Ramesh Kumar

We introduce a theoretical model for the photocurrent-voltage (I-V) characteristics designed to elucidate the interfacial phenomena in photoelectrochemical cells (PECs). This model investigates the sources of voltage losses and the distribution of photocurrent across the semiconductor–electrolyte interface (SEI). It calculates the whole exchange current parameter to derive cell polarization data at the SEI and visualizes the potential drop across n-type cells. The I-V model's simulation outcomes are utilized to distinguish between the impacts of bulk recombination and space charge region (SCR) recombination within semiconductor cells. Furthermore, we develop an advanced deep neural network model to analyze the electron–hole transfer dynamics using the I-V characteristic curve. The model's robustness is evaluated and validated with real-time experimental data, demonstrating a high degree of concordance with observed results.

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Brand Repositioning is a broad- based concept. Even an introduction of a brand variant in the same category, (for instance Ethnix from Raymond's) or a variant in a related category (Dove hair oil and face wash in cosmetics), is likely to have an impact on the original associations developed for the respective brand. The consumer's sub-conscious mind also plays an important role in their perception of brand associations.

Expectations from a brand and the consequent brand evaluations are predominantly the result of brand positioning and subsequent brand proposition claims.

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Brands using MarTech must balance AI-driven tools with human emotion to avoid losing their essence. Examples include AI-generated ads, automated calls, and misdirected personalization.

Rice is a water-intensive crop, conventionally grown under submerged conditions, with standing water for about 80% of its growth period. There is an urgent need for water-saving technologies to address challenges associated with conventional irrigation techniques for rice. The alternate wetting and drying (AWD) technique is one of these water-saving techniques; however, it requires continuous monitoring of water levels in the field. The implementation of real-time, electronic sensor-based precision irrigation technology may address the problems associated with conventional irrigation systems and AWD leading to high water use efficiency. Therefore, a study was undertaken to develop a suitable sensor-based automated irrigation system to maintain optimal water levels in rice fields. This study conceptualized an electronic sensor-based automated irrigation system for rice cultivated under the AWD technique. In this method, the rice field is initially flooded to a maximum depth of 5 cm. Irrigation is reapplied once the water level reduces to 10 cm below the soil surface. This developed system helps address water scarcity by regulating water levels, preventing excess ponding. It uses magnetic float-based sensors and electronic circuits to detect water levels, converting them into electronic signals transmitted wirelessly via radio frequency (RF) to a controller. The controller has been programmed for different growth stages that need to be set manually during the cropping period. The system is designed primarily for the AWD method but includes an option for continuous ponding (CP), needed during the flowering stage. The maximum water level at full maturity is set at 5 cm above the soil surface, while irrigation with the AWD method begins when the water level falls 10 cm below the soil surface. The developed system was tested during the Kharif season of 2018–19; the irrigation water productivity was 6.15 kg ha−1mm−1 with the automated system, compared to 3.06 kg ha−1mm−1 in the control (continuous ponding). Total water productivity was 4.80 kg ha−1mm−1 for the automated system and 2.63 kg ha−1mm−1 for the control. The automated system achieved 36% more water savings over the control, which used continuous ponding as farmers practice. The developed system supports AWD, a proven water-saving technique in rice cultivation.

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Department of Physics, College of Science, United Arab Emirates University, Al-Ain P.O. Box. 15551, United Arab Emirates

Articles Pharmacognosy Research, October 2024 Original Article