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The medical image phenomenon may be a developing and progressive field these days. The processing of MRI images differs between parts of this field. This paper presents an economical approach for identifying tumors in brain MRI imageries. The process consists of following steps: the occurrence of image processing using intermediate filters, image enlargement is obtained by calibration chart calculation (histogram measurement); image segmentation is performed by binding. This approach is considered for the incorporation of morphological practices. Finally, the tumor stage is determined by manipulation of the image editing strategy. This research work presents an automatic brain tumor diagnosis method using MR imaging. The target system identifies and classifies the image segmentation using k-values. It also divides part of the plant into blood and bruises.

The objective of this study was to understand the influence of anthropogenic organic matter on the spatial distribution microbial community in the continental shelf sediments of the Southeastern Arabian Sea (SEAS). The sediment samples were taken from the inner shelf (30 m depths) and outer shelf (100-200 m). The C:N

Particulate organic carbon (POC) and its variability were studied to assess the accuracy of ocean colour retrieval algorithms over the eastern Arabian Sea (EAS) as it controls the carbon sequestration, oxygen minimum zone and biogeochemical (C, N and P) cycles. The seasonality in the physical and biological processes strongly influenced the distribution of POC along the EAS. Higher POC and chlorophyll a (chl a) during the spring inter monsoon (SIM) in the north EAS were due to detrainment bloom. The lower POC:chl a ratios during the winter monsoon (WM) (299.8 ± 190.8) than the SIM (482.1 ± 438.3) were due to the influence of freshly derived organic matter with high nutrient levels. The moderate coefficient of regression values of POC with chl a (R

Nowadays, grass cutting machines are becoming very popular in the international market. In the conventional grass cutting machines, IC engines were used, which contributes to the increase in the pollution level. The primary purpose of this work is to reduce the use of a non-renewable resource (petrochemical products for example-fuels), control the pollution and to develop an eco-friendly automated grass cutter powered by the solar energy, and reduce the human effort to cut the grass. For the working of this, device is driven by the rechargeable batteries. For standby and powering operation, DC batteries are used. These batteries are charged using a solar panel. Node MCU microcontroller is used for controlling the device. Internet of Things (IoT)-based Android app (Blynk app) is used to access and control the device from the various distances from the robot.

Medical image processing systems are widely adopted in several real-time diagnostic systems due to their significant nature of information extraction and processing which helps to predict the early stages of illness. Alzheimer’s disease (AD) is one of the most chronic and challenging diseases in the medical diagnostic field. This disease is responsible for neurodegenerative brain disorder and attacks the brain cells and nerves that result in affecting the brain functionality and finally cause dementia. In this work, the prime focus is on the early prediction of Alzheimer’s disease using image processing-based machine learning techniques. Erstwhile, extensive studies are researched using pathological- and MRI-based systems which show the issues caused due to the brain’s white matter damage. Nevertheless, these studies do not provide that how white matter damage is associated with the AD and its classification at multiple stages. Conferring to the proposed approach, an improved feature extraction technique is introduced by combining empirical mode decomposition and gray-level co-occurrence matrix (GLCM). In order to abstract robust features, several image preprocessing steps are applied such as image enhancement, and later feature extraction is applied followed by the classification where multiple classifiers such as KNN, decision tree classifier, RBF, and support vector machine classification are castoff to assess the performance of feature extraction technique. Projected methodology obtains promising performance for the classification of various stages of AD and consequently can be employed for real-time application for early prediction of AD. An extensive experimental study is carried out for the anticipated approach that is implemented on OASIS brain imaging dataset. Experimental study shows that support vector machine, KNN, decision tree, and RBF classification techniques achieve that the accuracy as 39.06%, 80.20%, 98.43%, and 77.08%, respectively. Combination of the proposed feature extraction technique and decision tree classification scheme achieves a promising classification performance.

