DeepTMH: Multimodal Semi-supervised framework leveraging Affective and Cognitive engagement for Telemental Health

To aid existing telemental health services, we propose DeepTMH, a novel framework that models telemental health session videos by extracting latent vectors corresponding to Affective and Cognitive features frequently used in psychology literature. Our approach leverages advances in semi-supervised learning to tackle the data scarcity in the telemental health session video domain and consists of a multimodal semi-supervised GAN to detect important mental health indicators during telemental health sessions. We demonstrate the usefulness of our framework and contrast against existing works in two tasks: Engagement regression and Valence-Arousal regression, both of which are important to psychologists during a telemental health session. Our framework reports 40% improvement in RMSE over SOTA method in Engagement Regression and 50% improvement in RMSE over SOTA method in Valence-Arousal Regression. To tackle the scarcity of publicly available datasets in telemental health space, we release a new dataset, MEDICA, for mental health patient engagement detection. Our dataset, MEDICA consists of 1299 videos, each 3 seconds long. To the best of our knowledge, our approach is the first method to model telemental health session data based on psychology-driven Affective and Cognitive features, which also accounts for data sparsity by leveraging a semi-supervised setup

PolyMorphPredict: A Universal Web-Tool for Rapid Polymorphic Microsatellite Marker Discovery From Whole Genome and Transcriptome Data

Microsatellites are ubiquitously distributed, polymorphic repeat sequence valuable for association, selection, population structure and identification. They can be mined by genomic library, probe hybridization and sequencing of selected clones. Such approach has many limitations like biased hybridization and selection of larger repeats. In silico mining of polymorphic markers using data of various genotypes can be rapid and economical. Available tools lack in some or other aspects like: targeted user defined primer generation, polymorphism discovery using multiple sequence, size and number limits of input sequence, no option for primer generation and e-PCR evaluation, transferability, lack of complete automation and user-friendliness. They also lack the provision to evaluate published primers in e-PCR mode to generate additional allelic data using re-sequenced data of various genotypes for judicious utilization of previously generated data. We developed the tool (PolyMorphPredict) using Perl, R, Java and launched at Apache which is available at http://webtom.cabgrid.res.in/polypred/. It mines microsatellite loci and computes primers from genome/transcriptome data of any species. It can perform e-PCR using published primers for polymorphism discovery and across species transferability of microsatellite loci. Present tool has been evaluated using five species of different genome size having 21 genotypes. Though server is equipped with genomic data of three species for test run with gel simulation, but can be used for any species. Further, polymorphism predictability has been validated using in silico and in vitro PCR of four rice genotypes. This tool can accelerate the in silico microsatellite polymorphism discovery in re-sequencing projects of any species of plant and animal for their diversity estimation along with variety/breed identification, population structure, MAS, QTL and gene discovery, traceability, parentage testing, fungal diagnostics and genome finishing

CNN_FunBar: Advanced Learning Technique for Fungi ITS Region Classification

Fungal species identification from metagenomic data is a highly challenging task. Internal Transcribed Spacer (ITS) region is a potential DNA marker for fungi taxonomy prediction. Computational approaches, especially deep learning algorithms, are highly efficient for better pattern recognition and classification of large datasets compared to in silico techniques such as BLAST and machine learning methods. Here in this study, we present CNN_FunBar, a convolutional neural network-based approach for the classification of fungi ITS sequences from UNITE+INSDC reference datasets. Effects of convolution kernel size, filter numbers, k-mer size, degree of diversity and category-wise frequency of ITS sequences on classification performances of CNN models have been assessed at all taxonomic levels (species, genus, family, order, class and phylum). It is observed that CNN models can produce >93% average accuracy for classifying ITS sequences from balanced datasets with 500 sequences per category and 6-mer frequency features at all levels. The comparative study has revealed that CNN_FunBar can outperform machine learning-based algorithms (SVM, KNN, Naïve-Bayes and Random Forest) as well as existing fungal taxonomy prediction software (funbarRF, Mothur, RDP Classifier and SINTAX). The present study will be helpful for fungal taxonomy classification using large metagenomic datasets

