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Author Correction: Integrated approach for studying bioactive compounds from Cladosporium spp. against estrogen receptor alpha as breast cancer drug target (Scientific Reports, (2022), 12, 1, (22446), 10.1038/s41598-022-22038-x)
No full textThe original version of the Article contained an error in the Author Information section. “These authors contributed equally: Satish Anandan, Hittanahallikoppal Gajendramurthy Gowtham, C. S. Shivakumara, Anjana Thampy, Sudarshana Brijesh Singh, Mahadevamurthy Murali, Chandan Shivamallu, Sushma Pradeep, Natarajamurthy Shilpa, Ali A. Shati, Mohammad Y. Alfaifi, Serag Eldin I. Elbehairi, Joaquín Ortega‑Castro, Juan Frau, Norma Flores‑Holguín, Shiva Prasad Kollur and Daniel Glossman‑Mitnik.” now reads: “These authors contributed equally: Satish Anandan and Hittanahallikoppal Gajendramurthy Gowtham.” In addition, Shiva Prasad Kollur was incorrectly affiliated with “Department of Clinical Sciences, College of Veterinary Medicine, Kansas State University, Manhattan, Kansas 66506‑5606, USA” and “Midwest Veterinary Services, Inc., Oakland, NE 68045, USA”. The correct affiliation is listed below. School of Physical Sciences, Amrita Vishwa Vidyapeetham, Mysuru Campus, Mysuru, Karnataka, 570 026, India. The author, Mohammad Y. Alfaifi, was incorrectly affiliated with “Cell Culture Lab, Egyptian Organization for Biological Products and Vaccines (VACSERA Holding Company), 51 Wezaret El-Zeera St., Agouza, Giza, Egypt”. The correct affiliation is listed below: Biology Department, Faculty of Sciences, King Khalid University, Abha, Saudi Arabia. The original version of this Article also contained an error in Affiliation 10, which was incorrectly given as ‘Department of Clinical Sciences, College of Veterinary Medicine, Kansas State University, Manhattan, Kansas 66506‑5606, USA.’ The correct affiliation is listed below: School of Physical Sciences, Amrita Vishwa Vidyapeetham, Mysuru Campus, Mysuru, Karnataka, 570 026, India. In addition, Affiliation 11 ‘Midwest Veterinary Services, Inc., Oakland, NE 68045, USA’ was removed. © The Author(s) 2023
FAEO-ECNN: cyberbullying detection in social media platforms using topic modelling and deep learning
No full textThe widespread use of Social Media Platforms (SMP) such as Twitter, Instagram, Facebook, etc. by individuals has recently led to a remarkable increase in Cyberbullying (CB). It is a challenging task to prevent CB in such platforms since bullies use sarcasm or passive-aggressiveness strategies. This article proposes a new CB detection model named FAEO-ECNN for detecting and classifying cyberbullying on social media platforms. The proposed approach integrates Fuzzy Adaptive Equilibrium Optimization (FAEO) clustering-based topic modelling and Extended Convolutional Neural Network (ECNN) to enhance the accuracy of CB detection process. Initially, pre-processing is performed in order to cleanse the dataset. Next, the features are extracted using multiple models. The unsupervised Fuzzy Adaptive Equilibrium Optimization (FAEO) is utilized for discovering the latent topics from the pre-processed input data, which automatically examines the text data and creates clusters of words. Finally, the cyberbullying classification makes use of the ECNN and Rain Optimization (RO) algorithm to detect CB from posts/texts. We evaluated the proposed FAEO-ECNN thoroughly with two short text datasets: Real-world CB Twitter (RW-CB-Twitter) and Cyberbullying Menedely (CB-MNDLY) datasets in comparison to State of The Art (SoTA) models like Long Short Term Memory (LSTM), Bi-directional LSTM (BLSTM), RNN, and CNN-LSTM. The proposed FAEO-ECNN model outperformed the SoTA models in detecting Cyberbullying on SMP. It has obtained 92.91 of accuracy, 92.28 of recall, 92.53 of precision, and 92.40 of F-Measure over CB-MNDLY dataset. Moreover, it has achieved 91.89 of accuracy, 91.32 of recall, 91.81 of precision, and 91.56 of F-Measure on RW-CB-Twitter dataset. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature
Gender identification of Drosophila melanogaster based on morphological analysis of microscopic images
Get PDFDrosophila melanogaster (D. melanogaster) is an imperative genomic model organism that is employed widely in healthcare and biological research works. Roughly 61% of recognized human genes have a perceptible similarity with the genetic code of D. melanogaster flies, besides 50% of its protein structures have mammalian equivalents. In recent times, numerous studies have been done in D. melanogaster to investigate the functions of particular genes that are available in its central nervous system, including the major organs like the heart, liver and kidney. The findings of these research works through D. melanogaster are utilized as a key mechanism to explore human interrelated diseases. However, it is essential to recognize the male and female Drosophila flies for the better understanding of human disease related studies, and it is a tricky job. This paper describes a unique programmed system to categorize the gender of D. melanogaster from the ventral view portraits captured through microscope. The proposed method includes image segmentation of the body of D. melanogaster in the form of a binary image and the construction of a continuous morphological model based on its skeleton. An analysis of the skeleton makes it possible to assess the sharpness of the caudal end of the D. melanogaster abdomen through a detailed assessment of the curvature. Based on this assessment, a Drosophila melanogaster Gender (DMG) classifier is constructed for the gender determination of D. melanogaster flies. The accuracy of the DMG classifier is about 98% in proportion to the existing state-of-the-art shape-based classifiers with optimal computing time
Constitutions Without Constitutionalism: Reflections on Afghanistan’s Failed Constitutions
Get PDFhe failure of the Afghan constitution is attributed to societal values
incompatible with democracy, making the country appear ungovernable.
