An Empirical Comparison of Different Machine

Sketching has been used by humans to visualize and narrate the aesthetics of the world for a long time. With the onset of touch devices and augmented technologies, it has attracted more and more attention in recent years. Recognition of free-hand sketches is an extremely cumbersome and challenging task due to its abstract qualities and lack of visual cues. Most of the previous work has been done to identify objects in real pictorial images using neural networks instead of a more abstract depiction of the same objects in sketch. This research aims at comparing the performance of different machine learning algorithms and their learned inner representations. This research studies some of the famous machine learning models in classifying sketch images. It also does a study of legacy and the new datasets to classify a new sketch through various classifiers like support vector machines and the use of deep neural networks. It achieved remarkable results but still lacking behind the accuracy in the classification of the sketch images

Automatic Scam-Baiting Using ChatGPT

Automatic scam-baiting is an online fraud countermeasure that involves automated systems responding to online fraudsters in order to waste their time and deplete their resources, diverting attackers away from real potential victims. Previous work has demonstrated that text generation systems are capable of engaging with attackers as automatic scam-baiters, but the fluency and coherence of generated text may be a limit to the effectiveness of such systems. In this paper, we report on the results of a month-long experiment comparing the effectiveness of two ChatGPT-based automatic scam-baiters to a control measure. Within our results, with engagement from over 250 real email fraudsters, we find that ChatGPT-based scam-baiters show a marked increase in scammer response rate and conversation length relative to the control measure, outperforming previous approaches. We discuss the implications of these results and practical considerations for wider deployment of automatic scam-baiting.Comment: Proceedings of the 7th International Workshop on Applications of AI, Cyber Security and Economics Data Analytics (ACE-2023) (in press

Engineering the micro-environment to control the fate of mammalian cells

Bio-physical and bio-chemical factors in the local micro-environment like substrate stiffness, geometry, ligand density, and topography can have strong influences on determining the fate of cells. Mammalian cells respond to this myriad of micro-environmental cues by an interplay between actomyosin based cellular contractions and integrin mediated focal adhesions. A force balance is established between the intracellular micro-environment and the extracellular matrix. This mechanotransduction process is ultimately responsible for changes in the cytoskeletal characteristics, morphology, migration, division and gene expression of mammalian cells. The goal of this dissertation was to develop a platform to control the fate of mammalian cells by engineering the cellular micro-environment. Beating rate, force of contraction and cytoskeletal structure of embryonic chicken cardiac myocytes was examined by varying the elasticity of the underlying substrate. Cells cultured on substrates with elasticity comparable to the native myocardium (18 kPa) exhibited the highest beating rate during the first few days of culture. Higher percentage of mature focal adhesions were seen on cells on stiffer substrates (50 kPa or greater), while only small punctate focal adhesions could be noticed on soft substrates (1 kPa). As a result, cells on the soft substrate only showed non-aligned sarcomeric striations. However, cells on the substrate which mimicked the stiffness of the native myocardium showed highly aligned sarcomeric striations, hallmark of a striated muscle cell. In addition, quantitative analysis was performed to provide a bio-physical basis for understanding the affect of substrate elasticity on cell-cell interactions in cardiac tissue. Next, geometrical cues of the substrate were used to modulate the process of myogenesis on the murine derived muscle cell line (C2C12). By using micro-contact printing, three different protein geometries, linear, circular, and hybrid (linear and circular) were patterned on the surface of petri dishes. Hybrid 30o geometry showed the highest fusion and maturation indices for C2C12 cells. Myotubes on the hybrid 30o were highly aligned and showed the best response to an electrical pulse stimulation. It was verified that these differences in the myogenic parameters could not be attributed to the differences in density of cells on the different geometrical structures. The different morphologies of protein micro-patterns changed the cellular tractional stresses and cytoskeletal organization leading to the differences in myogenesis on the different patterns. A new class of sp2-hybridized carbon based allotrope, graphene, was then investigated as a potential biomaterial for muscle tissue engineering. C2C12 skeletal muscle myoblasts showed a very high degree of myogenic potential on graphene. Also, being an organic material, graphene could also provide a similar micro-environment as the native extracellular matrix in terms of its chemical composition and physical structure. Thus graphene could potentially be used for the development of artificial synthetic muscle scaffolds. Finally, different cues of geometry and stiffness were combined in a three dimensional poly ethylene glycol diacrylate hydrogel to truly mimic the native tissue. Stereolithography apparatus enabled modulating the stiffness of the substrate by controlling the degree of polymerization of the different polymers. Dielectrophoresis helped in controlling the spatial location of cells in these polymers. Thus by integrating stereolithography with dielectrophoresis, mouse embryonic stem cells were patterned and encapsulated in three dimensional hydrogels of physiologically relevant stiffnesses. The cells showed very high viability for both the aligned and the non-aligned samples. Since, embryoid body formation is the precursor to the differentiation of mouse embryonic stem cells, both the viability and alignment of embryoid bodies was verified in the hydrogels as well. Also, some preliminary results are presented that show the differentiation of mESCs. It is extremely important to independently control multiple cues simultaneously in a three-dimensional architecture to control the fate of cells. Cells in our body do not respond to one environmental cue at a time. Rather they simultaneously experience multiple cues like stiffness, geometry, topography, etc. and respond to them accordingly. This work first looked at different environmental cues in two-dimensions and then combined them in three-dimensional cultures to fully mimic the native in vivo tissue. This novel platform could thus open new doors in stem cell biology and enable applications in tissue engineering, regenerative medicine, and drug discovery/screening

Control of spatial cell attachment on carbon nanofiber patterns on polycarbonate urethane-1

<p><b>Copyright information:</b></p><p>Taken from "Control of spatial cell attachment on carbon nanofiber patterns on polycarbonate urethane"</p><p></p><p>International Journal of Nanomedicine 2006;1(3):361-365.</p><p>Published online Jan 2006</p><p>PMCID:PMC2426804.</p><p>© 2006 Dove Medical Press Limited. All rights reserved</p