[4-(2-Aminoethyl)morpholine-κ2N,N']di-bromidocadmium(II): synthesis, crystal structure and Hirshfeld surface analysis

The title compound, [CdBr2(C6H14N2O)], was synthesized upon complexation of 4-(2-aminoethyl)morpholine and cadmium(II) bromide tetra-hydrate at 303 K. It crystallizes as a centrosymmetric dimer, with one cadmium atom, two bromine atoms and one N,N'-bidentate 4-(2-aminoethyl)morpholine ligand in the asymmetric unit. The metal atom is six-coordinated and has a distorted octa-hedral geometry. In the crystal, O⋯Cd inter-actions link the dimers into a polymeric double chain and inter-molecular C-H⋯O hydrogen bonds form R 2 2(6) ring motifs. Further C-H⋯Br and N-H⋯Br hydrogen bonds link the components into a three-dimensional network. As the N-H⋯Br hydrogen bonds are shorter than the C-H⋯Br inter-actions, they have a larger effect on the packing. A Hirshfeld surface analysis reveals that the largest contributions to the packing are from H⋯H (46.1%) and Br⋯H/H⋯Br (38.9%) inter-actions with smaller contributions from the O⋯H/H⋯O (4.7%), Br⋯Cd/Cd⋯Br (4.4%), O⋯Cd/Cd⋯O (3.5%), Br⋯Br (1.1%), Cd⋯H/H⋯Cd (0.9%), Br⋯O/O⋯Br (0.3%) and O⋯N/N⋯O (0.1%) contacts.

Mobilisation and analyses of publicly available SARS-CoV-2 data for pandemic responses

The COVID-19 pandemic has seen large-scale pathogen genomic sequencing efforts, becoming part of the toolbox for surveillance and epidemic research. This resulted in an unprecedented level of data sharing to open repositories, which has actively supported the identification of SARS-CoV-2 structure, molecular interactions, mutations and variants, and facilitated vaccine development and drug reuse studies and design. The European COVID-19 Data Platform was launched to support this data sharing, and has resulted in the deposition of several million SARS-CoV-2 raw reads. In this paper we describe (1) open data sharing, (2) tools for submission, analysis, visualisation and data claiming (e.g. ORCiD), (3) the systematic analysis of these datasets, at scale via the SARS-CoV-2 Data Hubs as well as (4) lessons learnt. This paper describes a component of the Platform, the SARS-CoV-2 Data Hubs, which enable the extension and set up of infrastructure that we intend to use more widely in the future for pathogen surveillance and pandemic preparedness.

The European Nucleotide Archive in 2023

The European Nucleotide Archive (ENA; https://www.ebi.ac.uk/ena) is maintained by the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI). The ENA is one of the three members of the International Nucleotide Sequence Database Collaboration (INSDC). It serves the bioinformatics community worldwide via the submission, processing, archiving and dissemination of sequence data. The ENA supports data types ranging from raw reads, through alignments and assemblies to functional annotation. The data is enriched with contextual information relating to samples and experimental configurations. In this article, we describe recent progress and improvements to ENA services. In particular, we focus upon three areas of work in 2023: FAIRness of ENA data, pandemic preparedness and foundational technology. For FAIRness, we have introduced minimal requirements for spatiotemporal annotation, created a metadata-based classification system, incorporated third party metadata curations with archived records, and developed a new rapid visualisation platform, the ENA Notebooks. For foundational enhancements, we have improved the INSDC data exchange and synchronisation pipelines, and invested in site reliability engineering for ENA infrastructure. In order to support genomic surveillance efforts, we have continued to provide ENA services in support of SARS-CoV-2 data mobilisation and have adapted these for broader pathogen surveillance efforts.

