Synthesis, structure and ionic conductivity in scheelite type Li_0.5Ce_0.5-xLn_xMoO₄ (x = 0 and 0.25, Ln = Pr, Sm)

Scheelite type solid electrolytes, Li0.5Ce0.5-xLnxMoO4 (x = 0 and 0.25, Ln = Pr, Sm) have been synthesized using a solid state method. Their structure and ionic conductivity (σ) were obtained by single crystal X-ray diffraction and ac-impedance spectroscopy, respectively. X-ray diffraction studies reveal a space group of I41/a for Li0.5Ce0.5-xLnxMoO4 (x = 0 and 0.25, Ln = Pr, Sm) scheelite compounds. The unsubstituted Li0.5Ce0.5-xLnxMoO4 showed lithium ion conductivity ∼10−5-10−3 Ω−1cm−1 in the temperature range of 300-700°C (σ = 2.5 × 10−3 Ω−1cm−1 at 700°C). The substituted compounds show lower conductivity compared to the unsubstituted compound, with the magnitude of ionic conductivity being two (in the high temperature regime) to one order (in the low temperature regime) lower than the unsubstituted compound. Since these scheelite type structures show significant conductivity, the series of compounds could serve in high temperature lithium battery operations

Nucleotide Sequencing and Identification of Some Wild Mushrooms

The rDNA-ITS (Ribosomal DNA Internal Transcribed Spacers) fragment of the genomic DNA of 8 wild edible mushrooms (collected from Eastern Chota Nagpur Plateau of West Bengal, India) was amplified using ITS1 (Internal Transcribed Spacers 1) and ITS2 primers and subjected to nucleotide sequence determination for identification of mushrooms as mentioned. The sequences were aligned using ClustalW software program. The aligned sequences revealed identity (homology percentage from GenBank data base) of Amanita hemibapha [CN (Chota Nagpur) 1, % identity 99 (JX844716.1)], Amanita sp. [CN 2, % identity 98 (JX844763.1)], Astraeus hygrometricus [CN 3, % identity 87 (FJ536664.1)], Termitomyces sp. [CN 4, % identity 90 (JF746992.1)], Termitomyces sp. [CN 5, % identity 99 (GU001667.1)], T. microcarpus [CN 6, % identity 82 (EF421077.1)], Termitomyces sp. [CN 7, % identity 76 (JF746993.1)], and Volvariella volvacea [CN 8, % identity 100 (JN086680.1)]. Although out of 8 mushrooms 4 could be identified up to species level, the nucleotide sequences of the rest may be relevant to further characterization. A phylogenetic tree is constructed using Neighbor-Joining method showing interrelationship between/among the mushrooms. The determined nucleotide sequences of the mushrooms may provide additional information enriching GenBank database aiding to molecular taxonomy and facilitating its domestication and characterization for human benefits

AI systems as supplemental agents, rather than primary agents

In today’s information age, artificial intelligence has made a name for itself as a futuristic agent that will take away jobs and leave the planet in desolation. At least, that is what the skeptics believe. The proponents of AI choose to harbor a different philosophy, that it is an agent that will solve humanity’s most challenging problems. Perhaps both takes are justified—let us unpack why

An Intelligent Walking Stick for the Visually-Impaired People

Blind stick or white cane is introduced to blind people after the First World War as a mobility tool to detect the obstacles in the path of the user. This paper proposes an Arduino Nano based obstacle finding stick for visually-impaired people, which helps a blind person by detecting the obstacles using Ultrasonic sensors and android mobile application. It is able to inform the blind person about the circumstances & present condition of the path where he/she is walking. The main objective of this paper is to help a blind people to move more freely by using a reliable stick. The device consists of arduino nano, HC SR-04 ultrasonic sensor, HC-05 Bluetooth module, push buttons, 100nF ceramic capacitors and a 9V battery as the power source. And the android app is developed using MIT App Inventor 2

Stepwise Construction of Self-Assembled Heterometallic Cages Showing High Proton Conductivity

