Predicting agricultural and meteorological droughts using Holt Winter Conventional 2D-Long Short-Term Memory (HW-Conv2DLSTM).

Drought is an extended shortage of rainfall resulting in water scarcity and affecting a region's social and economic conditions through environmental deterioration. Its adverse environmental effects can be minimised by timely prediction. Drought detection uses only ground observation stations, but satellite-based supervision scans huge land mass stretches and offers highly effective monitoring. This paper puts forward a novel drought monitoring system using satellite imagery by considering the effects of droughts that devastated agriculture in Thanjavur district, Tamil Nadu, between 2000 and 2022. The proposed method uses Holt Winter Conventional 2D-Long Short-Term Memory (HW-Conv2DLSTM) to forecast meteorological and agricultural droughts. It employs Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data precipitation index datasets, MODIS 11A1 temperature index, and MODIS 13Q1 vegetation index. It extracts the time series data from satellite images using trend and seasonal patterns and smoothens them using Holt Winter alpha, beta, and gamma parameters. Finally, an effective drought prediction procedure is developed using Conv2D-LSTM to calculate the spatiotemporal correlation amongst drought indices. The HW-Conv2DLSTM offers a better R2 value of 0.97. It holds promise as an effective computer-assisted strategy to predict droughts and maintain agricultural productivity, which is vital to feed the ever-increasing human population.

HGATT_LR: transforming review text classification with hypergraphs attention layer and logistic regression.

Text classification plays a major role in research such as sentiment analysis, opinion mining, and customer feedback analysis. Text classification using hypergraph algorithms is effective in capturing the intricate relationships between words and phrases in documents. The method entails text preprocessing, keyword extraction, feature selection, text classification, and performance metric evaluation. Here, we proposed a Hypergraph Attention Layer with Logistic Regression (HGATT_LR) for text classification in the Amazon review data set. The essential keywords are extracted by utilizing the Latent Dirichlet Allocation (LDA) technique. To build a hypergraph attention layer, feature selection based on node-level and edge-level attention is assessed. The resultant features are passed as an input of Logistic regression for text classification. Through a comparison analysis of different text classifiers on the Amazon data set, the performance metrics are assessed. Text classification using hypergraph Attention Network has been shown to achieve 88% accuracy which is better compared to other state-of-the-art algorithms. The proposed model is scalable and may be easily enhanced with more training data. The solution highlights the utility of hypergraph approaches for text classification as well as their applicability to real-world datasets with complicated interactions between text parts. This type of analysis will empower the business people will improve the quality of the product.

Epidemic zone of COVID-19 from social media using hypergraph with weighting factor (HWF).

Online social network is one of the most prominent media that holds information about society's epidemic problem. Due to privacy reasons, most of the users will not disclose their location. Detecting the location of the tweet users is required to track the geographic location of the spreading diseases. This work aims to detect the spreading location of the COVID-19 disease from the Twitter users and content discussed in the tweet. COVID-19 is a disease caused by the "novel coronavirus." About 80% of confirmed cases recover from the disease. However, one out of every six people who get COVID-19 can become seriously ill, stated by the World health organization. Inferring the user location for identifying the spreading location for the disease is a very challenging task. This paper proposes a new technique based on a hypergraph model to detect the Twitter user's locations based on the spreading disease. This model uses hypergraph with weighting factor technique to infer the spreading disease's spatial location. The accuracy of prediction can be improved when a massive volume of streaming data is analyzed. The Helly property of the hypergraph was applied to discard less potential words from the text analysis, which claims this work of unique nature. A weighting factor was introduced to calculate the score of each location for a particular user. The location of each user is predicted based on the one that possesses the highest weighting factor. The proposed framework has been evaluated and tested for various measures like precision, recall and F-measure. The promising results obtained have substantiated the claim for this work compared to the state-of-the-art methodologies.

DNA binding, photoactivated DNA cleavage and cytotoxic activity of Cu(II) and Co(II) based Schiff-base azo photosensitizers.

A new class of Cu(II) and Co(II) complexes of azo-containing Schiff base of the type [Cu(L1)2] and [Co(L1)2], where L1=4-[(E)-{2-hydroxy-3-[(E)-(4-bromophenyl)diazenyl]benzylidene}amino]benzoic acid have been synthesized and characterized. Extension of conjugation and the presence of free carboxylic acid group of the ligand L1 increased the wavelength of the complexes from visible region to the near IR region (620-850 nm). The Cu(II) and Co(II) complexes interacted with CT-DNA via intercalative mode with the respective Kb value of 3.2×10(4) M(-1) and 2.9×10(4) M(-1) and acted as proficient photocleavers of SC pUC19 DNA in UV-A light, forming (1)O2 as the reactive oxygen species with the quantum yield of 0.38 and 0.36, respectively. Furthermore, the Cu(II) and Co(II) complexes showed photocytotoxicity toward two selected tumor cell lines MCF-7 and A549 by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide (MTT) method, and the Cu(II) complex exhibits higher photocytotoxicity than Co(II) complex against each of the selected cell lines, this result is identical with their DNA binding ability order.

Spectroscopic and molecular structure investigations of 9-vinylcarbazole by DFT and ab initio method.

