Government Medical College Thoothukudi

The recent developments made regarding the novel, cost-effective, and environmentally friendly nanocatalysts for the electrochemical sensing of biomolecules, pesticides, nitro compounds and heavy metal ions are discussed in this review article.

Polyhydroxyalkanoates (PHAs) are storage granules found in bacteria that are essentially hydroxy fatty acid polyesters. PHA molecules appear in variety of structures, and amongst all types of PHAs, polyhydroxybutyrate (PHB) is used in versatile fields as it is a biodegradable, biocompatible, and ecologically safe thermoplastic. The unique physicochemical characteristics of these PHAs have made them applicable in nanotechnology, tissue engineering, and other biomedical applications. In this review, the optimization, extraction, and characterization of PHAs are described. Their production and application in nanotechnology are also portrayed in this review, and the precise and various production methods of PHA-based nanoparticles, such as emulsion solvent diffusion, nanoprecipitation, and dialysis are discussed. The characterization techniques such as UV-Vis, FTIR, SEM, Zeta Potential, and XRD are also elaborated.

The main objective of the work is to study the different methods to fabricate zirconia reinforced alumina composite materials. Powder forming process is selected as the suitable fabrication method among the different processing methods. The alumina and zirconia are taken under different ratio for fabrication of the specimens. Further the powder is compacted and sintered. The hardness and the compression strength of the specimen are found. The characterization studies of the fabricated material composites are studied from the experiment conducted. The material properties are found and the results that by adding ZrO2 the properties of the composite are improved.

Raw seeds of tribal pulses Atylosia scarabaeoides, Canavalia gladiata, Lablab purpureus var. lignosus, Neonotonia wightii var. coimbatorensis, Rhynchosia filipes, Vigna trilobata and Vigna unguiculata subsp. unguiculata were investigated for their proximate composition, minerals, vitamins (niacin and ascorbic acid) and certain anti-nutritional substances. The seeds of L. purpureus var. lignosus and V. trilobata had a higher content of crude protein than the commonly consumed Indian pulses. The seeds were found to be a rich source of minerals like potassium when compared with recommended dietary allowance values. The total free phenolics, tannins, 3,4-dihydroxyphenylalanine and hydrogen cyanide were also analysed.

Tuticorin corporation stretches geographically from 8°43′–8°51′N latitude and 78°5′–78°10′E longitude, positioned in the East–West International sea routes on the South–East coast of India. The rapid urban developments in the past two decades of Tuticorin have caused depletion of groundwater quantity, and deterioration of quality through excessive consumption and influx of pollutants from natural and anthropogenic activities. The water samples collected in the field were analyzed for electrical conductivity, pH, total dissolved solids, major cations like calcium, magnesium, sodium, potassium, and anions SUCH AS bicarbonate, carbonate, chloride, nitrate and sulfate, in the laboratory using the standard methods given by the American Public Health Association. In order to assess the groundwater quality, 36 groundwater samples had been collected in year 2011. The geographic information system-based spatial distribution map of different major elements has been prepared using ArcGIS 9.2. The Piper plot shows that most of the groundwater samples fall in the field of Ca2+-Mg2+–Cl−-SO42− and Na+-K+–Cl−-HCO3− by projecting the position on the plots in the triangular field. The cation concentration indicate that 83, 39 and 22 % of the K+, Na+, Ca2+ concentrations exceed the WHO limit. As per Wilcox’s diagram and US Salinity laboratory classification, most of the groundwater samples are not suitable for irrigation due to the presence of high salinity and medium sodium hazard. Irrigation waters classified based on sodium absorption ratio, have revealed that 52 % groundwater are in general safe for irrigation, which needs treatment before use. permeability index also indicates that the groundwater samples are suitable for irrigation purpose.

