Bacterial Remediation of Phenolic Compounds

Biotechnology ◽  
2019 ◽  
pp. 1910-1943
Author(s):  
Veena Gayathri Krishnaswamy
Keyword(s):  
Phenolic Compounds ◽  
Industrial Revolution ◽  
Marine Ecosystem ◽  
Research Work ◽  
Cost Effective ◽  
Real Problem ◽  
Comprehensive Information ◽  
Treatment Technologies ◽  
Biological Methods ◽  
Micro Organisms

Environmental pollution has been an irrefutable fact of life for many centuries; but it has become a real problem, since the start of the industrial revolution. Discharge of these toxic compounds without treatment results in serious health risks to humans and the marine ecosystem. Several physical, chemical and biological methods have been employed for the remediation of the phenolics. Bioremediation is identified as the most efficient, cost effective and eco-friendly ways for treatment of phenolic compounds. This article is a comprehensive review on the sources of phenolic compounds, their hazards, and their fate once released into the environment; the treatment technologies employed and bioremediation of these compounds using both non-extremophlic and extremophilic organisms. The review, throws light on the enzymes involved in the remediation of phenolic compounds, highlights the importance of extremophilic organisms and biological treatment of phenol containing industrial wastewaters. Such comprehensive information on the research work performed for the remediation of phenolic compounds provide ways to explore the role played by micro organisms in the remediation of phenolic compounds, which could be applied in the remediation of phenol /contaminated sites even under extreme conditions.

Bacterial Remediation of Phenolic Compounds

2017 ◽  
pp. 416-450 ◽  
Author(s):  
Veena Gayathri Krishnaswamy
Keyword(s):  
Phenolic Compounds ◽  
Industrial Revolution ◽  
Marine Ecosystem ◽  
Research Work ◽  
Cost Effective ◽  
Real Problem ◽  
Comprehensive Information ◽  
Treatment Technologies ◽  
Biological Methods ◽  
Micro Organisms

Environmental pollution has been an irrefutable fact of life for many centuries; but it has become a real problem, since the start of the industrial revolution. Discharge of these toxic compounds without treatment results in serious health risks to humans and the marine ecosystem. Several physical, chemical and biological methods have been employed for the remediation of the phenolics. Bioremediation is identified as the most efficient, cost effective and eco-friendly ways for treatment of phenolic compounds. This article is a comprehensive review on the sources of phenolic compounds, their hazards, and their fate once released into the environment; the treatment technologies employed and bioremediation of these compounds using both non-extremophlic and extremophilic organisms. The review, throws light on the enzymes involved in the remediation of phenolic compounds, highlights the importance of extremophilic organisms and biological treatment of phenol containing industrial wastewaters. Such comprehensive information on the research work performed for the remediation of phenolic compounds provide ways to explore the role played by micro organisms in the remediation of phenolic compounds, which could be applied in the remediation of phenol /contaminated sites even under extreme conditions.

Microbe Associated Phytoremediation Technology for Management of Oil Sludge

2015 ◽  
pp. 1-28 ◽  
Author(s):  
Anil Kumar ◽  
Monika Chandrabhan Dhote
Keyword(s):  
Polyaromatic Hydrocarbons ◽  
Research Work ◽  
Chemical Properties ◽  
Cost Effective ◽  
Oil Sludge ◽  
Sludge Disposal ◽  
Physico Chemical ◽  
Treatment Technologies ◽  
Petroleum Refineries ◽  
Mutagenic Effects

Environmental contamination due to petroleum compounds is a serious global issue. Oil /petroleum refineries produce huge amount of oil sludge during drilling, storage, transport, refining which spoil soil and ground water resources. Such activities release different compounds viz. alkane, mono- polyaromatic hydrocarbons (PAH), asphaltene, resins and heavy metals. Due to physico-chemical properties, PAHs are one of most targeted compounds as they are highly persistent, carcinogenic, and have mutagenic effects on ecosystem. Such problems of PAHs drag researcher's attention to find some reliable and cost effective solution for oil sludge disposal management. Since last few decades, extensive research work has been carried out on various methods for treatment of oil sludge. In recent years, microbial assisted phytoremediation treatment technologies are being studied since these are reliable and cost effective for field applications. Here, we have discussed about combined eco-friendly technology of plant and microbe(s) to treat oil sludge for its better management.

