A review on value-addition to plastic waste towards achieving a circular economy.

Plastic and mixed plastic waste (PW) has received increased worldwide attention owing to its huge rate of production, high persistency in the environment, and unsustainable waste management practices. Therefore, sustainable PW management and upcycling approaches are imperative to achieve the objectives of the United Nations Sustainable Development Goals. Numerous recent studies have shown the application and feasibility of various PW conversion techniques to produce materials with better economic value. Within this framework, the current review provides an in-depth analysis of cutting-edge thermochemical technologies such as pyrolysis, gasification, carbonization, and photocatalysis that can be used to value plastic and mixed PW in order to produce energy and industrial chemicals. Additionally, a thorough examination of the environmental impacts of contemporary PW upcycling techniques and their commercial feasibility through life cycle assessment (LCA) and techno-economical assessment are provided in this review. Finally, this review emphasizes the opportunities and challenges accompanying with existing PW upcycling techniques and deliver recommendations for future research works.

Current research trends on emerging contaminants pharmaceutical and personal care products (PPCPs): A comprehensive review.

Pharmaceutical and personnel care products (PPCPs) from wastewater are a potential hazard to the human health and wildlife, and their occurrence in wastewater has caught the concern of researchers recently. To deal with PPCPs, various treatment technologies have been evolved such as physical, biological, and chemical methods. Nevertheless, modern and efficient techniques such as advance oxidation processes (AOPs) demand expensive chemicals and energy, which ultimately leads to a high treatment cost. Therefore, integration of chemical techniques with biological processes has been recently suggested to decrease the expenses. Furthermore, combining ozonation with activated carbon (AC) can significantly enhance the removal efficiency. There are some other emerging technologies of lower operational cost like photo-Fenton method and solar radiation-based methods as well as constructed wetland, which are promising. However, feasibility and practicality in pilot-scale have not been estimated for most of these advanced treatment technologies. In this context, the present review work explores the treatment of emerging PPCPs in wastewater, via available conventional, non-conventional, and integrated technologies. Furthermore, this work focused on the state-of-art technologies via an extensive literature search, highlights the limitations and challenges of the prevailing commercial technologies. Finally, this work provides a brief discussion and offers future research directions on technologies needed for treatment of wastewater containing PPCPs, accompanied by techno-economic feasibility assessment.

Heuristic Analysis of Genomic Sequence Processing Models for High Efficiency Prediction: A Statistical Perspective.

Genome sequences indicate a wide variety of characteristics, which include species and sub-species type, genotype, diseases, growth indicators, yield quality, etc. To analyze and study the characteristics of the genome sequences across different species, various deep learning models have been proposed by researchers, such as Convolutional Neural Networks (CNNs), Deep Belief Networks (DBNs), Multilayer Perceptrons (MLPs), etc., which vary in terms of evaluation performance, area of application and species that are processed. Due to a wide differentiation between the algorithmic implementations, it becomes difficult for research programmers to select the best possible genome processing model for their application. In order to facilitate this selection, the paper reviews a wide variety of such models and compares their performance in terms of accuracy, area of application, computational complexity, processing delay, precision and recall. Thus, in the present review, various deep learning and machine learning models have been presented that possess different accuracies for different applications. For multiple genomic data, Repeated Incremental Pruning to Produce Error Reduction with Support Vector Machine (Ripper SVM) outputs 99.7% of accuracy, and for cancer genomic data, it exhibits 99.27% of accuracy using the CNN Bayesian method. Whereas for Covid genome analysis, Bidirectional Long Short-Term Memory with CNN (BiLSTM CNN) exhibits the highest accuracy of 99.95%. A similar analysis of precision and recall of different models has been reviewed. Finally, this paper concludes with some interesting observations related to the genomic processing models and recommends applications for their efficient use.

Remediation of soils and sediments polluted with polycyclic aromatic hydrocarbons: To immobilize, mobilize, or degrade?

Polycyclic aromatic hydrocarbons (PAHs) are generated due to incomplete burning of organic substances. Use of fossil fuels is the primary anthropogenic cause of PAHs emission in natural settings. Although several PAH compounds exist in the natural environmental setting, only 16 of these compounds are considered priority pollutants. PAHs imposes several health impacts on humans and other living organisms due to their carcinogenic, mutagenic, or teratogenic properties. The specific characteristics of PAHs, such as their high hydrophobicity and low water solubility, influence their active adsorption onto soils and sediments, affecting their bioavailability and subsequent degradation. Therefore, this review first discusses various sources of PAHs, including source identification techniques, bioavailability, and interactions of PAHs with soils and sediments. Then this review addresses the remediation technologies adopted so far of PAHs in soils and sediments using immobilization techniques (capping, stabilization, dredging, and excavation), mobilization techniques (thermal desorption, washing, electrokinetics, and surfactant assisted), and biological degradation techniques. The pros and cons of each technology are discussed. A detailed systematic compilation of eco-friendly approaches used to degrade PAHs, such as phytoremediation, microbial remediation, and emerging hybrid or integrated technologies are reviewed along with case studies and provided prospects for future research.

Traditional System Versus DNA Barcoding in Identification of Bamboo Species: A Systematic Review.

Bamboo, a gramineous plant belonging to the family Poaceae, comprises of 1575 species from 116 genera across the globe. It has the ability to grow and evolve on degraded land and hence, can be utilized in the various applications as an alternative for plastic and wood. DNA barcoding, a long genomic sequence, identifies barcode region which shows species-specific nucleotide differences. This technology is considered as advanced molecular technique utilized for characterization and classification of the various species by applying distinctive molecular markers. Recent investigations revealed the potential application of various barcode regions such as matK, rbcL, rpoB, rpoC1, psbA-trnH, and ITS2, in identification of many bamboo species from different genus. In this review we comprehensively discussed the relevance of DNA barcoding as a tool in classification/identification of various bamboo species. We highlighted the methodology, how this advance technology overcomes the challenges associated with traditional methods along with prospects for future research.