Revelation of Varying Bonding Motif of Alloxazine, a Flavin Analogue, in Selected Ruthenium(II/III) Frameworks

The reaction of alloxazine (L) and Ru^II(acac)₂(CH₃CN)₂ (acac^– = acetylacetonate) in refluxing methanol leads to the simultaneous formation of Ru^II(acac)₂(L) (<b>1</b> = bluish-green) and Ru^III(acac)₂(L^–) (<b>2</b> = red) encompassing a usual neutral α-iminoketo chelating form of L and an unprecedented monodeprotonated α-iminoenolato chelating form of L^–, respectively. The crystal structure of <b>2</b> establishes that N5,O4^– donors of L^– result in a nearly planar five-membered chelate with the {Ru^III(acac)₂⁺} metal fragment. The packing diagram of <b>2</b> further reveals its hydrogen-bonded dimeric form as well as π–π interactions between the nearly planar tricyclic rings of coordinated alloxazine ligands in nearby molecules. The paramagnetic <b>2</b> and one-electron-oxidized <b>1</b>⁺ display ruthenium­(III)-based anisotropic axial EPR in CH₃CN at 77 K with ⟨<i>g</i>⟩/Δ<i>g</i> of 2.136/0.488 and 2.084/0.364, respectively (⟨<i>g</i>⟩ = {1/3­(<i>g</i>₁² + <i>g</i>₂² + <i>g</i>₃²)}^1/2 and Δ<i>g</i> = <i>g</i>₁ – <i>g</i>₃). The multiple electron-transfer processes of <b>1</b> and <b>2</b> in CH₃CN have been analyzed by DFT-calculated MO compositions and Mulliken spin density distributions at the paramagnetic states, which suggest successive two-electron uptake by the π-system of the heterocyclic ring of L (L → L^•– → L^2–) or L^– (L^– → L^•2– → L^3–) besides metal-based (Ru^II/Ru^III) redox process. The origin of the ligand as well as mixed metal–ligand-based multiple electronic transitions of <b>1</b>^<i>n</i> (<i>n</i> = +1, 0, −1, −2) and <b>2</b>^<i>n</i> (<i>n</i> = 0, −1, −2) in the UV and visible regions, respectively, has been assessed by TD-DFT calculations in each redox state. The p<i>K</i>_a values of <b>1</b> and <b>2</b> incorporating two and one NH protons of 6.5 (N3H, p<i>K</i>_a1)/8.16 (N1H, p<i>K</i>_a2) and 8.43 (N1H, p<i>K</i>_a1), respectively, are estimated by monitoring their spectral changes as a function of pH in CH₃CN–H₂O (1:1). <b>1</b> and <b>2</b> in CH₃CN also participate in proton-driven internal reorganizations involving the coordinated alloxazine moiety, i.e., transformation of an α-iminoketo chelating form to an α-iminoenolato chelating form and the reverse process without any electron-transfer step: Ru^II(acac)₂(L) (<b>1</b>) → Ru^II(acac)₂(L^–) (<b>2</b>^–) and Ru^III(acac)₂(L^–) (<b>2</b>) → Ru^III(acac)₂(L) (<b>1</b>⁺)

Emission analysis of Eu3+: CaO-La2O3-B2O3 glass

This paper reports on the analysis of the emission spectra of Eu3+: CaO-La2O3-B2O3 glass-From the measurement of its optical absorption spectrum, three phenomenological Judd-Ofelt intensity parameters have been computed and used to parameterize the radiative properties such as spontaneous emission probability (A), radiative rate (AT), radiative lifetime (TR), branching ratios (fl) and stimulated emission cross sections (sigma(E)(P)) of the measured emission transitions. A significant change has been observed in the fluorescence features of Eu3+ glass due to the occurrence of crystallization from the controlled heat treatment schedules. Local environment structure in the glass around the rare earth ion has also been understood. From the XRD spectral profiles of the ceramized Eu3+: calcium lanthanum borate glass, the crystalline phases have been analyzed in correlation with the measurement of FT-IR spectra of this red luminescent glass. (C) 2007 Elsevier B.V. All rights reserved

