Crystal structure of methyl 1-methyl-2-oxospiro[indoline-3,2′-oxirane]-3′-carboxylate

Acknowledgements The authors thank Dr Babu Vargheese, SAIF, IIT, Madras, India, for the data collection.Peer reviewedPublisher PD

Emotion classification in Parkinson's disease by higher-order spectra and power spectrum features using EEG signals: A comparative study

Deficits in the ability to process emotions characterize several neuropsychiatric disorders and are traits of Parkinson's disease (PD), and there is need for a method of quantifying emotion, which is currently performed by clinical diagnosis. Electroencephalogram (EEG) signals, being an activity of central nervous system (CNS), can reflect the underlying true emotional state of a person. This study applied machine-learning algorithms to categorize EEG emotional states in PD patients that would classify six basic emotions (happiness and sadness, fear, anger, surprise and disgust) in comparison with healthy controls (HC). Emotional EEG data were recorded from 20 PD patients and 20 healthy age-, education level- and sex-matched controls using multimodal (audio-visual) stimuli. The use of nonlinear features motivated by the higher-order spectra (HOS) has been reported to be a promising approach to classify the emotional states. In this work, we made the comparative study of the performance of k-nearest neighbor (kNN) and support vector machine (SVM) classifiers using the features derived from HOS and from the power spectrum. Analysis of variance (ANOVA) showed that power spectrum and HOS based features were statistically significant among the six emotional states (p < 0.0001). Classification results shows that using the selected HOS based features instead of power spectrum based features provided comparatively better accuracy for all the six classes with an overall accuracy of 70.10% ± 2.83% and 77.29% ± 1.73% for PD patients and HC in beta (13-30 Hz) band using SVM classifier. Besides, PD patients achieved less accuracy in the processing of negative emotions (sadness, fear, anger and disgust) than in processing of positive emotions (happiness, surprise) compared with HC. These results demonstrate the effectiveness of applying machine learning techniques to the classification of emotional states in PD patients in a user independent manner using EEG signals. The accuracy of the system can be improved by investigating the other HOS based features. This study might lead to a practical system for noninvasive assessment of the emotional impairments associated with neurological disorders

Efficient VQE Approach for Accurate Simulations on the Kagome Lattice

The Kagome lattice, a captivating lattice structure composed of interconnected triangles with frustrated magnetic properties, has garnered considerable interest in condensed matter physics, quantum magnetism, and quantum computing.The Ansatz optimization provided in this study along with extensive research on optimisation technique results us with high accuracy. This study focuses on using multiple ansatz models to create an effective Variational Quantum Eigensolver (VQE) on the Kagome lattice. By comparing various optimisation methods and optimising the VQE ansatz models, the main goal is to estimate ground state attributes with high accuracy. This study advances quantum computing and advances our knowledge of quantum materials with complex lattice structures by taking advantage of the distinctive geometric configuration and features of the Kagome lattice. Aiming to improve the effectiveness and accuracy of VQE implementations, the study examines how Ansatz Modelling, quantum effects, and optimization techniques interact in VQE algorithm. The findings and understandings from this study provide useful direction for upcoming improvements in quantum algorithms,quantum machine learning and the investigation of quantum materials on the Kagome Lattice.Comment: 7 pages,7 figure

3′-[Hy­droxy(4-oxo-4H-chromen-3-yl)meth­yl]-2-oxospiro­[indoline-3,2′-pyrrolidine]-3′-carbonitrile

In the title compound, C23H19N3O4, the pyran ring adopts a half-chair conformation, while the pyrrolidine (with a C atom as the flap atom) and the five-membered ring in the indoline (with a C atom as the flap atom) ring system adopt slight envelope conformations. The pyrrolidine ring makes dihedral angles of 83.3 (1) and 60.4 (1)° with the mean plane through all non-H atoms of the indoline and chromene ring systems, respectively. In the crystal, mol­ecules are connected by two unique N—H⋯O and O—H⋯O hydrogen-bonding inter­actions, which form centrosymmetric patterns described by graph-set motifs R 2 2(18) and R 2 2(14). These two motifs combine to form a hydrogen-bonded chain which propagates in the a-axis direction. The crystal structure is also stablized by C—H⋯O inter­actions and by aromatic π–π stacking inter­actions between the pyran and benzene rings of neighbouring mol­ecules [centroid–centroid distance = 3.755 (1) Å and slippage = 1.371 (2) Å]

IoT Based Real Time Energy Management of Virtual Power Plant using PLC for Transactive Energy Framework