The Taliban’s return has sparked debates on regime legitimacy and
constitutionalisation. This process will shape Afghanistan’s approach
to humanitarian and refugee law, and international aid. The 1964
Constitution was a milestone but was regarded as a failure while the 2004
Constitution, favouring democratic principles, is now illegal. Afghanistan’s
challenges stem from a legitimacy crisis, limited citizen participation and
parallel institutions. This article examines the successive failure of Afghan
constitutions, focusing on the 1923, 1964, and 2004 ones. The study utilises
doctrinal legal research, employing normative approaches to evaluate relevant
literature, including secondary, primary, and legal documents
The Role of Using Social Networking Sites to Achieve Competitive Advantage in the Tourism Companies in Afghanistan Botswana
Get PDFSynthesis, crystal structure and Hirshfeld surface analysis of N-(4-fluorophenyl)-N-isopropyl-2-(methylsulfonyl)acetamide
No full textThe synthesis and crystal structure of the title compound, C12H16FNO3S, which is related to the herbicide flufenacet, are presented. The dihedral angle between the amide group and the fluorinated benzene ring is 87.30 (5)° and the N—C—C—S torsion angle defining the orientation of the methylsulfonyl substituent relative to the amide group is 106.91 (11)°. In the crystal, inversion-related molecules form dimers as a result of pairwise C—H⋯O hydrogen bonds, which appear to be reinforced by short O⋯π contacts [O⋯Cg = 3.0643 (11) Å]. A Hirshfeld surface analysis was used to quantify the various types of intermolecular contacts, which are dominated by H atoms
Syntheses and crystal structures of three salts of 1-(4-nitrophenyl)piperazine
No full textThe crystal structures and Hirshfeld surface analyses of three salts of 1-(4-nitrophenyl)piperazine with 2-chlorobenzoic acid, 2-bromobenzoic acid and 2-iodobenzoic acid are reported. The chlorobenzoate salt, C10H14N3O2+·C7H4ClO2−, contains whole-ion-disordered cations and anions, which were modeled with two equivalent conformations with occupancies of 0.745 (10)/0.255 (10) and 0.563 (13)/0.437 (13), respectively. The bromobenzoate and iodobenzoate derivatives are isomorphous and crystallize as hemihydrates, viz. C10H14N3O2+·C7H4BrO2−·0.5H2O and C10H14N3O2+·C7H4IO2−·0.5H2O, respectively [the water molecule is disordered over two locations with occupancies of 0.276 (3)/0.223 (3) for the iodobenzoate derivative]. In the extended structures, all three salts feature an R44(12) loop of two anions and two cations linked by N—H⋯O hydrogen bonds
Crystal structure and Hirshfeld-surface analysis of a monoclinic polymorph of 2-amino-5-chlorobenzophenone oxime at 90 K
Get PDFThe synthesis and crystal structure of a monoclinic polymorph of 2-amino-5-chlorobenzophenone oxime, C13H11ClN2O, are presented. The molecular conformation results from twisting of the phenyl and 2-amino-5-chloro benzene rings attached to the oxime group, which subtend a dihedral angle of 80.53 (4)°. In the crystal, centrosymmetric dimers are formed as a result of pairs of strong O—H⋯N hydrogen bonds. A comparison is made to a previously known triclinic polymorph, including differences in atom–atom contacts obtained via a Hirshfeld-surface analysis
Multicomponent assessment and optimization of the cellulase activity by Serratia marcescens inhabiting decomposed leaf litter soil
No full textIn lignocellulosic biomass digestion, the enzymatic hydrolysis of lignocellulosic polymers is regarded as the rate-limiting step for enzyme synthesis. The present study is focused on hydrolytic microbial communities isolation from degraded leaf litter soil, and optimization efforts that aid in the decomposition of biomass in the environment. Based on morphological characteristics and leads from preliminary testing, four of the isolates were determined to be effective cellulose degraders. Molecular identification of robust microbial genera included Galactomyces sp. Cefu3, Aspergillus flavus N11, Serratia marcescens CH1, and Bacillus sp Cp4 species, respectively. Serratia marcescens CH1 was determined to be the most potent of the four isolates for cellulase enzyme activity. Further, Serratia marcescens CH1 exhibited highest multi-enzyme activity for endo-(1,4)B-D-glucanase, exo-(1,4)-B-D-glucanase, and B-glucosidase. The assay conditions were optimized and determined by the Response Surface Methodology (RSM)
