Sustainable development requires the development and promotion of environmental management and a constant search for green technologies to treat a wide range of aquatic and terrestrial habitats contaminated by increasing anthropogenic activities. Bioremediation is an increasingly popular alternative to conventional methods for treating waste compounds and media with the possibility to degrade contaminants using natural microbial activity mediated by different consortia of microbial strains. Many studies about bioremediation have been reported and the scientific literature has revealed the progressive emergence of various bioremediation techniques. In this review, we discuss the various in situ and ex situ bioremediation techniques and elaborate on the anaerobic digestion technology, phytoremediation, hyperaccumulation, composting and biosorption for their effectiveness in the biotreatment, stabilization and eventually overall remediation of contaminated strata and environments. The review ends with a note on the recent advances genetic engineering and nanotechnology have had in improving bioremediation. Case studies have also been extensively revisited to support the discussions on biosorption of heavy metals, gene probes used in molecular diagnostics, bioremediation studies of contaminants in vadose soils, bioremediation of oil contaminated soils, bioremediation of contaminants from mining sites, air sparging, slurry phase bioremediation, phytoremediation studies for pollutants and heavy metal hyperaccumulators, and vermicomposting.

A comprehensive overview of elements in bioremediation

Vermicomposting is a non-thermophilic, boioxidative process that involves earthworms and associated microbes. This biological organic waste decomposition process yields the biofertilizer namely the vermicompost. Vermicompost is a finely divided, peat like material with high porosity, good aeration, drainage, water holding capacity, microbial activity, excellent nutrient status and buffering capacity thereby resulting the required physiochemical characters congenial for soil fertility and plant growth. Vermicompost enhances soil biodiversity by promoting the beneficial microbes which inturn enhances plant growth directly by production of plant growth-regulating hormones and enzymes and indirectly by controlling plant pathogens, nematodes and other pests, thereby enhancing plant health and minimizing the yield loss. Due to its innate biological, biochemical and physiochemical properties, vermicompost may be used to promote sustainable agriculture and also for the safe management of agricultural, industrial, domestic and hospital wastes which may otherwise pose serious threat to life and environment.

https://link.springer.com/content/pdf/10.1186%2F2193-1801-1-26.pdf

Microbial diversity of vermicompost bacteria that exhibit useful agricultural traits and waste management potential

Vermitechnology for sewage sludge recycling.

The composting potential of two epigeic earthworms (P. excavatus and P. sansibaricus) was studied in 2002 to breakdown the domestic waste under laboratory conditions. The experimental container with P. sansibaricus showed maximum mineralization and decomposition rate than that of P. excavatus. Except for exchangeable K (it was higher (P = 0.004) in a container with P. excavatus), the domestic waste processed by P. sansibaricus showed about 6% more total nitrogen (P = 0.002) and about 7% more available P (P = 0.269) at the end than by P. excavatus. As compared with the initial level organic C content as well as C:N ratio showed a considerable reduction that was noted higher in substrate with P. sansibaricus than those by P. excavatus (organic C, t-test: P = 0.870; C:N ratio, t-test: P = 0.002). The growth (biomass increase) and reproduction parameters such as mean individual live weight, maximum individual growth rate (mg wt./worm/day), number of cocoons and reproduction rate (cocoon/worm/day) were higher in bedding with P. sansibaricus. The maximum earthworm mortality was in vermibed having P. sansibaricus (∼50% higher than by P. excavatus) (t-test: P = 0.423), since both species did not show a drastic difference in waste mineralization rate, but comparatively, P. excavatus exhibited better growth and reproduction performance, which further support the suitability of the species for large scale vermiculture operations.

/pdf/vermicomposting-of-domestic-waste-by-using-two-epigeic-mq0s7q1amv.pdf

Vermicomposting of domestic waste by using two epigeic earthworms (Perionyx excavatus and Perionyx sansibaricus)

Treatment of biowaste, the predominant waste fraction in low- and middle-income settings, offers public health, environmental and economic benefits by converting waste into a hygienic product, diverting it from disposal sites, and providing a source of income. This article presents a comprehensive overview of 13 biowaste treatment technologies, grouped into four categories: (1) direct use (direct land application, direct animal feed, direct combustion), (2) biological treatment (composting, vermicomposting, black soldier fly treatment, anaerobic digestion, fermentation), (3) physico-chemical treatment (transesterification, densification), and (4) thermo-chemical treatment (pyrolysis, liquefaction, gasification). Based on a literature review and expert consultation, the main feedstock requirements, process conditions and treatment products are summarized, and the challenges and trends, particularly regarding the applicability of each technology in the urban low- and middle-income context, are critically discussed. An analysis of the scientific articles published from 2005 to 2015 reveals substantial differences in the amount and type of research published for each technology, a fact that can partly be explained with the development stage of the technologies. Overall, publications from case studies and field research seem disproportionately underrepresented for all technologies. One may argue that this reflects the main task of researchers—to conduct fundamental research for enhanced process understanding—but it may also be a result of the traditional embedding of the waste sector in the discipline of engineering science, where socio-economic and management aspects are seldom object of the research. More unbiased, well-structured and reproducible evidence from case studies at scale could foster the knowledge transfer to practitioners and enhance the exchange between academia, policy and practice.

