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  1. Abstract Understanding the chemical and physical properties of particles is an important scientific, engineering, and medical issue that is crucial to air quality, human health, and environmental chemistry. Of special interest are aerosol particles floating in the air for both indoor virus transmission and outdoor atmospheric chemistry. The growth of bio- and organic-aerosol particles in the air is intimately correlated with chemical structures and their reactions in the gas phase at aerosol particle surfaces and in-particle phases. However, direct measurements of chemical structures at aerosol particle surfaces in the air are lacking. Here we demonstrate in situ surface-specific vibrational sum frequency scattering (VSFS) to directly identify chemical structures of molecules at aerosol particle surfaces. Furthermore, our setup allows us to simultaneously probe hyper-Raman scattering (HRS) spectra in the particle phase. We examined polarized VSFS spectra of propionic acid at aerosol particle surfaces and in particle bulk. More importantly, the surface adsorption free energy of propionic acid onto aerosol particles was found to be less negative than that at the air/water interface. These results challenge the long-standing hypothesis that molecular behaviors at the air/water interface are the same as those at aerosol particle surfaces. Our approach opens a new avenue inmore »revealing surface compositions and chemical aging in the formation of secondary organic aerosols in the atmosphere as well as chemical analysis of indoor and outdoor viral aerosol particles.« less
    Free, publicly-accessible full text available December 1, 2023
  2. Abstract Factory in a box (FiB) is an emerging technology that meets the dynamic and diverse market demand by carrying a factory module on vehicles to perform on-site production near customers’ locations. It is suitable for meeting time-sensitive demands, such as the outbreak of disasters or epidemics/pandemics. Compared to traditional manufacturing, FiB poses a new challenge of frequently reconfiguring supply chain networks since the final production location changes as the vehicle carrying the factory travels. Supply chain network reconfiguration involves decisions regarding whether suppliers or manufacturers can be retained in the supply chain or replaced. Such a supply chain reconfiguration problem is coupled with manufacturing process planning, which assigns tasks to each manufacturer that impacts material flow in the supply chain network. Considering the supply chain reconfigurability, this article develops a new mathematical model based on nonlinear integer programming to optimize supply chain reconfiguration and assembly planning jointly. An evolutionary algorithm (EA) is developed and customized to the joint optimization of process planning and supplier/manufacturer selection. The performance of EA is verified with a nonlinear solver for a relaxed version of the problem. A case study on producing a medical product demonstrates the methodology in guiding supply chain reconfiguration andmore »process planning as the final production site relocates in response to local demands. The methodology can be potentially generalized to supply chain and service process planning for a mobile hospital offering on-site medical services.« less
    Free, publicly-accessible full text available October 1, 2023
  3. Free, publicly-accessible full text available September 1, 2023
  4. Ding, Yu (Ed.)
    Additive manufacturing systems are being deployed on a cloud platform to provide networked manufacturing services. This article explores the value of interconnected printing systems that share process data on the cloud in improving quality control. We employed an example of quality learning for cloud printers by understanding how printing conditions impact printing errors. Traditionally, extensive experiments are necessary to collect data and estimate the relationship between printing conditions vs. quality. This research establishes a multi-printer co-learning methodology to obtain the relationship between the printing conditions and quality using limited data from each printer. Based on multiple interconnected extrusion-based printing systems, the methodology is demonstrated by learning the printing line variations and resultant infill defects induced by extruder kinematics. The method leverages the common covariance structures among printers for the co-learning of kinematics-quality models. This article further proposes a sampling-refined hybrid metaheuristic to reduce the search space for solutions. The results showed significant improvements in quality prediction by leveraging data from data-limited printers, an advantage over traditional transfer learning that transfers knowledge from a data-rich source to a data-limited target. The research establishes algorithms to support quality control for reconfigurable additive manufacturing systems on the cloud.
    Free, publicly-accessible full text available June 30, 2023
  5. Abstract

