agents increased from 10.00 for control to 16.00 cfu/g for treated (ripened) organic and inorganic plantain; while that of organic and inorganic banana increased from 7.50 for control to 14.50 cfu/g for ripened. Visual observation for the presence of fungal colonies and deterioration rates were monitored till seven days after the plantain and banana fingers have fully ripened. Inorganic plantain and banana from (Urban day) open market in Ile-Ife are more contaminated than organic plantain and banana fingers from OAUTRF. The ripening accelerators reduced the shelf life, increased senescence, and microbial load of plantain and banana. This study concluded that organic Agriculture is better and microbial friendlier than inorganic farming.

Keywords: organic agriculture, food security, Musaceae, calcium carbide, Irvingia gabonensis, Newbouldia laevis

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Authors: Zhang Xiaodong, Tang Zixin, Liu Xin

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In order to avoid self-collision of space manipulators during operation process, a real-time detection method is proposed in this paper. The manipulator is fitted into a cylinder enveloping surface, and then the detection algorithm of collision between cylinders is analyzed. The collision model of space manipulator self-links can be detected by using this algorithm in real-time detection during the operation process. To ensure security of the operation, a safety threshold is designed. The simulation and experiment results verify the effectiveness of the proposed algorithm for a 7-DOF space manipulator.

Keywords: space manipulator, collision detection, self-collision, the real-time collision detection

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Authors: Norzalina Othman, Nurul Na’imy Wan, Azliza Mohd Rusli, Wan Noor Syahirah Meor Idris

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Iris detection is a process where the position of the eyes is extracted from the face images. It is a current method used for many applications such as for security purpose and drowsiness detection. This paper proposes the use of eyes detection in controlling side mirror of motor vehicles. The eyes detection method aims to make driver easy to adjust the side mirrors automatically. The system will determine the midpoint coordinate of eyes detection on RGB (color) image and the input signal from y-coordinate will send it to controller in order to rotate the angle of side mirror on vehicle. The eye position was cropped and the coordinate of midpoint was successfully detected from the circle of iris detection using Viola Jones detection and circular Hough transform methods on RGB image. The coordinate of midpoint from the experiment are tested using controller to determine the angle of rotation on the side mirrors.

Keywords: iris detection, midpoint coordinates, RGB images, side mirror

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Authors: B. Samuel Raj, Solomon R. D. Jebakumar

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Microbial fuel cells (MFCs) are an emerging and promising method for achieving sustainable energy since they can remove contaminated organic matter and simultaneously generate electricity. Our approach was driven in three different ways like Bacterial fuel cell, Soil Microbial fuel cell (Soil MFC) and Plant Microbial fuel cell (Plant MFC). Bacterial MFC: Sulphate reducing bacteria (SRB) were isolated and identified as the efficient electricigens which is able to produce ±2.5V (689mW/m2) and it has sustainable activity for 120 days. Experimental data with different MFC revealed that high electricity production harvested continuously for 90 days 1.45V (381mW/m2), 1.98V (456mW/m2) respectively. Biofilm formation was confirmed on the surface of the anode by high content screening (HCS) and scanning electron Microscopic analysis (SEM). Soil MFC: Soil MFC was constructed with low cost and standard Mudwatt soil MFC was purchased from keegotech (USA). Vermicompost soil (V1) produce high energy (± 3.5V for ± 400 days) compared to Agricultural soil (A1) (± 2V for ± 150 days). Biofilm formation was confirmed by HCS and SEM analysis. This finding provides a method for extracting energy from organic matter, but also suggests a strategy for promoting the bioremediation of organic contaminants in subsurface environments. Our Soil MFC were able to run successfully a 3.5V fan and three LED continuously for 150 days. Plant MFC: Amaranthus candatus (P1) and Triticum aestivium (P2) were used in Plant MFC to confirm the electricity production from plant associated microbes, four uniform size of Plant MFC were constructed and checked for energy production. P2 produce high energy (± 3.2V for 40 days) with harvesting interval of two times and P1 produces moderate energy without harvesting interval (±1.5V for 24 days). P2 is able run 3.5V fan continuously for 10days whereas P1 needs optimization of growth conditions to produce high energy.

