Quantum paramagnetic ground states on the honeycomb lattice and field-induced transition to N\'eel order

Motivated by recent experiments on Bi$_3$Mn$_4$O$_{12}$(NO$_3$), and a broader interest arising from numerical work on the honeycomb lattice Hubbard model, we have studied the effect of a magnetic field on honeycomb lattice spin models with quantum paramagnetic ground states. For a model with frustrating second-neighbor exchange, $J_2$, we use a Lindemann-like criterion within spin wave theory to show that N\'eel order melts beyond a critical $J_2$. The critical $J_2$ increases with a magnetic field, implying the existence of a field-induced paramagnet-N\'eel transition over a range of $J_2$. We also study bilayer model using a spin-$S$ generalization of bond operator mean field theory. We show that there is a N\'eel-dimer transition for various spin values with increasing bilayer coupling, and that the resulting interlayer dimer state undergoes a field induced transition into a state with transverse N\'eel order. Finally, we study a spin-3/2 model which interpolates between the Heisenberg model and the Affleck-Kennedy-Lieb-Tasaki (AKLT) parent Hamiltonian. Using exact diagonalization, we compute the fidelity susceptibility to locate the Neel-AKLT quantum critical point, obtain the spin gap of the AKLT parent Hamiltonian, and argue that AKLT state also undergoes field-induced Neel ordering.Comment: 8 pages, revised longer version of arXiv:1012.0316. Corrected factor of 2 error in Eq.[16], replotted Fig.[4] and revised the critical $J_c/J_1$ needed to stabilize interlayer dimer state. We thank S. V. Isakov for discussions which uncovered this erro

Synthesis and Antimicrobial Evaluation of Novel Carbazole Based β-diketones and its Pyrazole Derivatives

Novel 9-ethyl-9H-carbazole-3-carboxylic acid derivatives including ester, β-diketone and pyrazole were prepared and characterized by FT-IR, 1H NMR, 13C NMR and mass spectroscopic techniques. All synthesized compounds evaluated for their in vitro antimicrobial activities against four bacteria (Escherichia coli, Pseudomonas putide, Bacillus subtilis, and Streptococcus lactis) and three fungi (Aspergillus niger, Penicillium sp and Candida albicans). Among the compounds tested, 3a, 3b, 3c, 4a, 4b, 4c, 5a and 5b exhibited pronounced antibacterial activity as compared with standard drug ampicillin. Notably, carbazole based pyrazole derivatives 5a and 5b showed potent antifungal activity against C. albicans comparable to reference drug greseofulvin. This work is licensed under a Creative Commons Attribution 4.0 International License

Assessment of sources and distribution metals in groundwater of Pondicherry region, India

The proposed study investigates the seasonal variation in the concentration and the source of the heavy metals like Mn, Cu, Pb, Zn and Fe in the groundwater samples of Pondicherry region. The study results reveal that, the heavy metal concentration is high during South West Monsoon season (SWM) compared to that of North East Monsoon season (NEM). The pH was near neutral and metal load representing most of the samples were low during NEM. Statistical analysis shows that the 63.7 % of the total variance is observed during NEM and 68.9% during SWM. Geographic information system (GIS) tool was considered for the study to understand the environmental pollution status of the groundwater systems of the study area and to identify the groundwater quality parameters. The multivariate statistical analysis explains that the source of trace metal in the groundwater is derived from natural origin except copper and lead as these contaminants were derived from anthropogenic activities. Based on the output of WATEQ4F, several species of heavy metals exist, in which the dominant species are Mn, CuCl2, PbCO3, Fe and Zn

Assessment of seasonal groundwater quality using CHIDAM software in Virudhunagar district of Tamil Nadu.