The high penetration of renewable sources owing to less environmental pollution creates challenges for the grid operators. Virtual Power Plant is a novel concept that will integrate the small distributed energy resources and will act as a single conventional power plant in the electricity market. As a core energy management system in VPP, the energy should be dispatched optimally for achieving the maximum profit. Therefore, smart energy management is developed in this article of VPP with PLC and IoT in a unified market environment that integrates the DA and RT market. The cost characteristics for the interruptible load, battery storage system are modelled individually. The proposed scheme can efficiently handle the energy demand for the VPP domain. Four different scenarios are considered with different loading conditions for validation of the concept of smart energy management. The profitability for each scenario is shown with the experimental results

The Effect of Lateralization of Motor Onset and Emotional Recognition in PD Patients Using EEG

The objective of this research was to investigate the relationship between emotion recognition and lateralization of motor onset in Parkinson’s disease (PD) patients using electroencephalogram (EEG) signals. The subject pool consisted of twenty PD patients [ten with predominantly leftsided (LPD) and ten with predominantly rightsided (RPD) motor symptoms] and 20 healthy controls (HC) that were matched for age and gender. Multimodal stimuli were used to evoke simple emotions, such as happiness, sadness, fear, anger, surprise, and disgust. Artifactfree emotion EEG signals were processed using the auto regressive spectral method and then subjected to repeated ANOVA measures. No group differences were observed across behavioral measures? however, a significant reduction in EEG spectral power was observed at alpha, beta and gamma frequency oscillations in LPD, compared to RPD and HC participants, suggesting that LPD patients (inferred righthemisphere pathology) are impaired compared to RPD patients in emotional processing. We also found that PD related emotional processing deficits may be selective to the perception of negative emotions. Previous findings have suggested a hemispheric effect on emotion processing that could be related to emotional response impairment in a subgroup of PD patients. This study may help in clinical practice to uncover potential neurophysiologic abnormalities of emotional changes with respect to PD patient’s motor onset

Inter-hemispheric EEG coherence analysis in Parkinson's disease : Assessing brain activity during emotion processing

Parkinson’s disease (PD) is not only characterized by its prominent motor symptoms but also associated with disturbances in cognitive and emotional functioning. The objective of the present study was to investigate the influence of emotion processing on inter-hemispheric electroencephalography (EEG) coherence in PD. Multimodal emotional stimuli (happiness, sadness, fear, anger, surprise, and disgust) were presented to 20 PD patients and 30 age-, education level-, and gender-matched healthy controls (HC) while EEG was recorded. Inter-hemispheric coherence was computed from seven homologous EEG electrode pairs (AF3–AF4, F7–F8, F3–F4, FC5–FC6, T7–T8, P7–P8, and O1–O2) for delta, theta, alpha, beta, and gamma frequency bands. In addition, subjective ratings were obtained for a representative of emotional stimuli. Interhemispherically, PD patients showed significantly lower coherence in theta, alpha, beta, and gamma frequency bands than HC during emotion processing. No significant changes were found in the delta frequency band coherence. We also found that PD patients were more impaired in recognizing negative emotions (sadness, fear, anger, and disgust) than relatively positive emotions (happiness and surprise). Behaviorally, PD patients did not show impairment in emotion recognition as measured by subjective ratings. These findings suggest that PD patients may have an impairment of inter-hemispheric functional connectivity (i.e., a decline in cortical connectivity) during emotion processing. This study may increase the awareness of EEG emotional response studies in clinical practice to uncover potential neurophysiologic abnormalities

Pre-B Cell Receptor Signaling Induces Immunoglobulin κ Locus Accessibility by Functional Redistribution of Enhancer-Mediated Chromatin Interactions

During B cell development, the precursor B cell receptor (pre-BCR) checkpoint is thought to increase immunoglobulin κ light chain (Igκ) locus accessibility to the V(D)J recombinase. Accordingly, pre-B cells lacking the pre-BCR signaling molecules Btk or Slp65 showed reduced germline Vκ transcription. To investigate whether pre-BCR signaling modulates Vκ accessibility through enhancer-mediated Igκ locus topology, we performed chromosome conformation capture and sequencing analyses. These revealed that already in pro-B cells the κ enhancers robustly interact with the ∼3.2 Mb Vκ region and its flanking sequences. Analyses in wild-type, Btk, and Slp65 single- and double-deficient pre-B cells demonstrated that pre-BCR signaling reduces interactions of both enhancers with Igκ locus flanking sequences and increases interactions of the 3′κ enhancer with Vκ genes. Remarkably, pre-BCR signaling does not significantly affect interactions between the intronic enhancer and Vκ genes, which are already robust in pro-B cells. Both enhancers interact most frequently with highly used Vκ genes, which are often marked by transcription factor E2a. We conclude that the κ enhancers interact with the Vκ region already in pro-B cells and that pre-BCR signaling induces accessibility through a functional redistribution of long-range chromatin interactions within the Vκ region, whereby the two enhancers play distinct roles