A Digital Economy Model for Talent Prediction Data Analytic

2019 ◽  
Vol 2 (4) ◽  
pp. 260-266
Author(s):  
Haru Purnomo Ipung ◽  
Amin Soetomo
Keyword(s):  
Business Model ◽  
Industrial Revolution ◽  
Technology Innovation ◽  
Cost Effective ◽  
Sharing Economy ◽  
Token Economy ◽  
Economy Model ◽  
New Business ◽  
The Cost ◽  
Data Analytic

This research proposed a model to assist the design of the associated data architecture and data analytic to support talent forecast in the current accelerating changes in economy, industry and business change due to the accelerating pace of technological change. The emerging and re-emerging economy model were available, such as Industrial revolution 4.0, platform economy, sharing economy and token economy. Those were driven by new business model and technology innovation. An increase capability of technology to automate more jobs will cause a shift in talent pool and workforce. New business model emerge as the availabilityand the cost effective emerging technology, and as a result of emerging or re-emerging economic models. Both, new business model and technology innovation, create new jobs and works that have not been existed decades ago. The future workers will be faced by jobs that may not exist today. A dynamics model of inter-correlation of economy, industry, business model and talent forecast were proposed. A collection of literature review were conducted to initially validate the model.

In-system Overflow Treatment Technologies Offer Cost-Effective Opportunities to Protect Water Quality

2015 ◽  
Vol 2015 (1) ◽  
pp. 1-16
Author(s):  
J Fitzpatrick ◽  
S Eisner ◽  
S Goris ◽  
J Hutchins ◽  
C O’Bryan ◽  
...  
Keyword(s):  
Water Quality ◽  
Cost Effective ◽  
Treatment Technologies

Knee Muscle Force Estimating Model Using Machine Learning Approach

2020 ◽  
Author(s):  
Anurag Sohane ◽  
Ravinder Agarwal
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Muscle Force ◽  
Vastus Lateralis ◽  
Input Parameter ◽  
Research Work ◽  
Cost Effective ◽  
Coefficient Of Determination ◽  
Muscle Forces ◽  
Knee Muscle

Abstract Various simulation type tools and conventional algorithms are being used to determine knee muscle forces of human during dynamic movement. These all may be good for clinical uses, but have some drawbacks, such as higher computational times, muscle redundancy and less cost-effective solution. Recently, there has been an interest to develop supervised learning-based prediction model for the computationally demanding process. The present research work is used to develop a cost-effective and efficient machine learning (ML) based models to predict knee muscle force for clinical interventions for the given input parameter like height, mass and angle. A dataset of 500 human musculoskeletal, have been trained and tested using four different ML models to predict knee muscle force. This dataset has obtained from anybody modeling software using AnyPyTools, where human musculoskeletal has been utilized to perform squatting movement during inverse dynamic analysis. The result based on the datasets predicts that the random forest ML model outperforms than the other selected models: neural network, generalized linear model, decision tree in terms of mean square error (MSE), coefficient of determination (R2), and Correlation (r). The MSE of predicted vs actual muscle forces obtained from the random forest model for Biceps Femoris, Rectus Femoris, Vastus Medialis, Vastus Lateralis are 19.92, 9.06, 5.97, 5.46, Correlation are 0.94, 0.92, 0.92, 0.94 and R2 are 0.88, 0.84, 0.84 and 0.89 for the test dataset, respectively.