Hard rock aquifer is the most predominant in the southern peninsula exclusively in Tamil Nadu, India. Virudhunagar district is situated in the South west part of Tamil Nadu, mostly of hard rock topography. Groundwater plays a major role in this area contributing to domestic, irrigation and industrial practices. Running down of groundwater by extreme consumption and less recharge in the study area has reduced the level of groundwater. On the other hand, intensive domestic, agriculture and industrial practices impacts the quality of quality of groundwater as well. Hydro geochemistry plays an important role in evaluation of suitability of groundwater for its usage in several purposes. A total of 72 samples from North East Monsoon (NEM) and Post Monsoon (POM) has been analyzed hydrochemically. The irrigation quality parameters such as sodium adsorption ratio (SAR), %Na, Residual Sodium Carbonate (RSC), Kelley’s index and Magnesium hazard were calculated using CHIDAM software 2020 in conjunction with USSL and Doneen diagrams. During NEM, EC and TDS ranges from 273 to 5869 mg/L and 194 to 4159 mg/L and during POM is from 235 to 6850 mg/L and 233.8 to 6916 mg/L. The hydrogeochemical facies represents that Ca-HCO3 and mixed Ca-Mg-Cl facies are predominant during NEM and Na-Cl and mixed Ca-Mg-Cl are predominant during POM. The higher concentration of TDS and EC in the samples reflects the unsuitability of groundwater in both seasons

Structural studies on MtRecA-nucleotide complexes: insights into DNA and nucleotide binding and the structural signature of NTP recognition

RecA protein plays a crucial role in homologous recombination and repair of DNA. Central to all activities of RecA is its binding to Mg+2-ATP. The active form of the protein is a helical nucleoprotein filament containing the nucleotide cofactor and single-stranded DNA. The stability and structure of the helical nucleoprotein filament formed by RecA are modulated by nucleotide cofactors. Here we report crystal structures of a MtRecA-ADP complex, complexes with ATPS in the presence and absence of magnesium as well as a complex with dATP and Mg+2. Comparison with the recently solved crystal structures of the apo form as well as a complex with ADP-AlF4 confirms an expansion of the P-loop region in MtRecA, compared to its homologue in Escherichia coli, correlating with the reduced affinity of MtRecA for ATP. The ligand bound structures reveal subtle variations in nucleotide conformations among different nucleotides that serve in maintaining the network of interactions crucial for nucleotide binding. The nucleotide binding site itself, however, remains relatively unchanged. The analysis also reveals that ATPS rather than ADP-AlF4 is structurally a better mimic of ATP. From among the complexed structures, a definition for the two DNA-binding loops L1 and L2 has clearly emerged for the first time and provides a basis to understand DNA binding by RecA. The structural information obtained from these complexes correlates well with the extensive biochemical data on mutants available in the literature, contributing to an understanding of the role of individual residues in the nucleotide binding pocket, at the molecular level. Modeling studies on the mutants again point to the relative rigidity of the nucleotide binding site. Comparison with other NTP binding proteins reveals many commonalties in modes of binding by diverse members in the structural family, contributing to our understanding of the structural signature of NTP recognition

Plant Disease Detection using Deep Learning in Banana and Sunflower

In recent years plant disease detection and classification is finding a lot of scope in the field of agriculture. The use of image pre-processing along with deep learning techniques is making the role of farmers easy in the process of plant leaf disease detection. In this paper we propose a deep learning technique, ResNet-50 for the identification and classification of leaf diseases mainly in banana and sunflower. Images for the training and testing purpose are collected by visiting the farms and from village dataset for normal, leaf spot, leaf blight, powdery mildew, bunchy top, sigatoka, panama wilt. Pre-processing is done to remove eliminate the noise in the image by converting the RGB input to HSV image. Binary pictures are retrieved to separate the diseased and unaffected portions based on the hue and saturation components. A clustering method is utilized to separate the diseased region from the normal portion and the background. Classification of the disease is carried out using ResNet-50 algorithm. The experimental results obtained are compared with CNN, machine learning algorithms like SVM, KNN, DT and Ensemble algorithm like RF and XG booster. The proposed algorithm provided maximum efficiency compared to other algorithms

Automated Accidental Precautions in Public Transportation Management System

This paper aims at different types of transportation problems by presenting a proper management process to improve the public transportation management system. In modern era, the accidents and the indifference makes the major death rate, this is because of the lagging of immediate precautionary actions. In order to decrease the death rate and also to improve the immediate measures for the effect is proposed by using the method of IoT. In this system, every bus contains GPS to track the bus if it met with an accident, crash sensor and pressure sensor is also used to check whether the bus dashed with other vehicles or not and piezo sensor is to check if the bus roll down due to any mechanical failures. The level of accident at the hazardous weather that is, the wind flow at hills station makes an unstable condition for the transportation system. Basically, in hill areas the wind flowin every day is unpredictable one and a challengeable one. To avoid those risky factors, we implemented cruise control which accommodate the speed limit of the vehicles according to the pre-moving vehicles