Smart Materials for Wearable Healthcare Devices

Wearable devices seem to have great potential that could result in a revolutionary non-clinical approach to health monitoring and diagnosing disease. With continued innovation and intensive attention to the materials and fabrication technologies, development of these healthcare devices is progressively encouraged. This chapter gives a concise review of some of the main concepts and approaches related to recent advances and developments in the scope of wearable devices from the perspective of emerging materials. A complementary section of the review linking these advanced materials with wearable device technologies is particularly specified. Some of the strong and weak points in development of each wearable material/device are clearly highlighted and criticized

CancerUniT: Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans

Human readers or radiologists routinely perform full-body multi-organ multi-disease detection and diagnosis in clinical practice, while most medical AI systems are built to focus on single organs with a narrow list of a few diseases. This might severely limit AI's clinical adoption. A certain number of AI models need to be assembled non-trivially to match the diagnostic process of a human reading a CT scan. In this paper, we construct a Unified Tumor Transformer (CancerUniT) model to jointly detect tumor existence & location and diagnose tumor characteristics for eight major cancers in CT scans. CancerUniT is a query-based Mask Transformer model with the output of multi-tumor prediction. We decouple the object queries into organ queries, tumor detection queries and tumor diagnosis queries, and further establish hierarchical relationships among the three groups. This clinically-inspired architecture effectively assists inter- and intra-organ representation learning of tumors and facilitates the resolution of these complex, anatomically related multi-organ cancer image reading tasks. CancerUniT is trained end-to-end using a curated large-scale CT images of 10,042 patients including eight major types of cancers and occurring non-cancer tumors (all are pathology-confirmed with 3D tumor masks annotated by radiologists). On the test set of 631 patients, CancerUniT has demonstrated strong performance under a set of clinically relevant evaluation metrics, substantially outperforming both multi-disease methods and an assembly of eight single-organ expert models in tumor detection, segmentation, and diagnosis. This moves one step closer towards a universal high performance cancer screening tool.Comment: ICCV 2023 Camera Ready Versio

Polydopamine nanoparticles for treatment of acute inflammation-induced injury

Nanotechnology-mediated anti-inflammatory therapy is emerging as a novel strategy for treatment of inflammation-induced injury. However, one of the main hurdles for these anti-inflammatory nano-drugs is their potential toxic side effects in vivo. Herein, we uncovered that polydopamine (PDA) nanoparticles with structure and chemical properties similar to melanin, a natural bio-polymer, displayed significant anti-inflammation therapeutic effect on acute inflammation-induced injury. PDA with enriched phenol groups functioned as a radical scavenger to eliminate reactive oxygen species (ROS) generated during inflammatory responses. As revealed by in vivo photoacoustic imaging with a H2O2-specific nanoprobe, PDA nanoparticles remarkably reduced intracellular ROS levels in murine macrophages challenged with either H2O2 or lipopolysaccharide (LPS). The anti-inflammatory capacity of PDA nanoparticles was further demonstrated in murine models of both acute peritonitis and acute lung injury (ALI), where diminished ROS generation, reduced proinflammatory cytokines, attenuated neutrophil infiltration, and alleviated lung tissue damage were observed in PDA-treated mice after a single dose of PDA treatment. Our work therefore presents the great promise of PDA nanoparticles as a biocompatible nano-drug for anti-inflammation therapy to treat acute inflammation-induced injury