Repeat observations over the Kochi and Mangalore shelves of the southeastern Arabian Sea (SEAS) during April to December 2012 revealed substantial accumulation of methane (CH4) in the nearshore waters (48.6 ± 34.4 nM) compared to the outer shelf (2.9 ± 0.7 nM). Sediment methanogenesis and estuarine discharge appear to be the major sources of CH4 in the nearshore regions during non-upwelling period. But under oxygen deficient conditions that prevail during the upwelling period, extremely low concentrations of CH4 in the nearshore anoxic region of Mangalore (14 ± 2 nM) compared to similar region of hypoxic Kochi shelf (35.5 ± 15.4 nM) have been observed. We propose that this is mainly due to its greater loss through anaerobic oxidation and in part by the reduced sedimentary inputs by weak bioturbation over Mangalore relative to Kochi. On an annual basis, SEAS is found to be a net source of CH4 to the atmosphere with its efflux ranging from 0.03 to 170 μmol m–2 d–1 (21.9 ± 36.7 μmol m–2 d–1). Following a zonal extrapolation approach, the estimated CH4 efflux from the SEAS (7–14°N; 3.2 Gg y–1) accounts for up to ∼16% of the total CH4 emission from the Arabian Sea.

Organelle-targeted photosensitizers (PSs) having luminescence properties are potential theranostic agents for simultaneous luminescence imaging and photodynamic therapy. Herein, we report a water-soluble luminescent cyclometalated IrIII complex, Ir-Bp-Ly, as a lysosome-targeted theranostic probe. Ir-Bp-Ly exhibits exceptional photophysical properties, with good triplet-state quantum yield (0.90), singlet oxygen generation quantum yield (0.71 at pH 4), and long lifetime (1.47 μs). Interestingly, Ir-Bp-Ly localizes mostly in lysosomes due to the presence of morpholine units, suggesting its potential use as a lyso-tracker. Ir-Bp-Ly displays a notable PDT effect in C6 glioma cells, efficiently generating reactive oxygen species owing to close proximity between the energy levels of its triplet state and those of molecular oxygen (3 O2 ). The mechanism of cell death has been studied through caspase-3/7 and flow cytometry analyses, which clearly established the apoptotic pathway.

Carbon isotopic composition of dissolved inorganic carbon (δ13CDIC) in the Cochin estuary, a tropical eutrophic estuary along the southwest coast of India, and the adjacent coastal Arabian Sea was measured to understand spatio-temporal variability in sources and processes controlling inorganic carbon (C) dynamics in this estuarine-coastal system. δ13CDIC in the Cochin estuary showed wide variation during three different seasons (premonsoon: − 12.2 to − 3.26‰; monsoon: − 13.6 to − 5.69‰; and postmonsoon: − 6.34 to + 0.79‰). Detailed mixing curve approximation modeling along with relationships of δ13CDIC with dissolved oxygen and nutrients suggest dominant role of freshwater mixing and degassing of CO2 on DIC dynamics during wet seasons (premonsoon and monsoon). Excess CO2 brought in by rivers and in situ production due to respiration in the Cochin estuary result into one of the highest pCO2 observed in estuarine systems, leading to its degassing. During postmonsoon, a relatively dry period with high salinity, calcite precipitation was a major process with calcite saturation index > 1 at few locations. Relatively lower average surface values of δ13CDIC in the coastal Arabian Sea (premonsoon: + 0.95‰; monsoon: + 0.88‰; and postmonsoon: + 0.66‰) compared to the predicted open ocean value along with mixing curve modeling suggest dominance of respiration/organic matter (OM) degradation over primary productivity. Estuarine influence on coastal DIC dynamics was observed in nearshore region (~ 10 km), whereas evidence of upwelling was found at farther locations.

