Height in splittings of relatively hyperbolic groups

Geometriae Dedicata - Given a finite graph of relatively hyperbolic groups with its fundamental group relatively hyperbolic and edge groups quasi-isometrically embedded and relatively quasiconvex...     

Synthesis and Crystal Structure Analysis of 3,3'-[(3-Sulfanyl Phenyl)Methylene]Bis(4-Hydroxy-2H-1-Benzopyran-2-One) : 5-Methyl-1,3-Thiazol-2(3H)-Imine

Crystallography Reports - The structure of 3,3'-[(3-sulfanylphenyl)methylene]bis(4-hydroxy-2H-1-benzopyran-2-one) : 5-methyl-1,3-thiazol-2(3H)-imine was determined by X-ray crystallography. It...     

Experimental investigation for stability and surface properties of TiO2 and Al2O3 water-based nanofluids

Journal of Thermal Analysis and Calorimetry - Nanofluids have gained recent attention because of their potential applications in diverse engineering fields like enhancing thermal transport,...     

H2-release from alcohols,diols, and compounds with amino functionality promoted by titanium(II) sandwich complex, [Cp2Ti]: a theoretical approach

Structural Chemistry - The role of Ti(II) sandwich complex, [Cp2Ti], generated by the combination of [Cp2TiCl2] and two equivalents of nBuLi, in situ, in toluene has been investigated theoretically...     

Artificial neural network‐based modeling of snow properties using field data and hyperspectral imagery

This study attempts to model snow wetness and snow density of Himalayan snow cover using a combination of Hyperspectral image processing and Artificial Neural Network (ANN). Initially, a total of 300 spectral signature measurements, synchronized with snow wetness and snow density, were collected in the field. The spectral reflectance of snow was then modeled as a function of snow properties using ANN. Four snow wetness and three snow density models were developed. A strong correlation was observed in near‐infrared and shortwave‐infrared region. The correlation analysis of ANN modeled snow density and snow wetness showed a strong linear relationship with field‐based data values ranging from 0.87–0.90 and 0.88–0.91, respectively. Our results indicate that an Artificial Intelligence (AI) approach, using a combination of Hyperspectral image processing and ANN, can be efficiently used to predict snow properties (wetness and density) in the Himalayan region. Recommendations for resource managers

• Snow properties, such as snow wetness and snow density are mainly investigated through field‐based survey but rugged terrains, difficult weather conditions, and logistics management issues establish remote sensing as an efficient alternative to monitor snow properties, especially in the mountain environment.
• Although Hyperspectral remote sensing is a powerful tool to conduct the quantitative analysis of the physical properties of snow, only a few studies have used hyperspectral data for the estimation of snow density and wetness in the Himalayan region. This could be because of the lack of synchronized snow properties data with field‐based spectral acquisitions.
• In combination with Hyperspectral image processing, Artificial Neural Network (ANN) can be a useful tool for effective snow modeling because of its ability to capture and represent complex input‐output relationships.
• Further research into understanding the applicability of neural networks to determine snow properties is required to obtain results from large snow cover areas of the Himalayan region.

     

Synthesis and biological evaluation of novel 4-(6-substituted quinolin-4-yl)-N-aryl thiazol-2-amine derivatives as potential antimicrobial agents

Cyclocondensation reaction of 4-(2-bromoacetyl)quinolin-1-ium bromide ( 4a–d ) with substituted arylthiourea, ( 5a–g ) afforded 4-(6-substituted quinolin-4-yl)-N-aryl/pyridyl thiazol-2-amine ( 6a-ab ). These newly synthesized derivatives were evaluated for in vitro antibacterial activity against Escherichia coli (NCIM 2574), Proteus mirabilis (NCIM 2388) (Gram-negative strains), Bacillus subtilis (NCIM 2063), Staphylococcus albus (NCIM 2178) (Gram-positive strains) and in vitro antifungal activity against Aspergillus niger (ATCC 504) and Candida albicans (NCIM 3100). Compounds 6a , 6b , 6d , 6f , 6k , and 6l showed moderate to good antibacterial activity against S. albus. Ten derivatives 6c , 6q , 6r , 6s , 6t , 6v , 6w , 6x , 6y , and 6aa , showed moderate to good activity against A. niger. N-[4-(Quinolin-4-yl)-1,3-thiazol-2-yl]pyridin-2-amine presented comparable activity against A. niger with respect to standard drug Rouconazole.     

Fibrillar Networks of Glycyrrhizic Acid for Hybrid Nanomaterials with Catalytic Features

Self‐assembly of the naturally occurring sweetening agent, glycyrrhizic acid (GA) in water is studied by small‐angle X‐ray scattering and microscopic techniques. Statistical analysis on atomic force microscopy images reveals the formation of ultralong GA fibrils with uniform thickness of 2.5 nm and right‐handed twist with a pitch of 9 nm, independently of GA concentration. Transparent nematic GA hydrogels are exploited to create functional hybrid materials. Two‐fold and three‐fold hybrids are developed by introducing graphene oxide (GO) and in situ‐synthesized gold nanoparticles (Au NPs) in the hydrogel matrix for catalysis applications. In the presence of GO, the catalytic efficiency of Au NPs in the reduction of p‐nitrophenol to p‐aminophenol is enhanced by 2.5 times. Gold microplate single crystals are further synthesized in the GA hydrogel, expanding the scope of these hybrids and demonstrating their versatility in materials design.     

Conjugated Polymer Nanoparticle‐Triplet Emitter Hybrids in Aqueous Dispersion: Fabrication and Fluorescence Quenching Behavior

Conjugated polymer nanoparticles based on poly[9,9‐bis(2‐ethylhexyl)fluorene] and poly[N‐(2,4,6‐trimethylphenyl)‐N,N‐diphenylamine)‐4,4′‐diyl] are fabricated using anionic surfactant sodium dodecylsulphate in water by miniemulsion technique. Average diameters of polyfluorene and polytriarylamine nanoparticles range from 70 to 100 and 100 to 140 nm, respectively. The surface of the nanoparticles is decorated with triplet emitting dye, tris(2,2′‐bipyridyl)ruthenium(II) chloride. Intriguing photophysics of aqueous dispersions of these hybrid nanoparticles is investigated. Nearly 50% quenching of fluorescence is observed in the case of dye‐coated polyfluorene nanoparticles; excitation energy transfer is found to be the dominant quenching mechanism. On the other hand, nearly complete quenching of emission is noticed in polytriarylamine nanoparticle‐dye hybrids. It is proposed that the excited state electron transfer from the electron‐rich polytriarylamine donor polymer to Ru complex leads to the complete quenching of emission of polytriarylamine nanoparticles. The current study offers promising avenues for developing aqueous solution processed‐electroluminescent devices involving a conjugated polymer nanoparticle host and Ru or Ir‐based triplet emitting dye as the guest.