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  • 1
    Language: English
    In: Catalysis Letters, 2018, Vol.148(7), pp.2190-2199
    Description: Two neutral endoglucanases (EG1 and EG2) from Stachybotrys microspora were purified and studied for their hydrolysis capacity and product profiles. Contrary to most of cellulases, especially the fungal endoglucanases such as those from Trichoderma reesei the most studied fungus, both EG1 and EG2 are more active on [beta]-glucan from barely ([beta]-1,3; [beta]-1,4) than on carboxymethyl cellulose (CMC) ([beta]-1,4). This result is much researched. Both enzymes are non specific. They hydrolyze less efficiently (30%) laminarin and only EG1 was able to attack xylan at 38%. The effectiveness of both cellulases was compared using these carbohydrates as substrates. EG1 had greater activity than EG2 on both substrates. Additionally, maximal activity (~fourfold) was observed in the presence of [beta]-glucan from barely. The distinguishing properties of EG1 and EG2 are presented in the kinetic parameters (km, Vmax), turnover number (kcat) and catalytic efficiency (kcat/Km). EG1 catalyzed the hydrolysis of CMC with a Km of 8.048 mg/mL and a Vmax of 16.58 U/min/mg, more efficiently than EG2 with a Km of 13.71 mg/mL and a Vmax of 2.524 U/min/mg. Both purified cellulases have two distinct catalytic mechanisms. EG1 was able to hydrolyze CMC and [beta]-glucan into soluble cellooligosaccharides (cellobiose, cellotriose) and (cellotriose, cellotetraose, cellobiose) as dominants products respectively, with a tiny amounts of glucose. In contrast, EG2 was able to efficiently hydrolyze both substrates into glucose. The relative amount of each product was dependent on the particular endoglucanase, substrate, kinetic constants and reaction time. Thus, these tow enzymatic hydrolysis behaviours should provide two alternatives for biotechnological applications. Graphical Abstract
    Keywords: Endoglucanases ; Glucan ; Mode of action ; Oligosaccharides ; Stachybotrys microspora
    ISSN: 1011-372X
    E-ISSN: 1572-879X
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  • 2
    Language: English
    In: International Journal of Agriculture and Biology, Oct 31, 2012, Vol.14(5)
    Description: Sorghum is capable of sustaining under high temperature and minimal soil moisture. Hydrocyanic acid toxin production is a serious problem associated with sorghum forage in dry areas and could be lethal to animals if ingested in higher quantities. Hydrocyanic acid (HCN) contents in forage sorghum were studied through field experiment executed at National Agricultural Research Centre, Islamabad during 2008 and 2009. Three sorghum cultivars JS-2002, Chakwal sorghum and Local sorghum were sown in a randomized complete block design in split-split plot arrangement with three seeding rates (75, 100 & 125 kg ha-1) and three nitrogen levels (0, 60 & 120 kg N ha-1). Increased nitrogen application progressively increased HCN production irrespective of cultivar and growth stage of the crop. Application of 120 kg N ha-1 recorded about 64% higher HCN than control treatment indicating the risk of higher doses of nitrogen fertilizer to sorghum forage in dry areas. Seeding rates had variable influence on HCN production. Cultivar JS-2002 produced 23, 36 and 57% less HCN contents compared to local sorghum at pre-booting, booting and 50% heading stage, respectively. On the basis of two year's field study, it may be concluded that approved cultivar JS-2002 produced less HCN sown with higher seed rate and applied low doses of N fertilizer under dryland farming conditions of Pothwar is recommended for general cultivation.
    Keywords: Cultivars -- Physiological Aspects ; Cultivars -- Composition ; Cultivars -- Growth ; Hydrogen Cyanide -- Chemical Properties ; Hydrogen Cyanide -- Identification And Classification ; Sorghum -- Physiological Aspects ; Sorghum -- Composition ; Sorghum -- Growth ; Plant Biochemistry -- Research ; Plant Growth -- Research
    ISSN: 1560-8530
    E-ISSN: 18149596
    Source: Cengage Learning, Inc.
