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In semiarid regions, water being the main constraint, the rainfall intensity–duration–frequency (IDF) curves play a significant role in water resources engineering and management. The IDF curves are used to assess the heavy rainfall events, climatic regimes classification, to derive design storms, etc. The objective of the present study is to develop IDF curves for the Ananthapuramu district in semiarid region of southern India. Annual peak rainfall data of 56 years (1966–2021) at Agricultural Research Station, Ananthapuramu, were analyzed for extraction of peak rain-storm intensity value, their corresponding durations and the frequency using Gumbel distribution method. The short-duration rainfall intensity was estimated using empirical reduction method described by the India Meteorological Department. The parameters of the IDF equation and correlation coefficient for different periods were calculated (2, 5, 10, 25, 50 and 100 years). The results of the data analysis indicated that rainfall intensity decreased with increase in rainfall duration. Further, a rainfall of any given duration will have larger intensity if its return period is large. The most frequent rainfall durations in the study area are 15, 30, and 45 min, and they were found to account for 22.4%, 28.2%, and 32.4%, respectively, of the total daily rainfall, whereas the percentage of the daily rainfall during 1-, 2-, and 3-h storm events was 34.9%, 44.5%, and 50.9%, respectively. By using these relations, short-duration rainfall can be quickly estimated, saving time, money, and other resources. The IDF curves can be recommended for the prediction of rainfall intensity and frequency of return period for Ananthapuramu district in semiarid region of Andhra Pradesh.

Purpose: This manuscript proposes an IoT-based E-healthcare monitoring method for constantly monitoring the important signs of patient and diagnoses biological and behavioral changes through the technologies of smart healthcare. Method: Patient health monitoring system is used to deep learning techniques for the performance of patient categorization. Here, Hybrid whale and grey wolf optimization approach (Hyb-WGWO) is proposed to the selection of cluster head with various internet of things (IoTs) devices. These devices are utilized to sense the healthcare data into clusters form. In this, the cluster head is chosen by using the proposed Hyb-WGWO approach. Data in the cloud server are transmitted to the cluster head. Then deep ensemble multitask classification (DEMC) model is proposed for identifying patient disease conditions, such as low, normal, abnormal and critical. Results: The experimental outcomes of the proposed Hyb-WGWO-DEMC approach show 25.98% and 31.86% improved accuracy, 28.08%, 26.87% better specificity than the existing methods, such as Elliptic Decryption Algorithm in Elman Neural Network (EDA-ENN) and Grasshopper Optimization and Particle Swarm Optimization with cryptographic encryption (GOPSO-CE) respectively. Conclusion: IoT-based E-healthcare monitoring method achieves higher accuracy and lower error rate through the technologies of smart healthcare.

In recent times, polymer composites have played an epochal role in transforming material science. Some of their properties such as toughness, strength, flexibility and rigidity have helped them supplant conventional materials such as iron, steel, and aluminium on several occasions. Apart from this, they are light in weight and more cost-efficient, which make them a viable alternative. They have found their application in several fields such as automobile industry, aerospace industry, construction and pipeline industry. Owing to its excellent impact strength, tensile and hardness, natural fibres serve as an excellent replacement. Natural fibres are an environmental friendly, biodegradable and are readily available. The present investigation uses a new fibre for manufacturing the eco-friendly composite material. Mechanical properties such as tensile strength, shear stress, flexural rigidity, impact strength and hardness of a coconut fibre-reinforced polymer composite material are evaluated as per respective ASTM standards. A surface analysis of the material using a scanning electron microscope is also performed. The results are categorized and tabulated accordingly. The values obtained appear to fall in line with the experimental data and hence can be espoused as an alternative material especially in the automotive sector.

Background:Fish oils, which are rich in health-promoting polyunsaturated fatty acids (PUFA), have emerged as promising functional foods in the global health and wellness food market. Their source regarding the fish type, season, and location of harvesting might influence the nutritional value of such bioactive oils and determine their market price. The differences in price among such oils often lead to economically motivated mislabeling and adulteration. Objective:In this study, our objective was to demonstrate how a qualitative targeted shotgun lipid profile workflow using an electrospray ionization–quadrupole-linear ion trap MS (QTrap) could differentiate fish oils originating from two different species. Methods:Five samples each of sardine (Sardinella longiceps) oil and shark (Echinorhinus brucus) liver oil were diluted to a concentration of 80 µg/mL in chloroform–methanol (1 + 2, v/v) with 5 mM ammonium acetate. These samples were directly infused into a QTrap MS. The data were acquired for 23 precursor ion and 4 neutral loss scan experiments in the positive ionization mode and compared. Results:We identified the following major lipid classes: cholesteryl ester, diacyl glycerol, triacylglycerol, monoalkyldiacylglycerol, and phophatydyl choline. The relative peak areas of the identified lipid species, when subjected to supervised multivariate analysis, could effectively distinguish the sardine oil and shark liver oil. Conclusions:The approach will be useful in establishing authenticity of fish oil and to support the regulatory agencies in dispute resolution. It can also be extended to establish authenticity in other agricultural and food commodities. Highlights:This paper reports a proof of concept for authenticating PUFA-rich fish supplements. A shotgun targeted lipidomics profile and chemometrics modeling successfully discriminated sardine oil and shark liver oil.