Keywords: microbial fuel cell, biofilm, soil microbial fuel cell, plant microbial fuel cell

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Authors: Sunil Dehipawala, Gayathrie Amarasuriya, N. Gadura, G. Tremberger Jr, D.Lieberman, Harry Gafney, Todd Holden, T. Cheung

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The iron environment in Fe-doped Vycor Anode was investigated with EXAFS using Brookhaven Synchrotron Light Source. The iron-reducing Shewanella oneidensis culture was grown in a microbial fuel cell under anaerobic respiration. The Fe bond length was found to decrease and correlate with the amount of biofilm growth on the Fe-doped Vycor Anode. The data suggests that Fe-doped Vycor Anode would be a good substrate to study the Shewanella oneidensis nanowire structure using EXAFS.

Keywords: EXAFS, fourier transform, Shewanella oneidensis, microbial fuel cell

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Authors: Leping Chen, Daoxiang An, Xiaotao Huang

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Automatic vehicle detection using synthetic aperture radar (SAR) image has been widely researched, as well as using optical remote sensing images. However, most researches treat the detection as an independent problem, failing to make full use of SAR data information. In circular SAR (CSAR), the two long borders of vehicle will shrink if the imaging surface is set higher than the reference one. Based on above variance, an automatic vehicle detection using CSAR image is proposed to enhance detection ability under complex environment, such as vehicles’ closely packing, which confuses the detector. The detection method uses the multiple images generated by different height plane to obtain an energy-concentrated image for detecting and then uses the maximally stable extremal regions method (MSER) to detect vehicles. A result of vehicles’ detection is given to verify the effectiveness and correctness of proposed method.

Keywords: circular SAR, vehicle detection, automatic, imaging

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Authors: Bouchemha Amel, Chachoui Takieddine, H. Maalem

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Automatic detection of targets in a modern communication system RADAR is based primarily on the concept of adaptive CFAR detector. To have an effective detection, we must minimize the influence of disturbances due to the clutter. The detection algorithm adapts the CFAR detection threshold which is proportional to the average power of the clutter, maintaining a constant probability of false alarm. In this article, we analyze the performance of two variants of adaptive algorithms CA-CFAR and OS-CFAR and we compare the thresholds of these detectors in the marine environment (no-Gaussian) with a Weibull distribution.

Keywords: CFAR, threshold, clutter, distribution, Weibull, detection

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Authors: Rashid Mahmood, Muhammad Junaid Sarwar

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Mobile ad hoc networks (MANETs) use has been well-known from the last few years in the many applications, like mission critical applications. In the (MANETS) prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in (MANETs). The authentication and encryption is considered the first solution of the MANETs problem where as now these are not sufficient as MANET use is increasing. In this paper we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in MANET and aim to comparing in some important fields.

Keywords: MANET, IDS, intrusions, signature, detection, prevention

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Authors: Rajesh P.P., Md. Tabish Noori, Makarand M. Ghangrekar

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Methanogenic substrate loss is reported to be a major bottleneck in microbial fuel cell which significantly reduces the power production capacity and coulombic efficiency (CE) of microbial fuel cell (MFC). Nitroethane is found to be a potent inhibitor of hydrogenotrophic methanogens in rumen fermentation process. Influence of nitroethane pre-treated sewage sludge inoculum on suppressing the methanogenic activity and enhancing the electrogenesis in MFC was evaluated. MFC inoculated with nitroethane pre-treated anodic inoculum demonstrated a maximum operating voltage of 541 mV, with coulombic efficiency and sustainable volumetric power density of 39.85 % and 14.63 W/m3 respectively. Linear sweep voltammetry indicated a higher electron discharge on the anode surface due to enhancement of electrogenic activity while suppressing methanogenic activity. A 63 % reduction in specific methanogenic activity was observed in anaerobic sludge pre-treated with nitroethane; emphasizing significance of this pretreatment for suppressing methanogenesis and its utility for enhancing electricity generation in MFC.

