Intermolecular Coulombic decay by concerted transfer of energy from photoreceptors to a reaction center

Molecular mechanisms that enable concerted transfer of energy from several photoacceptors to a distinct reaction center are most desirable for the utilization of light-energy. Here we show that intermolecular Coulombic decay, a channel which enables non-local disposal of energy in photoexcited molecules, offers an avenue for such a novel energy-transfer mechanism. On irradiation of pyridine-argon gas mixture at 266 nm and at low laser intensities, we observed a surprisingly dominant formation of argon cations. Our measurements on the laser-power dependence of the yield of the Ar cations reveal that intermolecular Coulombic interactions concertedly localize the excitation energy of several photoexcited pyridines at the argon reaction center and ionize it. The density of the reaction center offers an efficient handle to optimize this concerted energy-transfer. This mechanism paves the way for a new $\pi$-molecular light-harvesting system, and can also contribute to biomolecular stability against photodamage

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Some Studies on Acoustic Features of Human Speech in Relation to Hindi Speech Sounds

The present Paper aims to present a brief discourse on acoustic features related to human speech from the view point of analysis. After giving a brief review of modern methods currently in use in speech communication research, acoustic characteristics and features of human speech sound on the basis of spectrographic analysis of a limited number of Hindi Speech Sound are presented. The acoustic phonetic and the aeoustic prosodic parameters of human speech are briefly explained and the formant frequencies, and duration of Hindi vowels, concentration of acoustic energy for plosives and some affricates along with other related Parameters of conmsonants are presented in tabular form and discussed

Band-to-band tunneling based ultra-energy efficient silicon neuron

The human brain comprises about a hundred billion neurons connected through quadrillion synapses. Spiking Neural Networks (SNNs) take inspiration from the brain to model complex cognitive and learning tasks. Neuromorphic engineering implements SNNs in hardware, aspiring to mimic the brain at scale (i.e., 100 billion neurons) with biological area and energy efficiency. The design of ultra-energy efficient and compact neurons is essential for the large-scale implementation of SNNs in hardware. In this work, we have experimentally demonstrated a Partially Depleted (PD) Silicon-On-Insulator (SOI) MOSFET based Leaky-Integrate & Fire (LIF) neuron where energy-and area-efficiency is enabled by two elements of design - first tunneling based operation and second compact sub-threshold SOI control circuit design. Band-to-Band Tunneling (BTBT) induced hole storage in the body is used for the "Integrate" function of the neuron. A compact control circuit "Fires" a spike when the body potential exceeds the firing threshold. The neuron then "Resets" by removing the stored holes from the body contact of the device. Additionally, the control circuit provides "Leakiness" in the neuron which is an essential property of biological neurons. The proposed neuron provides 10x higher area efficiency compared to CMOS design with equivalent energy/spike. Alternatively, it has 10^4x higher energy efficiency at area-equivalent neuron technologies. Biologically comparable energy- and area-efficiency along with CMOS compatibility make the proposed device attractive for large-scale hardware implementation of SNNs.by Tanmay Chavan,Sangya Dutta,Nihar R. Mohapatra and Udayan Gangul

Electrical tunability of Partially Depleted Silicon on Insulator (PD-SOI) Neuron

The hardware realization of spiking neural network (SNN) requires a compact and energy efficient electronic analog to the biological neuron. A knob to tune the response of the as-fabricated neuron allows the network to perform various functioning without altering the hardware. Earlier, our group has experimentally demonstrated an LIF (leaky integrate & fire) neuron on a highly matured 32?nm SOI CMOS technology. In this work, we have experimentally demonstrated electrical tunability of the same through its intrinsic charge dynamics based on impact ionization (II) enabled floating body effect. First, a tunable input threshold (Vth) is achieved by changing the drain bias. Second, above threshold, a firing frequency (f) to input (V) sensitivity (df/dV) tuning is successfully demonstrated by controlling the SOI-MOSFET�s current threshold. We show that both the independent control of sensitivity and threshold is fundamentally enabled by the non-linearity of the impact ionization based carrier dynamics. The SOI neuron provides equivalent electrical tunability to Resistor-Capacitor (RC) based LIF neurons without degrading its original area and power advantages for clock-less, asynchronous SNNs. Further, we show that the neuronal behavior (threshold and sensitivity) is a key determinant of network performance, specifically the learning accuracy. Such flexibility based on post-fabrication electrical tuning will be an attractive enabler for the SNN hardware.by Sangya Dutta, Tanmay Chavan, Nihar R. Mohapatra and Udayan Gangul

An ultra energy efficient Neuron enabled by tunneling in sub-threshold regime on a highly manufacturable 32 nm SOI CMOS technology

by T. Chavan, S. Dutta, Nihar R. Mohapatra and U. Gangul

Transient variability in SOI-based LIF Neuron and impact on unsupervised learning