Revelation of Varying Bonding Motif of Alloxazine, a Flavin Analogue, in Selected Ruthenium(II/III) Frameworks

The reaction of alloxazine (L) and Ru^II(acac)₂(CH₃CN)₂ (acac^– = acetylacetonate) in refluxing methanol leads to the simultaneous formation of Ru^II(acac)₂(L) (<b>1</b> = bluish-green) and Ru^III(acac)₂(L^–) (<b>2</b> = red) encompassing a usual neutral α-iminoketo chelating form of L and an unprecedented monodeprotonated α-iminoenolato chelating form of L^–, respectively. The crystal structure of <b>2</b> establishes that N5,O4^– donors of L^– result in a nearly planar five-membered chelate with the {Ru^III(acac)₂⁺} metal fragment. The packing diagram of <b>2</b> further reveals its hydrogen-bonded dimeric form as well as π–π interactions between the nearly planar tricyclic rings of coordinated alloxazine ligands in nearby molecules. The paramagnetic <b>2</b> and one-electron-oxidized <b>1</b>⁺ display ruthenium­(III)-based anisotropic axial EPR in CH₃CN at 77 K with ⟨<i>g</i>⟩/Δ<i>g</i> of 2.136/0.488 and 2.084/0.364, respectively (⟨<i>g</i>⟩ = {1/3­(<i>g</i>₁² + <i>g</i>₂² + <i>g</i>₃²)}^1/2 and Δ<i>g</i> = <i>g</i>₁ – <i>g</i>₃). The multiple electron-transfer processes of <b>1</b> and <b>2</b> in CH₃CN have been analyzed by DFT-calculated MO compositions and Mulliken spin density distributions at the paramagnetic states, which suggest successive two-electron uptake by the π-system of the heterocyclic ring of L (L → L^•– → L^2–) or L^– (L^– → L^•2– → L^3–) besides metal-based (Ru^II/Ru^III) redox process. The origin of the ligand as well as mixed metal–ligand-based multiple electronic transitions of <b>1</b>^<i>n</i> (<i>n</i> = +1, 0, −1, −2) and <b>2</b>^<i>n</i> (<i>n</i> = 0, −1, −2) in the UV and visible regions, respectively, has been assessed by TD-DFT calculations in each redox state. The p<i>K</i>_a values of <b>1</b> and <b>2</b> incorporating two and one NH protons of 6.5 (N3H, p<i>K</i>_a1)/8.16 (N1H, p<i>K</i>_a2) and 8.43 (N1H, p<i>K</i>_a1), respectively, are estimated by monitoring their spectral changes as a function of pH in CH₃CN–H₂O (1:1). <b>1</b> and <b>2</b> in CH₃CN also participate in proton-driven internal reorganizations involving the coordinated alloxazine moiety, i.e., transformation of an α-iminoketo chelating form to an α-iminoenolato chelating form and the reverse process without any electron-transfer step: Ru^II(acac)₂(L) (<b>1</b>) → Ru^II(acac)₂(L^–) (<b>2</b>^–) and Ru^III(acac)₂(L^–) (<b>2</b>) → Ru^III(acac)₂(L) (<b>1</b>⁺)

Revelation of Varying Coordination Modes and Noninnocence of Deprotonated 2,2′-Bipyridine-3,3′-diol in {Os(bpy)₂} Frameworks