Keywords: coulombic efficiency, methanogenesis inhibition, microbial fuel cell, nitroethane

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Authors: Shreya Borthakur, Adhar Sharma

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The North-east states of India are well known for their age-old practice of preparing alcoholic beer from rice and millet. They do so in a traditional way by sprinkling starter cake (inoculum) on cooked rice or millet after which the fermentation starts and eventually, forms the beer. This starter cake has a rich composition of different microbes and medicinal herbs along with the powdered rice dough or maize dough with rice bran. The starter cake microbial composition has an important role in determining the microbial succession and metabolic secretions as the fermentation proceeds from the early to its late stage, thus, giving the beer a unique aroma, taste, and other sensory properties of traditionally prepared beer. Here, We have worked on identifying and characterizing the microbial community in the starter cakes prepared by the Monpa and Galo tribes of Arunachal Pradesh. A total of 18 microbial strains have been isolated from the starter cake of Monpa tribe, while 10 microbial isolates in that of Galo tribe. A metagenomic approach was applied to enumerate the cultural and non-cultural microbes present in the starter cakes prepared by the Monpa and Galo tribes of Arunachal Pradesh. The findings of the mini-project lays foundation to understand the role of microbes present in the starter cake in the beer’s fermentation process and will aide in future research on re-formulating the starter cakes to prevent the early spoilage of the ready to consume beer as the traditional rice beer has a short shelf-life. The paper concludes with the way forward being controlled CRISPR-Cas9.

Keywords: fermentation, traditional beer, microbial succession, preservation, CRISPR-Cas, food microbiology

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Authors: Jayesh M. Sonawane, Prakash C. Ghosh

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Landfill leachate emerges as a promising feedstock for microbial fuel cells (MFCs). In the present investigation, direct air-breathing cathode-based MFCs are fabricated to investigate the potential of landfill leachate. Three MFCs that have different cathode areas are fabricated and investigated for 17 days under open circuit conditions. The maximum open circuit voltage (OCV) is observed to be as high as 1.29 V. The maximum cathode area specific power density achieved in the reactor is 1513 mW m^-2. Further studies are under progress to understand the origin of high OCV obtained from landfill leachate-based MFCs.

Keywords: microbial fuel cells, landfill leachate, air-breathing cathode, performance study

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Authors: Sulaiman Al amro, Ali Alkhalifah

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The growing number of computer viruses and the detection of zero day malware have been the concern for security researchers for a large period of time. Existing antivirus products (AVs) rely on detecting virus signatures which do not provide a full solution to the problems associated with these viruses. The use of logic formulae to model the behaviour of viruses is one of the most encouraging recent developments in virus research, which provides alternatives to classic virus detection methods. In this paper, we proposed a comparative study about different virus detection techniques. This paper provides the advantages and drawbacks of different detection techniques. Different techniques will be used in this paper to provide a discussion about what technique is more effective to detect computer viruses.

Keywords: computer viruses, virus detection, signature-based, behaviour-based, heuristic-based

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Authors: Zeina Bourhane, Anders Lanzen, Christine Cagnon, Olfa Ben Said, Cristiana Cravo-Laureau, Robert Duran

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The anthropogenic pressure in coastal areas increases dramatically with the exploitation of environmental resources. Biomonitoring coastal areas are crucial to determine the impact of pollutants on bacterial communities in soils and sediments since they provide important ecosystem services. However, relevant biomonitoring tools allowing fast determination of the ecological status are yet to be defined. Microbial ecology approaches provide useful information for developing such microbial monitoring tools reporting on the effect of environmental stressors. Chemical and microbial molecular approaches were combined in order to determine microbial bioindicators for assessing the ecological status of soil and river ecosystems around the Ichkeul Lake (Tunisia), an area highly impacted by human activities. Samples were collected along soil/river/lake continuums in three stations around the Ichkeul Lake influenced by different human activities at two seasons (summer and winter). Contaminant pressure indexes (PI), including PAHs (Polycyclic aromatic hydrocarbons), alkanes, and OCPs (Organochlorine pesticides) contents, showed significant differences in the contamination level between the stations with seasonal variation. Bacterial communities were characterized by 16S ribosomal RNAs (rRNA) gene metabarcoding. Although microgAMBI indexes, determined from the sequencing data, were in accordance with contaminant contents, they were not sufficient to fully explain the PI. Therefore, further microbial indicators are still to be defined. The comparison of bacterial communities revealed the specific microbial assemblage for soil, river, and lake sediments, which were significantly correlated with contaminant contents and PI. Such observation offers the possibility to define a relevant set of bioindicators for reporting the effects of human activities on the microbial community structure. Such bioindicators might constitute useful monitoring tools for the management of microbial communities in coastal areas.