Two neutral tripodal metalloligands (CoL and FeL where L=C18H21N10) containing a clathrochelate core were synthesized and characterized in one-step. Reactions of these ligands with three different metal acceptors cis-(tmen)Pd(NO3)(2) (tmen = tetramethylethylenediamine), Zn(NO3)(2) and Mn(ClO4)(2) separately yielded a series of heterometallic coordination cages (1a3a and 1b-3b) in high yields. Depending on the nature of coordination geometry of the acceptors, the resulting assemblies have trigonal- bipyramidal (1a/1b), open-cubic (2a/2b), and closed-cubic structures (3a/3b). The structures of the complexes 1a, 2a, 2b, 3a, and 3b were confirmed by single-crystal X-ray diffraction studies. Analysis of crystal packing of the complexes 3a and 3b revealed the presence of several coordinated and lattice water molecules in the intermolecular channels. Both these complexes (3a and 3b) showed very high water adsorption under humid conditions. In addition, 3a and 3b exhibited promising proton conductivity of 3.31x10(-3) and 1.05x10(-4) S cm(-1) at 70 degrees C under 98 % relative humidity (RH) respectively, with activation energy of 1.000.78 eV

Synthesis, structure and ionic conductivity in scheelite type Li(0.5)Ce(0.5-x)Ln(x)MoO(4) (x=0 and 0.25, Ln = Pr, Sm)

Scheelite type solid electrolytes, Li(0.5)Ce(0.5-x)Ln(x)MoO(4) (x = 0 and 0.25, Ln = Pr, Sm) have been synthesized using a solid state method. Their structure and ionic conductivity (a) were obtained by single crystal X-ray diffraction and ac-impedance spectroscopy, respectively. X-ray diffraction studies reveal a space group of I4(1)/a for Li(0.5)Ce(0.5-x)Ln(x)MoO(4) (x = 0 and 0.25, Ln = Pr, Sm) scheelite compounds. The unsubstituted Li0.5Ce0.5MoO4 showed lithium ion conductivity similar to 10(-5)-10(-3) Omega(-1)cm(-1) in the temperature range of 300-700 degrees C (sigma = 2.5 x 10(-3) Omega(-1) cm(-1) at 700 degrees C). The substituted compounds show lower conductivity compared to the unsubstituted compound, with the magnitude of ionic conductivity being two (in the high temperature regime) to one order (in the low temperature regime) lower than the unsubstituted compound. Since these scheelite type structures show significant conductivity, the series of compounds could serve in high temperature lithium battery operations

Serum triacylglycerol: A putative early biomarker of disease severity of Type 2 diabetes mellitus compared to microalbuminuria

499-504Poorly controlled type 2 diabetes mellitus progresses to several complications including nephropathy. While glycated hemoglobin demarcates severity, urinary microalbumin indicates renal involvement. Considering nephropathy is a late manifestation of the disease, here, we explored whether serum triacylglycerol (TAG) can be used as an early disease severity biomarker. About 100 Type 2 diabetes mellitus patients were recruited and categorized as moderate (n=43) and severe (n=57) based on glycated haemoglobin (8%) level. Duration of the disease, BMI, systolic and diastolic BP, fasting and Post Prandial plasma glucose, glycated haemoglobin, serum lipid profile and urinary microalbumin were measured. Results obtained were compared between the groups and correlated. Taking glycated haemoglobin as reference, receiver operating characteristic curves were constructed for serum triacylglycerol and urinary microalbumin excretion to check their efficacy as classifier of disease severity. Significant differences (P <0.001) were recorded for plasma glucose, glycated haemoglobin, triacylglycerol and microalbuminuria but not for other parameters. Significant association (P <0.001) of glycated haemoglobin was displayed with triacylglycerol (r=0.67), fasting (r=0.0.71) and Post Prandial (r=0.82) plasma glucose and urine microalbumin levels (r=0.54). Serum triacylglycerol and urinary microalbumin levels also showed significant correlation (P <0.001, r=0.44). ROC curve analysis showed better performance of triacylglycerol (AUC=0.97) than microalbuminuria (AUC=0.88) to demarcate severity of diabetes. The results indicate that serum triacylglycerol is a better classifier of Type 2 diabetes mellitus than urinary microalbumin level, and may help in early assessment of the disease progression

In-situ data curation : A key to actionable AI at the edge

Machine learning (ML) algorithms have shown great potential in edge-computing environments, however, the literature mainly focuses on model inference only. We investigate how ML can be operationalized and how in-situ curation can improve the quality of edge applications, in the context of ML-assisted environmental surveys. We show that camera-enabled ML systems deployed on edge devices can enable scientists to perform real-time monitoring of species of interest or characterization of natural habitats. However, the benefit of this new technology is only as good as the quality and accuracy of the edge ML model inferences. In this demonstration, we show that with small additional time investment, domain scientists can manually curate ML model outputs and thus obtain highly reliable scientific insights, leading to more effective and scalable environmental surveys. </p