Synthesis, crystal structure and Hirshfeld surface analysis of di-acetato-bis-[4-(2-amino-eth-yl)morpholine]cadmium tetra-hydrate

The title coordination compound, [Cd(C2H3O2)2(C6H14N2O)2]·4H2O, was synthesized by mixing 2 moles of 4-(2-amino-eth-yl)morpholine and 1 mole of cadmium acetate in double-distilled water. The Cd atom is octa-hedrally coord-inated by two N,N'-bidentate ligands [4-(2-amino-eth-yl)morpholine] and two trans-located acetate mol-ecules. The Cd atom is located on a center of inversion, whereas the 4-(2-amino-eth-yl)morpholine and four water mol-ecules are adjacent to the acetate mol-ecules. The chair conformation of the morpholine mol-ecules is confirmed. In the crystal, adjacent metal complexes and uncoord-inated water mol-ecules are linked via N-H⋯O and O-H⋯O hydrogen-bonding inter-actions, generating R 2 2(6), R 6 6(16), R 6 6(20) and S 1 1(6) motifs and forming a three-dimensional network. A Hirshfeld surface analysis indicated the contributions of various contacts: H⋯H (71.8%), O⋯H/H⋯O (27.1%), and C⋯H/H⋯C (1.0%).

Convolutional neural network based children recognition system using contactless fingerprints

Biometric features are useful for unique identification, authentication, and security applications. Among all biometric features, fingerprints are the most commonly used because they contain ridges and valleys. There are challenges in recognizing child or infant fingerprints since the ridges are not mature as the hands are covered with a white substance and acquisition of fingerprint images is difficult. In the context of COVID-19 pandemic, contactless fingerprint acquisition gains importance as it is not infectious especially with children. In this study, a Convolutional Neural Network (CNN) based children recognition system named Child-CLEF, that uses Contact-Less Children Fingerprint (CLCF) dataset acquired using a mobile phone-based scanner is proposed. The quality of captured fingerprint images is enhanced using a hybrid image enhancement method. Furthermore, the minutiae features are extracted using the proposed Child-CLEF Net model and the identification of children is made using a matching algorithm. The proposed system is tested with a self-captured children fingerprint dataset, CLCF and publicly available PolyU fingerprint dataset. It is found that the proposed system outperforms the existing fingerprint recognition systems in terms of accuracy and equal error rate.

Cellulose-based hydrogel for adsorptive removal of cationic dyes from aqueous solution: isotherms and kinetics

The development of economic and recyclable adsorbents for removing pollutants from contaminated water is gaining increasing attention. Agro residue or nature-based material sourced absorbents could revolutionize the future of wastewater treatment. Hence in this study, nanocellulose was synthesized from coconut husk fiber and immobilized onto chitosan to form hydrogel beads. The BET surface area and zeta potential of the adsorbent nanocrystalline cellulose-chitosan hydrogel (NCC-CH) bead was 25.77 m² g^-1 and +50.6 mV, respectively. The functional group analysis also confirmed that the adsorbent had functional groups appropriate for the adsorption of textile dyes. The adsorption performance of NCC-CH and also the influence of initial dye concentration, adsorbent dose, pH, and contact time was evaluated by batch adsorption studies with crystal violet (CV) and methylene blue (MB) dyes. The most favorable operational conditions achieved through I-optimal design in response surface methodology were 0.5 g NCC-CH, 1 h, 9 pH, and 60 mg L^-1 for CV removal (94.75%) and 0.13 g NCC-CH, 1 h, 9 pH, and 30 mg L^-1 for MB removal (95.88%). The polynomial quadratic model fits the experimental data with an R ² value of 0.99 and 0.98 for CV and MB removal, respectively. The optimum depiction of the isotherm data was obtained using the Freundlich model for MB adsorption and Freundlich and Langmuir model for CV adsorption. The Dubinin-Radushkevich (D-R) isotherm was also a good fit to the adsorption of CV and MB dye, suggesting the physisorption due to its free energy of adsorption < 8 kJ mol^-1. The kinetics were effectively explained by a pseudo-second order model for both the dyes suggesting that chemical mechanisms influenced the adsorption of CV and MB dyes onto NCC-CH. The intraparticle diffusion model best suited the MB adsorption with three stages rather than the CV with a single step process. Also, the removal efficiency of adsorbent was retained at above 60% even after seven adsorption-desorption cycles indicating the effectiveness of the NCC-CH hydrogel beads for the removal of textile dyes.