Keywords: bacterial communities, biomonitoring, contamination, human impacts, microbial bioindicators

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Authors: Kaewmart Pongakkasira

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This study investigated how different levels of pixelation affect face detection in natural scenes. Eye movements and reaction times, while observers searched for faces in natural scenes rendered in different ranges of pixels, were recorded. Detection performance for coarse visual detail at lower pixel size (3 x 3) was better than with very blurred detail carried by higher pixel size (9 x 9). The result is consistent with the notion that face detection relies on gross detail information of face-shape template, containing crude shape structure and features. In contrast, detection was impaired when face shape and features are obscured. However, it was considered that the degradation of scenic information might also contribute to the effect. In the next experiment, a more direct measurement of the effect of pixelation on face detection, only the embedded face photographs, but not the scene background, will be filtered.

Keywords: eye movements, face detection, face-shape information, pixelation

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Authors: M. Ranjeeth, S. Anuradha

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Spectrum sensing is the main feature of cognitive radio technology. Spectrum sensing gives an idea of detecting the presence of the primary users in a licensed spectrum. In this paper we compare the theoretical results of detection probability of different fading environments like Rayleigh, Rician, Nakagami-m fading channels with the simulation results using energy detection based spectrum sensing. The numerical results are plotted as P_f Vs P_d for different SNR values, fading parameters. It is observed that Nakagami fading channel performance is better than other fading channels by using energy detection in spectrum sensing. A MATLAB simulation test bench has been implemented to know the performance of energy detection in different fading channel environment.

Keywords: spectrum sensing, energy detection, fading channels, probability of detection, probability of false alarm

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Authors: Flackson Tshuma, James Bennett, Pieter Andreas Swanepoel, Johan Labuschagne, Stephan van der Westhuizen, Francis Rayns

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Amongst other things, tillage and synthetic agrochemicals can be effective methods of seedbed preparation and pest control. Nonetheless, frequent and intensive tillage and excessive application of synthetic agrochemicals, such as herbicides and insecticides, can reduce soil microbial enzyme activity. A decline in soil microbial enzyme activity can negatively affect nutrient cycling and crop productivity. In this study, the effects of four tillage treatments; continuous mouldboard plough; shallow tine-tillage to a depth of about 75 mm; no-tillage; and tillage rotation (involving shallow tine-tillage once every four years in rotation with three years of no-tillage), and two rates of synthetic agrochemicals (standard: with regular application of synthetic agrochemicals; and reduced: fewer synthetic agrochemicals in combination with bio-chemicals/ or bio-stimulants) on soil microbial enzyme activity were investigated between 2018 and 2020 in a typical Mediterranean climate zone in South Africa. Four different bio-stimulants applied contained: Trichoderma asperellum, fulvic acid, silicic acid, and Nereocystis luetkeana extracts, respectively. The study was laid out as a complete randomised block design with four replicated blocks. Each block had 14 plots, and each plot measured 50 m x 6 m. The study aimed to assess the combined impact of tillage practices and reduced rates of synthetic agrochemical application on soil microbial enzyme activity in a dryland cropping system. It was hypothesised that the application of bio-stimulants in combination with minimum soil disturbance will lead to a greater increase in microbial enzyme activity than the effect of applying either in isolation. Six soil cores were randomly and aseptically collected from each plot for microbial enzyme activity analysis from the 0-150 mm layer of a field trial under a dryland crop rotation system in the Swartland region. The activities of four microbial enzymes, β-glucosidase, acid phosphatase, alkaline phosphatase and urease, were assessed. The enzymes are essential for the cycling of glucose, phosphorus, and nitrogen, respectively. Microbial enzyme activity generally increased with a reduction of both tillage intensity and synthetic agrochemical application. The use of the mouldboard plough led to the least (P<0.05) microbial enzyme activity relative to the reduced tillage treatments, whereas the system with bio-stimulants (reduced synthetic agrochemicals) led to the highest (P<0.05) microbial enzyme activity relative to the standard systems. The application of bio-stimulants in combination with reduced tillage, particularly no-tillage, could be beneficial for enzyme activity in a dryland farming system.