Summary Cloud computing offers comfortable service to business sectors as they can concentrate on their products. Over the internet, cloud computing is liable to various security threats and attacks which is a primary obstacle to the growth of cloud computing services. Distributed denial of service (DDoS) is one such attack that exploits cloud computing services using compromised machines; hence, its detection is a significant field of research. Several DDoS detection schemes have been proposed in the past, but they fail to detect real‐time active DDoS attacks because of their growth in severity and volume. Machine learning (ML) techniques are efficient in making predictions; hence, in this study, a hybrid ML intrusion detection system (IDS) model is proposed. The performance of the proposed IDS model is improved by employing a 10‐fold cross‐validation technique to perform feature selection, reducing data dimensions on the publicly available benchmark NSL‐KDD dataset. Performance validation of the proposed hybrid IDS model is done using the confusion matrix. Support vector machine (SVM) parameters are fine‐tuned using hybrid Harris Hawks optimization (HHO) and particle swarm optimization (PSO) algorithms. The performance of these hybrid algorithms is compared with other classical algorithms such as C4.5, K‐nearest neighbor, and SVM using performance metrics such as precision, sensitivity, specificity, F1 score, and accuracy. From these comparisons, it can be inferred that the proposed SVM with hybrid optimization HHO‐PSO machine learning IDS model performs better DDoS detection with good performance metric values.

In this study Cassia angustifolia (senna) is used for the environmentally friendly synthesis of silver nanoparticles. Stable silver nanoparticles having symmetric surface plasmon resonance (SPR) band centred at 420 nm were obtained within 10 min at room temperature by treating aqueous solutions of silver nitrate with C. angustifolia leaf extract. The water soluble components from the leaves, probably the sennosides, served as both reducing and capping agents in the synthesis of silver nanoparticles. The nanoparticles were characterized using UV–Vis, Fourier transform infrared (FTIR) spectroscopic techniques and transmission electron microscopy (TEM). The nanoparticles were poly-dispersed, spherical in shape with particle size in the range 9–31 nm, the average size was found to be 21.6 nm at pH 11. The zeta potential was –36.4 mV and the particles were stable for 6 months. The crystalline phase of the nanoparticles was confirmed from the selected area diffraction pattern (SAED). The rate of formation and size of silver nanoparticles were pH dependent. Functional groups responsible for capping of silver nanoparticles were identified from the FTIR spectrum. The synthesized silver nanoparticles exhibited good antibacterial potential against Escherichia coli and Staphylococcus aureus.

Accurate classification of Pap smear images becomes the challenging task in medical image processing. This can be improved in two ways. One way is by selecting suitable well defined specific features and the other is by selecting the best classifier. This paper presents a nominated texture based cervical cancer (NTCC) classification system which classifies the Pap smear images into any one of the seven classes. This can be achieved by extracting well defined texture features and selecting best classifier. Seven sets of texture features (24 features) are extracted which include relative size of nucleus and cytoplasm, dynamic range and first four moments of intensities of nucleus and cytoplasm, relative displacement of nucleus within the cytoplasm, gray level cooccurrence matrix, local binary pattern histogram, tamura features, and edge orientation histogram. Few types of support vector machine (SVM) and neural network (NN) classifiers are used for the classification. The performance of the NTCC algorithm is tested and compared to other algorithms on public image database of Herlev University Hospital, Denmark, with 917 Pap smear images. The output of SVM is found to be best for the most of the classes and better results for the remaining classes.

The growth of industry fulfills our necessity and promotes economic development. However, pollutants from such industries pollute water bodies which pose a high risk for living organisms. Thus, researchers have been urged to develop an efficient method to remove toxic heavy metal ions from water bodies. The adsorption method shows promising results for the removal of heavy metal ions and is easy to operate on a large scale, thus can be applied to practical applications. Numerous adsorbents were developed and reported, among them hydrogels, which attract great attention because of the reusability, ease of preparation, and handling. Hydrogels are generally prepared by the cross-linking of polymers that result in a three-dimensional structure, showing high porosity and high functionality. They are hydrophilic in nature because of the functional groups, and are non-toxic. Thus, this review provides various methods of hydrogel adsorbents preparation and summarizes recent progress in the use of hydrogel adsorbents for the removal of heavy metal ions. Further, the mechanism involved in the removal of heavy metal ions is briefly discussed. The most recent studies about the adsorption method for the treatment of heavy metal ions contaminated water are presented.

Distributed denial of service (DDoS) attack is a subclass of denial of service attack that performs severe attack in a cloud computing environment. It makes a malicious attempt to disturb the usual services of any network or server by using botnets. Hence, an efficient intrusion detection system (IDS) is essential to detect this attack. Some limitations in the existing IDS models for DDoS attack detection are delayed convergence, local stagnation issues, and local and global optimal trapping issues. These limitations are met by the recurrent neural network (RNN) and deep learning- (DL-) based proposed models that can utilize the previous states of the hidden neuron. The proposed research has used a long short-term memory (LSTM) recurrent neural network and autoencoder- and decoder-based deep learning strategy with gradient descent learning rule. The network parameters like weight vectors and bias coefficient are tuned optimally by employing the proposed a hybrid Harris Hawks optimization (HHO) and particle swarm optimization (PSO) algorithm. The proposed hybrid optimization algorithm selects the essential attributes, and the results obtained confirmed that the proposed LSTM and deep learning model outperformed all other models developed in the literature.