The seasonal upwelling along the southeastern Arabian Sea (SEAS) brings cold, nutrient-rich low oxygen subsurface water to the continental shelf. The subsurface oxygen deficiency due to upwelling is severe in some years, the intensity of which could profoundly influence the nutrient cycling along the SEAS. Herein, we studied the effect of seasonal anoxia on fractionation of phosphorus during the peak upwelling period of August 2013. Abundance of five fractions of phosphorus (P), namely exchangeable or loosely sorbed P (Pads), iron-bound P (PFe), authigenic P (Paut), detrital apatite plus other inorganic P (Pdet) and organic P (Porg), in surface sediments of SEAS shelf has been studied using a sequential extraction procedure (SEDEX) to examine their distributions and sources. Total P (TP) concentrations ranged from 209 to 1081 µg g−1 with an average of 508 ± 256 µg g−1. Among the five P fractions, the authigenic P was the dominant species, representing about 60% of TP. The relative abundance of P fractions was in the order: Paut>Pdet>Porg>PFe> Pads. Multivariate analyses revealed that the P fractions were primarily associated with the organic constituents and fine sediments. The hypoxic bottom condition associated with summer monsoon upwelling significantly reduced the concentrations of PFe, Pads and Porg in the surface sediments. The enhanced release of organic bound and iron oxides bound P under low oxygen condition was evident from the enhanced C/P and N/P ratios and lower C/N ratio in the sediments. The intense biomineralization of organic matter and reduction of Fe-Mn oxides due to the periodic anoxia resulted in the transformations of their associated P fractions and enhanced accumulation as authigenic calcium phosphate mineral.

The growing number of oxygen-deficient coastal zones around the world and their impacts on marine life has always been a controversial issue as their development is largely attributed to anthropogenic activities which can be mitigated by human actions. However, contrary to this prevailing understanding, we show here for the first time, using new coherent datasets from estuaries to coastal to offshore regions, that the world’s largest hypoxic-anoxic zone along the west coast of India is formed through a natural process, i.e. upwelling of deoxygenated waters during the summer monsoon. We further demonstrate that the persistence and extent of this coastal oxygen deficiency depend on the degree of deoxygenation of source waters for the upwelling. Consequently, the anoxia is confined only to the central shelf between 11° and 18° N, which is equivalent to almost half of the western Indian shelf, where upwelling brings suboxic waters from the core oxygen minimum zone in the Arabian Sea.

The paper describes the community composition of phytoplankton in the eastern Arabian Sea (EAS) during winter monsoon (WM, January–February 2018), encompassing the entire eastern part of the Arabian Sea basin (~6–22°N and 77–67°E) with high-resolution sampling (7 transects, 56 sites), from coastal to offshore regions. The phytoplankton pigment concentrations estimated by high-performance liquid chromatography were interpreted using ‘CHEMTAX’ (Mackey et al., 1996) to determine relative abundance and contribution of phytoplankton functional groups at the class level. A distinct spatial heterogeneity was observed in the distribution of phytoplankton groups in the coastal and offshore regions of the northern as well as southern part of the EAS. The basin-scale column integrated chlorophyll a (Chl a) concentration in the upper 100 m was higher (16–118 mg m−2) in the northeastern Arabian Sea (NEAS) as against 9–79 mg m−2 in the southeastern Arabian Sea (SEAS). The chromatographic analysis revealed the dominance of diatoms in the coastal waters of the EAS basin. A closer evaluation of the hydrodynamics and nutrient chemistry of the offshore regions revealed that entrainment of sub-halocline nutrients into the sunlit water column through convective mixing supported the dominant cyanobacterial population in the NEAS. In the warm oligotrophic waters of the SEAS, the substantially high NH4+ concentration indicates that the dominant prochlorophytes were sustained by the regenerated production. The dominance of large phytoplankton like diatoms indicates a herbivorous control in the food chain in coastal waters of the EAS. Offshore waters are characterised by large proportions of pico-nano plankton along with considerable micro phytoplankton, which suggests a mixotrophic ecosystem. The statistical analysis showed that the silicate (Si/N ratio) concentration played a major role in controlling the diatom abundance in the coastal areas of the north (south) EAS while temperature and salinity together with nutrients structured the phytoplankton assemblage in the offshore waters during WM.