The European Nucleotide Archive in 2022

The European Nucleotide Archive (ENA; https://www.ebi.ac.uk/ena), maintained by the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI), offers those producing data an open and supported platform for the management, archiving, publication, and dissemination of data; and to the scientific community as a whole, it offers a globally comprehensive data set through a host of data discovery and retrieval tools. Here, we describe recent updates to the ENA's submission and retrieval services as well as focused efforts to improve connectivity, reusability, and interoperability of ENA data and metadata.

Hybrid Grasshopper and Chameleon Swarm Optimization Algorithm for Text Feature Selection with Density Peaks Clustering

Clustering consists of various applications on machine learning, image segmentation, data mining and pattern recognition. The proper selection of clustering is significant in feature selection. Therefore, in this paper, a Text Feature Selection (FS) and Clustering using Grasshopper–Chameleon Swarm Optimization with Density Peaks Clustering algorithm (TFSC-G-CSOA-DPCA) is proposed. Initially, the input features are pre-processed for converting text into numerical form. These preprocessed text features are given to Grasshopper–Chameleon Swarm Optimization Algorithm, which selects important text features. In Grasshopper–Chameleon Swarm Optimization Algorithm, the Grasshopper Optimization Algorithm selects local feature from text document and Chameleon Swarm Optimization Algorithm selects the best global feature from local feature. These important features are tested using density peaks clustering algorithm to maximize the reliability and minimize the computational time cost. The performance of Grasshopper–Chameleon Swarm Optimization Algorithm is analyzed with 20 News groups dataset. Moreover, the performance metrics, like accuracy, precision, sensitivity, specificity, execution time and memory usage are analyzed. The simulation process shows that the proposed TFSC-G-CSOA-DPCA method provides better accuracy of 97.36%, 95.14%, 94.67% and 91.91% and maximum sensitivity of 96.25%, 87.25%, 93.96% and 92.59% compared to the existing methods such as TFSC-BBA-MCL, TFSC-MVO-K-Means C, TFSC-GWO-GOA-FCM and TFSC-WM-K-Means C, respectively.

A hybrid web analytic approach through click enabled vision based page segmentation in quest software for school students

The primary goal of this study is to optimize web content for a positive user experience and to develop a data-driven methodology to assess the success of visitor flow on a website for school children. Through Vision-Based Page Segmentation, the suggested study work intends to broaden the stated web approach’s reach and statistical inference. The improvisation has been made accordingly with the semantic structure observed from each node with the designated degree of coherence to indicate the content in spatial and block based on visual perception for each event. The click count (number of clicks) is calculated for all the possibilities of Quest Software. The most frequently accessed event is displayed at the top to enhance usability and visibility with an accuracy of about 92.80% . From the experimental analysis, it has been observed that most of the students preferred events corresponding to drawing, rhymes, and rangoli with a willingness rate of above 80%, respectively. Statistical analysis has been made using chi-square analysis, and it has been found that the levels from A to D are significant for three years with a P-value <  0.001. Sentimental analysis of feedback collected from the participants about the events is also done, and the most preferred event is suggested for the upcoming years.

