Aquatic Plants in phytoremediation of contaminated water: Recent knowledge and future prospects

The increase of heavy metals in natural resources, including land and water has been rapidly raised due to a variety of natural methods, higher agricultural activities, contaminated irrigation water, speedy industrial development, amplified industrial wastes and mining. Heavy metals (HM) are able to remain in the environment longer time and go in the food chain, and ultimately accumulate in humans for biomagnification since they are not biodegradable. HMs contamination is extremely dangerous for humans and the ecology due to its poisonous nature. Traditional methods of cleanup are expensive and could harm the environment. Therefore, phytoremediation is an alternate method via plants to eliminate toxic HMs from the atmosphere as well as to avoid additional contamination, due to its environment-friendly, economic, efficient, exclusive and cost-effective approach. Aquatic plants can be utilized to decontaminate the contaminated sites as they are not food crops, thus reducing the danger of food chain contamination. Here, sources of HMs and their impact on human health have been briefly discussed. Several phytoremediation techniques and factors affecting the phytoremediation methods are also described. In addition, different strategies to decontaminate the metal-polluted water using aquatic plants are also reviewed. Finally, future perspectives for usages of aquatic plants in phytoremediation techniques were briefly summarised

A Novel Membrane Protein-Specific Serine/Threonine Kinase: Tissue Distribution and Role in Sperm Maturation

Our recent studies have described for the first time the purification of an ectoprotein kinase to apparent homogeneity using caprine sperm as the model. Purified ectokinase (CIK) is a novel membrane protein-specific kinase that phosphorylates serine and threonine residues of ectophosphoproteins. This study, using ELISA based on ecto-CIK antibody demonstrates that ecto-CIK level is remarkably higher in the sperm membrane than in the cytosol. The epididymal sperm maturational event as well as sperm vertical velocity is associated with a significant increase in the ecto-CIK level. Ecto-CIK, the membrane protein-specific kinase, is also present in all the tissues tested and is predominantly localized in the cell membrane. Ubiquitous localization of the novel kinase on the mammalian cell membrane suggests that the kinase may play pivotal role in gamete as well as somatic cell regulation by modulating membrane biology through serine/threonine phosphorylation of specific membrane proteins located in the ectodomains

Entrada to Secure Graph Convolutional Networks

Graph convolutional networks (GCNs) are gaining popularity due to their powerful modelling capabilities. However, guaranteeing privacy is an issue when evaluating on inputs that contain users’ sensitive information such as financial transactions, medical records, etc. To address such privacy concerns, we design Entrada, a framework for securely evaluating GCNs that relies on the technique of secure multiparty computation (MPC). For efficiency and accuracy reasons, Entrada builds over the MPC framework of Tetrad (NDSS’22) and enhances the same by providing the necessary primitives. Moreover, Entrada leverages the GraphSC paradigm of Araki et al. (CCS’21) to further enhance efficiency. This entails designing a secure and efficient shuffle protocol specifically in the 4-party setting, which to the best of our knowledge, is done for the first time and may be of independent interest. Through extensive experiments, we showcase that the accuracy of secure GCN evaluated via Entrada is on par with its cleartext counterpart. We also benchmark efficiency of Entrada with respect to the included primitives as well as the framework as a whole. Finally, we showcase Entrada’s practicality by benchmarking GCN-based fraud detection application

PentaGOD: Stepping beyond Traditional GOD with Five Parties

Secure multiparty computation (MPC) is increasingly being used to address privacy issues in various applications. The recent work of Alon et al. (CRYPTO\u2720) identified the shortcomings of traditional MPC and defined a Friends-and-Foes (FaF) security notion to address the same. We showcase the need for FaF security in real-world applications such as dark pools. This subsequently necessitates designing concretely efficient FaF-secure protocols. Towards this, keeping efficiency at the center stage, we design ring-based FaF-secure MPC protocols in the small-party honest-majority setting. Specifically, we provide (1,1)-FaF secure 5 party computation protocols (5PC) that consider one malicious and one semi-honest corruption and constitutes the optimal setting for attaining honest-majority. At the heart of it lies the multiplication protocol that requires a single round of communication with 8 ring elements (amortized). To facilitate having FaF-secure variants for several applications, we design a variety of building blocks optimized for our FaF setting. The practicality of the designed (1,1)-FaF secure 5PC framework is showcased by benchmarking dark pools. In the process, we also improve the efficiency and security of the dark pool protocols over the existing traditionally secure ones. This improvement is witnessed as a gain of up to $62\times$ in throughput compared to the existing ones. Finally, to demonstrate the versatility of our framework, we also benchmark popular deep neural networks

Ornamental Plant in phytoremediation of contaminated soils: Recent progress and future directions