Keywords: bio-stimulants, soil microbial enzymes, synthetic agrochemicals, tillage

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Authors: Hana Barak, Alex Sivan, Ariel Kushmaro

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Microorganisms are the most diverse and abundant life forms on Earth and account for a large portion of the Earth’s biomass and biodiversity. To date though, our knowledge regarding microbial life is lacking, as it is based mainly on information from cultivated organisms. Indeed, microbiologists have borrowed from astrophysics and termed the ‘uncultured microbial majority’ as ‘microbial dark matter’. The realization of how diverse and unexplored microorganisms are, actually stems from recent advances in molecular biology, and in particular from novel methods for sequencing microbial small subunit ribosomal RNA genes directly from environmental samples termed next-generation sequencing (NGS). This has led us to use NGS that generates several gigabases of sequencing data in a single experimental run, to identify and classify environmental samples of microorganisms. In metagenomics sequencing analysis (both 16S and shotgun), sequences are compared to reference databases that contain only small part of the existing microorganisms and therefore their taxonomy assignment may reveal groups of unknown microorganisms or origins. These unknowns, or the ‘microbial sequences dark matter’, are usually ignored in spite of their great importance. The goal of this work was to develop an improved bioinformatics method that enables more complete analyses of the microbial communities in numerous environments. Therefore, NGS was used to identify previously unknown microorganisms from three different environments (industrials wastewater, Negev Desert’s rocks and water wells at the Arava valley). 16S rRNA gene metagenome analysis of the microorganisms from those three environments produce about ~4 million reads for 75 samples. Between 0.1-12% of the sequences in each sample were tagged as ‘Unassigned’. Employing relatively simple methodology for resequencing of original gDNA samples through Sanger or MiSeq Illumina with specific primers, this study demonstrates that the mysterious ‘Unassigned’ group apparently contains sequences of candidate phyla. Those unknown sequences can be located on a phylogenetic tree and thus provide a better understanding of the ‘sequences dark matter’ and its role in the research of microbial communities and diversity. Studying this ‘dark matter’ will extend the existing databases and could reveal the hidden potential of the ‘microbial dark matter’.

Keywords: bacteria, bioinformatics, dark matter, Next Generation Sequencing, unknown

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Authors: Anza-Vhudziki Mboyi, Ilunga Kamika, Maggy Momba

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The aim of this study was to ascertain the survival limit and capability of commonly found wastewater protozoan (Aspidisca sp, Trachelophyllum sp, and Peranema sp) and bacterial (Bacillus licheniformis, Brevibacillus laterosporus, and Pseudomonas putida) species to remove COD while exposed to commercial nanomaterials under varying pH conditions. The experimental study was carried out in modified mixed liquor media adjusted to various pH levels (pH 2, 7 and 10), and a comparative study was performed to determine the difference between the cytotoxicity effects of commercial zinc oxide (nZnO) and silver (nAg) nanomaterials (NMs) on the target wastewater microbial communities using standard methods. The selected microbial communities were exposed to lethal concentrations ranging from 0.015 g/L to 40 g/L for nZnO and from 0.015 g/L to 2 g/L for nAg for a period of 5 days of incubation at 30°C (100 r/min). Compared with the absence of NMs in wastewater mixed liquor, the relevant environmental concentration ranging between 10 µg/L and 100 µg/L, for both nZnO and nAg caused no adverse effects, but the presence of 20 g of nZnO/L and 0.65 g of nAg/L significantly inhibited microbial growth. Statistical evidence showed that nAg was significantly more toxic compared to nZnO, but there was an insignificant difference in toxicity between microbial communities and pH variations. A significant decrease in the removal of COD by microbial populations was observed in the presence of NMs with a moderate correlation of r = 0.3 to r = 0.7 at all pH levels. It was evident that there was a physical interaction between commercial NMs and target wastewater microbial communities; although not quantitatively assessed, cell morphology and cell death were observed. Such phenomena suggest the high resilience of the microbial community, but it is the accumulation of NMs that will have adverse effects on the performance in terms of COD removal.

Keywords: bacteria, biological treatment, chemical oxygen demand (COD) and nanomaterials, consortium, pH, protozoan

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Authors: John Onyima, Ikechukwu Ezepue

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Virtualization and cloud computing are among the fast-growing computing innovations in recent times. Organisations all over the world are moving their computing services towards the cloud this is because of its rapid transformation of the organization’s infrastructure and improvement of efficient resource utilization and cost reduction. However, this technology brings new security threats and challenges about safety, reliability and data confidentiality. Evidently, no single security technique can guarantee security or protection against malicious attacks on a cloud computing network hence an integrated model of intrusion detection and prevention system has been proposed. Anomaly-based and signature-based detection techniques will be integrated to enable the network and its host defend themselves with some level of intelligence. The anomaly-base detection was implemented using the local deviation factor graph-based (LDFGB) algorithm while the signature-based detection was implemented using the snort algorithm. Results from this collaborative intrusion detection and prevention techniques show robust and efficient security architecture for cloud computing networks.

