Low-cost, in vivo microscopy

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Development in laser peening of advanced ceramic

Laser peening is a well-known process applicable to surface treat metals and alloys in various industrial sectors. Research in the area of laser peening of ceramics is still scarce and a complete laser-ceramic interaction is still unreported. This paper focuses on laser peening of SiC ceramics employed for cutting tools, armor plating, dental and biomedical implants, with a view to elucidate the unreported work. A detailed investigation was conducted with 1064nm Nd:YAG ns pulse laser to first understand the surface effects, namely: the topography, hardness, KIc and the microstructure of SiC advanced ceramics. The results showed changes in surface roughness and microstructural modification after laser peening. An increase in surface hardness was found by almost 2 folds, as the diamond footprints and its flaws sizes were considerably reduced, thus, enhancing the resistance of SiC to better withstand mechanical impact. This inherently led to an enhancement in the KIc by about 42%. This is attributed to an induction of compressive residual stress and phase transformation. This work is a first-step towards the development of a 3-dimensional laser peening technique to surface treat many advanced ceramic components. This work has shown that upon tailoring the laser peening parameters may directly control ceramic topography, microstructure, hardness and the KIc. This is useful for increasing the performance of ceramics used for demanding applications particularly where it matters such as in military. Upon successful peening of bullet proof vests could result to higher ballistic strength and resistance against higher sonic velocity, which would not only prevent serious injuries, but could also help to save lives of soldiers on the battle fields

CheXFusion: Effective Fusion of Multi-View Features using Transformers for Long-Tailed Chest X-Ray Classification

Medical image classification poses unique challenges due to the long-tailed distribution of diseases, the co-occurrence of diagnostic findings, and the multiple views available for each study or patient. This paper introduces our solution to the ICCV CVAMD 2023 Shared Task on CXR-LT: Multi-Label Long-Tailed Classification on Chest X-Rays. Our approach introduces CheXFusion, a transformer-based fusion module incorporating multi-view images. The fusion module, guided by self-attention and cross-attention mechanisms, efficiently aggregates multi-view features while considering label co-occurrence. Furthermore, we explore data balancing and self-training methods to optimize the model's performance. Our solution achieves state-of-the-art results with 0.372 mAP in the MIMIC-CXR test set, securing 1st place in the competition. Our success in the task underscores the significance of considering multi-view settings, class imbalance, and label co-occurrence in medical image classification. Public code is available at https://github.com/dongkyuk/CXR-LT-public-solutio

Attribute Based Interpretable Evaluation Metrics for Generative Models

When the training dataset comprises a 1:1 proportion of dogs to cats, a generative model that produces 1:1 dogs and cats better resembles the training species distribution than another model with 3:1 dogs and cats. Can we capture this phenomenon using existing metrics? Unfortunately, we cannot, because these metrics do not provide any interpretability beyond "diversity". In this context, we propose a new evaluation protocol that measures the divergence of a set of generated images from the training set regarding the distribution of attribute strengths as follows. Single-attribute Divergence (SaD) measures the divergence regarding PDFs of a single attribute. Paired-attribute Divergence (PaD) measures the divergence regarding joint PDFs of a pair of attributes. They provide which attributes the models struggle. For measuring the attribute strengths of an image, we propose Heterogeneous CLIPScore (HCS) which measures the cosine similarity between image and text vectors with heterogeneous initial points. With SaD and PaD, we reveal the following about existing generative models. ProjectedGAN generates implausible attribute relationships such as a baby with a beard even though it has competitive scores of existing metrics. Diffusion models struggle to capture diverse colors in the datasets. The larger sampling timesteps of latent diffusion model generate the more minor objects including earrings and necklaces. Stable Diffusion v1.5 better captures the attributes than v2.1. Our metrics lay a foundation for explainable evaluations of generative models

