Self-Supervised Learning in Generative AI: A Game-Changer for Creativity

Self-supervised learning (SSL) has emerged as one of the most promising paradigms in artificial intelligence (AI), offering the ability to learn from vast amounts of unlabeled data and providing a new pathway to generative models that can create truly original content. In generative AI, SSL has become a game-changer, particularly for creative industries like art, music, literature, and design. This paper explores the role of self-supervised learning in generative AI, its impact on creativity, and how it is reshaping traditional creative processes. By leveraging the unlabelled data present in the world, SSL enables AI systems to learn sophisticated data representations that are foundational for generating high-quality and diverse creative outputs. In generative models, SSL allows the AI to predict or reconstruct parts of data based on its surrounding context, thereby teaching it to generate new instances that maintain underlying patterns and structures. The paper first provides an overview of self-supervised learning and its mechanism in the context of generative AI. It then delves into how SSL is applied to various generative models such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformers. Further, the paper explores its transformative impact on creative industries, allowing for the automatic generation of art, music, literature, and even design, offering more innovative, scalable, and personalized creative solutions. The potential benefits of SSL- powered generative AI are immense, offering new possibilities for artists and creators. However, the paper also discusses challenges such as the need for large unlabelled datasets, model interpretability, and ethical considerations. By the end of this paper, we aim to illustrate that self-supervised learning is poised to revolutionize the creative fields, enabling a more collaborative relationship between humans and machines

VITAMIN C AND ITS ROLE IN BODY

Ascorbic acid or Vitamin C is very important in our body because of its antioxidant property. But the main problem; that vitamin C uses is to maintain the stability as well as its drug distribution system. Vitamin C also plays a protective role in diabetes, cancer, heavy metal toxicity or poisoning, etc. Vitamin C is found in many sources present in nature, including tomatoes, broccoli, etc. Many factors in the body, as well as outside the body, affect the content of vitamin C in the body or sources like the season, climate, and pollution affect the content in fruits and vegetables besides sex, age, pregnancy, lactation, etc. affect the vitamin C content in the body. It is extensively used in the common cold, wound healing process, cancer, heavy metal poisoning or toxicity, and even in men's fertility. In this article, we focused on the general aspects: its bioavailability, sources, its toxicity and deficiency, and factors affecting vitamin C level as well as its use in humans. In the last, we conclude, the excess or lack of Vitamin C, both conditions have affected the human body in a significant range. It plays a protective role against many disorders and is required for kids, men, women, and even old-aged patients

The Radiopacity and Antimicrobial Properties of Different Radiopaque Double Antibiotic Pastes Used in Regenerative Endodontics

Introduction We evaluated the radiopacity and antibacterial properties of various concentrations of double antibiotic paste (DAP) containing barium sulfate (BaSO4) or zirconium oxide (ZrO2) radiopaque agents. Methods The radiopacity of 1, 10, and 25 mg/mL DAP containing 30% (w/v) BaSO4 or ZrO2, DAP-free radiopaque pastes, and commercially available radiopaque calcium hydroxide (Ca[OH]2) were evaluated according to ISO 6876/2001 with slight modifications (n = 6 per group). Dentin samples (n = 70) infected anaerobically for 3 weeks with bacterial biofilms obtained from a root canal of an immature tooth with pulpal necrosis were treated with similar experimental pastes or received no treatment (n = 7). After 1 week, the pastes were rinsed off, and biofilm disruption assays were conducted. To show the residual antibacterial effects, sterile dentin samples (n = 70) were pretreated for 1 week with the same pastes (n = 7). The pastes were rinsed off, and the samples were immersed in phosphate-buffered saline for 24 hours and infected anaerobically with the same bacterial biofilm mentioned earlier for 3 weeks before conducting biofilm disruption assays. Sterile dentin blocks were used in both antibacterial analyses as negative control groups (n = 7). Wilcoxon rank sum tests were used for statistical analyses. Results No tested concentrations of BaSO4 DAP or ZrO2 DAP showed significant differences from Ca(OH)2 in radiopacity. However, all tested concentrations of BaSO4 DAP, ZrO2 DAP, and Ca(OH)2 exhibited significant direct antibacterial effects. ZrO2 DAP at 1 mg/mL and Ca(OH)2 did not show significant residual antibacterial effects. Conclusions BaSO4 DAP at 1 mg/mL provided significantly superior residual antibacterial effects and comparable radiopacity with the commercially available Ca(OH)2

FABRIC AS STORAGE TO AVOID DOWNLOAD FAILURE ON MULTIPLE DEVICES AT BRANCH/DATA CENTERS

Presented herein are techniques to transmit virtual machine (VM) images from a controller to a switch fabric, based on capacity, and to distribute the VM images to a virtual network infrastructure, as needed

Targeted covalent inhibitors of MDM2 using electrophile-bearing stapled peptides.

Herein, we describe the development of a novel staple with an electrophilic warhead to enable the generation of stapled peptide covalent inhibitors of the p53-MDM2 protein-protein interaction (PPI). The peptide developed showed complete and selective covalent binding resulting in potent inhibition of p53-MDM2 PPI.Royal Society, Trinity College, A*STAR (IAF-PP H17/01/a0/010

Optimized Hydrophobic Interactions and Hydrogen Bonding at the Target-Ligand Interface Leads the Pathways of Drug-Designing

Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds.In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy.The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy

Integration of evidence across human and model organism studies: A meeting report.

The National Institute on Drug Abuse and Joint Institute for Biological Sciences at the Oak Ridge National Laboratory hosted a meeting attended by a diverse group of scientists with expertise in substance use disorders (SUDs), computational biology, and FAIR (Findability, Accessibility, Interoperability, and Reusability) data sharing. The meeting\u27s objective was to discuss and evaluate better strategies to integrate genetic, epigenetic, and \u27omics data across human and model organisms to achieve deeper mechanistic insight into SUDs. Specific topics were to (a) evaluate the current state of substance use genetics and genomics research and fundamental gaps, (b) identify opportunities and challenges of integration and sharing across species and data types, (c) identify current tools and resources for integration of genetic, epigenetic, and phenotypic data, (d) discuss steps and impediment related to data integration, and (e) outline future steps to support more effective collaboration-particularly between animal model research communities and human genetics and clinical research teams. This review summarizes key facets of this catalytic discussion with a focus on new opportunities and gaps in resources and knowledge on SUDs