Commencement of the Class of 2016

It’s amazing how fast three years passes. And in the end, IMSA is so much more than just a building. Others may never truly understand what it means to be a part of this community, but we will know. Years from now, we’ll remember the thrill of Clash or the nostalgic warmth of Carnival. We’ll remember late nights spent laughing with best friends, and we’ll remember what it felt like to belong here. It’s true, IMSA gave us the building blocks for academic and professional success. But it also gave us each other. And as we stand here as a class for the last time, I thank IMSA for bringing us together. Class of 2016, never stop learning and growing. Never lose that drive or that passion, and never forget what you have gained from IMSA. As we move on to another chapter of our lives, we will continue to expand our brick-and-mortar walls. We will gain countless more chances, and we will learn countless more things. It is my hope that we, as a class, will continue to seek out new opportunities, and I hope that we continue to find better ways of cementing it all together. Yet no matter how far we go, part of us will always belong in a residence hall at 1500 Sullivan Road. And no matter how far apart we may end up, we can find comfort in knowing that we have built something beautiful together Heidi Dong, Student Council Presiden

Open data and digital morphology

Over the past two decades, the development of methods for visualizing and analysing specimens digitally, in three and even four dimensions, has transformed the study of living and fossil organisms. However, the initial promise, that the widespread application of such methods would facilitate access to the underlying digital data, has not been fully achieved. The underlying datasets for many published studies are not readily or freely available, introducing a barrier to verification and reproducibility, and the reuse of data. There is no current agreement or policy on the amount and type of data that should be made available alongside studies that use, and in some cases are wholly reliant on, digital morphology. Here, we propose a set of recommendations for minimum standards and additional best practice for 3D digital data publication, and review the issues around data storage, management and accessibility

Aridity-driven shift in biodiversity–soil multifunctionality relationships

From Springer Nature via Jisc Publications RouterHistory: received 2021-01-07, accepted 2021-08-12, registration 2021-08-25, pub-electronic 2021-09-09, online 2021-09-09, collection 2021-12Publication status: PublishedFunder: National Natural Science Foundation of China (National Science Foundation of China); doi: https://doi.org/10.13039/501100001809; Grant(s): 31770430Abstract: Relationships between biodiversity and multiple ecosystem functions (that is, ecosystem multifunctionality) are context-dependent. Both plant and soil microbial diversity have been reported to regulate ecosystem multifunctionality, but how their relative importance varies along environmental gradients remains poorly understood. Here, we relate plant and microbial diversity to soil multifunctionality across 130 dryland sites along a 4,000 km aridity gradient in northern China. Our results show a strong positive association between plant species richness and soil multifunctionality in less arid regions, whereas microbial diversity, in particular of fungi, is positively associated with multifunctionality in more arid regions. This shift in the relationships between plant or microbial diversity and soil multifunctionality occur at an aridity level of ∼0.8, the boundary between semiarid and arid climates, which is predicted to advance geographically ∼28% by the end of the current century. Our study highlights that biodiversity loss of plants and soil microorganisms may have especially strong consequences under low and high aridity conditions, respectively, which calls for climate-specific biodiversity conservation strategies to mitigate the effects of aridification

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

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