Relating Methanogen Community Structure and Anaerobic Digester Function

Much remains unknown about the relationships between microbial community structure and anaerobic digester function. However, knowledge of links between community structure and function, such as specific methanogenic activity (SMA) and COD removal rate, are valuable to improve anaerobic bioprocesses. In this work, quantitative structure–activity relationships (QSARs) were developed using multiple linear regression (MLR) to predict SMA using methanogen community structure descriptors for 49 cultures. Community descriptors were DGGE demeaned standardized band intensities for amplicons of a methanogen functional gene (mcrA). First, predictive accuracy of MLR QSARs was assessed using cross validation with training (n = 30) and test sets (n = 19) for glucose and propionate SMA data. MLR equations correlating band intensities and SMA demonstrated good predictability for glucose (q2 = 0.54) and propionate (q2 = 0.53). Subsequently, data from all 49 cultures were used to develop QSARs to predict SMA values. Higher intensities of two bands were correlated with higher SMA values; high abundance of methanogens associated with these two bands should be encouraged to attain high SMA values. QSARs are helpful tools to identify key microorganisms or to study and improve many bioprocesses. Development of new, more robust QSARs is encouraged for anaerobic digestion or other bioprocesses, including nitrification, nitritation, denitrification, anaerobic ammonium oxidation, and enhanced biological phosphorus removal

Cloud Security in Crypt Database Server Using Fine Grained Access Control

Information sharing in the cloud, powered by good patterns in cloud technology, is rising as a guaranteeing procedure for permitting users to advantageously access information. However, the growing number of enterprises and customers who stores their information in cloud servers is progressively challenging users’ privacy and the security of information. This paper concentrates on providing a dependable and secure cloud information sharing services that permits users dynamic access to their information. In order to achieve this, propose an effective, adaptable and flexible privacy preserving information policy with semantic security, by using Cipher text Policy Element Based Encryption (CP-EBE) consolidated with Character Based Encryption (CBE) systems. To ensure strong information sharing security, the policy succeeds in protecting the privacy of cloud users and supports efficient and secure dynamic operations, but not constrained to, file creation, user revocation. Security analysis demonstrates that the proposed policy is secure under the generic bi- linear group model in the random oracle model and enforces fine-grained access control, full collusion resistance and retrogressive secrecy. Furthermore, performance analysis and experimental results demonstrate that the overheads are as light as possible

Dynamic Control System Based On Context for Mobile Devices

“To render the accurate information, at correct place in real period with custom-made setup and locality sensitiveness” is the inspiration for every location based information scheme. Android applications in mobile devices may often have access to susceptible data and resources on user device. “Location Based Services” can only provide services that give a data and information to person, wherever he might be through various android applications. To avoid the data misuse by malicious applications, an application may get privilege on the specific user location and thus a Context Based Access Control Mechanism (CBACM) is needed so that privileges can be established and revoked vigorously. A very interesting application include shadowing where immediate information is required to choose if the people being monitored are valid intimidation or an flawed object. The execution of CBACM differentiates between the narrowly located sub-areas within the distinct area. Android operating system is modified such that context based access restriction can be precise and imposed. DOI: 10.17762/ijritcc2321-8169.15057

Treatment of sugarmill effluent and simultaneous production of ethanol: Effect of pH and quantity of seed sludge

India is the largest producer of sugar and generates 0.16 – 0.76 m 3 of wastewater for every ton of crushed cane. In this paper, the effect of pH and seed sludge on simultaneous treatment and ethanol production from a sugar mill wastewater using anaerobic sludge was investigated. The sugar mill wastewater had following composition: pH (6.69 ±0.45 ), reducing sug ar (5 – 6.83 m g/mL), chemical oxygen demand (5000 – 8 000 mg/L), total nitrogen ( 22.73 – 22.97 mg/L), and NPOC (1589 – 1647 mg/L). Seed sludge (10 – 50 % v/v) and pH (4 - 5.5) were varied in this study. Organic carbon removal was determined by analyzing non - purgeable organic carbon (NPOC) in a TOC liquid analyzer. Fermentation process was carried out for 24, 48, 72, 96 and 120 h. Maximum ethanol yield of 0.00133 L/L of sugarcane wastewater was obtained at pH of 5.5 using 10 % v/v seed sludge. Moreover, 46 % NPOC removal was achieved under this condition. India produces 900000 m 3 of sugarcane wastewater annually. According to the present study, it is possible to produce 11 84 m 3 of ethanol per year from sugarcane wastewater by treating the wastewater in anaerob ic reactor under an acidic condition. However, detailed pilot study is required to determine the economic and technical feasibility

Fruits And Vegetables Consumption Among Dental Students in Private Dental Colleges

The objective of this study was to assess the consumption of fruits and vegetables among dental students. This is a cross sectional questionnaire survey conducted among dental students in various private dental colleges. A convenience sampling method was used for the study. A total of 107students have responded to the survey. Participants have been randomly enrolled in the online survey through a survey planet. A validated questionnaire consists of 20 closed ended and yes/ no questions distributed to assess their consumption of fruits and vegetables in their regular life. The responses have been taken and were analysed. The results were expressed as pie charts. 93.4% of the participants said yes to liking for having fruits and 6.6% of them said no . The study concluded that there is an optimum consumption of the fruits by the dental students and they were aware of the benefits of including fruits in their diet