The present study aimed to assess the effectiveness of sodium-acetate dip treatment (2%) on the quality and shelf life of seer fish (Scomberomorus commerson) steaks during chilled condition. For this, the seer fish steaks were packed in multilayered EVOH pouches having oxygen permeability of 3.86 cc m−224 h−1at 1 atm. pressure and water vapour transmission rate of 139.02 g m−224 h−1at 37 °C and 92% RH, and maintained at 1–2 °C for quality evaluation. The initial mesophilic and psychrotrophic bacterial load of the seer fish steaks was 4.48 and 4.47 log cfu g−1, respectively, which showed a lag phase in treated samples compared to control. The limit of 7 log cfu g−1was exceeded on 15 and 24th days for seer fish steaks in control air pack and NaA-treated samples, respectively, for both mesophilic and psychrotrophic counts. Lipid oxidation was significantly higher for control sample compared to treated sample throughout the storage period. Formation of volatile bases and degradation of nucleotide breakdown products were significantly (P < 0.05) inhibited in the sodium-acetate-treated samples resulting in a shelf life of 21 days compared to only 12 days for control samples.

Potential fishing zone (PFZ) alerts are critical in anticipating fishing places. Earlier PFZ predictions are based on NOAA’s advanced very high-resolution radiometer (AVHRR). To a significant degree, the expansion of the fishing industry may be attributed to the influence of research on fish growers, fishermen, fisheries planners, and managers. Artificial intelligence (AI) technologies are increasingly being used to improve the sustainability of smart fishing. While sustainability is frequently touted to be the intended consequence of AI applications, there is no data currently on how AI contributes to sustainable fishing. The purpose of this paper is to perform a feature selection using the fisher’s score (FS) technique to find the optimal features for final classification. Normalization is used as a preprocessing technique to remove missing and irrelevant data. Here, the collected features, financial derivatives, and geometrical features are used, which leads to poor classification accuracy for predicting the PFZ. Therefore, to improve the accuracy of the condition-based ensemble machine learning and deep learning classification technique (CECT), FS is used and provides the minimum number of features for classification. The experiment is carried out on collected data and tested with existing techniques in terms of accuracy, sensitivity, specificity, and F-measure. The simulation results proved that the proposed technique achieved 96.11% accuracy and 96% specificity compared to the FS technique.

Nanocrystalline SnO2powders were synthesized by hydrolysis and solvolysis of SnCl2followed by a fast nucleation process in Teflon lined autoclave. The as prepared samples were calcined at 400 °C for 4 h to attain stable phase. The X-ray diffraction pattern confirms tetragonal crystal structure for both hydrothermally and solvothermally prepared nanoparticles and the average crystallite size is calculated to be 14 and 30 nm respectively. Williamson–Hall plot (W–H plot) reveals low value of strain induced broadening using uniform deformation model. Absorption co-efficient of prepared SnO2was determined using UV–Visible absorption spectrum. Nyquist plane plot shows the decreased electrical resistance of SnO2with increasing the applied potential resulting in increased conductivity. The increasing conducting behavior of tin oxide nanoparticles can be used as conducting layer in photoelectrodes.

Weathering of native charnockites and sandstones of coastal Tamil Nadu occurs by granular disintegration, exfoliation, and tafoni development. This is the first report of tafoni in India. Mafic minerals begin to deteriorate near the coast within a dozen years, leaving irregular differential weathering pits. Colonial tombstones of charnockite, 200 to 400 years old, are covered with small round pits that are interpreted as incipient tafoni. Ancient Hindu and Jain temples, about a thousand years old have pits that are similar in size and shape. Ancient charnockite megaliths, that are about 3,000 years old, have weathering pits that are an up to 20 cm across, and several centimeters deep. Inselberg surfaces that are a few million years old have tafoni in which a person can walk upright. The frequency distributions of depths, widths and volumes of these pits, from the smallest to the largest, are heteroskedastic and lognormal.The megaliths do not have small pits such as the colonial tombstones and ancient temples. The inselbergs do not have pits such as those on the megaliths. We believe that at the same time as the pits are enlarging, the surfaces are exfoliating, that removes the smaller pits. But the small pits do not reform on the old surfaces. This strongly suggests that something is preventing the development of new pits that might be used to conserve ancient stone monuments.

Abstract: The Ministry of Shipping desires to revise the inland vessels’ limit (IVL) notification based on scientific rationale to improve the safety of vessels and onboard personnel. The Mormugao port region extending up to the Panaji was considered for this pilot study. Measured winds and wave parameters (AWS and moored buoy) as well as NCEP re-analysis and NCMRWF winds were used for the analysis and input to regional and local models. The results of wave model were validated with measured significant wave heights (SWHs) and the comparison shows a good match. The analysis indicates that SWHs do not exceed 2.0 m during non-monsoon months, and in monsoon months exceed 5.0 m, and even 7.0 m, especially during extreme events. In order to draw IVL contours for Goa coastal region, local model was set up and nearshore waves were simulated for the period May 2004–May 2005. Based on the nearshore SWH distribution, IVL contours have been fixed for the Mormugao port and Panaji coastal regions.

A simple, precise and accurate high-performance thin-layer chromatographic method has been established for the determination of rutin in the stem extract of Hibiscus micranthus Linn. A flavonoid fraction of methanolic extract of the stem powder was used for the experimental work. Separation was performed on silica gel 60 F254 HPTLC plates with n-butanol: acetic acid: water: ammonia 3:1:1:1(v/v), as mobile phase. The determination was carried out using the densitometric absorbance mode at 286 nm. Rutin response was linear over the range 50–400 ng/μL. The concentration of rutin in the flavanoidal fraction was found to be 9.93%. The HPTLC method was evaluated in terms of sensitivity, accuracy, precision and reproducibility.