A hybrid deep learning technique based integrated multi-model data fusion for forensic investigation

Digital evidence is an integral part of any trial. Data is critical facts, encrypted information that requires explanation in order to gain meaning and knowledge. The current process of digital forensic research cannot effectively address the various aspects of a complex infrastructure. Therefore, digital forensics requires the optimal processing of a complex infrastructure that differs from the current process and structure. For a long time, digital forensic research has been utilized to discuss these issues. In this research, we offer a forensic investigation hybrid deep learning approach based on integrated multi-model data fusion (HDL-DFI). First, we concentrate on digital evidence collection and management systems, which can be achieved by an integrated data fusion model with the help of an improved brain storm optimization (IBSO) algorithm. Here, we consider several multimedia data’s for evidence purposes, i.e. text, image, speech, physiological signals, and video. Then, we introduce a recurrent multiplicative neuron with a deep neural network (RM-DNN) for data de-duplication in evidence collection, which avoids repeated and redundant data. After that, we design a multistage dynamic neural network (MDNN) for sentimental analysis to decide what type of crime has transpired and classify the action on it. Finally, the accuracy, precision, recall, F1-score, G-mean, and area under the curve of our proposed HDL-DFI model implemented with the standard benchmark database and its fallouts are compared to current state-of-the-art replicas (AUC). The results of our experiments show that the computation time of the proposed model HDL-DFI is 20% and 25% lower than the previous model’s for uploading familiar and unfamiliar files, 22% and 29% lower for authentication generation, 23% and 31% lower for the index service test scenario, and 24.097% and 32.02% lower for familiarity checking.

Hydrogeochemical processes controlling the groundwater salinity in the coastal aquifers of Southern Tamil Nadu, India

The current study identifies groundwater quality issues and investigates the most important geochemical processes that control seawater intrusion using various ionic ratios, hydrochemical facies evolution, and geochemical modelling. Cl_-/Br ratio is an important indicator to identify the origin of groundwater salinity in coastal aquifers. Nineteen percent of the groundwater samples with Cl^-/Br^- ratio similar to that of Standard Mean Ocean Water (SMOW) are affected by seawater intrusion in the study area. Particularly, nine groundwater samples have high chloride values and are similar to SMOW, and it may derived salinity from seawater sources from the Bay of Bengal due to the over-pumping of production wells in the Uvari zone. Five samples are similar to SMOW, which is due to the presence of salt pan activities. The bivariate plots such as Ca²⁺ + Mg²⁺ vs Cl^-, EC vs Cl^-, and Na⁺/Cl^- ratio indicate that seawater intrusion is the primary source for groundwater salinisation. Evaporation is the dominant process controlling groundwater chemistry, rather than rock-water interaction and precipitation, according to mechanisms controlling groundwater chemistry. Direct ion exchange and converse ion exchange are the critical controlling factors for groundwater salinisation, according to the hydrochemical facies evolution diagram (HFED). The water quality index (WQI) shows that most groundwater belongs to the poor to the marginal category. The saturation indices show that the groundwater samples are saturated with minerals such as dolomite, calcite, aragonite and magnesite. Therefore, these minerals are susceptible to precipitation due to the effective leaching of calcareous minerals from the bedrocks. Compiled hydrogeochemical analysis and multivariate statistical analysis revealed that the Tiruchendur and Uvari zone was affected by the seawater intrusion and led to an increase in the salinity of the groundwater.

The European Nucleotide Archive in 2021

The European Nucleotide Archive (ENA, https://www.ebi.ac.uk/ena), maintained at the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI) provides freely accessible services, both for deposition of, and access to, open nucleotide sequencing data. Open scientific data are of paramount importance to the scientific community and contribute daily to the acceleration of scientific advance. Here, we outline the major updates to ENA’s services and infrastructure that have been delivered over the past year.