ABSTRACT Groundwater is a dynamic and replenishable natural resource. The numerical modeling techniques serve as a tool to assess the effect of artificial recharge from the water conservation structures and its response with the aquifers under different recharge conditions. The objective of the present study is to identify the suitable sites for artificial recharge structures to augment groundwater resources and assess its performance through the integrated approach of Geographic Information System (GIS) and numerical groundwater modeling techniques using MODFLOW software for the watershed located in the Kodaganar river basin, Dindigul district, Tamil Nadu. Thematic layers such as geology, geomorphology, soil, runoff, land use and slope were integrated to prepare the groundwater prospect and recharge site map. These potential zones were categorized as good (23%), moderate (54%), and poor (23%) zones with respect to the assigned weightage of different thematic layers. The major artificial recharge structures like percolation ponds and check dams were recommended based on the drainage morphology in the watershed. Finally, a three-layer groundwater flow model was developed. The model was calibrated in two stages, which involved steady and transient state condition. The transient calibration was carried out for the time period from January 1989 to December 2008. The groundwater model was validated after model calibration. The prediction scenario was carried out after the transient calibration for the time period of year up to 2013. The results show that there is 15 to 38% increase in groundwater quantity due to artificial recharge. The present study is useful to assess the effect of artificial recharge from the proposed artificial structures by integrating GIS and groundwater model together to arrive at reasonable results.

Three anthracene-based Schiff base complexes, R1-R3 (R1 = (E)-N´-((anthracen-10-yl)methylene)benzohydrazide; R2 = (E)-1-((anthracen-10-yl)methylene)-4-phenylsemicarbazide; and R3 = (E)-1-((anthracen-10-yl)methylene)-4-phenylthiosemicarbazide) were synthesized from 9-anthracenecarboxaldehyde, benzohydrazide, 4-phenylsemicarbazide and 4-phenylthiosemi-carbazide respectively, and characterized by various spectral techniques. The absorption spectral characteristics of R1-R3 were bathochromically tuned to the visible region by extending the π conjugation. These target compounds were weakly fluorescent in tetrahydrofuran (THF) solution because of rapid isomerization of the C=N double bond in the excited state. However, the aqueous dispersion of R1-R3 in the THF/water mixture by the gradual addition of water up to 90% resulted in an increase in the fluorescence intensity mainly due to aggregation-induced emission enhancement (AIEE) properties. The formation of nanoaggregates of R1-R3 were confirmed by scanning electron microscopy (SEM) and atomic force microscopy (AFM) techniques. The compounds R1-R3 are ideal probes for the fluorescence sensing of bovine serum albumin (BSA) and breast cancer cells by optical cell imaging.

Heavy metals and microbiological contamination were investigated in groundwater in the industrial and coastal city of Thoothukudi. The main sources of drinking water in this area are water bores which are dug up to the depth of 10–50 m in almost every house. A number of chemical and pharmaceutical industries have been established since past three decades. Effluents from these industries are reportedly being directly discharged onto surrounding land, irrigation fields and surface water bodies forming point and non-point sources of contamination for groundwater in the study area. The study consists of the determination of physico-chemical properties, trace metals, heavy metals and microbiological quality of drinking water. Heavy metals were analysed using Inductively Coupled Plasma Mass Spectrometry and compared with the (WHO in Guidelines for drinking water quality, 2004) standards. The organic contamination was detected in terms of most probable number (MPN) test in order to find out faecal coliforms that were identified through biochemical tests. A comparison of the results of groundwater samples with WHO guidelines reveals that most of the groundwater samples are heavily contaminated with heavy metals like arsenic, selenium, lead, boron, aluminium, iron and vanadium. The selenium level was higher than 0.01 mg/l in 82 % of the study area and the arsenic concentration exceeded 0.01 mg/l in 42 % of the area. The results reveal that heavy metal contamination in the area is mainly due to the discharge of effluents from copper industries, alkali chemical industry, fertiliser industry, thermal power plant and sea food industries. The results showed that there are pollutions for the groundwater, and the total Coliform means values ranged from 0.6–145 MPN ml−1, faecal Coliform ranged from 2.2–143 MPN ml−1, Escherichia coli ranged from 0.9 to 40 MPN ml−1 and faecal streptococci ranged from 10–9.20 × 102 CFU ml−1. The coastal regions are highly contaminated with total coliform bacteria, faecal coliform bacteria and E. coli. This might be due to the mixing of sewage from Thoothukudi town through the Buckle channel and fishing activity.