Carbon uptake rates in a tropical eutrophic estuary (Cochin estuary) and the adjacent coastal Arabian Sea were measured for the first time using 13C-NaHCO3 labeling technique. The rates in the estuarine water (pre-monsoon 3.0–20.4; monsoon 2.55–12.4; post-monsoon 3.1–16.3 μmol C l−1 h−1) were significantly higher than the coastal locations (pre-monsoon 0.02–0.1; monsoon 0.13–3.1; post-monsoon 0.007–0.032 μmol C l−1 h−1). The measured primary productivity in the estuary was relatively higher at mesohaline locations influenced with lateral inputs and TN:TP close to the Redfield ratio (16:1). It suggests that in nutrient replete tropical systems, TN:TP plays a major role in controlling the primary productivity rates. The primary productivity data from the coastal Arabian Sea suggests the effect of estuarine discharge on the carbon uptake rate at nearshore regions and ability of anthropogenic inputs to modulate the coastal biogeochemistry.

Accurate monitoring of pH variations inside cells is important for the early diagnosis of diseases such as cancer. Even though a variety of different pH sensors are available, construction of a custom-made sensor array for measuring minute variations in a narrow biological pH window, using easily available constituents, is a challenge. Here we report two-component hybrid sensors derived from a protein and organic dye nanoparticles whose sensitivity range can be tuned by choosing different ratios of the components, to monitor the minute pH variations in a given system. The dye interacts noncovalently with the protein at lower pH and covalently at higher pH, triggering two distinguishable fluorescent signals at 700 and 480 nm, respectively. The pH sensitivity region of the probe can be tuned for every unit of the pH window resulting in custom-made pH sensors. These narrow range tunable pH sensors have been used to monitor pH variations in HeLa cells using the fluorescence imaging technique.

Organelle-targeted photosensitizers (PSs) having luminescence properties are potential theranostic agents for simultaneous luminescence imaging and photodynamic therapy. Herein, we report a water-soluble luminescent cyclometalated Ir

The spatial and temporal variations of some trace metals in the surface sediments of Cochin Estuary were analyzed along with their geochemical associations to identify the possible sources, bioavailability and the health risks posed by them. The dominance of kaolinite and suggested that clay minerals distribution is influenced by sediment sorting. Total metal analysis revealed enrichment for Cd, Pb and Zn due to anthropogenic activities. The speciation analysis established that notwithstanding the large availability, carbonate as well as organic and sulfides bound fractions showed negligible associations with most of the metals. Hydrous Fe–Mn oxides appeared to play a major role in controlling the fate and transport of these metals in the sediments of Cochin Estuary. Lower contribution of the residual fractions for Cd (21%–26%), Pb (

Quantification of nitrogen (N) transformation rates in tropical estuarine-coastal water coupled systems undergoing anthropogenic disturbances is scant. A thorough understanding of these metabolic rates is required to evolve a mitigation strategy to save such systems from further degradation. Here, we report the first measurements of ammonium (NH4 +) and nitrate (NO3 −) uptake along with N2 fixation rates in the Cochin estuary, a tropical eutrophic ecosystem along the west coast of India, and two transects (off Cochin and off Mangalore) in the coastal Arabian Sea. In general, the Cochin estuary sustained higher uptake rates of NH4 + (0.32–0.91 μmol N l−1 h−1) and NO3 − (0.01–0.38 μmol N l−1 h−1) compared to coastal waters. The N uptake in the nearshore waters of Cochin transect (NH4 + : 0.34 μmol N l−1 h−1 and NO3 − : 0.18 μmol N l−1 h−1) was influenced more by estuarine discharge than was the Mangalore transect (NH4 + : 0.02 μmol N l−1 h−1 and NO3 − : 0.03 μmol N l−1 h−1). Despite high dissolved inorganic nitrogen (DIN) concentrations, the Cochin estuary also showed higher N2 fixation rates (0.59–1.31 nmol N l−1 h−1) than the coastal waters (0.33–0.55 nmol N l−1 h−1). NH4 + was the preferred substrate for phytoplankton growth, both in the Cochin estuary and coastal waters, indicating the significance of regenerative processes in primary production. A significant negative correlation between total nitrogen (TN): total phosphorus (TP), and NH4 + uptake (as well as N2 fixation) rates in the estuary suggests that nutrient stoichiometry plays a major role in modulating N transformation rates in the Cochin estuary.

