A Simple Complete Search for Logic Programming

Here, we present a family of complete interleaving depth-first search strategies for embedded, domain-specific logic languages. We derive our search family from a stream-based implementation of incomplete depth-first search. The DSL\u27s programs\u27 texts induce particular strategies guaranteed to be complete

Understanding the roles of three academic communities in a prospective learning health ecosystem for diagnostic excellence

Inaccurate, untimely, and miscommunicated medical diagnoses represent a wicked problem requiring comprehensive and coordinated approaches, such as those demonstrated in the characteristics of learning health systems (LHSs). To appreciate a vision for how LHS methods can optimize processes and outcomes in medical diagnosis (diagnostic excellence), we interviewed 32 individuals with relevant expertise: 18 who have studied diagnostic processes using traditional behavioral science and health services research methods, six focused on machine learning (ML) and artificial intelligence (AI) approaches, and eight multidisciplinary researchers experienced in advocating for and incorporating LHS methods, ie, scalable continuous learning in health care. We report on barriers and facilitators, identified by these subjects, to applying their methods toward optimizing medical diagnosis. We then employ their insights to envision the emergence of a learning ecosystem that leverages the tools of each of the three research groups to advance diagnostic excellence. We found that these communities represent a natural fit forward, in which together, they can better measure diagnostic processes and close the loop of putting insights into practice. Members of the three academic communities will need to network and bring in additional stakeholders before they can design and implement the necessary infrastructure that would support ongoing learning of diagnostic processes at an economy of scale and scope.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153643/1/lrh210204_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153643/2/lrh210204.pd

American Democracy in Crisis: The Challenges of Voter Knowledge, Participation, and Polarization

"American Democracy in Crisis: The Challenges of Voter Knowledge, Participation, and Polarization"— the first of a series of surveys from PRRI/The Atlantic examining challenges to democratic institutions and practices— finds an alarming number of Americans do not know what factors qualify people for or disqualify people from voting. The survey also finds large divides by political party, race, and ethnicity regarding the biggest problems facing the U.S. electoral system. At the same time, there is strong, bipartisan support for a range of policies that increase access to the ballot

Quantum Computing in Molecular Magnets

Shor and Grover demonstrated that a quantum computer can outperform any classical computer in factoring numbers and in searching a database by exploiting the parallelism of quantum mechanics. Whereas Shor's algorithm requires both superposition and entanglement of a many-particle system, the superposition of single-particle quantum states is sufficient for Grover's algorithm. Recently, the latter has been successfully implemented using Rydberg atoms. Here we propose an implementation of Grover's algorithm that uses molecular magnets, which are solid-state systems with a large spin; their spin eigenstates make them natural candidates for single-particle systems. We show theoretically that molecular magnets can be used to build dense and efficient memory devices based on the Grover algorithm. In particular, one single crystal can serve as a storage unit of a dynamic random access memory device. Fast electron spin resonance pulses can be used to decode and read out stored numbers of up to 10^5, with access times as short as 10^{-10} seconds. We show that our proposal should be feasible using the molecular magnets Fe8 and Mn12.Comment: 13 pages, 2 figures, PDF, version published in Nature, typos correcte

NASA's Evolution to K(sub a)- Band Space Communications for Near-Earth Spacecraft

Over the next several years, NASA plans to launch multiple earth-science missions which will send data from low-Earth orbits to ground stations at 1-3 Gbps, to achieve data throughputs of 5-40 terabits per day. These transmission rates exceed the capabilities of S-band and X-band frequency allocations used for science probe downlinks in the past. Accordingly, NASA is exploring enhancements to its space communication capabilities to provide the Agency's first Ka-band architecture solution for next generation missions in the near-earth regime. This paper describes the proposed Ka-band solution's drivers and concept, constraints and analyses which shaped that concept, and expansibility for future need