Stetigkeit und Unstetigkeit

The origin of this pieces stems ideas regarding discontinuity of the French philosopher Michel Foucault, referenced in his 1969 book, L'Archéologie du Savoir (The Archaeology of Knowledge). He observes these ideas from an historian's perspective. Foucault argues that it is more important to recognize a phenomenon as a distinct individual entity (discontinuity), rather than viewing the phenomenon as a link in a long chain of events (continuity). This piece emerges from this concept. Stetigkeit und Unstetigkeit represents several isolated gestures within one continuous larger gesture. The isolated gestures symbolize discontinuity. The piece begins with a gesture of continuity that develops and transforms until the other polyphonic layers emerge as discontinuous elements. This piece presents a possible model of how discontinuity and continuity can coexist within a broader space and time

Enacting Diversity and Racial Projects on College Campuses: Tensions and Possibilities for Transforming Pedagogical Practices

Racial, socioeconomic, and political segregation patterns currently surpass pre-1960s levels in America (Anderson, 2010). Higher education may be the first--and perhaps only--time students interact with diversity of ideas and people (Harper & Hurtado, 2011). My dissertation examined how universities mediated diversity initiatives where students learned about diversity and race while participating in seminars that fostered cross-racial interactions. Informed by a cultural historical approach to learning and development, I examined two case studies of one public and one private university. The following research questions guided my inquiry: (a) How do postsecondary educators (administrators, faculty, and volunteers) theorize issues of diversity and race? (b) How do postsecondary educators organize student learning about issues of diversity and race? (c) What are the affordances and constraints of how postsecondary educators organize student learning? and (d) How do racial attitudes of student participants shift from the beginning to the end of the seminars? Using Cultural-Historical Activity Theory to address these questions, I analyzed three sources of data: audio recordings of interviews with postsecondary educators, video recordings of seminar interactions, and student responses to the Color-Blind Racial Attitudes Scale (CoBRAS; Neville, Lilly, Duran, Lee & Browne, 2000). My findings show how different kinds of pedagogical practices created or shut down entry points for students to engage with issues of diversity and race. By "re-purposing" tools from everyday life, postsecondary educators facilitated opportunities for students to make connections between personal experiences and abstract concepts. However, powerful modes of silencing, such as questioning practices and rules to ensure safety sometimes suppressed discussions. Subsequently, how students related to issues of diversity and race within the seminars was promoted or hindered by how postsecondary educators organized learning environments

Acceleration of FM-Index Queries Through Prefix-Free Parsing

FM-indexes are a crucial data structure in DNA alignment, but searching with them usually takes at least one random access per character in the query pattern. Ferragina and Fischer [Ferragina and Fischer, 2007] observed in 2007 that word-based indexes often use fewer random accesses than character-based indexes, and thus support faster searches. Since DNA lacks natural word-boundaries, however, it is necessary to parse it somehow before applying word-based FM-indexing. Last year, Deng et al. [Deng et al., 2022] proposed parsing genomic data by induced suffix sorting, and showed the resulting word-based FM-indexes support faster counting queries than standard FM-indexes when patterns are a few thousand characters or longer. In this paper we show that using prefix-free parsing - which takes parameters that let us tune the average length of the phrases - instead of induced suffix sorting, gives a significant speedup for patterns of only a few hundred characters. We implement our method and demonstrate it is between 3 and 18 times faster than competing methods on queries to GRCh38. And was consistently faster on queries made to 25,000, 50,000 and 100,000 SARS-CoV-2 genomes. Hence, it is very clear that our method accelerates the performance of count over all state-of-the-art methods with a minor increase in the memory

Another virtue of wavelet forests?

A wavelet forest for a text $T [1..n]$ over an alphabet $\sigma$ takes $n H_0 (T) + o (n \log \sigma)$ bits of space and supports access and rank on $T$ in $O (\log \sigma)$ time. K\"arkk\"ainen and Puglisi (2011) implicitly introduced wavelet forests and showed that when $T$ is the Burrows-Wheeler Transform (BWT) of a string $S$, then a wavelet forest for $T$ occupies space bounded in terms of higher-order empirical entropies of $S$ even when the forest is implemented with uncompressed bitvectors. In this paper we show experimentally that wavelet forests also have better access locality than wavelet trees and are thus interesting even when higher-order compression is not effective on $S$, or when $T$ is not a BWT at all

Causal Reasoning: Charting a Revolutionary Course for Next-Generation AI-Native Wireless Networks

Despite the basic premise that next-generation wireless networks (e.g., 6G) will be artificial intelligence (AI)-native, to date, most existing efforts remain either qualitative or incremental extensions to existing ``AI for wireless'' paradigms. Indeed, creating AI-native wireless networks faces significant technical challenges due to the limitations of data-driven, training-intensive AI. These limitations include the black-box nature of the AI models, their curve-fitting nature, which can limit their ability to reason and adapt, their reliance on large amounts of training data, and the energy inefficiency of large neural networks. In response to these limitations, this article presents a comprehensive, forward-looking vision that addresses these shortcomings by introducing a novel framework for building AI-native wireless networks; grounded in the emerging field of causal reasoning. Causal reasoning, founded on causal discovery, causal representation learning, and causal inference, can help build explainable, reasoning-aware, and sustainable wireless networks. Towards fulfilling this vision, we first highlight several wireless networking challenges that can be addressed by causal discovery and representation, including ultra-reliable beamforming for terahertz (THz) systems, near-accurate physical twin modeling for digital twins, training data augmentation, and semantic communication. We showcase how incorporating causal discovery can assist in achieving dynamic adaptability, resilience, and cognition in addressing these challenges. Furthermore, we outline potential frameworks that leverage causal inference to achieve the overarching objectives of future-generation networks, including intent management, dynamic adaptability, human-level cognition, reasoning, and the critical element of time sensitivity

Joint Location, Bandwidth and Power Optimization for THz-enabled UAV Communications

In this paper, the problem of unmanned aerial vehicle (UAV) deployment, power allocation, and bandwidth allocation is investigated for a UAV-assisted wireless system operating at terahertz (THz) frequencies. In the studied model, one UAV can service ground users using the THz frequency band. However, the highly uncertain THz channel will introduce new challenges to the UAV location, user power, and bandwidth allocation optimization problems. Therefore, it is necessary to design a novel framework to deploy UAVs in the THz wireless systems. This problem is formally posed as an optimization problem whose goal is to minimize the total delays of the uplink and downlink transmissions between the UAV and the ground users by jointly optimizing the deployment of the UAV, the transmit power and the bandwidth of each user. The communication delay is crucial for emergency communications. To tackle this nonconvex delay minimization problem, an alternating algorithm is proposed while iteratively solving three subproblems: location optimization subproblem, power control subproblem, and bandwidth allocation subproblem. Simulation results show that the proposed algorithm can reduce the transmission delay by up to $59.3\%$, $49.8\%$ and $75.5\%$ respectively compared to baseline algorithms that optimize only UAV location, bandwidth allocation or transmit power control.Comment: 5 pages IEEE Communications Letter