The COVID-19 Data Portal: accelerating SARS-CoV-2 and COVID-19 research through rapid open access data sharing

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic will be remembered as one of the defining events of the 21st century. The rapid global outbreak has had significant impacts on human society and is already responsible for millions of deaths. Understanding and tackling the impact of the virus has required a worldwide mobilisation and coordination of scientific research. The COVID-19 Data Portal (https://www.covid19dataportal.org/) was first released as part of the European COVID-19 Data Platform, on April 20th 2020 to facilitate rapid and open data sharing and analysis, to accelerate global SARS-CoV-2 and COVID-19 research. The COVID-19 Data Portal has fortnightly feature releases to continue to add new data types, search options, visualisations and improvements based on user feedback and research. The open datasets and intuitive suite of search, identification and download services, represent a truly FAIR (Findable, Accessible, Interoperable and Reusable) resource that enables researchers to easily identify and quickly obtain the key datasets needed for their COVID-19 research.

Potential bactericidal activity of S. nux-vomica-ZnO nanocomposite against multidrug-resistant bacterial pathogens and wound-healing properties

Multidrug resistance in bacterial strains has become the greatest challenge for healthcare professionals for treating non-healing ulcers such as diabetic foot infections (DFI). Plant-mediated synthesis of S. nux-vomica-ZnO nanocomposite appears as a potential new alternative therapeutic agent that might be capable of tackling antibiotic-resistant bacterial pathogens and for treating a non-healing ulcer. The aim of the study was to investigate the antibacterial potential of S. nux-vomica-ZnO nanocomposite biosynthesised from Strychnos nux-vomica against multidrug-resistant organisms (MDROs) from DFU, wound-healing properties, and cytotoxic effects. The antibacterial potential was assessed by minimum inhibitory concentration (MIC)/ minimum bactericidal concentration (MBC) assays, time-kill kinetics, protein-leakage, and flow cytometric analysis. The wound-healing properties were assessed by scratch assay on mouse L929 fibroblastic cell line to quantify cell migration towards the injured area. Cytotoxicity was assessed using 3-[4,5-dimethyl-2-thiazol-yl]-2,5-diphenyl- 2H-tetrazolium bromide (MTT) cellular viability assay on the L929 cell line and human embryonic kidney epithelial (HEK-293) cell line. Strychnos nux-vomica-ZnO nanocomposite at a size range of 10-12 nm exhibited significant bactericidal potency at a concentration of 100-200 μg/ml against MDR-Methicillin-resistant Staphylococcus aureus, MDR-Escherichia coli, MDR-Pseudomonas aeruginosa, MDR-Acinetobacter baumannii, and also against standard bacterial strains S. aureus ATCC 29213, E. coli ATCC 25922, P. aeruginosa ATCC 27853, E. faecalis ATCC 29212. S. nux-vomica-ZnO nanocomposite also exhibited wound-healing and reduced cytotoxic properties at the antimicrobially active concentrations. Our findings thus suggested remarkable bactericidal properties of S. nux-vomica-ZnO nanocomposite and can be further exploited towards for the development of an antibacterial agent against the threatening superbugs.

Synthesis and characterization of ZnO phytonanocomposite using Strychnos nux-vomica L. (Loganiaceae) and antimicrobial activity against multidrug-resistant bacterial strains from diabetic foot ulcer

Nanobiotechnology has been emerged as an efficient technology for the development of antimicrobial nanoparticles through an eco-friendly approach. In this study, green synthesized phytonanocomposite of ZnO from Strychnos nux-vomica leaf aqueous extract was characterized by X-ray diffraction analysis (XRD), UV–visible-spectroscopy, Photoluminescence spectroscopy (PL), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), High-resolution Transmission Electron Microscopy (HR-TEM), and Energy dispersive X-ray analysis (EDX). Antibacterial activity was investigated against multidrug-resistant bacteria (MDR) isolated from diabetic foot ulcers (DFUs), such as MDR–methicillin resistant Staphylococcus aureus (MRSA), MDR–Escherichia coli, MDR–Pseudomonas aeruginosa, MDR–Acinetobacter baumannii, as well as against standard bacterial strains, S. aureus ATCC 29213, E. coli ATCC 25922, P. aeruginosa ATCC 27853, and E. faecalis ATCC 29212 through disc diffusion assays on Muller Hinton Agar. The characterization studies revealed a size-controlled synthesis of quasi-spherical hexagonal wurtzite structured ZnO phytonanocomposite with an average size of 15.52 nm. Additionally, remarkable bactericidal activities against MDR clinical as well as ATCC bacterial strains were exhibited, with a maximum zone of inhibition of 22.33 ± 1.53 mm (against S. aureus ATCC 29213) and 22.33 ± 1.16 mm (MDR–MRSA) at a concentration of 400 µg/mL. This study thus established the possibility of developing antimicrobial ZnO nanocomposite of Strychnos nux-vomica leaf extract to combat developing drug resistance currently being experienced in health care facilities.