Editorial: Current water challenges require holistic and global solutions

The world population is exploding and is estimated to reach 9.8 billion within the next 10 years (Gerland et al. 2014). Desire for more convenient lifestyles is not likely to be satisfied (United Nations 2009). Such lifestyles entail the unsustainable exploitation of water resources and the environment (Vitousek et al. 1997). Advanced technology and transportation systems have enabled the transfer of goods across the world and, eventually, also the water that is used to produce them. This means that luxurious lifestyles on one side of the planet can cause water and food scarcity on the other side (Hoekstra & Mekonnen 2012). We are also witnessing drastic global climate change: sea levels are rising, and droughts and floods have become more intense. These have exacerbated the global water and food crises (Vorosmarty et al. 2000; Hanjra & Qureshi 2010). Our generation's water challenge is no longer a local or isolated issue. It must be recognized, understood, and analyzed from a holistic and global perspective (Wagener et al. 2010). As such, the growing complexity of global water challenges requires better collection and analysis of ever increasing data with equipping

Feasibility Study on Laser Microwelding and Laser Shock Peening using Femtosecond Laser Pulses.

Ultrafast lasers of sub-picosecond pulse duration have thus far been investigated for ablation, drilling and cutting processes. Ultrafast lasers also have the potential for laser welding of small components of the order of microns, and for laser shock peening to enhance the peening depth. First, the two-temperature model is implemented in a general-purpose commercial FEM package, ABAQUS, to enable broad based application of the two-temperature model in practical engineering problems. The implementation is validated by comparison with linear solutions obtained using separation of variables. It is then used to investigate the potential for microwelding using an ultrafast laser pulse. Next, the two-temperature model is analyzed using ABAQUS to study the feasibility of laser microwelding with ultrafast lasers. A material model is constructed using material properties and the subsurface boiling model for ablation. Laser processing parameters of repetition rate, pulse duration, and focal radius are then investigated, in terms of molten pool generated in the material, and requirements for those parameters are discussed to obtain feasible parameter ranges for laser microwelding using ultrafast lasers. Then, the feasibility of laser shock peening using ultrafast laser pulses was experimentally investigated. A zinc coating was used for the thermo-protective effect, and a water confining layer was considered in the investigation. A high numerical aperture focusing lens was used to avoid optical breakdown of the water layer. Laser fluence and feed rate were selected as experimental parameters. Microhardness measurements were made on the top surface of the shock peened specimen and compared with the original material hardness. Improvement in microhardness obtained after laser shock peening with ultrafast laser pulses was slight, compared to results in the literature. Finally, conditions to achieve feasible laser microwelding and laser shock peening using femtosecond laser pulses are discussed from the numerical and experimental observations.Ph.D.Mechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/60763/1/dongkyun_1.pd

Miniature grating for spectrally-encoded endoscopy

Spectrally-encoded endoscopy (SEE) is an ultraminiature endoscopy technology that acquires high-definition images of internal organs through a sub-mm endoscopic probe. In SEE, a grating at the tip of the imaging optics diffracts the broadband light into multiple beams, where each beam with a distinctive wavelength is illuminated on a unique transverse location of the tissue. By encoding one transverse coordinate with the wavelength, SEE can image a line of the tissue at a time without using any beam scanning devices. This feature of the SEE technology allows the SEE probe to be miniaturized to sub-mm dimensions. While previous studies have shown that SEE has the potential to be utilized for various clinical imaging applications, the translation of SEE for medicine has been hampered by challenges in fabricating the miniature grating inherent to SEE probes. This paper describes a new fabrication method for SEE probes. The new method uses a soft lithographic approach to pattern a high-aspect-ratio grating at the tip of the miniature imaging optics. Using this technique, we have constructed a 500 μm-diameter SEE probe. The miniature grating at the tip of the probe had a measured diffraction efficiency of 75%. The new SEE probe was used to image a human finger and formalin fixed mouse embryos, demonstrating the capability of this device to visualize key anatomic features of tissues with high image contrast. In addition to providing high quality imaging SEE optics, the soft lithography method allows cost-effective and reliable fabrication of these miniature endoscopes, which will facilitate the clinical translation of SEE technology.Chemistry and Chemical Biolog

Big Data Analytics in the Internet-Of-Things And Cyber-Physical Systems

Lv, Z.; Song, H.; Lloret, J.; Kim, D.; De Souza, J. (2019). Big Data Analytics in the Internet-Of-Things And Cyber-Physical Systems. IEEE Access. 7:18070-18075. https://doi.org/10.1109/ACCESS.2019.2895441S1807018075