Keywords: anomaly-based detection, cloud computing, intrusion detection, intrusion prevention, signature-based detection

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Authors: Doaa Wael, Naswa Abdelbaky

Abstract:

Malware is malicious software that is built to cause destructive actions and damage information systems and networks. Malware infections increase rapidly, and types of malware have become more sophisticated, which makes the malware detection process more difficult. On the other side, the Internet of Things IoT technology is vulnerable to malware attacks. These IoT devices are always connected to the internet and lack security. This makes them easy for hackers to access. These malware attacks are becoming the go-to attack for hackers. Thus, in order to deal with this challenge, new malware detection techniques are needed. Currently, building a blockchain solution that allows IoT devices to download any file from the internet and to verify/approve whether it is malicious or not is the need of the hour. In recent years, blockchain technology has stood as a solution to everything due to its features like decentralization, persistence, and anonymity. Moreover, using blockchain technology overcomes some difficulties in malware detection and improves the malware detection ratio over-than the techniques that do not utilize blockchain technology. In this paper, we study malware detection models which are based on blockchain technology. Furthermore, we elaborate on the effect of blockchain technology in malware detection, especially in the android environment.

Keywords: malware analysis, blockchain, malware attacks, malware detection approaches

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Authors: Nurcan Cetinkaya, Nadide Hulya Ozdemir

Abstract:

The aim of the study was to investigate the effect of Saccharomyces cerevisiae (SC) live yeast culture on microbial protein supply to the small intestine in Kivircik male yearlings when fed with different ratio of forage and concentrate diets. Four Kivircik male yearlings with permanent rumen canula were used in the experiment. . The treatments were allocated to a 4x4 Latin square design. Diet I consisted of 70% alfalfa hay and 30% concentrate, Diet II consisted of 30% alfalfa hay and 70% concentrate, Diet I and II were supplemented with a SC. Daily urine was collected and stored at -20°C until analysis. Calorimetric methods were used for the determination of urinary allantoin and creatinin levels. The estimated microbial N supply to small intestine for Diets I, I+SC, II and II+SC were 2.51, 2.64, 2.95 and 3.43 g N/d respectively. Supplementation of Diets I and II with SC significantly affected the allantoin levels in µmol/W0. 75 (p<0.05). Mean creatinine values in µmol/W0. 75 and allantoin:creatinin ratios were not significantly different among diets. In conclusion, supplementation with SC live yeast culture had a significant effect on urinary allantoin excretion and microbial protein supply to small intestine in Kivircik yearlings fed with high concentrate Diet II (P<0.05). Hence urinary allantoin excretion may be used as a tool for estimating microbial protein supply in Kivircık yearlings. However, further studies are necessary to understand the metabolism of Saccharomyces cerevisiae live yeast culture with different forage: concentrate ratio in Kıvırcık Yearlings.

Keywords: allantoin, creatinin, Kivircik yearling, microbial nitrogen, Saccharomyces cerevisia

Procedia PDF Downloads 377

Authors: Khaoula Bensaida, Osama Eljamal

Abstract:

The electrical energy generation through Microbial Fuel Cells (MFCs) using microorganisms is a renewable and sustainable approach. It creates truly an efficient technology for power production and wastewater treatment. MFC is an electrochemical device which turns wastewater into electricity. The most important part of MFC is microbes. Nano zero-valent Iron NZVI technique was successfully applied in degrading the chemical pollutants and cleaning wastewater. However, the use of NZVI for enhancing the current production is still not confirmed yet. This study aims to confirm the effect of these particles on the current generation by using MFC. A constructed microbial fuel cell, which utilizes domestic wastewater, has been considered for wastewater treatment and bio-electricity generation. The two electrodes were connected to an external resistor (200 ohms). Experiments were conducted in two steps. First, the MFC was constructed without adding NZVI particles (Control) while at a second step, nanoparticles were added with a concentration of 50mg/L. After 20 hours, the measured voltage increased to 5 and 8mV, respectively. To conclude, the use of zero-valent iron in an MFC system can increase electricity generation.

Keywords: bacterial growth, electricity generation, microbial fuel cell MFC, nano zero-valent iron NZVI.

Procedia PDF Downloads 112