A baseline record of trace elements concentration along the beach placer mining areas of Kanyakumari coast, South India

Trace element concentration in the beach placer mining areas of Kanyakumari coast, South India was assessed. Sewage and contaminated sediments from mining sites has contaminated the surface sediments. Enrichment factor indicates moderately severe enrichment for Pb, minor enrichment for Mn, Zn, Ni, Fe and no enrichment for Cr and Cu. The Igeo values show higher concentration of Pb ranging in the scale of 3-4, which shows strong contamination due to high anthropogenic activity such as mining and terrestrial influences into the coastal regions. Correlation coefficient shows that most of the elements are associated with each other except Ni and Pb. Factor analysis reveals that Mn, Zn, Fe, Cr, Pb and Cu are having a significant loading and it indicates that these elements are mainly derived from similar origin. The cluster analysis clearly indicated that the mining areas are grouped under cluster 2 and non-mining areas are clustered under group 1.

In Vitro Cytotoxicity Analysis of Chloroform Extract of Novel Poly Herbal Formulation

Objective: It is of interest to investigate the in vitro cyto toxicity effects of chloroformic extract of Novel polyherbal formulation were studied. Materials and Methods: Cytotoxicity of the crude extract of polyherbal formulation was evaluated on LLCMK2 monkey kidney epithelial cells and Cell viability was determined by using MTT assay. Results and Discussion: Our results indicate that the non toxic nature of a poly herbal formulation of Novel polyherbal formulation on control and experimental cell lines. Conclusion: The current mode of treatment for various diseases including cancer is based on synthetic drugs. These drugs are effective but they show serious adverse effects and also alter the genetic and metabolic activity of the patient. Furthermore, in vivo activity of the active compounds of a poly herbal formulation Novel polyherbal formulation needs to be determined in animal models and human subjects, so as to determine their efficacy in a metabolic environment.

Evolution of a Hybrid Model for an Effective Perimeter Security Device

Clustering and classification models, or hybrid models are the most widely used models that can handle the diverse nature of NIDS dataset. Dirichlet process clustering technique is a non-parametric Bayesian mixture model that considers the data distribution of the dataset for the formation of distinct clusters. The number of clusters is not known a priori and it differs across different datasets. Determining the number of clusters based on the distribution of data instances can increase the performance of the model. Naive Bayes model, a supervised learning classification technique, maintains a better computational efficiency, by reducing the training time. In this paper, we propose a hybrid model to exploit the positive aspect of proper clustering of data instances and the computational efficiency in building a NIDS. RIPPER algorithm is used to extract rules from the traffic description for updation of the rule database. Experiments were conducted in the KDD CUP’99 and SSENet-2011 datasets to study the performance of the proposed model. Also, a comparison of three hybrid methods with the proposed hybrid model was carried out. The results showed that the proposed hybrid model is superior in building a robust perimeter security device.

Antiproliferative efficacy of Tabernaemontana divaricata against HEP2 cell line and Vero cell line

Background:

Laryngeal cancer may also be called cancer of the larynx or laryngeal carcinoma. Conventional plants are a precious source of novel anticancer agents and are still in performance better role in health concern. The study was intended to estimation of the anticancer activity of the chloroformic extract of Tabernaemontana divaricata on the human epidermoid larynx carcinoma cell line (Hep 2).