The present study focused on the estimation of submarine groundwater discharge (SGD) and the effects of nutrient fluxes due to the SGD process. The parameters of SGD such as magnitude, character, and nutrient flux in Punnakayal region of South East coast of India were evaluated using multiple tracers of groundwater inputs in 2019. It was found that the elevated values for the tracers in the study area, displayed a gradational change in the values as move from estuarine part to the offshore. Simultaneous occurrence of fresh and saline SGD is observed on the study sites. Also, indicated that the SGD fluxes ranged from 0.04 to 0.12 ​m3 ​m−2 ​d−1 ​at the estuary and 0.03–0.15 ​m3 ​m−2 ​d−1 ​at the groundwater site. A substantially increased value for 222Rn activities is distinguished in the estuary to values over 312 dpm L−1. Nutrient embellishments were generally greatest at locations with substantial meteoric elements in groundwater; however, the recirculation of saltwater through the geological formation could provide a way of transferring terrestrially-derived nutrients to the coastal zone at many places.

Insects, integral to Earth's ecosystems, play multifaceted roles that underpin environmental balance and human survival. Spanning roles from pollination to decomposition, these organisms also intersect with socio-economic, cultural, and public health sectors. This review delves into the diverse spheres of insect interactions within ecosystems, from their evolutionary histories to their roles as both predators and prey. The paper sheds light on the intricate predator-prey dynamics, emphasizing insects' roles in pest control and as pivotal food sources for various taxa. The significance of insects in soil ecosystems is elaborated upon, highlighting their contribution to soil health, nutrient cycling, and plant growth. With the looming threats of climate change, habitat destruction, and pollution, insects face unprecedented challenges, which in turn can have cascading effects on ecosystems. In the realm of public health, the review underscores the role of insects as disease vectors, necessitating a balanced approach to ecosystem health and disease management. As vectors, they also catalyze the spread of diseases, creating an intricate balance between maintaining biodiversity and safeguarding human health. The review also touches upon the cultural and economic contributions of insects, from traditional medicine to their utilization in contemporary diets, demonstrating their deep-rooted ties with human societies. With burgeoning technological advancements, the research landscape in entomology is undergoing a seismic shift. Embracing tools such as molecular studies, drones, and AI, the field is poised for groundbreaking insights. As the review suggests, the path forward demands an interdisciplinary approach, amalgamating knowledge from varied scientific domains to grasp the complexities of insect behaviors and interactions fully. In conclusion, insects, though diminutive in size, cast a vast shadow on our planet's functioning. Understanding their roles, challenges, and potential can pave the way for sustainable futures, balancing ecological health with human progress.

Chromatographic characterization and the GC-MS evaluation of the black pigmented ink of Loligo duvauceli in the present study have yielded an array of bioactive compounds with potent antimicrobial property. Facing an alarm of antimicrobial resistance globally, a need for elucidating antimicrobial agents from natural sources will be the need for the hour. In this view, this study is aimed at characterizing the black pigmented ink of the Indian squid L. duvauceli. The squid ink was subjected to crude solvent extraction and was fractionated by silica gel column chromatography. TLC and HPTLC profiles were recorded. Antimicrobial bioassay of the squid ink fractions was done by agar well diffusion method. The antimicrobial fraction was then characterized using GC-MS analysis. The results showed that the n-hexane extract upon column fractionation yielded a total of 8 fractions with the mobile phase of Hex/EtOAc in different gradients. TLC and HPTLC profiles showed a single spot with a retention factor of 0.76. Fraction 1 showed significant antibacterial activity against Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, and Lactobacillus acidophilus and a promising antifungal activity against Candida albicans. The antimicrobial fraction upon GC-MS analysis of bis(2-ethylhexyl) phthalate (BEHP) possesses the highest percentage of area normalisation (91%) with other few minor constituents. The study is concluded by stating that the antimicrobial efficacy of the squid ink might be due to the synergistic effects of the phthalate derivative and the other minor volatile compounds analysed in the squid ink.