Prosthetic Implications Of Dental Anomalies

This paper is aimed to describe a number of dental anomalies which every dental practitioner of all discipline will be destined to encounter. The dental anomalies, how it affects the particular prosthetic implications and what could be done for treatment, if alterations could be done in the prosthetic implications are discussed in this review article.A number of articles around 40 were collected from search engines like PubMed , scholar and so much more.The articles were thoroughly reviewed to write this article on Dental Anomalies affecting prosthetic implications. Dental anomalies are the abnormalities present in the teeth and oral cavity. Dental anomalies are a wide range of disorders comprising various disorders of the teeth into the categories : acquired abnormalities and developmental abnormalities.. Developmental anomalies are divided into five groups for classification. They are abnormalities in size, number, morphology, shape and the location of the tooth. The teeth number anomalies are hypodontia, hyperdontia. In these abnormalities there will be less number of teeth and increased number of teeth respectively. We also have positional anomalies which include transposition. Morphological anomalies include Concrescence, fusion and gemination( double teeth).The other abnormalities are taurodontism, dilaceration including supernumerary roots, Dens Evaginatus and Dens Invaginatus. Structural anomalies include Dentinogenesis Imperfecta and Amelogenesis Imperfecta. Tooth impaction is also one of the developmental anomalies seen. Acquired tooth disorders include tooth ankylosis, resorption. Hypercementosis, pulpstone, tooth fluorosis, abrasion, erosion, Syphilitic Hypoplasia, molar incisor hypo mineralisation are some of the other acquired dental anomalies

Probing Mechanisms of Binding and Allostery in the SARS-CoV-2 Spike Omicron Variant Complexes with the Host Receptor: Revealing Functional Roles of the Binding Hotspots in Mediating Epistatic Effects and Communication with Allosteric Pockets

In this study, we performed all-atom MD simulations of RBD–ACE2 complexes for BA.1, BA.1.1, BA.2, and BA.3 Omicron subvariants, conducted a systematic mutational scanning of the RBD–ACE2 binding interfaces and analysis of electrostatic effects. The binding free energy computations of the Omicron RBD–ACE2 complexes and comprehensive examination of the electrostatic interactions quantify the driving forces of binding and provide new insights into energetic mechanisms underlying evolutionary differences between Omicron variants. A systematic mutational scanning of the RBD residues determines the protein stability centers and binding energy hotpots in the Omicron RBD–ACE2 complexes. By employing the ensemble-based global network analysis, we propose a community-based topological model of the Omicron RBD interactions that characterized functional roles of the Omicron mutational sites in mediating non-additive epistatic effects of mutations. Our findings suggest that non-additive contributions to the binding affinity may be mediated by R493, Y498, and Y501 sites and are greater for the Omicron BA.1.1 and BA.2 complexes that display the strongest ACE2 binding affinity among the Omicron subvariants. A network-centric adaptation model of the reversed allosteric communication is unveiled in this study, which established a robust connection between allosteric network hotspots and potential allosteric binding pockets. Using this approach, we demonstrated that mediating centers of long-range interactions could anchor the experimentally validated allosteric binding pockets. Through an array of complementary approaches and proposed models, this comprehensive and multi-faceted computational study revealed and quantified multiple functional roles of the key Omicron mutational site R493, R498, and Y501 acting as binding energy hotspots, drivers of electrostatic interactions as well as mediators of epistatic effects and long-range communications with the allosteric pockets

Interpretable Machine Learning Models for Molecular Design of Tyrosine Kinase Inhibitors Using Variational Autoencoders and Perturbation-Based Approach of Chemical Space Exploration

In the current study, we introduce an integrative machine learning strategy for the autonomous molecular design of protein kinase inhibitors using variational autoencoders and a novel cluster-based perturbation approach for exploration of the chemical latent space. The proposed strategy combines autoencoder-based embedding of small molecules with a cluster-based perturbation approach for efficient navigation of the latent space and a feature-based kinase inhibition likelihood classifier that guides optimization of the molecular properties and targeted molecular design. In the proposed generative approach, molecules sharing similar structures tend to cluster in the latent space, and interpolating between two molecules in the latent space enables smooth changes in the molecular structures and properties. The results demonstrated that the proposed strategy can efficiently explore the latent space of small molecules and kinase inhibitors along interpretable directions to guide the generation of novel family-specific kinase molecules that display a significant scaffold diversity and optimal biochemical properties. Through assessment of the latent-based and chemical feature-based binary and multiclass classifiers, we developed a robust probabilistic evaluator of kinase inhibition likelihood that is specifically tailored to guide the molecular design of novel SRC kinase molecules. The generated molecules originating from LCK and ABL1 kinase inhibitors yielded ~40% of novel and valid SRC kinase compounds with high kinase inhibition likelihood probability values (p \u3e 0.75) and high similarity (Tanimoto coefficient \u3e 0.6) to the known SRC inhibitors. By combining the molecular perturbation design with the kinase inhibition likelihood analysis and similarity assessments, we showed that the proposed molecular design strategy can produce novel valid molecules and transform known inhibitors of different kinase families into potential chemical probes of the SRC kinase with excellent physicochemical profiles and high similarity to the known SRC kinase drugs. The results of our study suggest that task-specific manipulation of a biased latent space may be an important direction for more effective task-oriented and target-specific autonomous chemical design models