Materials and Method:

The aerial parts (leaves, stem, and flowers) of T. divaricata were tested for its inhibitory effect in 96 microplate formats against Hep 2 cell line. The anticancer activity of samples on Hep 2 and Vero was determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay and various enzymatic parameters like catalase, reduced glutathione (GSH), GSH peroxidase, and superoxide anion scavenging activity. Viable cells were determined by the absorbance at 540 nm. Measurements were performed, and the concentration required for a 50% inhibition of viability (IC50) was determined graphically. The effect of the samples on the proliferation of Hep 2 and Vero cells was expressed as the % cell viability.

Results:

The extract on Hep 2 cell line up to 7.8 μg/ml and that IC50 value on Hep 2 cell line was 112 μg whereas 94 μg for Vero cell line. Hence, T. divaricata has lesser significant action on Vero cell line.

Conclusion:

Medicinal plant drug discovery continues to provide new and important leads against various pharmacological targets including cancer. Our results clearly indicate the anticancer property of the medicinal plant T. divaricata against the human laryngeal carcinoma cell lines (Hep 2 cell line).

Mapping of coastal aquifer vulnerable zone in the south west coast of Kanyakumari, South India, using GIS-based DRASTIC model

The south west coast of Kanyakumari district in Tamil Nadu, India, is significantly affected by seawater intrusion and diffusion of pollutants into the aquifers due to unregulated beach placer mining and other anthropogenic activities. The present study investigates the vulnerability of the coastal aquifers using Geographic Information System (GIS)-based DRASTIC model. The seven DRASTIC parameters have been analyzed using the statistical equation of this model to demarcate the vulnerable zones for aquifer contamination. The vulnerability index map is prepared from the weighted spatial parameters, and an accounting of total index value ranged from 85 to 213. Based on the categorization of vulnerability classes, the high vulnerable zones are found near the beach placer mining areas between Manavalakurichi and Kodimanal coastal stretches. The aquifers associated with settlements and agricultural lands in the middle-eastern part have experienced high vulnerability due to contaminated water bodies. Similarly, the coastal areas of Thengapattinam and Manakudi estuary and around the South Tamaraikulam have also been falling under high vulnerability condition due to backwater and saltpan. In general, the nearshore region except the placer mining zone and the backwater has a moderately vulnerable condition, and the vulnerability index values range from 149 to180. Significantly, the northern and northeastern uplands and some parts of deposition zones in the middle-south coast have been identified as low to no vulnerable conditions. They are structurally controlled by various geological features such as charnockite, garnet biotite gneiss and granites, and sand dunes, respectively. The aquifer vulnerability assessment has been cross-verified by geochemical indicators such as total dissolved solids (TDS), Cl(-), HCO₃(-), and Cl(-)/HCO₃(-) ratio. The high ranges of TDS (1,842--3,736 mg/l) and Cl(-) (1,412--2,112 mg/l) values are well correlated with the observed high vulnerable zones in the study area. The Cl(-)/HCO₃(-) ratio (7.13 to 12.18) of the high vulnerable zone obviously indicates deterioration of the aquifer contamination. Sensitivity analysis has also been performed to evaluate sensitivity of the individual DRASTIC parameters to aquifer vulnerability. This reveals the net recharge rate and groundwater table depth are becoming more sensitive to aquifer contamination. It is realized that the GIS is an effective platform for aquifer vulnerability mapping with reliable accuracy, and hence, the study is more useful for sustainable water resource management and the aquifer conservation.

Near-infrared light-responsive nanomaterials in cancer therapeutics

Near-infrared light sensitive nanomaterials provide ideal nanoplatforms in site specific noninvasive cancer therapy.