    Despite major advances in HIV testing, ultrasensitive detection of early infection remains challenging, especially for the viral capsid protein p24, which is an early virological biomarker of HIV-1 infection. Here, To improve p24 detection in patients missed by immunological tests that dominate the diagnostics market, we show a click chemistry amplified nanopore (CAN) assay for ultrasensitive quantitative detection. This strategy achieves a 20.8 fM (0.5 pg/ml) limit of detection for HIV-1 p24 antigen in human serum, demonstrating 20~100-fold higher analytical sensitivity than nanocluster-based immunoassays and clinically used enzyme-linked immunosorbent assay, respectively. Clinical validation of the CAN assay in a pilot cohort shows p24 quantification at ultra-low concentration range and correlation with CD4 count and viral load. We believe that this strategy can improve the utility of p24 antigen in detecting early infection and monitoring HIV progression and treatment efficacy, and also can be readily modified to detect other infectious diseases.

  6. Free, publicly-accessible full text available August 1, 2023
  7. Abstract

    The plant-specific family of WUSCHEL (WUS)-related homeobox (WOX) transcription factors is key regulators of embryogenesis, meristem maintenance, and lateral organ development in flowering plants. The modern/WUS clade transcriptional repressor STENOFOLIA/LAMINA1(LAM1), and the intermediate/WOX9 clade transcriptional activator MtWOX9/NsWOX9 antagonistically regulate leaf blade expansion, but the molecular mechanism is unknown. Using transcriptome profiling and biochemical methods, we determined that NsCKX3 is the common target of LAM1 and NsWOX9 in Nicotiana sylvestris. LAM1 and NsWOX9 directly recognize and bind to the same cis-elements in the NsCKX3 promoter to repress and activate its expression, respectively, thus controlling the levels of active cytokinins in vivo. Disruption of NsCKX3 in the lam1 background yielded a phenotype similar to the knockdown of NsWOX9 in lam1, while overexpressing NsCKX3 resulted in narrower and shorter lam1 leaf blades reminiscent of NsWOX9 overexpression in the lam1 mutant. Moreover, we established that LAM1 physically interacts with NsWOX9, and this interaction is required to regulate NsCKX3 transcription. Taken together, our results indicate that repressor and activator WOX members oppositely regulate a common downstream target to function in leaf blade outgrowth, offering a novel insight into the role of local cytokinins in balancing cell proliferation and differentiation during lateral organ development.

  8. Abstract

    Accurate prediction of global land monsoon rainfall on a sub-seasonal (2–8 weeks) time scale has become a worldwide demand. Current forecasts of weekly-mean rainfall in most monsoon regions, however, have limited skills beyond two weeks, calling for a more profound understanding of monsoon intraseasonal variability (ISV). We show that the high-frequency (HF; 8–20 days) ISV, crucial for the Week 2 and Week 3 predictions, accounts for about 53–70% of the total (8–70 days) ISV, generally dominating the sub-seasonal predictability of various land monsoons, while the low-frequency (LF; 20–70 days)’s contribution is comparable to HF only over Australia (AU; 47%), South Asia (SA; 43%), and South America (SAM; 40%). The leading modes of HFISVs in Northern Hemisphere (NH) monsoons primarily originate from different convectively coupled equatorial waves, while from mid-latitude wave trains for Southern Hemisphere (SH) monsoons and East Asian (EA) monsoon. The Madden-Julian Oscillation (MJO) directly regulates LFISVs in Asian-Australian monsoon and affects American and African monsoons by exciting Kelvin waves and mid-latitude teleconnections. During the past four decades, the HF (LF) ISVs have considerably intensified over Asian (Asian-Australian) monsoon but weakened over American (SAM) monsoon. Sub-seasonal to seasonal (S2S) prediction models exhibit higher sub-seasonal prediction skills over AU,more »SA, and SAM monsoons that have larger LFISV contributions than other monsoons. These results suggest an urgent need to improve the simulation of convectively coupled equatorial waves and two-way interactions between regional monsoon ISVs and mid-latitude processes and between MJO and regional monsoons, especially under the global warming scenarios.

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