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  • 3
    Language: English
    In: Process Biochemistry, March 2017, Vol.54, pp.59-66
    Description: In this study, we isolated a novel endoglucanase (EG1) that exhibits optimal activity at pH 7 and 50 °C and retained 〉85% of its activity between pH 5 and 9 and 〉80% at 60 °C. In addition to its alkali tolerance, this EG1 is a halophilic enzyme as its activity was enhanced to 152% in the presence of 5 M NaCl. In this condition, optimal activity was observed at pH 8 and 70 °C. More interestingly, EG1 was active in the presence of an ionic liquid (IL) (100% and 80% activity in 5% and 10% [Bmim]Cl, respectively). Furthermore, it was extremely stable in the presence of various detergents, especially SDS (10%), which is a very rare property amongst fungal cellulases. All these properties make this enzyme suitable for many applications, mainly in biofuel, textile and detergent industries.
    Keywords: Stachybotrys Microspora ; Halophilic Endoglucanase ; Ionic Liquid ; Purification ; Solvent Tolerance ; Engineering
    ISSN: 1359-5113
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  • 4
    Language: English
    In: Applied biochemistry and biotechnology, March 2014, Vol.172(5), pp.2640-9
    Description: The production profile of cellulases of the mutant strain A19 from the filamentous fungus Stachybotrys microspora was studied in the presence of various carbon sources (glucose, lactose, cellulose, carboxymethylcellulose (CMC), and wheat bran) and a range of medium initial pH (5, 7, and 8). Two extracellular cellulases from the Stachybotrys strain (endoglucanases and β-glucosidases) were monitored by enzymatic assay, sodium dodecyl sulfate-polyacrylamide gel electrophoresis, and zymogram analysis. Glucose and lactose repressed CMCase time course production while they permitted a strong β-glucosidase one. On Avicel cellulose, CMC, and wheat bran, both activities were highly produced. Wheat bran (WB) is the best carbon source with an optimum of production at days 5 and 6. The production kinetics of both activities were shown to depend on the medium initial pH, with a preference for neutral or alkaline pH in the majority of conditions. The exception concerned the β-glucosidase which was much more produced at acidic pH, on glucose and cellulose. Most interestingly, a constitutive and conditional expression of an alkaline endoglucanase was revealed on the glucose-based medium at an initial pH of 8 units. The zymogram analysis confirmed such conclusions and highlighted that carbon sources and the pH of the culture medium directed a differential induction of various endoglucanases and β-glucosidases.
    Keywords: Cellulases -- Biosynthesis ; Fungal Proteins -- Biosynthesis ; Stachybotrys -- Metabolism
    ISSN: 02732289
    E-ISSN: 1559-0291
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  • 5
    In: IOSR Journal of Applied Geology and Geophysics, 04/2016, Vol.04(04), pp.42-52
    ISSN: 23210982
    E-ISSN: 23210990
    Source: CrossRef
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  • 6
    Language: English
    In: Structural Health Monitoring, January 2018, Vol.17(1), pp.91-107
    Description: Structural health monitoring offers new approaches to interrogate the integrity of complex structures. The structural health monitoring process classically relies on four sequential steps: damage detection, localization, classification, and quantification. The most critical step of such process is the damage detection step since it is the first one and because performances of the following steps depend on it. A common method to design such a detector consists of relying on a statistical characterization of the damage indexes available in the healthy behavior of the structure. On the basis of this information, a decision threshold can then be computed in order to achieve a desired probability of false alarm. To determine the decision threshold corresponding to such desired probability of false alarm, the approach considered here is based on a model of the tail of the damage indexes distribution built using the Peaks Over Threshold method extracted from the extreme value theory. This approach of tail distribution estimation is interesting since it is not necessary to know the whole distribution of the damage indexes to develop a detector, but only its tail. This methodology is applied here in the context of a composite aircraft nacelle (where desired probability of false alarm is typically between 10−4 and 10−9) for different configurations of learning sample size and probability of false alarm and is compared to a more classical one which consists of modeling the entire damage indexes distribution by means of Parzen windows. Results show that given a set of data in the healthy state, the effective probability of false alarm obtained using the Peaks Over Threshold method is closer to the desired probability of false alarm than the one obtained using the Parzen-window method, which appears to be more conservative.