Increasing anthropogenic practices for industrialization and rapid gloalization have contributed to problems of metal – induced toxicity, results in severe environmental deterioration. In the current scenario, heavy- metals contamination is a major threat to living beings of the world because of these toxic metals persist in the environment for a prolong time.   The phytoremediation is considered as a suitable process in present days to eliminate heavy-metals from environment as its cost- effectiveness, eco-friendliness etc. In the field of phytoremediation, the ornamental plants can be used for dual purpose – cleaning the environment and bringing the aesthetic value to the site. The ornamental plant is used as a test plant because of their high biomass and accumulate more heavy metal concentration from the soil. Moreover, as ornamental plants are not edible, so the risk of biomagnifications and bioaccumulation into the food web is reduced. This comprehensive review highlights recent progress on the applicability and advantages of ornamental plant for the phytoremediation potential in heavy- metals contaminated soil. In addition, briefly discuss on several factors that affecting the phytoremediation techniques of heavy metals and addressed their future directions for sustainable treatment of heavy metals. &nbsp

A review on phytoremediation capability of Tagetes erecta Linn. against heavy metals

Now a days, Phytoremediation is treated as a set of emerging techniques that use several selected plants to contain, eradicate, immobilize or degrade contaminants from water and soil in order to clean the contaminated sites. Recent researches have directed to the application of non-edible floriculture plants having the capability to erase the toxic metals from polluted environment including their aesthetic value as a good proposal for phytoremediation. The plant Tagetes erecta Linn., locally recognized as Ganda Phul (Marigold) that belongs to the family of Asteraceae can grow widely in heavy metal stress of Cd, Cr, Pb etc. The plant species can absorb and accumulate varieties of contaminated heavy metals like Pb, Cr, As, Cd, Co, Hg etc. This article includes a brief overview about the toxic impact of the Cr, Cd, and Pb on the plant. In addition, the discussion highlights recent progress on the application of phytoremediation competence of the plant, Tagetes erecta Linn. concerning with the heavy metals

Shield: Secure Allegation Escrow System with Stronger Guarantees

The rising issues of harassment, exploitation, corruption, and other forms of abuse have led victims to seek comfort by acting in unison against common perpetrators (e.g., #MeToo movement). One way to curb these issues is to install allegation escrow systems that allow victims to report such incidents. The escrows are responsible for identifying victims of a common perpetrator and taking the necessary action to bring justice to them. However, users hesitate to participate in these systems due to the fear of such sensitive reports being leaked to perpetrators, who may further misuse them. Thus, to increase trust in the system, cryptographic solutions are being designed to realize secure allegation escrow (SAE) systems. In the work of Arun et al. (NDSS\u2720), which presents the state-of-the-art solution, we identify attacks that can leak sensitive information and compromise victim privacy. We also report issues present in prior works that were left unidentified. To arrest all these breaches, we put forth an SAE system that prevents the identified attacks and retains the salient features from all prior works. The cryptographic technique of secure multi-party computation (MPC) serves as the primary underlying tool in designing our system. At the heart of our system lies a new duplicity check protocol and an improved matching protocol. We also provide additional features such as allegation modification and deletion, which were absent in the state of the art. To demonstrate feasibility, we benchmark the proposed system with state-of-the-art MPC protocols and report the cost of processing an allegation. Different settings that affect system performance are analyzed, and the reported values showcase the practicality of our solution

Find Thy Neighbourhood: Privacy-Preserving Local Clustering

Identifying a cluster around a seed node in a graph, termed local clustering, finds use in several applications, including fraud detection, targeted advertising, community detection, etc. However, performing local clustering is challenging when the graph is distributed among multiple data owners, which is further aggravated by the privacy concerns that arise in disclosing their view of the graph. This necessitates designing solutions for privacy-preserving local clustering and is addressed for the first time in the literature. We propose using the technique of secure multiparty computation (MPC) to achieve the same. Our local clustering algorithm is based on the heat kernel PageRank (HKPR) metric, which produces the best-known cluster quality. En route to our final solution, we have two important steps: (i) designing data-oblivious equivalent of the state-of-the-art algorithms for computing local clustering and HKPR values, and (ii) compiling the data-oblivious algorithms into its secure realisation via an MPC framework that supports operations over fixed-point arithmetic representation such as multiplication and division. Keeping efficiency in mind for large graphs, we choose the best-known honest-majority 3-party framework of SWIFT (Koti et al., USENIX\u2721) and enhance it with some of the necessary yet missing primitives, before using it for our purpose. We benchmark the performance of our secure protocols, and the reported run time showcases the practicality of the same. Further, we perform extensive experiments to evaluate the accuracy loss of our protocols. Compared to their cleartext counterparts, we observe that the results are comparable and thus showcase the practicality of the designed protocols