An accurate analysis of medical images is progressively demanding in providing the absolute detection and diagnosis of diseases in medical imaging. The significant pre-processing step in MRI data processing is noise elimination. Noise deletion is essential step to increase image quality and performance of all the tasks desirable for quantitative imaging analysis. In this paper a new scheme for impulse noise removal in corrupted MRI brain images is introduced. The proposed scheme is a simple & efficient filtering technique that effectively detects and removes the salt and pepper noise. The experimental results of suggested noise purifying process executed on standard set of assessment images shows that algorithm provides a very good results with low mean-squared-error and high signal-to-noise ratio values for noise density up to 95% and outperforms significant tradeoff between fine detail preservation and noise removal in brain MRI images.

People detection and tracking is one of the important research fields that have gained a lot of attention in the last few years. Although person detection and counting systems are commercially available today, there is a need for further research to address the challenges of scenarios. Automated video surveillance system or Anomaly detection addresses observation of people within a busy environment leading to the description of their actions and interactions. It requires detection and tracking of people to ensure security, safety and site management. Object detection is one of the fundamental steps in Anomaly detection or automated video surveillance. Object detection from the video sequence is mainly performed by background subtraction technique. It is widely used approach for detecting moving objects from static cameras. As the name suggests, background subtraction is the process of separating out the foreground objects from the background in a sequence of video frames. The main aim of the Anomaly detection here is, to detect and track an object in motion by using single video recorded image. Video is recorded and fixed at the database; the background subtraction algorithm is used for segmenting moving object in video. If human entity is detected the tracking lines are formed around human and the object is tracked. The main aim is to develop anomaly detection for real-time security system.

The design of fluorescent molecular platforms capable of responding to multiple analytes is a topic of great interest. Herein, the use of a Zn2+ -complexed unsymmetrical squaraine dye, Sq-Zn2+ , as a chemical platform for recognizing structurally distinct analytes is reported. The squaraine ring is substituted on one side with a dipicolylamine unit, which acts as the metal ion receptor, whereas the other part of the molecule carries a dibutylaniline moiety, which is an electron donor. The molecular system is unique because it can respond specifically to different types of analytes, namely, atmospheric carbon dioxide, cyclic phosphates, and picric acid. Moreover, the interaction of these analytes can be monitored colorimetrically and fluorimetrically, which favors both qualitative and quantitative analyses. The distinct response towards cyclic and linear phosphates, as well as the selective response towards picric acid, among the various nitroaromatic compounds was achieved with sensitivity at the ppm level. The flexible coordination offered by Zn2+ plays a significant role in the discrimination of these analytes with high specificity. Dye Sq-Zn2+ introduced herein is a single-molecule construct that can be used for the selective and sensitive response towards analytes of environmental and biological relevance.

A comprehensive analysis on the phytoplankton ecology with special reference to different phytoplankton size classes was carried out at green Noctiluca scintillans (hereafter Noctiluca) bloom and non-bloom locations in offshore waters of the northern Arabian Sea. At the bloom locations, green Noctiluca represented a dense mono-specific proliferation with average cell density of 10.16 ± 5.806 × 104 cells-L−1 and relative abundance share of 98.63%. Active photosynthesis through prasinophytic endosymbiont was depicted from net community production magnitude reaching 85.26 mgC/m3/Day under low prey abundance. Parallel swarming of Porpita porpita, a voracious copepod feeder signified the competitive advantage of Noctiluca to have the phytoplankton prey. Average concentration of picophytoplankton biomass was eleven times lower in surface waters of non-bloom stations in comparison to bloom. Higher N:P ratio in subsurface waters of non-bloom stations signified non-utilization of nitrogenous nutrients. Green Noctiluca bloom onset subsequent to diatom rich conditions was evident from spatio-temporal ocean colour satellite imageries.