    Keywords: Damage Detection ; Extreme Value Theory ; Peaks Over Threshold ; Generalized Pareto Distribution ; Lamb Waves ; Composite Structures ; Engineering
    ISSN: 1475-9217
    E-ISSN: 1741-3168
    Source: Sage Journals (Sage Publications)
    Source: SAGE STM (Sage Publications)
    Source: SAGE Materials Science and Engineering (Sage Publications)
    Source: SAGE Communication and Media Studies (Sage Publications)
    Source: SAGE Journals (Sage Publications)
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  • 7
    Language: English
    In: Academy of Accounting and Financial Studies Journal, 2018, Vol.22(4), p.1l(16)
    Description: This research aims to find out the pattern of local government expenditures, especially regional expenditures directly related to economic growth, namely regional expenditures in education, health, agriculture, housing, transportation, and social, and linking the respective superior sectors in the New Autonomous Region (NAR) In Sumatera Island. The result of study shows that potential sectors having criteria of the basic sector, and high growth and competitiveness are still dominated by the agricultural sector and services. Meanwhile, local government expenditures for education, health, and social affairs have a positive and significant effect, housing has a negative and significant effect, and government spending on agriculture and transportation has no significant effect on the growth of the new autonomous regions, with the agricultural sector, Manufacturing, electricity, gas and water supply sectors, construction sector, trade, hotel and restaurant sector, as well as transportation and communications sectors being the ones supporting economic development in New Autonomous Regions (NAR). Keywords: Government Expenditure, Government Spending, Economic Growth, Potential Sectors.
    Keywords: Indonesia ; Studies ; Local Government ; Government Spending ; Economic Growth ; Regions ; Municipal Government;
    ISSN: 1096-3685
    E-ISSN: 15282635
    Source: Cengage Learning, Inc.
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  • 8
    Language: English
    In: Applied Radiation and Isotopes, June 2018, Vol.136, pp.104-110
    Description: In this study, the dosimetric characterization for The BEBIG Co High Dose Rate (HDR) brachytherapy source model Co0.A86 was investigated and the validity of the EGS5 Monte Carlo code to reproduce the dosimetric parameters in water phantom was checked. In addition, the dose distribution for different tissue phantoms was calculated. The BEBIG Co HDR brachytherapy source was modeled using EGS5 Monte Carlo simulation code. A description of the source design, geometry and materials used in this work were provided. According to the update TG43-U1 formalism of AAPM, the air kerma strength, the dose rate constant, 2D rectangular dose distribution in water were calculated, moreover, the results of the radial dose function were obtained in water and different tissue phantoms; bone, lung, adipose tissue, breast and muscle. The obtained results were tabulated and presented in graphical formats for the comparison with available data. The calculated value of the air kerma strength of this study, 3.0419 U Bq , agree well with that of the other Monte Carlo calculation. The 2D look-up along-away rectangular dose were obtained in water, the results were similar to the published data for all distances larger than 1 cm, for the distances near to the source region on the transversal source axis small differences are apparent. The radial dose function were presented in graphical format for the comparison between the dose distribution in water and different tissue phantoms. The EGS5 results obtained in this study shows good consistency with the published data for the dosimetric parameters of the of the BEBIG Co HDR brachytherapy source. It seems that the radial dose function calculated in water differed in tissue phantoms due to the atomic composition and densities for media that are not taken account by the TG43-U1 formalism.
    Keywords: Monte Carlo ; Brachytherapy ; Dose ; 60co ; Medicine ; Physics
    ISSN: 0969-8043
    E-ISSN: 1872-9800
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  • 9
    Language: English
    In: 2017 International Conference on Green Energy Conversion Systems (GECS), March 2017, pp.1-4
    Description: Packet communication's useful in cell-phone, mail, images. The goal is to let communications line effectively, its benefits billing by volume of data that is sent and received and not the call time, whenever packet creation's required; payloads is required. whenever a payload require a header and trailers; Headers and Trailers Supplies an entity, while Packet Generator Merges the entities representing header, payload, and trailer into one entity, and finally Parity Bit Assigns a ParityBit attribute to each packet. And then Transmission been via a Channel, And parity bit is used to decide whether the packet is correct or contains an error.