Variability is an integral part of biology. A biological neural network performs efficiently despite variability and sometimes its performance is facilitated by the variability. Hence, the study of variability on its electronic analog is essential for constructing biomimetic neural networks. We have recently demonstrated a compact leaky integrate and fire (LIF) neuron on PD-silicon on insulator (SOI) MOSFET. In this paper, we have studied impact ionization (II)-induced variability both device-to-device (D2D) and cycle-to-cycle (C2C) in the SOI neuron. The C2C variability is attributed to the fluctuation in the II-generated charge storage and it is enhanced by at least 2.5x as compared to the no-II case. The D2D variability, on the other hand, is related to the II-induced sharp subthreshold slope (~ 40 mV/decade), which enhanced the variability by ~20x compared to the no-II case. The impact of the enhanced variability in SOI neurons on an unsupervised classification task was evaluated by simulating a spiking neural network (SNN) with both analog and binary synapses. For analog synapse-based SNN, the C2C variability improved the performance by ~ 5% relative to ideal LIF neurons. However, the D2D variability, as well as combined D2D and C2C variability, degrades learning by -~ 10%. For binary synapses, we observe that performance drastically degrades for ideal LIF neurons as the synaptic weight initialization becomes nonrandom. However, neurons with the experimentally demonstrated variability (C2C and D2D) mitigate this challenge. Therefore, this enables binary synapses to perform at par with analog synapses, which allows for deterministic weight initialization. This makes RNG circuits for random weight initialization redundant.by Sangya Dutta, Tinish Bhattacharya, Nihar R. Mohapatra, Manan Suri and Udayan Gangul

Leaky integrate and fire neuron by charge-discharge dynamics in floating-body MOSFET

Neuro-biology inspired Spiking Neural Network (SNN) enables efficient learning and recognition tasks. To achieve a large scale network akin to biology, a power and area efficient electronic neuron is essential. Earlier, we had demonstrated an LIF neuron by a novel 4-terminal impact ionization based n+/p/n+ with an extended gate (gated-INPN) device by physics simulation. Excellent improvement in area and power compared to conventional analog circuit implementations was observed. In this paper, we propose and experimentally demonstrate a compact conventional 3-terminal partially depleted (PD) SOI- MOSFET (100 nm gate length) to replace the 4-terminal gated-INPN device. Impact ionization (II) induced floating body effect in SOI-MOSFET is used to capture LIF neuron behavior to demonstrate spiking frequency dependence on input. MHz operation enables attractive hardware acceleration compared to biology. Overall, conventional PD-SOI-CMOS technology enables very-large-scale-integration (VLSI) which is essential for biology scale (~1011 neuron based) large neural networks.by Sangya Dutta, Vinay Kumar, Aditya Shukla, Nihar R. Mohapatra and Udayan Gangul

Ms DIFFERENT ULTRAVIOLET SPECTROSCOPIC METHODS: A RETROSPECTIVE STUDY ON ITS APPLICATION FROM THE VIEWPOINT OF ANALYTICAL CHEMISTRY

 In routine practice, some simple and rapid analytical methods are needed for the assessment of formulations containing multiple elements, complex matrix system and for biotherapeutic products. There are several methods available for ultraviolet (UV) spectrophotometry that rely on the concept of absorbance difference, absorbance spectra, and additivity, also included in the list are simultaneous equation method, Q-absorbance ratio method, derivative spectrophotometry, ratio derivative spectra, successive ratio-derivative spectra, absorption and absorptivity factor method, and difference spectrophotometry along with multivariate chemometric methods. In this review, emphasis has been given to the theories, mathematical context, advantages, and disadvantages along with the vast applications of UV spectrophotometry. The findings further highlighted that for the analysis of drugs, UV spectrophotometry remains as one of the most simple, cheap, and promising option for routine practice in the field of pharmaceuticals

Dynamics, design, and application of a silicon-on-insulator technology based neuron

Spiking Neural Networks propose to mimic nature’s way of recognizing patterns and making decisions in a fuzzy manner. To develop such networks in hardware, a highly manufacturable technology is required. We have proposed a silicon-based leaky integrate and fire (LIF) neuron, on a sufficiently matured 32 nm CMOS silicon-on-insulator (SOI) technology. The floating body effect of the partially depleted (PD) SOI transistor is used to store “holes” generated by impact ionization in the floating body, which performs the “integrate” function. Recombination or equivalent hole loss mimics the “leak” functions. The “hole” storage reduces the source barrier to increase the transistor current. Upon reaching a threshold current level, an external circuit records a “firing” event and resets the SOI MOSFET by draining all the stored holes. In terms of application, the neuron is able to show classification problems with reasonable accuracy. We looked at the effect of scaling experimentally. Channel length scaling reduces voltage for impact ionization and enables sharper impact ionization producing significant designability of the neuron. A circuit equivalence is also demonstrated to understand the dynamics qualitatively. Three distinct regimes are observed during integration based on different hole leakage mechanism.by S. Dutta, T. Chavan, S. Shukla, V. Kumar, A. Shukla, Nihar R. Mohapatra and U. Gangul