The Cochin estuarine system (CES) has experienced rapid changes over the last few decades from extensive urbanisation, industrialisation, agricultural development activities and aquaculture practices. Intense pollution and other anthropogenic disturbances have led to an accelerated increase in organic matter (OM) and dissolved inorganic nitrogen (DIN) in the estuarine complex. This study explores nitrous oxide (N 2 O) fluxes and its drivers in the CES. Relatively higher N 2 O concentrations were observed in the inner estuary when compared to the outer estuary. Higher DIN with varying salinity gradients likely controlled the production and flux of N 2 O into the inner portions of the system. Hypoxia was never established in the water column indicating that conditions were favourable for nitrification, which in turn possibly led to increased N 2 O concentrations. It was observed particularly during the monsoon season that the inorganic nutrients and dissolved greenhouse gases from the river Periyar at the head of the estuary, contributed to the increased N 2 O concentrations. The N 2 O water to air flux ranged from 0.49 to 29. 73 μ m ol m−2 day−1, which was higher than what was documented in earlier reports. Although the CES exports a substantial amount of nutrients to the adjacent Arabian Sea, the estuary effectively processes nitrogen inputs as N 2 O making CES a net source of N 2 O emissions.

In medical image processing, the accurate understanding and analysis of medical images is progressively challenging and demanding in providing the clear detection and diagnosis of the diseases. A very important and primary step in automatic detection of abnormalities in brain MRI images is reliable elimination of presence of the noise in the acquired images. Evaluation of the various noise removal algorithms to estimate the noise parameters is widely recognized as a typical standards for medical image processing solicitations. Validation of such brain MRI images can be done based on the evaluation through various statistical noise parameters. But the enactment of noise removal procedure profoundly depend on superiority of input brain MRI images and image processing skills employed for restoring original quality of brain MRI image by eliminating noises present in it and make the input image free from noises. This paper projects the type of noise existing in the brain MRI images and also removal of noises from the images using different types of noise elimination filters. The work proposes the design and implementation of the simple and efficient filtering technique for removal of noises in medical images specifically for brain MRI images and to upsurges the performance capabilities of the method. The experimental outcomes of suggested filtering algorithm are compared with the additional existing filtering approaches. The simulated results of filtering process executed on a standard set of assessment images shows that proposed algorithm provides good results with high SNR and low MSE values for the noise level of 95% and outperforms the conventional steps for removal of noise present in brain MRI images.

Iron ore was mined from the banded iron formations of Goa, India, and transported through the Mandovi and Zuari estuaries for six decades until the ban on mining from September 2012. Here we focus on the environmental magnetic properties of sediments from the catchment area, upstream and downstream of these estuaries, and adjacent shelf during peak mining time. Magnetic susceptibility (χ lf) and saturation isothermal remanent magnetization (SIRM) values of sediments were highest in upstream (catchment area and estuaries), decreased gradually towards downstream (catchment area and estuaries), and were lowest on the adjacent shelf. The χ lf values of the Mandovi estuary were two to fourfold higher than those in the Zuari. The sediments of these two estuaries after the mining ban showed enrichment of older magnetite and sharp decrease in the SIRM values. Although the input of ore material has been reduced after mining ban, more flushing of estuarine sediments is required for healthier environment.

A very important step in automatic fingerprint recognition system is to automatically and reliably extract minutia from the fingerprint images. Minutia based fingerprint recognition algorithms have been widely accepted as a standard for single fingerprint recognition applications. But the performance of a minutia extraction algorithm relies heavily on the quality of the input fingerprint images and the image processing techniques used for enhancing the ridges and valleys of the fingerprint image and make the minutia distinguishable from the other parts of the fingerprint image. This paper basically focuses on how the minutia points are extracted from fingerprint images and the proposed method is to design and implement the current techniques for fingerprint recognition specifically public key cryptography (RSA Algorithm) to improve the performance of the system. The design is mainly decomposed into image preprocessing, feature extraction, implementation of RSA algorithm for extracted feature and finally matches.