Neutrino Physics with JUNO

The Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton multi-purposeunderground liquid scintillator detector, was proposed with the determinationof the neutrino mass hierarchy as a primary physics goal. It is also capable ofobserving neutrinos from terrestrial and extra-terrestrial sources, includingsupernova burst neutrinos, diffuse supernova neutrino background, geoneutrinos,atmospheric neutrinos, solar neutrinos, as well as exotic searches such asnucleon decays, dark matter, sterile neutrinos, etc. We present the physicsmotivations and the anticipated performance of the JUNO detector for variousproposed measurements. By detecting reactor antineutrinos from two power plantsat 53-km distance, JUNO will determine the neutrino mass hierarchy at a 3-4sigma significance with six years of running. The measurement of antineutrinospectrum will also lead to the precise determination of three out of the sixoscillation parameters to an accuracy of better than 1\%. Neutrino burst from atypical core-collapse supernova at 10 kpc would lead to ~5000inverse-beta-decay events and ~2000 all-flavor neutrino-proton elasticscattering events in JUNO. Detection of DSNB would provide valuable informationon the cosmic star-formation rate and the average core-collapsed neutrinoenergy spectrum. Geo-neutrinos can be detected in JUNO with a rate of ~400events per year, significantly improving the statistics of existing geoneutrinosamples. The JUNO detector is sensitive to several exotic searches, e.g. protondecay via the $p\to K^++\bar\nu$ decay channel. The JUNO detector will providea unique facility to address many outstanding crucial questions in particle andastrophysics. It holds the great potential for further advancing our quest tounderstanding the fundamental properties of neutrinos, one of the buildingblocks of our Universe

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Sensing mechanism of the zirconia-based highly selective NO sensor by using a plate-like Cr2O3 sensing electrode

Plate-like Cr2O3 has been proved to be highly selective in sensing of nitric oxide (NO), while the sensing response of irregular shape and cubic-like Cr2O3 toward NO was significantly interfered by hydrocarbons (HCs), e.g. C3H6. In this paper, sensing mechanism of the plate-like Cr2O3 for selective sensing of NO (against HCs) was studied via crystallographic phase analysis, lattice fringes investigation and evaluation of the catalytic activity (gas-phase catalytic activity & electrochemical catalytic activity). The Cr2O3 samples with plate-like, irregular shape and cubic-like microstructures have been confirmed to be the same crystallographic phase through XRD measurements, however, significant difference in the lattice fringes of these Cr2O3 samples were observed via high-resolution transmission electron microscopy (HRTEM) & selected-area electron diffraction (SAED). The comparison results of catalytic activity for plate-like, irregular shape and cubic-like Cr2O3 indicated that the unique selectivity for the plate-like Cr2O3 was mainly caused by the electrochemical reaction specifically toward NO, which occurred near the interface between plate-like Cr2O3 and zirconia-based electrolyte. (C) 2015 Elsevier B.V. All rights reserved

Plate-like Cr2O3 for highly selective sensing of nitric oxide

Selective sensing of nitric oxide (NO) in exhaust for so far reported exhaust gas sensors, particularly, without any interference from the coexist hydrocarbons (e.g., C3H6) is still a challengeable issue. In this research, Cr2O3 with various microstructures were successfully synthesized via hydrothermal route and used as sensing-electrodes (SEs) for detection of NO at high temperatures. Surprisingly, Cr2O3 with plate-like microstructure demonstrated high selectivity towards NO against C3H6. In addition, the sensing performance of the plate-like Cr2O3 towards NO was found to be unaffected by the change of oxygen concentration at 475 degrees C. (C) 2014 Elsevier B.V. All rights reserved

Optimal Manufacturer Recycling Strategy under EPR Regulations

Under extended producer responsibility (EPR) regulations, trade-in programs allow manufacturers to play a vital role in recycling. Simultaneously, third-party recyclers (TPRs) can use their recycling network to compensate for manufacturers having only a single recycling channel, which increases the competition between them. To study whether companies should authorize TPRs, we constructed and analyzed a Stackelberg game model with trade-in programs under EPR regulations by focusing on three different closed-loop supply chain (CLSC) structures and differentiating consumer categories. The analytical results showed that when the government does not act as the decision maker, the optimal product selling price of the manufacturer does not change under each strategy. Otherwise, the manufacturer’s decision is affected by the cost structure and amount of subsidy, as well as funds determined by the government under the optimal environmental benefit. Furthermore, when the residual value coefficient of the used products is high, manufacturers authorize TPRs to recycle used products