Yoga as a practice and philosophy of life has been followed for more than 4500 years with known evidence of Yogic practices in the Indus Valley Civilization. A plethora of scholars have contributed to the development of the field, but in last century the profound knowledge remained inaccessible and incomprehensible to the general public. Last few decades have seen a resurgence in the utility of Yoga and Meditation as a practice with growing scientific evidence behind it. Significant scientific literature has been published, illustrating the benefits of Yogic practices including asana, pranayama and dhyana on mental and physical well being. Electrophysiological and recent functional Magnetic Resonance Imaging (fMRI) studies have found explicit neural signatures for Yogic practices. In this article, we present a review of the philosophy of Yoga, based on the dualistic Sankhya school, as applied to consciousness summarized by Patanjali in his Yoga Sutras followed by discussion on the five vritti (modulations of mind), practice of pratyahara, dharana, dhyana, different states of samadhi, and samapatti. We introduce Yogic Theory of Mind and Consciousness (YTMC), a cohesive theory that can model both external modulations and internal states of the mind. We propose that attention, sleep and mind wandering should be understood as unique modulatory states of the mind. YTMC allows us to model the external states, internal states of meditation, samadhi and even the disorders of consciousness. Further, we list some testable neuroscientific hypotheses that could be answered using YTMC, analyse the benefits, outcomes and possible limitations.

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The output of a solar photovoltaic (PV) system can be predicted using a parameterized model. The parameters can be obtained from the datasheet of the panel or from the measured current-voltage (I-V) characteristics. Measurement-based parameter estimation is shown to provide better results, as compared with the datasheet-based method. This effect magnifies for older panels due to the deterioration of panel characteristics with time, leading to a deviation from the datasheet specifications. Leastsquares minimization is applied on the measured data using the Levenberg-Marquardt algorithm (LMA), trust region reflective Newton, and steepest descent optimization, which are compared on the basis of accuracy and speed. Low computational complexity and high parameter accuracy is ensured by introducing a novel sequential parameter estimation, in which two of the parameters are analytically evaluated, and a separate sequential evaluation of the shunt resistance parameter is performed. The predicted maximum power from the proposed method matches the experimental measurements with high accuracy.Index Terms-Gradient methods, least-squares minimization, maximum power point (MPP), parameter estimation, photovoltaic (PV) cells.

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Global maximum power point tracking (GMPPT) refers to the extraction of the maximum power from photovoltaic (PV) modules in real time under changing ambient conditions. Due to the installation of PV systems in densely built-up areas, partial shading scenarios are commonplace. Commercially established GMPPTs suffer from low tracking speeds and inefficiency. A novel GMPPT algorithm is proposed here based on the rectangular power comparison (RPC), which exploits the fundamental relationship between the shading factor, the bypass diode voltage and the global maximum power point. The entire theoretical formulation of RPC is presented systematically for the first time. This method boasts of increased conversion speeds owing to the precomputation of the module voltage versus the shading factor correlations using the regression of diode model from the experimentally obtained bypass diode characteristics. The proposed method is simple to implement with the computational complexity of order n, which represents the number of uniquely shaded PV modules in a series string. The proposed approach addresses the much-needed intersection problem between the distributed and centralized PV systems and therefore targets PV strings which are most common in residential and small to medium scale commercial PV installations world over. The proposed approach is validated with the in-house developed prototype hardware set-up and software control implementation giving a 99% tracking efficiency with a recorded tracking time of 10 ms. The experimental results show 50 times improvement in speed and 95% increase in power gain as compared to the other popular existing methods namely scanning based GMPPT and local MPPT methods respectively, with negligible computational burden and less than 0.5% added cost to the conventional PV energy conversion system. INDEX TERMS Efficiency optimization, Global maximum power point tracking, Partial shading, Photovoltaic module measurements and Solar energy conversion.