scholarly journals An IOTA-Based Service Discovery Framework for Fog Computing

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 844
Author(s):  
Tsung-Yi Tang ◽  
Li-Yuan Hou ◽  
Tyng-Yeu Liang
Keyword(s):  
Service Discovery ◽  
Fog Computing ◽  
Cost Effective ◽  
Public Access ◽  
Hash Tables ◽  
Network Attacks ◽  
Comprehensive Information ◽  
Data Flows ◽  
Multiple Levels ◽  
Discovery Method

With the rise in fog computing, users are no longer restricted to only accessing resources located in central and distant clouds and can request services from neighboring fog nodes distributed over networks. This can effectively reduce the network latency of service responses and the load of data centers. Furthermore, it can prevent the Internet’s bandwidth from being used up due to massive data flows from end users to clouds. However, fog-computing resources are distributed over multiple levels of networks and are managed by different owners. Consequently, the problem of service discovery becomes quite complicated. For resolving this problem, a decentralized service discovery method is required. Accordingly, this research proposes a service discovery framework based on the distributed ledger technology of IOTA. The proposed framework enables clients to directly search for service nodes through any node in the IOTA Mainnet to achieve the goals of public access and high availability and avoid network attacks to distributed hash tables that are popularly used for service discovery. Moreover, clients can obtain more comprehensive information by visiting known nodes and select a fog node able to provide services with the shortest latency. Our experimental results have shown that the proposed framework is cost-effective for distributed service discovery due to the advantages of IOTA. On the other hand, it can indeed enable clients to obtain higher service quality by automatic node selection.

scholarly journals Molecular identification and antimicrobial activities of some wild Egyptian mushrooms: Bjerkandera adusta as a promising source of bioactive antimicrobial phenolic compounds

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Elham R. S. Soliman ◽  
Heba El-Sayed
Keyword(s):  
Phenolic Compounds ◽  
Micrococcus Luteus ◽  
Cost Effective ◽  
Antimicrobial Activities ◽  
Bjerkandera Adusta ◽  
Internal Transcribed Spacer Region ◽  
Agrocybe Aegerita ◽  
Encoding Gene ◽  
Promising Source ◽  
Related Compounds

Abstract Background The discovery of potential, new cost-effective drug resources in the form of bioactive compounds from mushrooms is one way to control the resistant pathogens. In the present research, the fruiting bodies of five wild mushrooms were collected from Egypt and identified using internal transcribed spacer region (ITS) of the rRNA encoding gene and their phylogenetic relationships, antimicrobial activities, and biochemical and phenolic compounds were evaluated. Results The sequences revealed identity to Bjerkandera adusta, Cyclocybe cylindracea, Agrocybe aegerita, Chlorophyllum molybdites, and Lentinus squarrosulus in which Cyclocybe cylindracea and Agrocybe aegerita were closely related, while Chlorophyllum molybdites was far distant. Cyclocybe cylindracea and Agrocybe aegerita showed 100% similarity based on the sequenced ITS-rDNA fragment and dissimilar antimicrobial activities and chemical composition were detected. Bjerkandera adusta and Cyclocybe cylindracea showed strong antimicrobial activity against Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, Micrococcus luteus, Streptococcus pneumoniae, and Candida albicans. This activity could be attributed to the detected phenolic and related compounds’ contents. Conclusion Our finding provides a quick and robust implement for mushroom identification that would facilitate mushroom domestication and characterization for human benefit.

scholarly journals Operationalization of Remote Sensing Solutions for Sustainable Forest Management

2021 ◽  
Vol 13 (4) ◽  
pp. 572
Author(s):  
Gintautas Mozgeris ◽  
Ivan Balenović
Keyword(s):  
Remote Sensing ◽  
Forest Management ◽  
Natural Resources ◽  
Sustainable Management ◽  
Sustainable Forest Management ◽  
Cost Effective ◽  
Development Trends ◽  
Comprehensive Information ◽  
The Status

The pre-requisite for sustainable management of natural resources is the availability of timely, cost-effective, and comprehensive information on the status and development trends of the management object [...]

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