    Keywords: Payloads ; Matlab ; Receivers ; Error Analysis ; Electronic Mail ; Component ; Communication ; Packets ; Error Detection ; Error Correction ; Circuit-Switching ; Network ; Simulation ; Entities
    Source: IEEE Conference Publications
    Source: IEEE Xplore
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  • 10
    Dissertation
    Dissertation
    Nottingham Trent University
    Description: Speech is a desirable communication method between humans and computers. The major concerns of the automatic speech recognition (ASR) are determining a set of classification features and finding a suitable recognition model for these features. Hidden Markov Models (HMMs) have been demonstrated to be powerful models for representing time varying signals. Artificial Neural Networks (ANNs) have also been widely used for representing time varying quasi-stationary signals. Arabic is one of the oldest living languages and one of the oldest Semitic languages in the world, it is also the fifth most generally used language and is the mother tongue for roughly 200 million people. Arabic speech recognition has been a fertile area of reasearch over the previous two decades, as attested by the various papers that have been published on this subject. This thesis investigates phoneme and acoustic models based on Deep Neural Networks (DNN) and Deep Echo State Networks for multi-dialect Arabic Speech Recognition. Moreover, the TIMIT corpus with a wide variety of American dialects is also aimed to evaluate the proposed models. The availability of speech data that is time-aligned and labelled at phonemic level is a fundamental requirement for building speech recognition systems. A developed Arabic phoneme database (APD) was manually timed and phonetically labelled. This dataset was constructed from the King Abdul-Aziz Arabic Phonetics Database (KAPD) database for Saudi Arabia dialect and the Centre for Spoken Language Understanding (CSLU2002) database for different Arabic dialects. This dataset covers 8148 Arabic phonemes. In addition, a corpus of 120 speakers (13 hours of Arabic speech) randomly selected from the Levantine Arabic dialect database that is used for training and 24 speakers (2.4 hours) for testing are revised and transcription errors were manually corrected. The selected dataset is labelled automatically using the HTK Hidden Markov Model toolkit. TIMIT corpus is also used for phone recognition and acoustic modelling task. We used 462 speakers (3.14 hours) for training and 24 speakers (0.81 hours) for testing. For Automatic Speech Recognition (ASR), a Deep Neural Network (DNN) is used to evaluate its adoption in developing a framewise phoneme recognition and an acoustic modelling system for Arabic speech recognition. Restricted Boltzmann Machines (RBMs) DNN models have not been explored for any Arabic corpora previously. This allows us to claim priority for adopting this RBM DNN model for the Levantine Arabic acoustic models. A post-processing enhancement was also applied to the DNN acoustic model outputs in order to improve the recognition accuracy and to obtain the accuracy at a phoneme level instead of the frame level. This post process has significantly improved the recognition performance. An Echo State Network (ESN) is developed and evaluated for Arabic phoneme recognition with different learning algorithms. This investigated the use of the conventional ESN trained with supervised and forced learning algorithms. A novel combined supervised/forced supervised learning algorithm (unsupervised adaptation) was developed and tested on the proposed optimised Arabic phoneme recognition datasets. This new model is evaluated on the Levantine dataset and empirically compared with the results obtained from the baseline Deep Neural Networks (DNNs). A significant improvement on the recognition performance was achieved when the ESN model was implemented compared to the baseline RBM DNN model’s result. The results show that the ESN model has a better ability for recognizing phonemes sequences than the DNN model for a small vocabulary size dataset. The adoption of the ESNs model for acoustic modeling is seen to be more valid than the adoption of the DNNs model for acoustic modeling speech recognition, as ESNs are recurrent models and expected to support sequence models better than the RBM DNN models even with the contextual input window. The TIMIT corpus is also used to investigate deep learning for framewise phoneme classification and acoustic modelling using Deep Neural Networks (DNNs) and Echo State Networks (ESNs) to allow us to make a direct and valid comparison between the proposed systems investigated in this thesis and the published works in equivalent projects based on framewise phoneme recognition used the TIMIT corpus. Our main finding on this corpus is that ESN network outperform time-windowed RBM DNN ones. However, our developed system ESN-based shows 10% lower performance when it was compared to the other systems recently reported in the literature that used the same corpus. This due to the hardware availability and not applying speaker and noise adaption that can improve the results in this thesis as our aim is to investigate the proposed models for speech recognition and to make a direct comparison between these models.
    Keywords: 006.4
    Source: Networked Digital Library of Theses and Dissertations
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