ABSTRACT Groundwater qualities of coastal aquifers in the Ottapidaram taluk of Thoothukudi district, Tamil Nadu have been extensively monitored in post monsoon seasons in 2014 to assess its suitability in relation to domestic and drinking uses in four regions (N-S-E-W). 34 groundwater samples were analyzed for various physico-chemical attributes like pH, electrical conductivity (EC), Total dissolved solid (TDS), Na, K, Ca, Mg, Cl, HCO3, CO3, SO4, NO3, PO4. Most of these parameters fall under not permissible limits. The western part of the study area is highly polluted from K, Cl, HCO3 due to industrial/agriculture activity. The southern part is less polluted compared to other region. Hydrogeochemical processes controlling the water chemistry (Gibbs) indicates that most of groundwater samples fall at rock-weathering supremacy zone. Geochemical processes and temporal variation in the groundwater in this area are influenced by evaporation processes, ion exchange and dissolution of minerals. Major cation and anion ionic interaction indicate that weathering reactions have an inconsequential role in the hydrochemical processes of the shallow groundwater system. As a result of the hydrogeochemical analysis, seawater intrusion, aquifer rock weathering, sewer leakage are the overriding factors that determine the major ionic composition. The appropriate management plan is necessary to preserve precious groundwater resources.

Blockchain Technology has acquired notoriety in both scholar and industry due to its decentralized, versatile, security and irrefutable characteristics. The blockchain is a disseminated data set that holds record of exchanges that are conveyed among members in its most essential structure. Manufactured exchanges can't pass aggregate certification since every exchange requires the understanding of various individuals. A record can never be changed or erased after it has been made and recognized by the blockchain. After the Internet, blockchain innovation is presently viewed as the main development. The previous could tackle the trust issue utilizing shared systems administration and public-key cryptography assuming the last option interfaces individuals to all the more likely comprehend online business processes. The objective of this paper is to take a gander at the critical instances of blockchain innovation's comprehensive effect and see it as an inseparable part of our daily existences.

In this study, ethanolic extract of Zea mays L was utilized against urinary tract infection (UTI) causing bacteria, vegetable spoilage causing fungi and anticancer activity. The antimicrobial activity of ethanol extracts of corn silk was determined by the agar well diffusion method against UTI pathogens. The most effective antibacterial activity of ethanol corn silk extract was found at 900 ​μg and antifungal activity was found against Aspergillus niger and Aspergillus brasiliensis at 2mg/20 ​ml. It showed 75% nitric oxide inhibition activity and 67%. amylase inhibiting activity. GC-MS analysis showed several bio active compounds with antimicrobial, antioxidant, anticancer activities etc.

Summary The cloud computing environment is subject to unprecedented cyber‐attacks as its infrastructure and protocols may contain vulnerabilities and bugs. Among these, Distributed Denial of Service (DDoS) is chosen by most cyber extortionists, creating unusual traffic that drains cloud resources, making them inaccessible to customers and end users. Hence, security solutions to combat this attack are in high demand. The existing DDoS detection techniques in literature have many drawbacks, such as overfitting, delay in detection, low detection accuracy for attacks that target multiple victims, and high False Positive Rate (FPR). In this proposed study, an Artificial Neural Network (ANN) based hybrid GBS (Grey Wolf Optimizer (GWO) + Back Propagation Network (BPN) + Self Organizing Map (SOM)) Intrusion Detection System (IDS) is proposed for intrusion detection in the cloud computing environment. The base classifier, BPN, was chosen for our research after evaluating the performance of a comprehensive set of neural network algorithms on the standard benchmark UNSW‐NS 15 dataset. BPN intrusion detection performance is further enhanced by combining it with SOM and GWO. Hybrid Feature Selection (FS) is made using a correlation‐based approach and Stratified 10‐fold cross‐validation (STCV) ranking based on Weight matrix value (W). These selected features are further fine‐tuned using metaheuristic GWO hyperparameter tuning based on a fitness function. The proposed IDS technique is validated using the standard benchmark UNSW‐NS 15 dataset, which consists of 1,75,341 and 82,332 attack cases in the training and testing datasets. This study's findings demonstrate that the proposed ANN‐based hybrid GBS IDS model outperforms other existing IDS models with a higher intrusion detection accuracy of 99.40%, fewer false alarms (0.00389), less error rate (0.001), and faster prediction time (0.29 ns).