Fourier transform infrared (FT-IR) and FT-Raman spectra have been recorded and widespread spectroscopic investigations have been carried out on 9-vinylcarbazole (9VC). The optimized geometries, vibrational wavenumbers, intensity of vibrational bands and various atomic charges of 9VC have been investigated using Hartree-Fock (HF) and density functional theory (DFT-B3LYP) method using 6-31G(d,p) as basis set. Experimental fundamental vibrational modes are scrutinized and compared with the calculated results. (13)C and (1)H NMR spectra were recorded and the chemical shifts of the molecule have been computed using GIAO method. The nonlinear property of the title compound was confirmed by hyperpolarizability. Molecular stability and bond strength was analyzed by Natural Bond Orbital analysis. Electronic structure properties such as UV and frontier molecular orbital examination have been reported.

Spectral analysis, vibrational assignments, NBO analysis, NMR, UV-Vis, hyperpolarizability analysis of 2-aminofluorene by density functional theory.

In this present investigation, the collective experimental and theoretical study on molecular structure, vibrational analysis and NBO analysis has been reported for 2-aminofluorene. FT-IR spectrum was recorded in the range 4000-400 cm(-1). FT-Raman spectrum was recorded in the range 4000-50 cm(-1). The molecular geometry, vibrational spectra, and natural bond orbital analysis (NBO) were calculated for 2-aminofluorene using Density Functional Theory (DFT) based on B3LYP/6-31G(d,p) model chemistry. (13)C and (1)H NMR chemical shifts of 2-aminofluorene were calculated using GIAO method. The computed vibrational and NMR spectra were compared with the experimental results. The total energy distribution (TED) was derived to deepen the understanding of different modes of vibrations contributed by respective wavenumber. The experimental UV-Vis spectra was recorded in the region of 400-200 nm and correlated with simulated spectra by suitably solvated B3LYP/6-31G(d,p) model. The HOMO-LUMO energies were measured with time dependent DFT approach. The nonlinearity of the title compound was confirmed by hyperpolarizabilty examination. Using theoretical calculation Molecular Electrostatic Potential (MEP) was investigated.

Metal based photosensitizers of tetradentate Schiff base: promising role in anti-tumor activity through singlet oxygen generation mechanism.

In the present investigation, a Schiff base N'(1),N'(3)-bis[(Z)-(2-hydroxynapthyl)methylidene]benzene-1,3-dicarbodihydrazide (L1) and its Co(II), Ni(II) and Cu(II) complexes have been synthesized and characterized as novel photosensitizing agents for photodynamic therapy (PDT). The interaction of these complexes with calf thymus DNA (CT DNA) has been explored using absorption, thermal denaturation and viscometric studies. The experimental results revealed that Co(II) and Ni(II) complexes on binding to CT DNA imply a covalent mode, most possibly involving guanine N7 nitrogen of DNA, with an intrinsic binding constant Kb of 4.5×10(4)M(-1) and 4.2×10(4)M(-1), respectively. However, interestingly, the Cu(II) complex is involved in the surface binding to minor groove via phosphate backbone of DNA double helix with an intrinsic binding constant Kb of 5.7×10(4)M(-1). The Co(II), Ni(II) and Cu(II) complexes are active in cleaving supercoiled (SC) pUC19 DNA on photoexposure to UV-visible light of 365nm, through (1)O2 generation with quantum yields of 0.28, 0.25 and 0.30, respectively. Further, these complexes are cytotoxic in A549 lung cancer cells, showing an enhancement of cytotoxicity upon light irradiation.

Cobalt(II), Nickel(II) and Copper(II) complexes of a tetradentate Schiff base as photosensitizers: Quantum yield of 1O2 generation and its promising role in anti-tumor activity.

In the present investigation, a Schiff base N'1,N'3-bis[(E)-(5-bromo-2-hydroxyphenyl)methylidene]benzene-1,3-dicarbohydrazide and its metal complexes have been synthesized and characterized. The DNA-binding studies were performed using absorption spectroscopy, emission spectra, viscosity measurements and thermal denatuaration studies. The experimental evidence indicated that, the Co(II), Ni(II) and Cu(II) complexes interact with calf thymus DNA through intercalation with an intrinsic binding constant Kb of 2.6×10(4) M(-1), 5.7×10(4) M(-1) and 4.5×10(4) M(-1), respectively and they exhibited potent photodamage abilities on pUC19 DNA, through singlet oxygen generation with quantum yields of 0.32, 0.27 and 0.30 respectively. The cytotoxic activity of the complexes resulted that they act as a potent photosensitizers for photochemical reactions.

Synthesis, DNA-binding, DNA-photonuclease profiling and antimicrobial activity of novel tetra-aza macrocyclic Ni(II), Co(II) and Cu(II) complexes constrained by thiadiazole.

A new tetra-aza macrocyclic ligand, L (C(24)H(16)N(12)O(2)S(4)) and its complexes of type, [MLCl(2)] and [CuL]Cl(2) (where M=Ni(II), Co(II); L=N,N'-(benzene-1,3-diyldi-1,3,4-thiadiazole-5,2-diyl)bis{2-[(5-benzene-1,3-diyl-1,3,4-thiadiazol-2-yl)amino]acetamide}) were synthesized and characterized by the spectral and analytical techniques. An octahedral geometry has been proposed for Ni(II) and Co(II) complexes while Cu(II) complex exhibit a square planar geometry. All the synthesized metal complexes were screened for their in vitro antimicrobial activity against selected species of pathogenic bacteria and fungi. The binding property of the complexes with CT-DNA was studied by absorption spectral analysis, followed by viscosity measurement and thermal denaturation studies. The photo induced cleavage studies revealed that the complexes possess photonuclease property against pUC19 DNA under UV-visible irradiation.