马里兰大学系统

Planets orbiting M-dwarf stars are prime targets in the search for rocky exoplanet atmospheres. The small size of M dwarfs renders their planets exceptional targets for transmission spectroscopy, facilitating atmospheric characterization. However, it remains unknown whether their host stars' highly variable extreme-UV radiation environments allow atmospheres to persist. With JWST, we have begun to determine whether or not the most favorable rocky worlds orbiting M dwarfs have detectable atmospheres. Here, we present a 2.8-5.2 micron JWST NIRSpec/G395H transmission spectrum of the warm (700 K, 40.3x Earth's insolation) super-Earth GJ 486b (1.3 R$_{\oplus}$ and 3.0 M$_{\oplus}$). The measured spectrum from our two transits of GJ 486b deviates from a flat line at 2.2 - 3.3 $\sigma$, based on three independent reductions. Through a combination of forward and retrieval models, we determine that GJ 486b either has a water-rich atmosphere (with the most stringent constraint on the retrieved water abundance of H2O > 10% to 2$\sigma$) or the transmission spectrum is contaminated by water present in cool unocculted starspots. We also find that the measured stellar spectrum is best fit by a stellar model with cool starspots and hot faculae. While both retrieval scenarios provide equal quality fits ($\chi^2_\nu$ = 1.0) to our NIRSpec/G395H observations, shorter wavelength observations can break this degeneracy and reveal if GJ 486b sustains a water-rich atmosphere.

business cycles, and borrower default frequencies. The model is parameterized to match a set of key aggregate and cross-sectional statistics for the U.S. banking industry. As in the data, the model generates countercyclical interest rates on loans, bank failure rates, borrower default frequencies, and charge-off rates as well as a procyclical loan supply and entry rates. The model can be used to study bank competition and the benefits/costs of policies to subsidize/mitigate bank entry/exit.

We describe a new dependent-rounding algorithmic framework for bipartite graphs. Given a fractional assignment G (R) of values to edges of a graph G = (* U +, E), the algorithms return an integral solution -(R) such that each right-node E E + has at most one neighboring edge 5 with - f = 1, and the variables -e also satisfy broad nonpositive-correlation properties. In particular, for any edges 41, 42 sharing a left-node D E * , the variables -e1, -e2 have strong negative correlation, i.e. the expectation of -e1-e2 is significantly below Ge1Ge2. This algorithm is based on generating negatively correlated Exponential random variables and using them for a rounding method inspired by a contention-resolution scheme of Im and Shadloo [2020]. Our algorithm gives stronger and much more flexible negative correlation properties. Dependent rounding schemes with negative correlation properties have been used for approximation algorithms for job-scheduling on unrelated machines to minimize weighted completion times [Bansal et al., 2021; Im and Li, 2023; Im and Shadloo, 2020]. Using our new dependent-rounding algorithm, among other improvements, we obtain a 1.398-approximation for this problem. This significantly improves over the prior 1.45-approximation ratio of Im and Li [2023].

We present an overview of the field of malware analysis with emphasis on issues related to document engineering. We will introduce the field with a discussion of the types of malware, including executable binaries, malicious PDFs, polymorphic malware, ransomware, and exploit kits. We will conclude with our view of important research questions in the field. This is an updated version of last year's tutorial, with more information about web-based malware and malware targeting the Android market.

A paradigm shift process has begun in stormwater governance and management in the United States, away from centralized infrastructure and toward more decentralized practices. This transition is prompted by heightened climate change, increased urbanization, and an intense call for change in regulatory measures. Within this shift, two key and related developments have arisen: (1) the implementation of small-scale, green infrastructure, and (2) the increasing involvement of individuals and communities in managing stormwater. Despite a perceived need for this paradigm shift by most experts, there continues to be slow progress toward achieving decentralization due to changes involving redefining who is responsible for managing stormwater and how and where stormwater management is being managed. Through semi-structured interviews and Q-methodology within two urban watersheds in Maryland and Washington DC, we assess perspectives on the evolving stormwater paradigm among residents and stormwater professionals, such as nonprofit organizations, funders, policy makers and researchers. We evaluated differences in stakeholder perspectives related to who is responsible for management, the best ways to do it, and the future of stormwater management. We identified three hydrosocial relationships that stakeholders have with stormwater: Market Decentralists, Anti-Market Decentralists, and Technocratic Opportunists. Across these hydrosocial relationships, we demonstrate that there is agreement for decentralizing stormwater management through infrastructural changes and involvement of residents and communities. Nevertheless, substantial differences remain as to how stormwater is viewed, the role and responsibilities of residents, and the most effective policies to engage with residents and communities. We highlight how these differences represent significant hurdles toward implementing decentralized infrastructure and involving residents and communities in managing stormwater. Using these insights, we discuss the potential for alignment and cooperation among these diverging hydrosocial relationships and continuing the shift toward decentralized stormwater management.