/pdf/treatment-technologies-for-urban-solid-biowaste-to-create-3tgqhscs3u.pdf

Treatment technologies for urban solid biowaste to create value products: a review with focus on low- and middle-income settings

Vermicomposting of different types of waste using Eisenia foetida: A comparative study

A robust technique for biometric image authentication using invisible watermarking

Almost every person today owns a mobile phone with at least the most basic facilities like messaging and calling. Spam calls are already infamous for the constant ringing of cell phones for promotional or fraudulent pitching to innocent customers. With the reducing costs of bulk messaging services from network providers, a massive base of these spam calls has shifted to messaging. SMS, standing for a short messaging service, has become a dumping ground of unwanted product descriptions and scam offers. Here, in this scenario, classification becomes a necessity. Classification in this context occurs as separating spam messages from ‘ham’ or legitimate messages. For this aforementioned purpose, we used natural language processing techniques and machine learning algorithms in this paper. We used four simple classification models on a dataset from UCI Machine Learning Repository. We compared the accuracies at the end, which pointed towards the most suitable model being SVM, with an accuracy of 98.797%.

SMS Spam Classification Using Machine Learning Techniques

Cowdung (Control) , Putranjiva roxburghii (5%) + Cow dung (95%), Putranjiva roxburghii (1%)+Cow dung (99%),Pongamia pinnata (5%)+ Cowdung ( 95%),Pongamia pinnata (1%) + Cowdung ( 95%), Neem leaves (5%) + Cowdung (99%), Neem leaves (1%) + Cowdung (99%),Neem cake (50%) + Cowdung (50%), Mustard cake (50%) + Cowdung (50%), Azotobactor (2.5%) + Cowdung (97.5),Biogas slurry (100%). Abstract: Comparative studies were performed to see the effect of different substrates on the earthworm biomass and growth rate of Eisenia fetida (Exotic species) and Allolobophora parva (Local species). Earthworms were reared in different substrates viz. Cowdung (Control) , Putranjiva roxburghii (5%) + Cow dung (95%), Putranjiva roxburghii(1%)+Cow dung (99%),Pongamia pinnata (5%)+ Cowdung ( 95%),Pongamia pinnata (1%) + Cowdung ( 95%), Neem leaves (5%) + Cowdung (99%), Neem leaves (1%) + Cowdung (99%),Neem cake (50%) + Cowdung (50%), Mustard cake (50%) + Cowdung (50%), Azotobactor (2.5%) + Cowdung (97.5),Biogas slurry (100%). The maximum number of local earthworm (Allolobophora parva) was observed after 45 days in 5% waste material substrate combination in following order: Neem leaves (122)> Pongamia pinnata (118) > Putranjiva roxburghii (91)> Azatobactor (62)> Biogas slurry (37). ). In case of Eisenia fetida earthworms, the growth order was: control (168), > Neem leaves (157), > Putranjiva roxburghaii (156), > Azatobactor (135) >Pongamia pinnata (112) > Biogas slurry (34). Both earthworm species could not survive in the substrate combination of neem cake and mustard cake. The observations indicate that there is a possibility to use local earthworms for vermicomposting and the required number of local earthworms Allolobophora parva may also be obtained, for waste management by culturing on suitable substrate combinations.

Culturing of exotic (Eisenia fetida) and Local (Allolobophora parva) Earthworm Species in Different Substrates for Rural Waste Management

Sentiment analysis has become an important field in the last few years. By performing sentiment analysis of user reviews, news, blogs, etc. we gain a deeper understanding of the general opinion towards a movie, product, etc. Sentiment Analysis is a very valuable tool for organizations to understand the opinion of the public towards their product, service movie, etc. Rather than reading an entire post, blog, or review, Sentiment Analysis allows companies to know the general opinion about their product or movie by deducing the emotion present in the piece of text. Sentiment analysis identifies the keywords in a piece of text and determines the emotion contained in it. Several works have been carried out in the subject area of sentiment analysis on English but hardly any work on Hindi. Hindi is a widely spoken language with a growing number of speakers. The social media platforms too see a large number of reviews, blogs in Hindi. Due to the rising amount of web content in Hindi, there was a requirement to perform sentiment analysis on the Hindi language. We propose a system for sentiment analysis on Hindi by using the Bag of Words model and applying four Machine Learning models.

Payal Garg

Papers

Vermicomposting of different types of waste using Eisenia foetida: A comparative study

A robust technique for biometric image authentication using invisible watermarking

SMS Spam Classification Using Machine Learning Techniques

Culturing of exotic (Eisenia fetida) and Local (Allolobophora parva) Earthworm Species in Different Substrates for Rural Waste Management

Sentiment Analysis of Movie Reviews in Hindi Language Using Machine Learning