The reaction of 2,2′-bipyridine-3,3′-diol (H₂L) and <i>cis</i>-Os^II(bpy)₂­Cl₂ (bpy = 2,2′-bipyridine) results in isomeric forms of [Os^II(bpy)₂(HL^–)]­ClO₄, [<b>1</b>]­ClO₄ and [<b>2</b>]­ClO₄, because of the varying binding modes of partially deprotonated HL^–. The identities of isomeric [<b>1</b>]­ClO₄ and [<b>2</b>]­ClO₄ have been authenticated by their single crystal X-ray structures. The ambidentate HL^– in [<b>2</b>]­ClO₄ develops the usual N,N bonded five-membered chelate with a strong O–H···O hydrogen bonded situation (O–H···O angle: 160.78°) at its back face. The isomer [<b>1</b>]­ClO₄ however represents the monoanionic O^–,N coordinating mode of HL^–, leading to a six-membered chelate with the moderately strong O–H···N hydrogen bonding interaction (O–H···N angle: 148.87°) at its backbone. The isomeric [<b>1</b>]­ClO₄ and [<b>2</b>]­ClO₄ also exhibit distinctive spectral, electrochemical, electronic structural, and hydrogen bonding features. The p<i>K</i>_a values for [<b>1</b>]­ClO₄ and [<b>2</b>]­ClO₄ have been estimated to be 0.73 and <0.2, respectively, thereby revealing the varying hydrogen bonding interaction profiles of O–H···N and O–H···O involving the coordinated HL^–. The O–H···O group of HL^– in <b>2</b>⁺ remains invariant in the basic region (pH 7–12), while deprotonation of O–H···N group of HL^– in <b>1</b>⁺ estimates the p<i>K</i>_b value of 11.55. This indeed has facilitated the activation of the exposed O–H···N function in [<b>1</b>]­ClO₄ by the second {Os^II(bpy)₂} unit to yield the L^2– bridged [(bpy)₂Os^II(μ-L^2–)­Os^II(bpy)₂]­(ClO₄)₂ ([<b>3</b>]­(ClO₄)₂). However, the O–H···O function in [<b>2</b>]­ClO₄ fails to react with {Os^II(bpy)₂}. The crystal structure of [<b>3</b>]­(ClO₄)₂ establishes the symmetric N,O^–/O^–,N bridging mode of L^2–. On the other hand, the doubly deprotonated L′^2– (H₂L′ = 2,2′-biphenol) generates structurally characterized twisted seven-membered O^–,O^– bonded chelate (torsion angle >50°) in paramagnetic [Os^III(bpy)₂­(L′^2–)]­ClO₄ ([<b>4</b>]­ClO₄). The electronic structural aspects of the complexes reveal the noninnocent potential of the coordinated HL^–, L^2–, and L′^2–. The <i>K</i>_c value of 49 for <b>3</b>³⁺ reveals a class I mixed-valent Os^IIOs^III state

PolyMorphPredict: Web server for rapid polymorphic SSR locus discovery from whole genome and transcriptome data

Not AvailableMicrosatellites are ubiquitously distributed, polymorphic repeat sequence valuable for association, selection, population structure and identification. They can be mined by genomic library, probe hybridization and sequencing of selected clones. Such approach has many limitations like biased hybridization and selection of larger repeats. In silico mining of polymorphic markers using data of various genotypes can be rapid and economical. Available tools lack in some or other aspects like: targeted user defined primer generation, polymorphism discovery using multiple sequence, size and number limits of input sequence, no option for primer generation and e-PCR evaluation, transferability, lack of complete automation and user-friendliness. They also lack the provision to evaluate published primers in e-PCR mode to generate additional allelic data using re-sequenced data of various genotypes for judicious utilization of previously generated data. We developed the tool (PolyMorphPredict) using Perl, R, Java and launched at Apache which is available at http://webtom.cabgrid.res.in/polypred/. It mines microsatellite loci and computes primers from genome/transcriptome data of any species. It can perform e-PCR using published primers for polymorphism discovery and across species transferability of microsatellite loci. Present tool has been evaluated using five species of different genome size having 21 genotypes. Though server is equipped with genomic data of three species for test run with gel simulation, but can be used for any species. Further, polymorphism predictability has been validated using in silico and in vitro PCR of four rice genotypes. This tool can accelerate the in silico microsatellite polymorphism discovery in re-sequencing projects of any species of plant and animal for their diversity estimation along with variety/breed identification, population structure, MAS, QTL and gene discovery, traceability, parentage testing, fungal diagnostics and genome finishing.Not Availabl