Morpholin-4-ium hydrogen l-tartrate monohydrate

In the title compound, C₄H₁₀NO⁺·C₄H₅O₆⁻·H₂O, the morpholine ring adopts a chair conformation. In the crystal, the tartrate anions are linked via O—H⋯O hydrogen bonds, forming chains propagating along [101]. These chains are linked via N—H⋯O and O—H⋯O hydrogen bonds, involving the morpholinium cation and the water molecule, forming a three-dimensional network.

Reprinted article "Factors associated with early failure of arteriovenous fistulae for haemodialysis access"

The radiocephalic arteriovenous fistula remains the method of choice for haemodialysis access. In order to assess their suitability for fistula formation, the radial arteries and cephalic veins were examined preoperatively by ultrasound colour flow scanner in conjunction with a pulse-generated run-off system. Intraoperative blood flow was measured after construction of the fistulae. Post-operative follow-up was performed at various intervals to monitor the development of the fistulae. Radial artery and cephalic vein diameter less than 1.6 mm was associated with early fistula failure. The intraoperative fistula blood flow did not correlate with the outcome of the operation probably due to vessel spasm from manipulation. However, blood flow velocities measured non-invasively 1 day after the operation were significantly lower in fistulae that failed early compared with those that were adequate for haemodialysis. Most of the increase in fistula diameter and blood flow occur within the first 2 weeks of surgery.

Vice to virtue: intracellular biogenic nanoparticles for the generation of carbon supported catalysts

Intracellular biogenic nanoparticles are considered disadvantageous as the separation of the nanoparticles from the biomass becomes intricate. However realizing the importance of carbon supported catalyst for many important organic reactions we envisaged these nanoparticles as a source for carbon supported catalyst. Herein we demonstrate the heat treatment of intracellular biogenic nanoparticles under inert atmosphere as an efficient method for the preparation of carbon supported metal oxide catalysts. Aspergillus ochraceus, a fungus isolated from foundries, on incubation with K2TiF6 led to the synthesis of intracellular titanium oxide nanoparticles. The nanoparticles embedded biomass upon heat treatment at 600 degrees C in a nitrogen environment gave titanium oxide nanoparticles implanted in a carbonaceous matrix. The material thus formed was characterized using FTIR spectroscopy, Raman spectroscopy, HRTEM and X-ray diffraction. Appreciable benzaldehyde selectivity was observed when styrene oxidation was carried out over such immobilized catalysts. The conversion rate was determined to be 76% and the benzaldehyde selectivity was greater than 80%.

Accuracy of 64-slice coronary CT angiography in predicting percentage diameter stenosis

OBJECTIVE

Aim of our study was to evaluate the diagnostic accuracy of 64-slice CT coronary angiogram in measuring the percentage diameter stenosis compared to invasive angiography.

METHODS AND RESULTS

100 consecutive patients with more than 50% stenosis in at least one major coronary artery measured by 64-slice CT angiogram were included in the study. Patients with atrial fibrillation, history of allergy to contrast agent, acute coronary syndrome, renal insufficiency, history of previous coronary bypass surgery or percutaneous transluminal coronary stent, heart rate more than 70 per minute at the time of scan in spite of beta-blocker therapy, and calcium score >2000 Agaston units were not included in the study. 15-segment American Heart Association classification was used, and segments were compared using qualitative angiography. 192 segments (12.80%) could not be assessed due to poor image quality. The major cause for poor image quality was dense calcification precluding the luminal assessment (60.42%). Comparing the maximal percentage diameter stenosis by 64-slice CT versus invasive angiogram, the Spearman correlation coefficient between the two modalities was 0.788 and p value was <0.001. Bland-Altman analysis showed a mean difference in percentage stenosis of 2.1 +/- 16.22%. A total of 91.97% (401 of 436) of segments were within 1.96 standard deviations.

CONCLUSION

This study shows that 64-slice CT coronary angiogram is accurate in detecting percentage diameter stenosis compared to coronary angiogram if the image quality is good. Calcifications and motion artifacts are the main culprits of poor image quality.