IPS Academy

Efficient sampling of low-energy conformational states remains a central challenge in protein folding simulations. In this study, we investigated the performance and limitations of standard Monte Carlo (MC) and parallel tempering Monte Carlo (PTMC) methods in exploring protein energy landscapes using two representative systems: the small peptide Met-enkephalin and the FBP28 WW-Domain protein. For Met-enkephalin, standard MC simulations achieved equilibrium at higher temperatures but showed insufficient sampling in low-energy regions. In contrast, PTMC significantly improved sampling efficiency across a wide temperature range, particularly in the low-energy regime, enabling robust exploration of the energy landscape. PTMC successfully identified the global minimum structure of Met-enkephalin with an energy of -11.23 kcal/mol and a root-mean-square deviation of 1.18 Å from the reference structure. The applicability of PTMC to larger proteins was further examined through extensive simulations of the WW-Domain, revealing pronounced energy fluctuations and folding–unfolding transitions at higher temperatures, while sampling at lower temperatures remained limited. The number of visits per unit energy range for two consecutive temperatures have also monitored to check the exchange rate and conformational sampling of the entire landscape. The average energy and specific heat with respect to temperature have also calculated to check the folding unfolding transition of WW-Domain. These results demonstrated the superiority of PTMC over standard MC for protein folding studies; however, they also highlighted challenges associated with larger protein systems.

The objective of this study is to investigate the equilibrium thermodynamic and structural properties of small proteins in the presence of an implicit solvent using the SMMP package. The work primarily focuses on performing parallel tempering simulations for the peptides Met-enkephalin. The thermodynamic parameters, such as specific heat and average energy, structural properties like radius of gyration and end to end distance with respect to temperature were calculated as functions of temperature to analyze the stability and Conformational behavior of the proteins.

The chapter studies the growing importance of green investment within industrial settings. It also focuses on its contribution made towards sustainable development. The chapter explored the reorientation of the production process of the industries to attain environmental as well as economic priorities. The primary focus was to focus on the conceptual understanding of the green investment and the role it plays in bridging the gap between the industrial growth and ecological responsibilities. It highlights the major forces that motivate industries to adopt sustainable practices, including technological innovation, financial incentives, policy frameworks, and market expectations. It also explores the challenges that hinder green investment, including financial limitations, institutional shortcomings, and a lack of awareness among industry stakeholders. Through examining various national and international experiences, the discussion uncovers patterns of progress that illustrate how coordinated policy measures and supportive financial systems can drive industrial transformation forward.

Tuning nonlinear optical (NLO) phenomena are crucial for next‐generation light modulation technologies like optical limiting and switching as well as quantum photonics. To that end, metal–semiconductor nanohybrids have emerged as important systems. Herein, the NLO behavior of Au/MoS 2 hybrids is investigated using the Z‐scan technique in the nanosecond regime. A key observation is a pronounced reverse saturable absorption (RSA) response in strongly coupled Au/MoS 2 , markedly distinct from the behavior of weakly coupled Au/MoS 2 , as well as pristine MoS 2 nanosheets and Au nanoparticles (NPs), which give saturable absorption (SA). The RSA in strongly coupled Au/MoS 2 is attributed to strong interplay between the semiconductor electronic states and localized surface plasmon resonances of the metal NPs, enabling an excited‐state absorption (ESA) process following one‐photon excitation. A field‐assisted carrier trapping model is proposed to account for this unique noninstantaneous RSA, where charge separation across the hybrid interface enhances excited‐state population. Further, comparison with a weakly coupled hybrid structure underscores the critical role of interfacial interactions in switching between SA and RSA regimes. These findings demonstrate the importance of controlling the interfacial interactions at metal‐semiconductor hybrids in NLO applications where dynamic range, noninstantaneity, and broadband control are critical.

As the technology of deepfakes becomes more efficient at a rapid pace, it is now a necessity for industries like education to research methods for identifying tampered content. This paper presents an evaluation of current methods used in AI-based deepfake detection, employing machine learning approaches such as convolutional neural networks (CNNs) and generative adversarial networks (GANs). This chapter also contrasts the strengths and weaknesses of these techniques, comparing their effectiveness in detecting deepfake videos, images, and audio. Apart from a comparative evaluation of existing methods, the paper addresses other advancements and emerging technologies for improved deepfake detection, specifically multimodal detection techniques that utilise visual, audio, and text analysis. The work also provides a brief explanation of how to stay ahead of the ever-evolving nature of deepfake technology, emphasising the need for continuous innovation in detection methods.

This research paper explores the dynamics of a cascaded optical klystron with betatron oscillations in free-electron lasers theoretically. By integrating multiple optical klystron stages in sequence, energy extraction efficiency and electron bunching are improved. An analytical treatment has been employed to evaluate spectral properties of the free electron lasers. The results demonstrate that the proposed configuration significantly enhances free-electron laser gain and intensity compared to the conventional single-stage optical klystron setup. The Liénard–Wiechert potentials and generalized Bessel functions have been introduced in the analysis. This study reveals that the cascaded optical klystron configuration serves as a highly effective method for improving gain efficiency and enhancing stability in free-electron lasers, even in the presence of the adverse effects of betatron oscillations.